Hypothalamic neural networks in control of glucose homeostasis

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Hypothalamic neural networks in control of glucose homeostasis
Hypothalamic neural networks in control of glucose homeostasis
Hypothalamic neural net works
in control of glucose homeostasis
AC A DE M I S C H PROE F S C H R I F T
Ter verkrijging van de graad van doctor
aan de Universiteit van Amsterdam
op gezag van de Rector Magnificus
prof. dr. D.C. van den Boom
ten overstaan van een door het college voor promoties
ingestelde commissie,
in het openbaar te verdedigen in de Agnietenkapel
op donderdag 28 januari 2010, te 10:00 uur
door
Chun-Xia Yi
geboren te Hunan, China
PROMOTIECOMMISSIE
Promotores
Prof. dr. E. Fliers
Prof. dr. R.M. Buijs
Co-promotores
Dr. A. Kalsbeek
Dr. M. J. M. Serlie
Overige leden
Prof. dr. R.A.H. Adan
Prof. dr. J.M. Aerts
Dr. S.E. La Fleur
Prof. dr. J.H. Meijer
Prof. dr. H. Pijl
Prof. dr. H.P. Sauerwein
Faculteit der Geneeskunde
The research in this thesis was carried out at
Netherlands Institute for Neuroscience
The research was financially supported by
Dutch Diabetes Research Foundation and Royal Netherlands Academy of Arts and Sciences
Publication of this thesis was financially supported by
University of Amsterdam, Dutch Diabetes Research Foundation, Novo Nordisk
Goodlife Healthcare, Boehringer Ingelheim and GlaxoSmithKline
Netherlands Institute for Neuroscience
Cover illustration: Hang-Zhi Yi (易航智)
Book design: Henk Stoffels
Print: Gildeprint bv, Enschede
I asked my father to make a Chinese water painting for my thesis cover.
Via a telephone call to China, I told him my general idea about this
painting: ‘a Chinese girl fishing in the dark water under moon light’.
I did not explain to him what this design means: the data of our
chronobiology study are often obtained by lots of overnight experiments.
My father sent me the painting a month later, it is as beautiful as I had
imagined. Then he called me and explained to me: ‘I painted a very
light moon, because I think you need a very strong scientific hypothesis
to enlighten all your studies. I also added a bit weak light in a window,
because only a hypothesis is not enough, sometimes you need inspiration
as well. By the way, you can do some Photoshop work by yourself with
the water. I made it very dark, as I understood from your weekly phone
calls to your mother that glucose metabolism is a very difficult research
field, so I wanted to make it very mysterious. If you think you already
know a lot about glucose, you can make it a bit lighter’.
I asked Henk Stoffels, the best artist I know, to keep that water dark
when he designed my thesis.
Contents
General Introduction
Chapter 1 The role of liver innervation in the control of metabolism
11
Chun-Xia Yi, Susanne E. la Fleur, Eric Fliers & Andries Kalsbeek. Biochimica et Biophysica Acta - Molecular Basis of Disease, in press
Chapter 2 Mammalian clock output mechanisms
35
Andries Kalsbeek, Chun-Xia Yi, Cathy Cailotto, Susanne E. la Fleur,
Eric Fliers & Ruud Buijs. Essays in Biochemistry, in press
Scope of the thesis
47
Hypothalamic sensing of peripheral metabolic signals
Chapter 3 Ventromedial arcuate nucleus communicates peripheral metabolic information to the suprachiasmatic nucleus
51
Chun-Xia Yi, Jan van der Vliet, Jiapei Dai, Guanfu Yin, Liqiang Ru
& Ruud M Buijs.
Endocrinology, 147:283-294 (2006)
Chapter 4 A circulating ghrelin mimetic attenuates light induced phase delay of mice and light-induced Fos expression
in the suprachiasmatic nucleus of rat
73
Chun-Xia Yi, Etienne Challet, Paul Pévet, Andries Kalsbeek,
Carolina Escobar & Ruud M Buijs. Eur J Neurosci, 27:1965-1972 (2008)
Chapter 5 Dorsomedial hypothalamic neuropeptide FF neurons provide food anticipatory information to the site of
retinal termination in the suprachiasmatic nucleus
85
Chun-Xia Yi, Jan van der Vliet, Michael Proper,
Manuel Angeles-Castellanos, Valeri Goncharuk, Jack H.Jhamandas,
Andries Kalsbeek, Carolina Escobar & Ruud M.Buijs. Submitted
Hypothalamic modulation of glucose metabolism
Chapter 6 A major role for perifornical orexin neurons in the control of glucose metabolism in rats
Chun-Xia Yi, Mireille J. Serlie, Mariëtte T. Ackermans, Ewout Foppen,
Ruud M. B
­ uijs, Hans P. Sauerwein, Eric Fliers & Andries Kalsbeek. Diabetes, 58:1998-2005 (2009)
101
Contents
Chapter 7 Pmch expression during early development is a critical determinant of energy homeostasis
123
Joram D. Mul, Chun-Xia Yi, Pim W. Toonen, Martine C. van der Elst,
Bart A. Ellenbroek, Andries Kalsbeek, Susanne E. la Fleur
& Edwin Cuppen. Submitted
Chapter 8 Pituitary adenylate cyclase-activating polypeptide stimulates glucose production through glycogenolysis and via the
hepatic sympathetic innervation in rats
145
Chun-Xia Yi, Ning Sun, Mariëtte T Ackermans, Anneke Alkemade,
Ewout Foppen, Jing Shi, Ruud M Buijs, Mireille J Serlie, Eric Fliers
& Andries Kalsbeek. Diabetes, under revision
Chapter 9 Glucocorticoid signaling in the arcuate nucleus is involved in the control of hepatic insulin sensitivity
165
Chun-Xia Yi, Susanne E. la Fleur, Ewout Foppen, Mireille J. Serlie,
Ruud M. Buijs, Eric Fliers & Andries Kalsbeek. In preparation
Chapter 10 Floating rhythms in plasma glucose concentration and glucose appearance -a technical note-
177
General Discussion
183
Summary 191
Samenvatting
194
References
197
Authors
233
Publications
235
Acknowledgements
237
General Introduction
Chapter 1
Based on: The role of the autonomic nervous liver innervation in the control
of energy metabolism
To be published in: Biochimica et Biophysica Acta - Molecular Basis of Disease
Chun-Xia Yi, Susanne E. la Fleur, Eric Fliers & Andries Kalsbeek
Abstract
Despite a longstanding research interest ever since the early work by Claude Bernard, the functional significance of autonomic liver innervation, either sympathetic
or parasympathetic, is still ill defined. This scarcity of information not only holds for
the brain control of hepatic metabolism, but also for the metabolic sensing function
of the liver and the way in which this metabolic information from the liver affects
the brain. Clinical information from the bedside suggests that successful human liver
transplantation (implying a complete autonomic liver denervation) causes no life
threatening metabolic derangements, at least in the absence of severe metabolic challenges such as hypoglycemia. However, from the benchside data are accumulating
that interference with the neuronal brain-liver connection does cause pronounced
changes in liver metabolism. This review provides an extensive overview about how
metabolic information is sensed by the liver and how this information is processed via
neuronal pathways to the brain, to control its own metabolism as well as that of other
organs and tissues. Special attention is paid to the hypothalamic pathways involved in
these brain - liver circuits. At this stage we still do not know the final destination and
processing of the metabolic information that is sent from the liver to the brain. On the
other hand, in recent years there has been a considerable increase in the understanding
of brain areas that control the autonomic output to the liver. However, in view of the
ever rising prevalence of type 2 diabetes, this potentially highly relevant knowledge is
still by far too limited. Thus the autonomic innervation of the liver and its role in the
control of metabolism needs our continued and devoted attention.
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Chapter 1 content
1. Introduction
13
2. Neuroanatomy of the hepatic innervation
14
3. Afferent pathways and hepatic metabolic sensing
18
Glucose sensing
Lipid sensing
Protein sensing
Hormone sensing
4. Efferent pathway and the control of hepatic metabolism 23
Neuronal signals in control of liver glucose and lipid metabolism
Intrahepatic signal transduction in control of glucose metabolism
Brain areas involved in the control of liver glucose metabolism
Liver innervation and the disarrangement between glycogenolysis and GNG
5. Metabolic integration in liver and brain
27
Intrahepatic interaction of neuronal and humoral signals
The brain as an intermediate for liver control of other organs
CNS integration of liver and blood born metabolic information
6. Discussion and Perspective
What can be learned from “gain of function” and “loss of function” studies?
Perspective
12
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1. Introduction
The autonomic nervous system is the unconscious part of the peripheral nervous
system and comprises the motor system for viscera, smooth muscles and exocrine
glands. The scientific interest for the innervation of the liver by the autonomic nervous system and its function in the control of energy metabolism can be traced back
to a time when the need to understand the pathophysiology of metabolic diseases
like type 2 diabetes mellitus may have been less urgent than in our modern affluent
society. The great French physiologist Claude Bernard was the first to discover and
describe that the liver can store and release glucose, and he named this stored form
of glucose glycogen. At that time in history the general assumption was that the body
could not synthesize glucose de novo (gluconeogenesis). However, Claude Bernard
believed that hepatic glucose production was under the control of autonomic nerves
and carried out the earliest study on the autonomic innervation of the liver and glucose
metabolism in 1848. He observed a decrease in hepatic glucose output after peripheral
vagotomy, but failed to show increased glucose output by electrically stimulating the
vagal nerves. He then tried to punch the floor of the fourth ventricle, i.e., the place of
origin of the vagal nerves. The short-term “artificial diabetes” he induced in this way
(the well-known piqûre diabetique) was not blocked by cutting the vagal nerves, but
it could be blocked by transection of the spinal cord, i.e., the origin of the sympathetic
nerves that innervate the liver. Although this earliest functional study did not mean
he could distinguish the glucoregulatory function of the liver from that of other visceral organs, it was the first indication of a brain mechanism controlling peripheral
glucose homeostasis and of the involvement of the autonomic nervous system. Despite
this inspiring starting point, the role liver innervation plays in the control of energy
metabolism is still not fully uncovered today, especially regarding metabolic sensing
by the liver.
After insulin was discovered by Banting and Macleod in the 1920s, physiologists and
biochemists focused their attention on the control of liver metabolism by hormones,
and in subsequent years only little attention was paid to the involvement of neuronal
signaling in liver metabolism. In the 1950s Mayer put forward the “glucostatic theory”,
the “lipostatic theory” and the “glucoreceptor” conception 1-3 as explanatory brain
mechanisms involved in the control of feeding behavior and glucose metabolism.
Although these theories renewed interest in neuronal sensing mechanisms involved in
the control of liver function, the “glucostatic theory” itself was soon rejected based on
experimental studies by others 4. In the early sixties the existence of glucose sensitive
neurons in the ventromedial hypothalamus (VMH) and lateral hypothalamus (LH)
was proven by Anand 5 and Oomura 6. Russek then proposed the existence of glucose
receptors in the liver 7. Soon after, a change of vagal activity was recorded by Niijima
upon glucose infusions into the portal vein 8.
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The term “glucoreceptor” was gradually replaced by “glucose sennsing”, glucokinase
(hexokinase) (GK) 9 and glucose transporters (GLUT) 10, 11 are considered to be the
main molecular components of neuronal glucose sensing 12, other mechanism such
as sodium/glucose cotransporter type 3 (SGLT3) 13 and twik1-related acid-sensitive
K+ channel subunit (TASK) 1 and 3 14, 15 could be also involved.
In contrast to glucose sensing, a mechanism for lipid sensing by the liver was strongly doubted at the beginning of last century. It was thought that, of the three macronutrients, only hydrophilic glucose and amino acids could enter the liver via the portal
vein after absorption from the intestine into the mesenteric veins. Fatty acids were
thought to be absorbed in the intestinal lymph and to enter the heart through the
thoracic duct and the superior vena cava. Compared with other organs and tissues, the
liver was thus thought to have only nutritional input via glucose and amino acids, but
not via lipids. It was Frazer 16 who discovered that indeed neutral fat globules will only
enter the systemic circulation, but that fatty acids do pass into the portal capillaries
and enter the liver. Thereafter, short- and medium-chain fatty acids were confirmed
to be transported into the portal vein 17, 18, and this was later confirmed for long-chain
fatty acids and triglycerides as well 19.
As was the case with glucose, lipids proved to be a metabolic signal that can be
sensed by vagal nerves as well 20. More importantly, however, it became clear that the
brain too, is an important metabolic sensing organ. Today, there is no doubt that the
brain (especially the hypothalamus) and liver, as well as the gastrointestinal tract, can
independently detect glucose, lipids and other metabolic information. The relative
importance, however, of each of these components separately has only recently become
the subject of both animal and human studies.
This review will start with an overview of the anatomical and physiological approaches used to identify the pattern of autonomic liver innervation. Then we describe
the different roles played by the spinal and vagal afferents and efferents in liver metabolic sensing as well as in liver glucose and lipid production. The review ends with a
description of the different levels of integration of metabolic information followed by
a discussion of the current status of the known connections and missing links between
brain and liver in the control of energy metabolism.
2. Neuroanatomy of the hepatic innervation
The liver is innervated by sympathetic and parasympathetic nerves, both containing
afferent as well as efferent fibers. The sympathetic splanchnic nerves innervating the
liver originate from neurons in the celiac and superior mesenteric ganglia, which are
innervated by preganglionic neurons located in the intermediolateral column of the
spinal cord (T7-T12). The parasympathetic nerves innervating the liver originate from
preganglionic neurons in the dorsal motor nucleus of the vagus (DMV) located in the
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dorsal brainstem. Unlike other visceral organs, no clear intrahepatic postganglionic
neurons have been identified 21.
The distribution of sympathetic and parasympathetic nerves in the liver is markedly
species-dependent. Histochemical and immunochemical studies have been performed
using a variety of markers for autonomic liver innervation. For instance, vasoactiveintestinal peptide (VIP), tyrosine hydroxylase (TH) and neuropeptide Y (NPY) have
been used as markers for sympathetic efferent fibers 22, 23, In addition, α-adrenergic
and β-adrenergic receptors for the sympathetic neurotransmitter noradrenaline are
present in the hepatic artery and portal vein 24, 25. On the other hand, acetylcholinesterase (AChE) and vesicular acetylcholine transporter (VAChT) 26 contained by parasympathetic postganglionic cells 21, tend to be the vagal efferent markers of choice 27,
28
. Calcitonin gene-related peptide (CGRP) has been used as a spinal afferent marker,
since the nodose ganglia expresses much less CGRP than the dorsal root ganglia
(DRG) 29. Finally, substance P (SP) has been used as a marker for both vagal and
spinal afferents 30, 31. Different combinations of these markers have been applied to
the hepatic tissue of human, monkey, dog, rabbit, rat, hamster, guinea pig, mouse,
carp, bullfrog, and turtle. Some results are not firmly established as they could not be
repeated in later studies, but this is probably due to non-specific technical limitations,
such as those encountered using earlier histochemical methods for the demonstration
of acetylcholinesterase (AChE) in rat parenchyma 32. Generally, in most of the examined species, sympathetic and parasympathetic markers (either neurotransmitters or
synthesizing enzymes) could be detected in the hepatic artery, the portal vein region
and the area around the bile ducts. Differences mainly exist in the interlobular area and
parenchyma. In several studies, TH and NPY showed co-localization, and both kinds
of terminals have been observed in the connective tissue of the interlobular septum
and parenchyma from human, monkey, and guinea pig, but not from rat, hamster and
mouse. In rabbit liver parenchyma, TH is expressed without co-localization of NPY.
AChE fibers were not found in human liver parenchyma, nor in any other species
studied 22, 23, 33-37. Although NPY is sometimes also considered a neurotransmitter for
post-ganglionic parasympathetic nerves 38, 39, no study has shown co-localization of
NPY and AChE in liver tissue. A major difference between sympathetic innervation
of humans and the most commonly used animal models, i.e., rats and mice, is that
the latter have no clear parenchymal sympathetic innervation, while in human liver
(also in guinea pig), sympathetic noradrenaline-immunoreactive fibes penetrate deep
into the lobule to end on hepatocytes 40. However, the functionality of the sympathetic
efferent innervation of species with parenchymal sympathetic innervation could still
correspond to that of species without 41 as information from aminergic and peptidergic nerve terminals can be relayed electrically to individual cells by structures such as
cell-to-cell connecting gap junctions 42, 43.
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Only few approaches are available to investigate and differentiate the intra-hepatic
neuroanatomy of the autonomic innervation, such as neuronal tracing or neuronal
denervation in combination with physiological interventions. In rats, liver vagal afferents mainly ascend to the left nodose ganglion 44, 45, with the axon processes from
the nodose ganglion projecting to the nucleus of the solitary tract (NTS). Sympathetic
afferents from the liver enter the dorsal root ganglion (DRG), with the DRG axons
terminating in the dorsal horn of the spinal cord 21. The remarkable lack of either vagal
efferent or afferent innervation of liver parenchyma as indicated by the (immuno)
histochemical studies was confirmed by neuronal tracing studies in rats, as no anterograde labeling was found in the parenchymal liver tissue from anterograde tracer
injections in either the nodose ganglion or the dorsal motor nuclei 44. In addition,
it was reported that the hepatic vagal nerve is only a sub-branch from the common
hepatic branch that terminates in the upper duodenum, pancreas, pyloric sphincter,
and antral stomach 44 (Fig. 1). This observation was not in line with the assumption
that vagal nerve fibers derived from the common hepatic branch and the periarterial
plexus of the hepatic artery proper exclusively innervate the liver. The anatomical
observation that the gastroduodenal vagal branch joins the hepatic vagal branch to
form the so-called “common hepatic branch” complicates the interpretation of data
when the common hepatic vagal branch is disrupted or its neural activity is recorded.
This is well evidenced by the separation of the gastroduodenal branch from the common hepatic branch by means of denervation, as it turns out that an electrical signal
of the common hepatic branch that is sensitive to serotonin is blocked in this case 46.
In other words, stimulation of the intestinal tract may affect recordings of the hepatic
branch, and “hepatic parasympathetic denervation” may in fact denervate the common hepatic branch.
Retrograde tracing from liver parenchyma close to the hilus (i.e., where all nerve
bundles enter the liver) only results in a limited amount of DRG labeling from Th7-11,
indicating that only very few DRG afferents innervate the hepatoportal system 21.
As just mentioned, the classic anterograde and retrograde tracers are only able to
reveal the location of first order sensory and motor neurons. The location of second
order motor neurons in the central nervous system can be revealed with the multisynaptic viral tracing technique. After injection of the pseudo-rabies virus in rat liver,
several hypothalamic areas are highlighted (in addition to the brainstem) as containing
second-order neurons, such as the lateral hypothalamus (LH), the paraventricular
nucleus (PVN) and the retrochiasmatic area 47. Combining the viral tracing technique
with selective denervations of either sympathetic or parasympathetic liver innervation
clearly demonstrated the presence of separate populations of, respectively, parasympathetic and sympathetic motor neurons, both first and second orders 48.
Human liver nerve fibers show a strong plasticity in their distribution. Pathological
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Subdiaphragmatic
vagal nerves
Left
Right
Liver
Common
hepatic
branch
Hepatic
branch
proper
Gastroduodenal
branch
Hepatic
artery
proper
Hepatoesophageal
artery
B
A
Stomach
Common
hepatic
artery
Gastroduodenal
artery
Artery
Vagus
Figure 1 Illustration of the relationship between the hepatic common vagal branch, the hepatic vagal branch proper and the gastro-duodenal vagal branch (which terminates further
up in the upper duodenum, pancreas, pyloric sphincter, and antral stomach) (partly adapted
from [21,281]). Hepatic parasympathetic denervation includes denervation of the left branch
(site A) and the right branch (site B) originating from the right posterior subdiaphragmatic
vagal nerve (the nerve branch running behind the stomach is illustrated by dotted line).
It is not feasible to selectively remove the hepatic branch proper and therefore left branch
denervation is routinely performed at the common hepatic branch and not by transsecting
the hepatic branch proper.
challenges related to autonomic hyperactivity, such as (pre)cirrhosis and noncirrhotic
portal hypertension, cause a decreased parenchymal innervation 49, whereas nerves
are proliferating in the portal region 50, 51 as indicated by an increased number of NPY
fibers 52. Whether this redistribution is related to a change in liver metabolism is not
clear.
Summarizing it is evident that despite the clear evidence for both a sympathetic and
parasympathetic innervation of the liver, many details still have to be filled in and a
lot is still to learn about the autonomic innervation of the liver. Technical limitations
still prevent a clear mapping of some parts of the liver neuronal network, such as, for
instance, the location of parasympathetic postganglionic cell bodies. This lack of more
detailed knowledge is a major obstacle for functional studies on the role of the auto17
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nomic innervation in the control of liver metabolism as they are very much depends
on the existing knowledge on its neuroanatomy. Also the difficulty of separating the
sensory and motor branches still provides a profound obstacle to differentiate the
different aspect of their functionality. Despite these neuroanatomical difficulties, however, the evidence presented below clearly shows that the liver is a powerful metabolic
sensor, and a crucial link in the brain control of energy metabolism.
3. Afferent pathways and hepatic metabolic sensing
All macronutrients absorbed from intestinal digestion will be “sensed” first by the
gastrointestinal tract 53, before entering the liver via the portal vein. Cephalic, postprandial and post-absorptive gastro-intestinal secretions will also reach the liver via
the portal vein. With the large variety of chemoreceptors located in the hepatoportal
system, it is more than likely that these metabolic signals will also be sensed by the liver
and reported to the brain. For a long time, metabolic sensing by the liver (or hepatoportal system) was therefore considered to be the primary source of information for
the brain to regulate metabolism. However, in the last two decades, the prominent
role of liver metabolic sensing has been challenged, since it has become clear that the
brain is able to sense metabolic information from many more sources than just the
liver. For instance, the presence of insulin 54, leptin 55, 56, adiponectin 57, ghrelin 58 and
neuropeptide Y 59 receptors in the brain makes it very likely that the brain can also
sense metabolic information coming from organs such as the pancreas, adipose tissue, stomach and gut directly. The liver releases a number of factors that function as
paracrine and endocrine regulators of glucose and lipid metabolism, such as adropin
60
and fibroblast growth factor 21 (FGF21) 61, 62. Remarkably, to date, none of these
circulating factors have been reported to convey metabolic information from the liver
to the brain. Therefore, brain and liver are probably specialized in collecting different
types of information, and this information is converging into integration centers, such
as the nucleus of the solitary tract (NTS) in the hindbrain 63 and the paraventricular nucleus (PVN) in the hypothalamus 64. The studies on glucose and lipid sensing
provide some of the best examples to illustrate this complex network. In addition, a
different type of metabolic sensing is relayed within the afferent fibers from intrahepatic metabolic sensors such as the liver X receptor (LXR) 65 and the carbohydrate
response element binding protein (ChREBP) 66, as these intra-hepatic sensors mainly
work as coordinators between glucose sensing and lipid synthesis at the intracellular level. Recently, the peptide adropin, secreted by liver and brain, was identified
as a downstream signal regulated by LXR. Adropin mainly functions as a paracrine
factor, but it also works as an endocrine factor to regulate glucose homeostasis and
lipid metabolism 60. Whether adropin acts locally on its targets or via an autonomic
neuronal connection has not been elucidated yet. Finally, there is the hepatic insulin
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sensitizing substance (HISS), a substance released from the liver by parasympathetic
stimulation, but not yet identified at the molecular level, that seems to be involved in
the remote control of skeletal muscle glucose uptake 67.
Glucose sensing
The brain is unable to either synthesize or store the amount of glucose required for
its normal cellular function, therefore it accurately keeps track of the whole process
of glucose metabolism, from the initial stages of glucose intake, through absorption,
storage, production and ultimately utilization. The mechanism of glucose detection,
or glucose sensing, takes place in different areas of the brain 5, 6, 12, 68-70, as well as in
the periphery. Moreover, in the brain, not only neurons can detect glucose levels,
glial cells express glucose transporter type 2 (glut2) are also involved, especially in
hypoglycemia-stimulated glucagon secretion mechanism 71, 72. The primary places of
peripheral glucose sensing are located in the taste bud cells 73, the intestinal lumen 74,
75
, the carotid body 76, and the best studied locus, the hepatoportal area 77-80. For an up
to date review on this issue the reader is referred to the recent review by Watts and
Donovan 81.
In the earliest study of liver glucose sensing, using fairly high concentrations of
glucose, Niijima 8 proposed three different locations for the “glucose receptor”: 1) the
wall of the portal vein, 2) the parenchyma of the liver, and 3) the wall of the hepatic
vein. Nowadays it is generally accepted that glucosensors are mainly located in the
portal area 77-79, which is innervated by both sympathetic and vagal afferents 82, 83. The
functional meaning of glucosensing by these two types of afferents is still under investigation. High concentrations of glucose presented in the portal vein by a positive
porto-arterial glucose gradient are mainly sensed by the vagus nerve and inhibit its
activity 8. The signal transduction from portal vein glucose infusion to the NTS can
be blocked by hepatic vagotomy 84, 85.
One hypothesis is that hepatic glucosensors participate in the control of food intake,
by sensing the flow of digested glucose when its concentration is high. However, total
liver denervation does not seem to affect feeding behavior in any significant way 86,
87
. Possibly the portal-peripheral glucose gradient alone is not sufficient to inhibit
feeding, but when joined with brain glucose sensing it may be able to reduce food
intake. On the other hand, decreasing the portal-peripheral glucose gradient will activate vagal afferent activity 88, and this activation has been proven to be essential for
the initiation of food intake 80, 89, 90, 90, 91. Therefore, in the control of feeding behavior,
hepatic glucosensing might play a more important role in triggering the initiation of
feeding than in its termination.
In more recent studies, hypoglycemia sensed by the portal vein has received increased attention especially in the setting of insulin therapy in view of its essential role
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in tight glycemic control in diabetes patients. The occurrence of frequent and severe
hypoglycemia may partially originate from defective glucose counterregulation 92.
Hypoglycemia detection is not mediated by vagal afferents 93, 94, but does involve the
capsaicin-sensitive primary spinal afferent nerves 95. It has also been suggested that
portal vein glucose sensors only play a key role in the response to slow-onset hypoglycemia 96, but that the primary place of detection shifts to other loci such as the brain
when hypoglycemia develops rapidly 97, 98.
In animal studies, a selective sympathetic or parasympathetic hepatic denervation
is not sufficient to prevent the counterregulatory response resulting from an insulin
induced hypoglycemia 94, 99, 100. On the other hand, contradictory results were found
when a total denervation was applied 94, 99, apparently the results are very much depending on denervation method.
The hypoglycemia counterregulatory response has also been investigated in patients
who received a liver transplantation. In clinical studies carefully excluding bias from
immunosuppressive treatment such as prednisone 101 data from chronic uveitis patients are compared with data from liver transplant patients. During a hypoglycemic
clamp, liver transplanted patients appeared to have impaired hypoglycemic counterregulation as shown by less epinephrine and a cortisol release and a blunt recovery of
endogenous glucose production (EGP) to basal level 102. These defects indicate that
neuronal inputs from liver to brain (and/or brain to liver) are important to elicit the
appropriate hypoglycemic counterregulation.
The exact intrahepatic mechanism of glucose sensing is not clear yet, but it has similarities with the pancreatic β-cells, as it needs activation of the glucagon-like peptide-1
(GLP-1) receptor 103-106, 106-108, and is GLUT-2 dependent 109.
Lipid sensing
Although normal feeding behavior does not require intact liver innervation, overingestion of lipids can affect food intake through the autonomic innervation of the
liver. Experimentally administered free fatty acids (FFAs) in the small intestine can
be directly transported to the portal vein to enter the liver. Gastrointestinal primary
sensory nerves have been reported to be involved in mediating the suppressive effect
of intestinal lipid on feeding behavior 110, 111. Further studies specifically differentiating general abdominal vagotomy from hepatic vagotomy suggested that the hepatic
vagus has a major involvement in this mechanism 112. Hepatic portal infusions of
lipids significantly increase hepatic vagal afferent activity 20. The inhibitory effect on
feeding behavior induced by hepatic lipid sensing has also been confirmed under
diabetic conditions in experimental animals. A high-fat diet normalizes food intake in
STZ-diabetic rats 113-115, but common branch hepatic vagotomy can completely block
both the fat-induced decrease in caloric intake as well as normalize the increased
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hypothalamic NPY and CRF mRNA expression 114-116.
Still, in some studies, the inhibitory effects of FFAs on food intake cannot be simply
blocked by subdiaphragmatic bilateral vagotomy 117. Thus, in addition to FFA, high fat
diets might contain information that affects feeding. Alternatively, FFAs may be able
to manipulate feeding via other mechanisms such as the hypothalamus 118.
Under physiological conditions not only food-derived lipids will enter the liver. Fatty
acids are also the metabolically most important product of adipose tissue lipolysis,
and especially triglycerides stored in the abdominal adipose tissue will release FFAs
into the portal vein. The hepatoportal vagal sensing of lipids may therefore not only be
important for the “reflexive” regulation of feeding behavior, but it may also play a role
in the pathophysiology of metabolic abnormalities such as hepatic insulin resistance.
Physiologically, abdominal adipose tissue only contributes a small part of the total
amount of FFAs entering the portal vein, but an increased release of FFAs from the
adipose tissue can be triggered by stress, anger, frustration, and other factors, such as
smoking 119. Elevated levels of FFAs in the portal vein have been suggested to be the
cause of insulin resistance, as they might directly reduce insulin clearance by the liver
120-122
. Furthermore, since the anti-lipolytic effect of insulin on omental adipose tissue
is minor, due to the low insulin receptor number 123, insulin resistance will result in a
further increase of the amount of FFAs released. The overloading of the liver by FFAs
may finally cause an increased synthesis of triglycerides and an excess secretion of
very low density lipoprotein (VLDL).
As with glucose sensing, a specific lipid receptor has not yet been identified, but
lipids are natural ligands for the peroxisome-proliferator-activated receptors (PPARs)
124
that are also involved in glucose metabolism. A knock-out of the lipogenic enzyme
fatty-acid synthase (FAS) will not only induce hypoglycemia and a fatty liver, but also
a defective expression of PPARα. Furthermore, PPARα deficiency prevents glucose
intolerance caused by diet-induced obesity 125, 126. Unlike glucose sensing, splanchnicnerve afferent activity is not affected by jejunal lipid administration 112, and no study
so far has shown spinal afferent responses to any other kind of adiposity information.
Protein sensing
Protein digestion will elevate portal vein amino acid levels and high protein feeding
has been reported to stimulate glucagon release independently of amino acids blood
levels 127. It is hard to say whether this is due to a special portal amino acid sensor,
because surprisingly, only few studies on hepatoportal protein sensing are available.
A high protein diet is able to inhibit food intake 128, 129, this effect might not be due
to a direct hepatoportal protein sensing mechanism, but rather to the stimulation
of intestinal gluconeogenesis 130-132 which may consequently activate portal glucose
sensing 133. This high glucose loading may then eventually result in inhibited feeding.
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Hormone sensing
Not only nutrition itself can be sensed by the liver, but the nutrition and absorption
process will elicit the release of a variety of hormones (so-called incretins), that can
also be sensed by the liver. Glucagon-like peptide-1 (GLP-1) is one of the best studied
signals in this class of hormones.
Besides its brain origin and regulation of food intake by a central mechanism 134,
135
, GLP-1 is also secreted from the intestines during meal absorption. Its stimulatory
effect on insulin secretion and its depressive effect on glucagon secretion implicate a
remote control on the pancreas 136, 137. Because of its low postprandial plasma levels
and its rapid degradation, the action of GLP-1 is probably close to its site of release
138
. Action of GLP-1 most likely also involves a neuronal pathway. Indeed, GLP-1
receptors are expressed in the hepatoportal area 139. Infusion of a truncated form of
GLP-1(7-36)amide (tGLP-I) into the portal vein increases hepatic vagal afferent activity and pancreatic vagal efferent activity 107, while it augments glucose-stimulated
insulin secretion 140. Peripheral GLP-1 is also able to influence feeding behavior. Its
effects on meal size are mediated by the vagal nerve, but this effect does not involve
the hepatoportal mechanism 141, on whcih we will discuss later.
The brain has been proved to be the main sensor of the adipokine leptin, which
affects hepatic vagal afferent activity directly in a dose-dependent manner, low doses
inhibit its activity and high doses increase it. In addition, the activity of glucosesensitive units is inhibited by low concentrations of leptin 142. The gastrointestinal
peptide cholecystokinin (CCK) released from the duodenal mucosa also has satiety
effects, which are mediated by the gastric branch of the vagus 143. CCK can be sensed
by hepatoportal regional terminals 46, but whether its inhibitory effect on feeding is
mediated by the hepatoportal vagal branch or via the gastric vagal branch is not clear.
The fact that lesions of the termination centers of the common vagal afferents, i.e., area
postrema and NTS, do not impair the satiety induced by CCK 144, further complicates
the understanding of the central processing of peripheral CCK information. Portal
infusion of somatostatin, yet another one of the gastroenteropancreatic hormones,
also increases hepatic vagal afferent activity 145. How this signal is processed further,
within the brain, is not yet known.
The inhibitory effect of illness on feeding activity is thought to be mediated by
inflammatory factors 146. The cytokine interleukin-1 (IL-1) released during immune
activation, has been studied in great detail. Intraperitoneal administration of IL-1β
inhibits food intake 147, and this effect is proposed to involve hepatic vagal sensing since
its afferent activity is increased by IL-1β stimulation 148. Peripheral administration of
IL-1α has similar anorexic effects 149. However, hepatic vagotomy is unable to block
this effect 150.
In conclusion, the contribution of metabolic sensing in the liver to the overall whole
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body energy balancing network is still under discussion. Unlike the brain, where
the glucose concentration is sensed by glucose excitatory and inhibitory neurons, in
the liver the glucose concentration is more likely monitered by the sympathetic and
parasympathetic nerves. The glucose sensing mechanisms in brain and liver clearly
interact, but many details still need further clarification. Unfortunately, very little is
still known about the cellular mechanism of glucose sensing in the liver
4. Efferent pathway and the control of hepatic metabolism
Neuronal signals in control of liver glucose and lipid metabolism
After the initial findings of Bernard, numerous efforts have been made to understand
in more detail the brain mechanisms responsible for the control of liver metabolism, be
it with some delay. First of all, Bernard’s findings on the control of liver glucose output
by the autonomic nerves were confirmed and extended. For instance, liver glycogen
content can be changed by neuronal inputs independent of influences from circulating
glucoregulatory hormones, such as the catecholamines, insulin and glucagon. Followup studies focused on specific brain-liver connections, such as the information from
different brain regions and their output pathway to liver via specific autonomic nerves.
The early studies often used surgical removal of other metabolic organs or a total
isolation of the liver. For instance, it was shown that in adrenalectomized and/or
pancreatectomized animals, electrical stimulation of the splanchnic nerve decreases
liver glycogen content and causes an increased release of glucose by increasing the
activity of the liver glycogen phosphorylase and glucose-6-phosphatase enzymes 151,
152
, as well as a partial inactivation of phosphorylase phosphatase activity 153. Stimulation of the vagus nerve, alternatively, accelerates glycogen synthesis, and this effect
could be completely counteracted by a simultaneous stimulation of the splanchnic
nerve 154, 155. Later on, the independence of this neuronal pathway in the control of
liver glucose production was also confirmed in an eviscerated animal model. In these
experiments the authors showed that the reduction of blood glucose concentrations
induced by insulin administration to the brain (via the carotid artery) was conserved
after a total pancreatectomy together with the removal of the entire gastrointestinal
tract and the spleen 156. Recently, the original data on the inhibitory effects of central
insulin on plasma glucose concentrations were confirmed when insulin was applied
directly into the cerebral ventricle. In addition, it was shown that the inhibitory effect
of central insulin on hepatic glucose production could be blocked by both hepatic
vagotomy and sympathectomy, and that this central insulin effect only needs vagal
efferents (not afferents) without affecting glucose uptake 157, 158. Very recently, evidence
also showed vagal efferent to liver plays a vital role to convey CCK signal generated in
the gut to regulate hepatic glucose production and maintain glucose homeostasis. In
this study, the intraduodenal administration of CCK-8 can enhance hepatic insulin
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sensitivity and inhibit glucose production, and these effects can be negated by hepatic
vagotomy 159.
Lipid metabolism in the liver mainly includes the synthesis and secretion of VLDL,
ketone bodies and fatty acid oxidation. Reducing liver noradrenaline by phenol-induced hepatic sympathetic denervation can decrease carnitine palmitoyltransferase
(CPT), which is responsible for transferring long-chain fatty acid into the mitochondria 160. The hepatic sympathetic input is also involved in regulating the secretion
of apoB-containing lipoproteins, including VLDL 161. In the perfused liver model,
noradrenaline is able to inhibit the secretion of triglyceride and apoB as well as the
release of VLDL at a post-transcriptional level 162, 163. In line with this, hepatic sympathetic denervation results in lower VLDL secretion, and higher concentrations of
plasma cholesterol and VLDL-cholesterol 164. The sympathetic innervation to the liver
also influences ketone body metabolism. In the perfused liver model, sympathetic
stimulation inhibits hepatic ketogenesis 165, resulting in a reduced ketone-body output
from the liver 166.
Perfusion of isolated liver has also been used to highlight the importance of the autonomic innervation of the liver and eliminates the possibility of extra-liver humoral
inputs. In the perfusion model, splanchnic nerve stimulation caused an increased
glucose and lactate output, whereas decreased urea, glutamine formation and ketone
body production were observed 167, 168. These effects mainly involved activation of the
α1-adrenergic receptors 169, and to a much lesser degree that of the β-receptors 170..
However, the physiological significance of the sympathetic innervation for hepatic glucose production is constantly being questiones. For instance, in systemic α1-adrenergic
receptors deficient mice higher liver glycogen content was found together with a higher parasympathetic tone 171. However, blocking the portal α1 and β-receptors during
heavy exercise does not change the hepatic glucose production 172.
In the perfusion model, effects of neuronal manipulation on liver hemodynamics
are inevitable. For instance, acetylcholine (Ach) applied into such an isolated model
causes vasoconstriction and a reduction of blood flow and oxygen supply to the liver
173
. However, the early liver perfusion studies provided convincing evidence that the
metabolic changes observed in the liver were not caused by hemodynamic changes
in the liver or an overflow of noradrenalin into the hepatic vein 174, 175.
Intrahepatic signal transduction in control of glucose metabolism
Sympathetic stimulation of glycogenolysis is enhanced further via Ca2+ release from
mitochondria, the stimulation of phosphorylaseβ kinase activity, and the subsequent
activation of phosphorylase activity 176-179. Vagal efferent activity is thought to regulate
gluconeogenesis (GNG) 157 by targeting liver IL-6 and STAT3 signaling 180 via SirT1 181.
Different signaling pathways in the liver are probably involved in the autonomic nerv24
chapter 1
ous control of glucose metabolism. First of all, the efferent innervation pattern of the
liver varies between species, with some rodents (such as the guinea pig) and human
having a direct contact between the autonomic nerves and the hepatocytes, whereas
in rats and mice a direct parenchymal liver innervation is absent. Consequently, noradrenaline overflow during hepatic nerve stimulation in the perfused liver was much
higher in the guinea pig than in the rat 168. As a number of recent breakthrough studies in mice and rats indicated an important role for the autonomic innervation of the
liver in the control of glucose metabolism, one needs to keep in mind that mice and
rat liver probably have compensatory mechanisms. Signal propagation through gap
junctions, i.e., via electrotonic coupling, can compensate for the sparse direct inputs to
the hepatocytes, especially with respect to sympathetic signal transduction 43, 182. Also,
there is considerable homology between the rat and human liver gap junctions 183. This
brought about the idea of additional functions of the gap junction, such as the relaying of hormonal signals from the periportal area to the hepatocytes 184. Furthermore,
the sympathetic signal may be propagated via the release of prostaglandins from Ito
cells 185, 186 [The Ito or stellate cells are located in the space of Disse, which is separated
from the lumen by the fenestrated endothelium, while Kupffer cell and dendritic cell
face the sinusoidal lumen 187].
Despite gap junctions and other intracellular mechanisms to propagate sympathetic
signaling, a clear organization of GNG based on zone can be observed in the liver,
with higher rates of GNG being found in the periportal zone of the rat as compared
to the pericentral zone, both under fed 188 and fasting conditions 189.
Brain areas involved in liver control of glucose metabolism
Stimulation of several brain areas has been shown to induce similar changes in liver
glucose metabolism as produced by direct stimulation of sympathetic or parasympathetic nerves. These brain areas are either proposed or proven to be able to affect liver
glucose metabolism via their effect on autonomic neuronal output. For instance, electrical stimulation of the VMH causes an increased activity of the liver gluconeogenic
enzyme phosphoenolpyruvate carboxykinase (PEPCK), and a marked suppression
of hepatic pyruvate kinase (PK) activity, a key glycolytic enzyme 190. These responses
could not be abolished by adrenalectomy 191. Stimulation of the LH, on the other hand,
resulted in a decrease in PEPCK activity but did not alter PK activity 190. Physiologically, it seems that cholinergic, but not noradrenergic, dopaminergic or serotonergic receptors in the LH are selectively involved in the stimulation of liver glycogen
synthesis 192. These early proposals for putative direct neuronal pathways were only
recently supported by evidence from more detailed studies on the effects of brain insulin signaling on liver glucose metabolism. Brain insulin signaling inhibits liver GNG
via neurons in the mediobasal hypothalamus that contain ATP-sensitive potassium
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(KATP) channels 193, an effect that can be largely blocked by hepatic vagotomy 157, but
also involves NPY signaling to sympathetic pre-autonomic neurons 158
Electrical stimulation of the suprachiasmatic nucleus (SCN) has also been reported
to induce hyperglycemia 194. This hyperglycemia might involve both direct hepatic
and indirect (i.e., pancreatic) stimulatory effects on glycogenolysis 195. Blocking the
GABA-containing projections from the SCN to the PVN by bicuculline also induces
hyperglycemia, and this hyperglycemia could be eliminated by hepatic sympathetic
but not parasympathetic denervation 48. The autonomic innervation of the liver is also
involved in the hepatic insulin resistance and in increased hepatic glucose production induced by thyrotoxicosis, again an effect that seems to be mediated via a PVN
mechanism and is independent of circulating glucoregulatory hormones, including the
thyroid hormone itself 196, 197. Among the aforementioned hypothalamic peptidergic
systems, NPY is well defined as a target of several circulating factors, due to its location
in the arcuate nucleus (ARC), i.e., the “metabolic window of the brain”. For instance,
the adipokine resistin can modulate lipid metabolism and increase glucose production
via its action on NPY neurons 198-200. Considering the well-established role of NPY in
the control of hepatic insulin sensitivity via the hepatic sympathetic innervation 158, 201,
it is very likely that autonomic nerves will also mediate the central effects of resistin on
liver metabolism. The involvement of NPY and other hypothalamic neuropeptides in
control of glucose homeostasis will be discussed in more details in the next paragraph.
Virtually nothing is known about brain areas that are in control of hepatic lipid metabolism. Two recent papers have described effects of the ICV administration of glucose
and NPY on hepatic lipid metabolism 201, 202, but no information is available about the
possible location of these effects.
Liver innervation and the balance between glycogenolysis and gluconeogenesis
One important issue in glucose metabolism is how the balance between glycogenolysis
and GNG is regulated, or under which conditions GNG can be augmented. Clarification of this issue is of direct importance for understanding the mechanisms that
underlie the development of the metabolic syndrome and, maybe more importantly,
how obesity can trigger the development of type 2 diabetes. One of the hallmarks of
type 2 diabetes is the excessive hepatic glucose production. Hepatic insulin resistance
has been considered to be central to the pathophysiology of the excessive glucose
production, especially via an increased GNG through the increased activity of PEPCK
and G6Pase 203. However, this change in GNG is not explained by an alteration in
glucoregulatory hormones. An acute increase or decrease in the insulin concentration
mainly influences the rate of glycogenolysis but has little effect on GNG in nondiabetic
subjects and/or in type 2 diabetic patients 204-206, and infusion of glucagon in nondiabetic subjects does not increase the rate of GNG either 207.
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The involvement of brain signaling was thus considered and most of the evidence
highlights the importance of hypothalamic mechanisms. Electrical stimulation of the
VMH and LH changes the activity of the gluconeogenic enzyme PEPCK 190, whereas
increased insulin signaling in the mediobasal hypothalamus inhibits liver GNG via
the hepatic vagal innervation 157. In addition, central administration of leptin has been
shown to redistribute intrahepatic glucose fluxes, in such a way that GNG is increased
and glycogenolysis suppressed. However, unlike the inhibitory action of central insulin
on total glucose production 193, leptin does not change total liver glucose production 208,
209
. When one of the downstream signaling components of the leptin – the melanocortin pathway - is interrupted, total glucose production is decreased due to abolishment
of GNG. In addition, activation of melanocortin receptors can stimulate GNG 210.
In addition to leptin and insulin, evidence is accumulating that FFAs are also sensed by
the hypothalamus directly. It has been shown that fatty acids within the hypothalamus
stimulate liver GNG 118. However, it remains to be elucidated where and at what level
FFAs elicit this effect.
Although there are indications that K(ATP) channels in the mediobasal hypothalamus are involved, the (neuronal) pathways from brain to liver that control GNG
are still poorly defined. In the hypothalamus, ARC NPY/AGRP neurons, LH orexin
neurons and PVN neurons (in the lateral magnocellular subdivision) are all activated
during fasting 211, 212.
In summary, in recent years a major progress has been made in the unraveling of
the hypothalamic circuitry that is involved in the control of hepatic glucose production. This progress involves both the awareness that many peripheral nutritional and
metabolic signals may “use” the central nervous system as an intermediate to affect
hepatic glucose metabolism, as well as more detailed information on neural pathways
and neurotransmitters able to affect hepatic glucose production. Main challenge in
the years to come will be to connect all these peripheral signals to the appropriate
hypothalamic pathways.
5. Metabolic integration in liver and brain
Intrahepatic interaction of neuronal and humoral signals that control metabolism
Sympathetic and parasympathetic liver efferent nerves contain the classic aminergic
(epinephrine and norepinephrine) and cholinergic neurotransmitters, as well as peptidergic components such as NPY which can be co-released with the classic neurotransmitters from both sympathetic and parasympathetic terminals 213, 214. At the same
time, the liver also receives a large amount of humoral information via the portal vein
or arterial inputs. One of the unsettled issues is the interaction between the humoral
signals and the neuronal signals that the liver receives during different energetic situations. First of all, insulin has an antagonizing effect on sympathetic (adrenergic)
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stimulation of glucose production 215, probably by interrupting the Ca2+ flux into the
mitochondria of the hepatocytes 216. Secondly, sympathetic nerve stimulation in the
presence of glucagon increases the output of glucose further and reduces the enhanced
lactate uptake by glucagon 215. These data implicate that the stimulatory effects of
hepatic nerves on glucose output can be modulated by circulating glucoregulatory
hormones. The opposite pathway, i.e., neuronal signals modulating a hormonal signal,
does not seem to exist since in dogs complete liver denervation has no clear effects on
the glucose production-increasing properties of glucagon 217.
NPY may interact with both humoral and neuronal signaling in the liver. In dogs,
NPY infusion into the portal vein stimulates hepatic glucose uptake without significantly altering whole body glucose disposal 218. On the other hand, although NPY
per se is not able to directly regulate hepatic glucose production, it can inhibit the
stimulatory effects of glucagon and noradrenaline on glucose production 219. In contrast to NPY, galanin, the other neuropeptide released from the celiac ganglion as a
sympathetic neurotransmitter, has no effects on its own when infused into the portal
vein, but it does potentiate the action of norepinephrine to stimulate hepatic glucose
production 220.
It has been hypothesized that insulin induces liver glucose uptake and storage into
glycogen when the glucose level is higher in the portal vein than in the hepatic artery (portal-artery gradient). Thus this gradient sensing is involved in the stimulatory action of insulin on liver glucose uptake 221. This process can be augmented by
vagal stimulation as mimicked by an intraportal infusion of acetylcholine 222. Type 3
muscarinic receptors in the hepatocyte possibly mediate these effects 173. In contrast,
blocking vagal efferent signals by atropine can inhibit insulin-mediated glucose uptake
under the portal-artery gradient situation 223. Not surprisingly, the effects of vagal activation on the effects of glucagon are opposite to its synergistic action on insulin, i.e.,
the glucagon-stimulated glucose release is antagonized by either vagal nerve stimulation or Ach 224. Whether these interactions take place at the level of receptor sensitivity
or are due to a direct influence on the fractional extraction of these hormones is not
clear.
The brain as an intermediary for the outflow of metabolic liver information to
other organs
The increased PPAR activity in the liver needs intact vagal afferents to the brain in
order to result in the expected systemic effects 225. Interestingly, vagal inputs seem to
be mediating strikingly different signals, since on the one hand disruption of vagal
afferent fibers can prevent PPARα mediated glucocorticoid-induced metabolic derangements including insulin resistance 226, whereas on the other they are also essential
for hepatically expressed PPARγ2 to increase insulin sensitivity 225. Again, this brings
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back the topic of the location of vagal sensing: due to the apparent lack of vagal afferent innervation in parenchyma, the above-described mechanisms seem to depend
mainly on sensors located in the portal region.
Within the brain-liver circuit, hepatoportal afferents and efferents form an autonomic feedback loop. This circuit could be “built” as a simple sensory-motor reflex,
but most likely involves a complex brain mechanism 81. Net hepatic glucose uptake is
more pronounced when glucose is loaded directly into the portal vein instead of into
the general circulation, despite controlled insulin and glucagon levels 227-230. This means
that the hepatoportal signal evoked by glucose has to be sensed by a specific pathway.
Indeed, it was reported that an intact nerve supply to the liver is vital for this response.
First, after a complete liver denervation the extra uptake by the overload of glucose
into the portal vein was blocked 227; second, after hepatic vagotomy liver glucose uptake
was decreased by approximately 40% under euglycemic-hyperinsulinemic conditions
during portal glucose infusions 231. It is therefore logical to expect that the storage of
glucose in the liver will be changed by interruption of liver innervation. However,
a complete denervation only changes the variability of both glycogen synthesis and
GNG but not its absolute level 232, 233. The central pathway can thus influence these
processes, but the liver also contains a strong autoregulatory mechanism. Interestingly,
under hyperinsulinemic conditions, total hepatic glucose production can be increased
during portal glucose loading 231. This raises the possibility that the autonomic nerves
interact with insulin signaling as discussed before.
Stimulation of the hepatoportal glucose sensors by glucose infusions can stimulate
glucose uptake in heart, brown adipose tissue, and muscle. These portal glucoseinduced changes in glucose utilization involve both an insulin-dependent and an
insulin–independent mechanism 234. The insulin–independent mechanism possibly
relates to GLUT-4 and AMP-activated protein kinase (AMPK) signaling in muscle 235.
Besides glucose, high physiological doses of GLP-1 infusion in the portal vein are also
able to stimulate glucose clearance in non-hepatic tissues 104.
CNS integration of liver and blood borne metabolic information
The brain controls energy metabolism by balancing energy expenditure and energy
intake and/or production. In order to maintain the right balance, the brain, liver,
gastrointestinal and other metabolic sensing mechanisms, either via the neuronal or
the humoral pathway, cannot be separated from each other.
From the information provided above it is clear that a multilevel network is dedicated to receiving and relaying the liver and other visceral metabolic information to
the brain via both hormonal and neuronal routes. The first-order of convergence for
the neural information from the metabolic sensing from the different visceral organs
is found at the level of the nodose and dorsal root ganglions. Hereafter, the second
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level for convergence of information is in the NTS and the dorsal horn of spinal cord.
Although this has never been investigated specifically for the liver, there is the possibility of an ultrashort feedback loop via projections from the dorsal horn to IML, or from
NTS to the dorsal motor nucleus of the vagus (DMV). Interestingly, although spinal
ascending pathways and the NTS both project into the parabrachial nuclei (PB), the
topographic separation of spinal and NTS inputs into PB 236 does not make this area
a likely integration place for spinal and vagal inputs. One of the possible integration
sites in the midbrain is the periaqueductal gray matter (PAG), which receives inputs
from both the general-visceral recipient part of the NTS and the thoracic spinal cord
237
. How this sympathetic-parasympathetic integration overlaps or “interferes” with
the proposed columnar organization of the PAG 238 in the control of liver metabolism
is not yet known.
Within the hypothalamus, the lateral hypothalamus (LH) has been reported to respond to portal vein infusions of glucose or CCK 239, 240. The responses to glucose
were not found in other hypothalamic areas like the supraoptic nucleus, PVN or
ventromedial hypothalamus 241. Furthermore, the excitability of LH neurons seems
to follow the rhythmy of the day/night cycle 242. Interestingly, splanchnic denervation
eliminates the LH responses to glucose, whereas vagal denervation exaggerates this
response 241. These data suggest that the LH receives both spinal and vagal liver glucose
sensing information and thus may be one of the main hypothalamic integration areas
for these neuronal inputs.
Regarding the integration of neuronal and humoral sensing information, the arcuate
nucleus, which is the unique metabolic sensor for almost all circulating metabolites
and their relatives, is a strong candidate for the integration of humoral and vagal
inputs via the NTS-ARC projection 243. Another major candidate is the PVN, as both
sympathetic and parasympathetic metabolic sensing information reaches the PVN
by direct and indirect pathways 64. Moreover, other forebrain areas, such as the bed
nucleus of the stria terminalis and a number of hypothalamic nuclei also innervate
the PVN. This unique position allows the PVN to integrate a very broad spectrum of
neuronal and humoral metabolic sensing information and to organize its autonomic
and neuroendocrine outflow consequently according to these different inputs.
Finally, at the level of the hypothalamus probably also the integration of information from the metabolic-homeostatic system and the cognitive-hedonic processes
involved in the control of food intake and energy balance take place, as information
from the limbic system and cortex also reaches the PVN via projections to the BNST
and subPVN 244.
Vice versa it is clear that hepatic autonomic afferents transmit glucosensing information to higher brain areas, but how the many different brain regions are involved
in accepting and integrating this information is still very ill defined, although a very
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recently published anatomical study on the communication within the hypothalamic,
cortical and mesolimbic circuitries involved in the regulation of energy balance, provided a clear clue that indeed neuronal pathways do transfer energy sensory information from the hypothalamus to cerebral cortex 245.
6. Discussion and Perspective
What can be learned from “gain of function” and “loss of function” studies?
Despite all the evidence for manipulation-induced effects of neuronal elements on
liver glucose and lipid metabolism, the physiological significance of the afferent and
efferent liver innervations is still not clear.
Liver transplanted humans and animals are a suitable model to study the consequences of a complete denervation on liver metabolism. In liver transplanted patients,
no reinnervation of either hepatic sympathetic efferent or afferent nerves has been
observed until 30 months 246. In transplanted rats, by using growth-associated protein
(GAP)-43 as an axonal marker, regenerating axons possibly originating from parasympathetic ganglion cells in the hepatic hilus of liver allografts have been observed
247, 248
, but a centrally derived reinnervation has never been claimed.
Liver transplanted patients have relatively normal insulin-dependent glucose metabolism, and after a long term recovery from the initial effects of the immunosuppressive treatment, also protein and FFA metabolism return to nearly normal 102, 249. When
comparing results from matched healthy subjects and kidney-transplant patients who
received immunosuppressive medication similar to that received by the liver-transplant patients, exercise data showed glucose production increased to a similar extent
in control subjects as in liver transplanted patients 250.
In mice, 9 months after orthotopic liver transplantation, body weight and other
hepatic and general metabolic parameters are in the normal range, despite an increase
in LDL cholesterol, LDL/HDL ratio and in hepatic glucose production. In short-term
(2 weeks) completely liver denervated dogs, liver glycogenolysis response to a physiological increase in glucagon is unaltered 217, despite the fact that in the intact situation
vagal activity will antagonize the effects of glucagon. A similar observation has been
made in other experimental animals 233.
Taken together, these data indicate that the direct efferent liver innervation may
not be essential for maintaining normal liver glucose, amino acid and lipid metabolism, and that autoregulatory mechanism inside the liver are fully able to control
liver metabolism in basal (i.e., non-stimulated) conditions. However, the defective
hypoglycemic counterregulation observed in the liver transplanted individuals as
discussed before, suggests the autonomic innervation of the liver might be more essential during “fight or flight” responses, by triggering catabolic responses such as
stimulation of glucose output via a fast neuronal pathway, preparing the individual
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for emergency conditions. Interestingly, if only a sympathetic or parasympathetic liver
denervation is performed, the normal daily rhythm in plasma glucose concentrations
is eliminated but a complete denervation of both branches simultaneously does not
result in such disturbed glucose rhythmicity 251. Apparently for the remaining humoral
and autoregulatory control systems it is easier to maintain a balanced glucose output
without any autonomic innervation, than with an unbalanced autonomic input. Thus
these findings support the idea that disorders of (hepatic) glucose metabolism are
more likely to be derived from an unbalanced autonomic input to the liver than from
a complete absence of such inputs.
Perspective
From the viewpoint of whole-body harmonization, afferent liver signaling is important for allowing the brain to synchronize liver physiology with that of other parts of
the body. The liver can be considered as a primary nutritional sensor, while the brain
serves as an overall energy sensor. Metabolic sensing in the liver is organized in such
a way that most of the metabolic signals that indicate “plentifulness” are sensed by the
vagal nerves, i.e., high concentrations of glucose and lipid absorbed from food, leptin
released from adipose tissue, and lipid-activated PPARs activity (Fig. 2). Continuous
Sympathetic outputs
(+)Glycogenolysis
(+)Gluconeogenesis
(+)VLDL secretion
(-) Ketogenesis
PVN
Sympathetic spinal sensing
Hypoglycemia
VMH
ARC
Integrated signal
PB
NTS
DMV
Vagal sensing
High glucose (vs. artery level)
High protein (indirectly)
FFA, PPAR α/γ
γ
GLP-1, leptin, CCK
Parasympathetic outputs
(-)Gluconeogenesis
Liver
Hepatic artery
Bile duct
Portal vein
Figure 2 Summary of the hepatic metabolic sensing and the neuronal pathways involved.
Vagal and sympathetic afferents originate from both the liver itself and the portal vein.
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high levels of lipid sensed by the portal vein nerves may lead this sensing system to
increase its threshold; consequently more lipids are needed to generate the appropriate
afferent signal. In a chronic situation this may mean that the brain integration center
loses this piece of peripheral information. However, whether this eventually results
in a profound loss of feedback about the metabolic situation from periphery to brain
needs to be investigated. Probably, parallel running humoral factors such as the newly
defined lipid sensor ghrelin O-acyl transferase (Goat)-ghrelin can also signal to the
brain about the availability of energy 252, and this pathway may either complete the
neuronal metabolic sensing from liver or even take over when neuronal sensing from
the liver is not available, for instance after liver transplantation. Checking the metabolic profile after blocking the (Goat)-ghrelin signaling with hepatic vagal denervation
could test this possibility.
In contrast to vagal innervation, spinal nerves predominantly sense the “inadequate”
metabolic information, especially the lack of glucose. These opposing roles might also
be involved in a dysbalance during pathophysiological states. One of the hypotheses
is that a hypoglycemia counterregulation pathway may be activated inappropriately
during a euglycemic or hyperglycemic condition, driving the liver continuously to
produce glucose, and overriding the inhibition from insulin.
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Chapter 2
Based on: Mammalian Clock Output Mechanisms
To be published in: Essays in Biochemistry
Andries Kalsbeek, Chun-Xia Yi, Cathy Cailotto, Susanne E. la Fleur, Eric Fliers & Ruud Buijs
Rhythms are everywhere
In mammals many behaviors (eg, sleep/wake, feeding) as well as physiological (eg,
body temperature, blood pressure) and endocrine (eg, plasma corticosterone concentration) events display a 24-rhythmicity. These 24-hour rhythms are induced by
a timing system that is composed of a hierarchical arrangement of oscillators. It is
thought that this internal timing system has developed during evolution in order to
enable organisms to coordinate and anticipate their metabolism and milieu intérieur
in accordance with the (predictable) changes in the external environment. The master
oscillator is the biological (brain) clock located in the hypothalamic suprachiasmatic
nuclei (SCN). Additional oscillators have been reported in a variety of other structures in the central nervous system, including other hypothalamic nuclei, as well as
in all peripheral organs studied thus far (among which for instance, pancreas, liver
and muscle) 253.
The intrinsic period of the master brain oscillator in the hypothalamic SCN displays
an intrinsic rhythm of approximately 24-hours (i.e., circadian) that is generated and
maintained at the molecular level by transcription/translational feedback loops of the
so-called clock genes 254. As the intrinsic period of the master brain oscillator in the
hypothalamic SCN, is approximately, but not exactly 24-hours, this oscillator has to be
reset on a regular basis in order for the organism and its internal homeostasis not to
drift out of phase with the (exact) 24-hour rhythm of the environment. The circadian
rhythm generated by the SCN is entrained with or synchronized to the external day/
night cycle mainly by the action of environmental light relayed from the retina through
the retinohypothalamic tract. The current model for the light-induced entrainment of
the master clock proposes that glutamate and pituitary adenylate cyclase-activating
peptide (PACAP) are co-released in the SCN upon photic stimulation 255. Next to this
light-induced entrainment, the SCN is certainly also sensitive to other, so-called nonphotic, stimuli, such as feeding, social interactions, sleep deprivation and exercise 256.
Subsequently the entrained rhythm of the central oscillator in the SCN is relayed to the
peripheral oscillators in the brain and periphery. However, whereas the environmental
light/dark cycle is the most important entraining signal for the SCN oscillator, the
peripheral oscillators seem to be sensitive to many more stimuli, such as hormones,
35
chapter 2
temperature and metabolic cues 256, 257, next to the light-entrained synchronizing signals from the SCN 258.
Neural versus humoral
In order for an organism to benefit from its biological clock, the timing signal should
be communicated to the rest of the body. Therefore, the products (i.e., proteins) of
the clock genes in the SCN neurons are not only involved in the maintenance of the
24-hour transcription/translational feedback loops, but they also drive the day/night
rhythm in neuronal firing of the SCN neurons 259 as well as the expression of so-called
clock-controlled (output) genes (CCGs) such as vasopressin 260 and vasoactive intestinal polypeptide (VIP) 261, two well-known peptidergic neurotransmitters of the SCN
(Fig. 1). Indeed daily rhythms in the mRNA and peptide expression in SCN neurons,
A
B
C
Figure 1Confocal laser scanning microscopic image of the bilateral rat suprachiasmatic
nuclei (SCN). A vibratome section was double-immunostained with a mixture of primary
antibodies against vasopressin (AVP) and vasoactive intestinal polypeptide (VIP) followed
by a mixture of Cy3- and Cy5-conjugated secondary antibodies. Laser scanning took place
with a 543 and 633 nm laser beam where after the corresponding pictures (of the same optical section) were combined and displayed in pseudo-colors: VIP-immunoreactive perikaryal
profiles, nerve fibers and endings, green; AVP-immunoreactive perikaryal profiles, nerve
fibers and endings, red. The yellow color indicates a close connection between AVP- and
VIP-immunoreactive structures, i.e. AVP terminals on VIP-containing cell bodies (b) or vice
versa (c).
36
chapter 2
as well as release of these peptidergic neurotransmitters (i.e., neuropeptides) have been
described several times. In principle the SCN has 2 ways to convey its rhythmic message to the rest of the brain and subsequently the rest of the organism, i.e., a humoral
or a neural pathway. Transplantation and parabiosis experiments as well as “temporal
chimeras” have provided support for the humoral mechanism 262-264, suggesting that the
SCN drives circadian rhythms of (e.g., locomotor) behavior by the rhythmic secretion
of paracrine factors in its immediate surroundings and in the third ventricle. By now a
number of peptides have been proposed to serve as a humoral SCN output, the most
notable examples being vasopressin, TGF-ά, prokineticin-2 and cardiotrophin-like
cytockine 265-267. But, of course, many more may be out there 268. On the other hand,
the same transplantation experiments also provided evidence for the existence of a
neural transmission pathway due to the absence of hormonal rhythms in the animals
in which (encapsulated) graphs had re-instated behavioral rhythms 269, 270. But the
clearest evidence for the existence of point-to-point neural connections was provided
by the elegant experiment of de la Iglesia et al 271.
SCN output rhythms
In this chapter we will provide evidence that the master clock in the SCN imposes
a temporal structure on the brain and subsequently the peripheral organs via daily
rhythms in the release of its (peptidergic) neurotransmitters in its target areas. Given
the pivotal role of the hypothalamus in homeostatic regulation, the discovery that
the master circadian clock resides in this region was not surprising. After this discovery in 1972 272 numerous neuro-anatomical tracing studies have shown that the
Increased release
Inhibitory SCN signal
Stimulatory SCN signal
Corticosterone
0
6
12
18
24
Circadian time (h)
Figure 2 Schematic representation of the diurnal release pattern of SCN transmitters involved in the circadian control of corticosterone release.
37
chapter 2
projection fibers from the SCN are surprisingly limited and by large restricted to a
few hypothalamic nuclei, prime targets being the paraventricular nucleus of the hypothalamus (PVN), the medial preoptic area (MPOA) and the dorsomedial nucleus of
the hypothalamus (DMH). Therefore propagation of the timing signal from the SCN
mainly proceeds through its contacts with the neuro-endocrine and pre-autonomic
motorneurons of the hypothalamus 273. In the following paragraphs we will show examples of how the SCN enforces its circadian rhythmicity onto the endocrine rhythms
via its neuronal projections to the neuro-endocrine neurons within the hypothalamus,
as well as how it controls metabolic rhythms via its projections to the sympathetic and
parasympathetic pre-autonomic neurons within the hypothalamus. Most likely the
SCN control of behavioral rhythms, such as the daily sleep/wake rhythm, is effectuated via its projections to so-called intermediate neurons in integrative hypothalamic
nuclei such as the DMH and subparaventricular zone (SPZ or subPVN) 274. Indeed, we
will show an example of how the SCN control of glucose metabolism and sleep/wake
behavior can be integrated via its projections to the orexin (also known as hypocretin) neurons in the lateral DMH. Finally, we will provide evidence that light-induced
phase-shifts of the SCN can be transmitted instantaneously from the SCN to the
molecular clocks of the peripheral organs via the autonomic nervous system.
SCN control of neuro-endocrine rhythms
Under baseline conditions, plasma concentrations of the glucocorticoid hormones
released from the cortex of the adrenal gland vary predictably across the day/night
cycle. Both in nocturnal and diurnal species plasma corticosterone (cortisol in humans) concentrations are highest around the time of arousal (i.e., morning for humans and evening for rats). Adrenal glucocorticoid hormones have highly integrated
effects on both energy metabolism and behavior 275. It is thought that the increased
levels of corticosterone at awakening act to enable foraging behavior by increasing the
amount of available energy. Corticotrophin-releasing hormone (CRH) is the principal
neural signal controlling the release of corticosterone from the adrenal gland via its
stimulatory action on the adrenocorticotrophic hormone (ACTH) producing cells
in the anterior pituitary. Together this neuro-endocrine pathway is known as the
hypothalamo-pituitary-adrenal (HPA) axis. CRH is synthesized in neuroendocrine
neurons in the medial parvocellular part of the PVN. Therefore we set out to test the
hypothesis that the circadian rhythms generated in the SCN were incorporated in the
daily activity of the HPA-axis via the release of SCN neurotransmitters onto the CRH
neurons in the medial PVN 276. The combined results of this and several follow-up
experiments are shown in Fig. 2 & 3.
It turned out that vasopressin was an important signal from the SCN necessary to
shape the daily rhythm in plasma corticosterone. As for now the hunt for the hypoth38
chapter 2
esized excitatory SCN signal is still open, although VIP seems a likely candidate 277.
Contrary to our initial hypothesis, however, not the direct connections between SCN
fibers and CRH neurons, but indirect connections via GABAergic interneurons in the
subPVN and the DMH, were most important for this SCN control. The intermediate
neurons in the subPVN and DMH explain the sparse contacts between SCN fibers
and CRH neurons (Fig. 4) as well as the inhibitory effect of an excitatory transmitter
such as vasopressin on the activity of the HPA-axis. More importantly, however, these
intermediate neurons provide a degree of flexibility to the system that helps to explain
how a 12-hour shift can occur in the timing of the corticosterone peak between nocturnal and diurnal species, if the timing of the daily peak in vasopressin release is not
changing between diurnal and nocturnal species.
The daily rhythm in vasopressin release also turned out to be important for the
control of the daily surge in luteinizing hormone (LH) in female rats 278, 279. Again the
SCN projection to intermediate neurons, in this case in the MPOA, seems to be most
important for the control of the daily LH surge, despite the existence of direct SCN
projections also to the GnRH neurons 280.
Our investigations on the circadian control of the nocturnal rhythm in melatonin
release from the pineal gland revealed that in this case vasopressin release from the
SCN fibers was of no importance 281. On the other hand, the recent work of Li et al.
shows that in addition to serving as an important SCN output, vasopressin also has an
important influence within the SCN 282, 283. Moreover, in Alzheimer patients the loss
of SCN vasopressin neurons correlates significantly with an increases fragmentation
of their sleep/wake-rhythms 284.
SCN control of the autonomic nervous system
Using similar experiments as just described to unravel the function of vasopressin in
the circadian control of the HPA- and HPG-axis, we found that the daily rhythm in
plasma melatonin concentrations is generated by a combination of glutamatergic and
GABAergic SCN outputs. However, in this case the prime targets of the SCN projections are not the neuro-endocrine or intermediate neurons, but the pre-autonomic
neurons that are at the origin of the sympathetic innervation of the pineal 285. Ultimately the synthesis and release of melatonin is controlled by the sympathetic input
to the pineal gland 286. We proposed that the activity of the pre-autonomic PVN neurons that are in charge of the sympathetic input to the pineal gland is controlled by
the combination of glutamatergic and GABA-ergic inputs from the SCN 287, 288. The
circadian and light-induced daytime activity of the GABA-ergic SCN projections to
the PVN ensures low melatonin levels during the light period. The nocturnal arrest of
the inhibitory GABA-ergic inputs, combined with the continuously active glutamatergic inputs, enables the pre-autonomic PVN neurons that control the sympathetic
39
chapter 2
Rat
Arvicanthis
DMH
DMH
PVN
PVN
Sub PVN
Sub PVN
SCN
SCN
AVP neuron
CRH neuron
GABA neuron
GLU neuron
Figure 3 Detailed anatomical scheme of demonstrated and putative connections of the suprachiasmatic nucleus (SCN) in the nocturnal rat and the diurnal Arvicanthis ansorgei brain to
explain the opposite effects of VP on the HPA axis in these two species. VP is released during
the light period, both in the nocturnal rat and the diurnal A. ansorgei. In rats VP release
during the light period will inhibit the corticotropin-releasing hormone (CRH)-containing
neurons in the paraventricular nucleus of the hypothalamus (PVN) by contacting gammaaminobutyric acid (GABA)ergic interneurons in the subPVN and dorsomedial nucleus of the
hypothalamus (DMH). On the other hand, in the A. ansorgei, AVP release during the light
period will stimulate CRH-containing neurons because it acts on the glutamatergic, instead
of GABAergic, interneurons in the subPVN and DMH.
40
chapter 2
DAY
NIGHT
Pineal
Melatonin
PVN
Inhibitory
Stimulatory
Silent
SCN
Retina
Figure 5 Schematic presentation of the daily activity pattern of populations of GABAergic
and glutamatergic neurons within the SCN that are implicated in the autonomic control of
the daily rhythm in melatonin release from the pineal gland. During the light period the
pineal-dedicated sympathetic pre-autonomic neurons in the PVN are inhibited by GABAergic neurons that are either active according their intrinsic circadian rhythm or because they
are stimulated by light through the glutamergic efferents from the retina. Although during
the light period also a glutamatergic input to the PVN neurons is active, this does not result
in an increased activity of the pre-autonomic neurons due to the overwhelming inhibitory
GABA input. During the dark period the GABA-ergic neurons are silent either because of
their intrinsic rhythmicity or because they are not activated by light, thus enabling the excitatory glutamatergic input to become effective in stimulating the pre-autonomic PVN neurons
and subsequently melatonin synthesis and release. However, during nocturnal light exposure
(dashed lines in the right half of the figure) the silent GABA neurons (in the ventral SCN) will
be rapidly activated and immediately inhibit the activity of the pre-autonomic PVN neurons
and thereby shut down the synthesis and release of melatonin.
← Figure 4 A transversal section of the hypothalamus in the region of the paraventricular
nucleus (PVN) shows fibers arising from the suprachiasmatic nucleus (SCN), as labeled by
an iontophoretic injection with the anterograde tracer Phaseolus vulgaris leucoagglutinin
(PHA-L) into the SCN, that penetrate the boundaries of the PVN in which cell bodies immunoreactive for corticotrophin-releasing factor (CRF) are stained (dark brown). Branching
and putative termination of SCN fibers are visible just ventral of the PVN close to the ventricle
and in the periventricular and dorsal part of the PVN.
41
chapter 2
input to the pineal gland to become active again and start a new period of melatonin
synthesis and release (Fig. 5).
To investigate further the SCN control of the autonomic nervous system (ANS),
especially its parasympathetic branch, next we focused our attention on the daily
rhythm in plasma glucose concentrations. Maintaining a constant blood glucose level
is essential for normal physiology in the body, particularly for the central nervous
system (CNS), as the CNS can neither synthesize nor store the amount of glucose
required for its normal cellular function. The liver plays a pivotal role in maintaining
optimal glucose levels by balancing glucose entry into and removal from the circulation. From a hypothalamic and chronobiological view glucose production by the liver
is especially interesting because of the clear involvement of both the sympathetic and
parasympathetic input to the liver in glucose metabolism 289-291 and the recently demonstrated strong circadian control of (glucose) metabolism in the liver 292-295. In order
to maintain glucose homeostasis, a complex glucose sensing and regulatory system
has developed within the central nervous system, especially involving hypothalamic
brain areas such as the arcuate nucleus (ARC), the ventromedial hypothalamic nucleus
(VMH), and the lateral hypothalamus (LH). The major part of the neurochemical
make-up of this hypothalamic network is still largely unknown, although recently it
has been shown that the neuropeptide-Y (NPY) containing neurons in the arcuate
nucleus are an important hypothalamic link to effectuate the inhibitory effect of insulin
on hepatic glucose production 296. Using local intra-hypothalamic administration of
GABA and glutamate receptor (ant)agonists we probed the contribution of changes in
ANS activity to the daily control of plasma glucose and plasma insulin concentrations.
The daily rhythm in plasma glucose concentrations turned out to be controlled predominantly by the activity of the sympathetic liver innervation. In fact, the activity of
these liver-dedicated sympathetic pre-autonomic neurons in the PVN was controlled
according to a mechanism very much similar to the mechanism just described for the
SCN control of the daily rhythm in melatonin release, i.e., a combination of rhythmic
GABA-ergic inputs and continuous glutamatergic stimulation. The major difference
between the liver-dedicated and pineal-dedicated pre-autonomic neurons seems to be
the timing of the GABA-ergic inputs. In case of the pineal-dedicated pre-autonomic
neurons this inhibitory input is present during the major part of the light period with
an acrophase around ZT6, whereas for the liver-dedicated pre-autonomic neurons the
acrophase of the GABA-ergic inhibition is somewhere around ZT2 (Fig. 6).
As has become evident from the daily variation in meal-induced insulin responses
296
, intestinal glucose uptake 297 and respiratory functioning 298 also the parasympathetic branch of the autonomic nervous system is under control of the circadian timing
system. Our intra-hypothalamic infusion studies revealed that also the daily changes
in the activity of the parasympathetic pre-autonomic neurons involved a combination
42
chapter 2
of GABA-ergic and glutamatergic inputs. The daily rhythm in SCN-derived GABAergic inputs turned out to be a general principle. However, a major difference between
the circadian control of parasympathetic and sympathetic pre-autonomic neurons
appears to be the origin of the excitatory glutamatergic inputs (Fig. 7). SCN-lesion
studies clearly proved that the excitatory input to the sympathetic pineal-dedicated
pre-autonomic neurons was derived from the SCN neurons 287, but similar SCNlesion studies also clearly showed that the glutamatergic inputs to the parasympathetic
pancreas-dedicated pre-autonomic neurons are not derived from SCN neurons 299.
At present, it is not clear from which extra-SCN source the glutamatergic inputs to
the parasympathetic pancreas-dedicated pre-autonomic neurons originate, but likely
candidates are the ventromedial hypothalamic nucleus (VMH) and arcuate nucleus.
SCN control of peripheral oscillators?
The discovery of clock genes outside the SCN initially scrutinized the status of the
SCN as master oscillator. However, viable transplants of non-SCN tissue do not restore
behavioral rhythms in SCN-lesioned animals 300, and co-culture models showed that
only SCN cells, but not fibroblasts, can confer molecular and metabolic rhythms to
co-cultured cells 301. According to the current opinion, the central pacemaker in the
SCN coordinates the activity of local oscillators in peripheral tissues via behavioral,
neuroendocrine and autonomic pathways 262, 273, 302, 303. However, a clear understanding
of the role of peripheral oscillators in the regulation of the physiological functions of
peripheral organs is still lacking. We investigated whether peripheral oscillators in
the liver are a necessary link in the transfer of circadian information from the central
biological clock to the hepatic glucose production. Removal of either the sympathetic
or the parasympathetic input to the liver indeed caused an obliteration of the daily
rhythm in plasma glucose concentrations 48, 251, but to our surprise transcript levels
of all 5 clock genes studied maintained their rhythmicity in the liver 304. On the other
hand, a liver-specific deletion of the clock-gene Bmal1 caused an exaggerated drop
of plasma glucose concentrations during the light period 305, and demonstrated that
>90% of the >300 rhythmically expressed hepatic genes are dependent on a functional
clock in the hepatocyte 306. Consequently a rhythmic expression of clock genes in
the liver is not sufficient to maintain a rhythmic glucose output from the liver, while
suppressing the rhythmic expression of >90% of the rhythmically expressed genes in
the liver severely disturbs glucose homeostasis. The ~10% cyclically expressed liver
genes not affected by the liver-specific Bmal1 deletion must be regulated by oscillating
systemic signals. Previously, corticosterone, feeding behaviour and body temperature
have already been implicated as important systemic signals for the liver clocks 257, and
now also the autonomic innervation can be added to this list. Using nocturnal light
exposure we found immediate changes in the expression level of both clock genes and
43
chapter 2
PVN
Pineal
Liver
GABA
GLU
SCN
Figure 6 Schematic presentation of the daily activity pattern of suprachiasmatic populations
of GABAergic and glutamatergic neurons implicated in the autonomic control of the daily
rhythms in pineal melatonin release and hepatic glucose production.
A.
PVN
B.
Sympathetic
PVN
LIVER
Parasympathetic
PANCREAS
GLU
GABA
SCN
GLU
GABA
VMH
SCN
Figure 7 Schematic presentation of the daily activity pattern of hypothalamic populations
of GABAergic and glutamatergic neurons implicated in the autonomic control of the daily
rhythms in hepatic glucose production (A) and feeding-induced insulin release (B).
44
chapter 2
glucoregulatory genes in the liver. Interestingly, a selective denervation of the autonomic liver innervation completely prevented the light-induced changes in both clock
genes and glucoregulatory genes 258, again pinpointing the autonomic nervous system
as an important gateway for the SCN to (immediately) reset peripheral physiology.
Conclusions
From the above it will be clear that, in mammals, the output of the biological clock
not only controls daily rhythms in behavior, such as the sleep/wake or feeding/fasting rhythms, but also exerts direct control over many physiological and endocrine
rhythms. Our studies indicate that by balancing its stimulatory and inhibitory output
pathways the biological uses a “push-and-pull” mechanism to control the different
hormone rhythms and the autonomic nervous system. Remarkably, a number of behavioral studies came to the same conclusion 264, 307. In our opinion, one of the most
important aspects of the output of the biological clock is its control of the sympathetic/
parasympathetic balance. In view of the widespread influence of the autonomic nervous system on the physiological state of an organism, it is obvious that a “ying-yang”
balanced regulation of their antagonistic properties is essential for a healthy control
of our daily lives. However, there’s a reverse to every medal, thus a malfunctioning of
the biological clock (or a misalignment of the central and peripheral oscillators) due to
either aging 284, 308, shift-work 309, 310 or a modern Western lifestyle 311 may be an important pre-disposing factor for pathologies characterized by an imbalanced autonomic
nervous system, such as hypertension, type 2 diabetes and the metabolic syndrome.
45
Scope of the thesis
The overall aim of this thesis is to investigate the biochemical and neuronal pathways
utilized by the central nervous system and more specifically the hypothalamus, to
sense and control the daily fluctuations in peripheral glucose metabolism. First, with
regard to the hypothalamic sensing of glucose metabolism I focused on the question:
“How does the biological clock that is located in the hypothalamus and is responsible
for all day/night rhythms in behavior and physiology, receive the necessary metabolic
(feedback) information in order to be able to generate the appropriate output”? Our
second aim was to unravel in part the complex hypothalamic control mechanisms
involved in the control of glucose metabolism and studied which hypothalamic brain
areas and neurotransmitter systems are in control of endogenous glucose production
and peripheral glucose uptake.
In chapter 1 we focus on available data on the role of the autonomic innervation
of the liver in relation to glucose and lipid metabolism as well as on how metabolic
signals are integrated via the gut-brain-liver axis. In chapter 2, we describe how the
biological clock controls the endocrine milieu via the paraventricular nucleus of the
hypothalamus (PVN). The PVN is an important target area of the biological clock and
it contains many neuroendocrine as well as pre-autonomic neurons, both providing
an important gateway to peripheral organs. Recently there has been a revival of the
interest in the CNS control of glucose metabolism. In fact this renewed interest was
an important driving force to start the work described in this thesis.
The research chapters of this thesis are divided in two parts, each describing several
experiments devoted to the two research questions described in the first paragraph.
The experiments in chapters 3-5 were initiated because we hypothesized that in order
to synchronize energy homeostasis with the daily sleep/wake-cycle, the endogenous
biological clock located in the hypothalamic suprachiasmatic nuclei (SCN) needs
to be informed adequately about the peripheral metabolic situation. Therefore, in
chapter 3, we investigated the projections of the arcuate nucleus (ARC) also known
as the “window-of-the-brain”, because this brain area not only contains receptors for
several peripherally circulating metabolic hormones, but is also thought to have a leaky
blood–brain-barrier. Retrograde and anterograde tracing studies were performed to
find out whether the ARC has direct anatomical projections to the SCN, which would
enable a functional connection as well. To study a possible functional significance of
the ARC-SCN projection, in chapter 4 we studied the effect of ghrelin, known for its
role on food intake, as a metabolic challenge to test whether changes in ARC activity
would also result in simultaneous changes in SCN activity. Chapter 5 describes the
search for the anatomical origin of the neuropeptide FF (NPFF) containing terminals
47
in the SCN, as well as a first set of experiments to investigate the functional significance
of this innervation.
Chapters 6-10 describe a number of experiments that were aimed at revealing brain
areas and (peptidergic) neurotransmitter systems in the hypothalamus that provide
input to the pre-autonomic neurons in the PVN that are in control of hepatic glucose
production. In chapter 6 and chapter 7 we studied two peptidergic neurotransmitter
systems, i.e., orexin and melanin-concentrating hormone (MCH) respectively, that
have their origin in the lateral hypothalamus and both had been implicated in the control of feeding behavior and energy metabolism. The MCH studies were performed in
mch precursor (Pmch) gene knockout rats in cooperation with the Hubrecht Institute.
In chapter 8 we investigated the possible involvement of another peptidergic neurotransmitter system, i.e., pituitary adenylate cyclase-activating polypeptide (PACAP).
The hypothalamus contains a high density of PACAP-containing fibers, but PACAPproducing neurons can be found in different brain sides, both within and outside the
boundaries of the hypothalamus. Our interest in PACAP was evoked by the strong
metabolic phenotype of several PACAP and PACAP-receptor knock-out mice. In
chapter 9, we investigated the role of local hypothalamic glucocorticoid signaling in
the well known effects of systemic glucocorticoids on glucose homeostasis. In all of
the above studies we used the tracer dilution technique with a stable glucose isotope
to measure endogenous glucose production rates during the different experimental
conditions. The tracer dilution studies were combined with either euglycemic hyperinsulinemic clamp conditions to study insulin sensitivity, specific denervation of
the autonomic liver innervation to study the involvement of the autonomic nervous
system in the effects observed, or neuroanatomical tracing studies and immunocytochemistry to unravel further the hypothalamic pathways involved.
In chapter 10, a technical note on the measurement of glucose production profiles
along the day/night cycle. Exactly 10 years ago our group clearly showed that there
is a pronounced daily fluctuation in plasma glucose concentrations. At that time it
was also shown that this rhythmic pattern is independent of the day/night-rhythm
in feeding activity, but does need input from the SCN timing mechanism. To study
the relative contribution of changes in glucose production versus changes in glucose
uptake on these fluctuations in plasma glucose concentrations, we performed hourly
blood sampling during infusion of a glucose isotope tracer along the day/night-cycle.
This thesis ends with a perspective and recommendations for future research to
further unravel the role of the biological clock and hypothalamus in control of metabolism.
48
Hypothalamic sensing
of peripheral
metabolic signals
Chapter 3
Ventromedial arcuate nucleus communicates peripheral metabolic information to the suprachiasmatic nucleus
Endocrinology 147(1):283-294 (2006)
Chun-Xia Yi, Jan van der Vliet, Jiapei Dai, Guangfu Yin, Liqiang Ru & Ruud M. Buijs
Abstract
The arcuate nucleus (ARC) is crucial in the maintenance of energy homeostasis as
an integrator of long- and short-term hunger and satiety signals. The expression of
receptors for metabolic hormones like insulin, leptin and ghrelin allows the ARC to
sense information from the periphery and signal it to the central nervous system.
The ventromedial ARC (vmARC) mainly comprises orexigenic neuropeptide AGRP
and NPY neurons that are sensitive to circulating signals. To investigate the neural
connections of vmARC within the central nervous system, we injected the retrograde
and anterograde neuronal tracer cholera toxin B into vmARC. Due to the variation
of injection sites, tracer was also injected into the subependymal layer of the median
eminence (seME) which showed similar projection patterns as the vmARC. The reciprocal connections between vmARC-seME and viscerosensory areas in brainstem and
other circumventricular organs suggest exchange of metabolic and circulating information. For the first time the vmARC-seME was shown to have reciprocal interaction
with the suprachiasmatic nucleus (SCN). Activation of vmARC neurons by systemic
administration of the ghrelin mimetic GHRP-6 combined with SCN tracing showed
vmARC neurons to transmit feeding related signals to the SCN. The functionality of
this pathway was demonstrated by systemic injection of GHRP-6, which induced Fos
in the vmARC, and resulted in about 40% reduction of early daytime Fos immunoreactivity in the SCN. This observation suggests an anatomical and functional pathway
for peripheral hormonal feedback to the hypothalamus which may serve to modulate
the activity of SCN.
Introduction
Although most research on non-photic input to the suprachiasmatic nucleus (SCN)
focused on the intergeniculate leaflet and raphe nuclei, also signals from other parts of
the brain are possible. Herein, one has to consider that the secretion of many hormones
is synchronized by the SCN, therefore logically, feedback from peripheral hormones
to the hypothalamus could also influence this central clock and adjust its output.
Although many metabolic active peripheral hormones/substances have transport sys51
chapter 3
tems to pass the blood brain barrier (BBB), still selected areas in the central nervous
system (CNS) have special sensory functions for circulating substances such as the
arcuate nucleus (ARC). Several studies analyzing the possibility of the ARC to sense
blood borne substances, indicate that the ventromedial ARC (vmARC) may sense
signals directly from the general circulation via the median eminence (ME) 312-314,
and thus functions as an important sensory “window” for blood born substances
to the brain 315-317. This is firmly supported by the presence of receptors with high
expression levels for nearly all known circulating metabolic active hormones such
as leptin, insulin, glucocorticoid and ghrelin in the vmARC 318-321. These hormones
and also glucose can modulate the electrical activity of vmARC neurons 54, 322, 323 and
thus affect the output of vmARC in energy homeostasis. This special role of vmARC
in integrating hormonal signaling was confirmed by the fact that leptin signaling to
CNS crucially depends on normal ARC functioning 324, 325.
The anatomical mapping of ARC in CNS is still updated with different methods
as trans-synaptic 326 or mono-synaptic tracing studies 324, 327. Since a specific vmARC
tracing has not been done yet, a systematic retrograde and anterograde tracing study
is necessary to understand the anatomical relationship of vmARC within CNS.
We therefore studied the connections of vmARC with the CNS and utilized injection
of fluorophore conjugated cholera toxin B (CTB-Alexa Fluor 555) as retrograde and
anterograde tracer into this area. The specificity of the projections of vmARC to SCN
and nucleus of the solitary tract (NTS) were confirmed by control tracing from SCN
and NTS respectively.
The functional interaction between vmARC and SCN was demonstrated by the use
of the natural leptin antagonist, the gut-brain peptide ghrelin 328, which is the only
metabolic molecule so far that can activate vmARC neurons by targeting specifically
AGRP/NPY neurons, and stimulates food ingestion 329. With systemic administration
of the ghrelin mimetic GHRP-6 combined with SCN tracing and AGRP/Fos staining,
the present data showed that GHRP-6 activated vmARC neurons project to the SCN.
Finally the influence of systemic GHRP-6 stimulation on diurnal Fos immunoreactivity in SCN was investigated.
Materials and Methods
CTB tracing
All of the following experiments were conducted under the approval of the Animal
Care Committee of the Royal Netherlands Academy of Sciences. Male Wistar rats
weighing 300±10g (Harlan Nederland, Horst, Netherlands) were housed at room
temperature with a 12 hr light/dark schedule (lights on at 7:00 A.M.). For tract tracing,
rats were anesthetized (0.8ml/kg i.m. Hypnorm, 0.4ml/kg s.c. Dormicum), mounted
with their heads in a standard stereotaxic apparatus, tooth bar set at -3.2 mm, and
52
chapter 3
received tracer injection. Since in contrast to CTB, fluorophore labeled CTB cannot
be applied by iontophoresis, we have used pressure injection. Thus fluorophore conjugated CTB (With Alexa Fluor 555, Molecular Probes, USA, CTB in the text will be
used as abbreviation of CTB-Alexa Fluor 555 for convenience) was used for purpose
of combination of neurotransmitter detection in tracing target area. Finally in 30 cases
CTB injections were aimed at the vmARC. To confirm the reciprocity of connection,
injections with CTB were also aimed at the SCN (n=30) or NTS (n=10), all coordinates
for these regions were adapted from the atlas of Paxinos (1998).
CTB was injected with optimal blow pressure using a glass pipette with a tip of
maximally 50 μm in diameter to minize damage of passing fibers; the glass pipette
was filled with an injection volume of 50-100 nl. For the blowing, we used the similar
pressure as we tried with in vitro tissue, which is strong enough for pushing out the
tracer but relatively limiting the tracer around the tip. The coordinates for the vmARC
injection was 3.3 mm caudal to bregma, 0.4 mm lateral to the midline, and 10.4 mm
below the dura. The coordinates for SCN injection followed Buijs et al 330, for NTS
injection, the coordinate was 0.4 lateral to the midline, 13.8 mm caudal to bregma, 5
mm ventral from dura. After the tracer was injected by pressure injection, the pipettes
were fixed with dental cement to the skull and left in the brain to minimize leakage
from the tract till the animals were sacrificed. This procedure did not lead to visible
extra discomfort of the animals, while the reduction in leakage along the pipette track
is substantial. 15 rats of the SCN tracing were also combined with the placement of a
jugular vein catheter for the intravenous injection of GHRP-6. See below for details
on this operation protocol.
GHRP-6 intravenous infusion
For the intravenous infusion of the GHRP-6, a silicone catheter was implanted in the
right jugular vein according to the method of Steffens (1969). The operation of the
first group of rats (n=15) was combined with SCN tracing such that both operations
were carried out at same time. The second group of rats (n=8) received only catheter
implantation for intravenous infusion of GHRP-6 (n=4) or vehicle (Ringer solution,
n=4) in order to examine Fos immunoreactivity in vmARC and SCN. After surgery, all
rats were given 10 days to recover. After the operation the animals were handled every
day and connected to the jugular catheter to familiarize the rats with experimental
procedures. At day 9, the rats were connected to a drug administration catheter for
24 hr which was kept out of reach of the rats by means of counterbalanced beam. This
allowed all manipulations to be carried out outside the cages without handling the rat.
All of the experiments were performed in the rat home cage.
The drug administration catheter was connected to a syringe containing vehicle
with or without GHRP-6. Infusion into the catheter was initiated at Zeitgeber time
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chapter 3
(ZT)1, ZT0 being defined as the onset of the light period. GHRP-6 was used at a dose
of 5 μg/rat dissolved in 0.4 ml Ringer solution, and 0.4 ml Ringer solution was utilized
as vehicle control infusion, the infusion speed was kept at 0.1 ml/min. All rats were
sacrificed by perfusion 100 min after the infusion.
Food deprivation
We found neurons in subependymal layer of ME (seME) have similar projection pattern as vmARC, and previous studies supposed them to be extension of vmARC 331,
therefore we examine whether seME neurons show a comparable increase in the expression of NPY/AGRP following food deprivation as observed in vmARC neurons 332,
food but not water was removed at ZT1 from four intact rats for 48 hr , subsequently,
animals were sacrificed by perfusion.
Immunocytochemical staining
All rats were deeply anesthetized with a lethal dose of sodium pentobarbital and perfused with saline followed by a solution of 4% paraformaldehyde in 0.1 M phosphate
buffered saline (PBS, pH 7.4) at 4 °C. The brains were removed and kept in fixative
at 4 °C for overnight post-fixation, equilibrated 48 hours with 30% sucrose in 0.1 M
Tris buffered saline (TBS, pH 7.2). Brains were coronal cut in a cryostat into 30μm
section; sections used for immunolabeling were collected and rinsed in 0.1 M TBS.
With ARC, ME, SCN and NTS tracing, whole brain sections were incubated with
rabbit anti-CTB primary antibody (Sigma, USA) at 1:100,000 dilution. Sections of
fasted rats were incubated with rabbit anti-AGRP (1:1500, Phoenix Pharmaceuticals,
USA) or NPY (1:2000, Niepke 091188, NIBR) primary antibody. Sections of second
group of GHRP-6 infusion rats were incubated with goat anti-Fos (1:1500, Santa Cruz,
USA). After all these primary antibody incubation overnight at 4 °C, sections were
rinsed and incubated in biotinylated secondary antibody (goat anti-rabbit or horse
anti-goat IgG) for 1 hr; rinsed and incubated in avidin–biotin complex (ABC, Vector) for 1 hr, reaction product was visualized by incubation in 1% diaminobenzidine
(DAB) (0.05% nickel ammonium sulfate was added to the DAB solution to darken the
reaction product) with 0.01% hydrogen peroxide for 5–7 min. Sections were mounted
on gelatin-coated glass slides, dried, run through ethanol and xylene, covered for
observation by light microscope.
Confocal microscopy
To characterize the functionality of neurons in vmARC that project to the SCN, we
used triple-labeling immunofluorescence to show the colocalization of GHRP-6 induced Fos with AGRP in retrogradely CTB labeled neurons in vmARC from SCN
tracing. Hereto, sections were incubated overnight at 4 °C with goat anti-Fos and rab54
chapter 3
bit anti-AGRP primary antibody, rinsed in 0.1 M TBS, incubated 1 hr in biotinylated
horse anti-goat IgG, and rinsed and incubated with streptoavidin-Cy5 and donkey
anti-rabbit-Cy2 for 1 hr, rinsed, mounted on gelatin-coated glass slides, dried and
covered with glycerol in 0.1 M PBS (PH 9.0) and observed by confocal laser scanning
microscopy.
Analysis of Fos immunoreactivity
The effect of GHRP-6 treatment on Fos immunoreactivity in SCN was determined in
four GHRP-6 or four Ringer solution infusion rats. From SCN sections, tiled images
were captured by a computerized image analysis system consisting of an Axioskop
9811 + Sony XC77 black and white video camera. In these images, the right side of
middle portion SCN was manually outlined. The Fos positive nuclear profiles were
automatically (no user interaction) segmented by a dedicated macro written within
the ImagePro programming environment. For each rat, three sections were measured
90 μm apart (from bregma -1.20 mm to -1.40 mm); the mean number of Fos positive
nuclear profiles from these three sections was calculated. All values are expressed as
the mean ± SEM and data were analyzed using one-way ANOVA. Statistical significance was set at P < 0.01.
Results
CTB injections into the vmARC and seME
Of all animals injected, two rats had a successful injection within the middle part
of vmARC along its rostro-caudal extension, and two within the seME. Due to the
difficulties of accurate vmARC injection, we only focused on middle part (in the anterior posterior direction) of the vmARC which guaranteed maximal vmARC space
for tracing. Misplaced injections were mainly located in a different coronal plane but
usually with same distance from bregma. The misplaced injections in the parenchymal
area, including the external zone of the median eminence and the dorsal or ventrolateral ARC, served as controls for the specificity of the projections of the vmARC and
seME. Misplacement and injection in the third ventricle served as control for leakage
of tracer into cerebral spinal fluid which is almost inevitable. The injections in which
the small tip of glass pipette was blocked by brain tissue and the tracer could not be
pushed out by pressure were used as specificity controls of the used antibodies. In
none of the latter cases any staining was observed which shows that all the observed
staining is due to CTB.
Tracer injections into the vmARC resulted in spread of CTB not only limited to
the ventromedial part of the nucleus, but expanding also into the ipsilateral and the
contralateral subependymal layer of the ME (Fig. 1A). After seME injection, the CTB
distribution covered the dorsal aspect of the ME, between ependymal layer and fibrous
55
chapter 3
p
III
III
A
B
III
III
C
D
III
III
III
E
F
Figure 1 Coronal sections of the hypothalamus show the injection sites of the ARC and ME
and immunocytochemical staining for NPY and AGRP in vmARC and seME. A, CTB was
injected into the vmARC (arrow) and illustrates the spread of tracer into the ipsilateral part
of the seME (double arrows). B, Control injection into ventrolateral ARC resulted in strong
terminal labeling in vmARC area which confirms the interaction between the lateral POMCCART neuron group with ventromedial AGRP-NPY neuron group. Yet such injection did
not result in labeling of fibers in SCN or SON in contrast with vmARC injections (see Fig
2). C, CTB was injected into the middle part of the seME (arrow) and the distribution area
covers the entire dorsal aspect of the ME. D, Injection site of CTB in the external zone of
ME. E, F, 48 hr fasting resulted in incremental visualization of AGRP (E) or NPY (F) in the
ARC neurons, the AGRP and NPY positive neurons are also clearly visible in the seME area
(arrows). III, Third ventricle. Scale bar: A, B, 100μm; C, D 200μm; E, F, 50μm.
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chapter 3
Table 1 Anterograde and retrograde labeling with CTB injection into vmARC and seME
R122
DPi dorsal endopiriform nucleus
Acb nucleus accumbens
LSV lateral septal nucleus ventral part
CLA Claustrum
OVLT organum vasculosum lamina terminalis
VLPO ventrolateral preoptic nucleus
AVPe anteroventral periventricular nucleus
MPOL medial preoptic nucleus, lateral part
VMPO ventromedial preoptic nucleus
BST bed nucleus of the stria terminalis
SFO subfornical organ
Pe periventricular hypothalamic nucleus
PVP paraventricular thalamic nucleus,
R173
R121
R144
N
00
00
000
00
0
vmARC
F
N
–
00
+
00
+
000
–
00
++
0
F
–
+
+
–
+
N
0
0
00
0
0
F
–
–
–
–
+
seME
N
*
*
0
–
0
F
–
–
–
–
++
0
00
00
0
0
000
0
0
*
++
+
++
–
++
++
–
0
000
00
00
0
000
0
–
+
++
+
++
–
+
++
–
–
0
00
0
0
00
0
0
*
+
+
+++
–
+
+
–
*
*
*
*
0
00
0
–
–
++
*
++
–
+
*
–
0
00
–
–
–
0
000
00
0
00
0
0
000
0
0
–
0
00
0
00
00
00
00
0
00
+
+
++
++
++
++
+
++
++
–
+++
+
+
+
+
–
+
++
++
–
++
++
++
–
++
00
00
–
–
–
00
00
00
0
00
00
0
000
00
0
–
0
0
0
0
000
–
0
0
00
+
+++
+++
+++
++
+++
++
++
++
–
++
+
+
+
+++
+
+
+
+
–
++
–
+
–
+
–
0
–
–
–
0
–
00
0
–
00
0
00
0
–
–
0
0
0
0
00
00
00
0
*
–
++
++
++
+
+
–
+
+
–
+
–
+
+
++
+
+
–
–
–
++
++
+++
–
*
–
0
–
–
–
0
–
00
0
–
0
0
0
–
0
–
–
0
–
0
0
0
00
0
000
–
++
+
+
*
+
–
+
+
–
*
–
+
–
+
–
–
+
+
posterior part
LH lateral hypothalamus
SCN suprachiasmatic nucleus
SON supraoptic nucleus
RCh retrochiasmatic area
TC tuber cinerum area
PVN paraventricular nucleus
Sub PVN sub paraventricular nucleus
ARCdm arcuate nucleus, dorsomedial part
ARCvl arcuate nucleus, ventrolateral part
A amygdaloid complex
DMH dorsomedial hypothalamic nucleus
VMH ventromedial hypothalamic nucleus
PMV premammillary nucleus, ventral part
VTM ventral tuberomammillary nucleus
DTM dorsal tuberomammillary nucleus
IGL intergeniculate nucleus
PAG periaqueductal grey
LC locus coeruleus
Bar Barrington’s nucleus
Pr/C1 prepositus nucleus/C1 adrenaline cells
PBr parabrachial nucleus, rostral part
PBc parabrachial nucleus, caudal part
NTS nucleus of the solitary tract
DMNV dorsal motor nucleus of vagus
AP area postrema
*
*
+
–
+
Column N: retrograde labeling neurons; column F: anterograde labeling fibers and terminals.
N, –: no neurons, *:faint, 0: a few, 00:modest, 000: strong.
F, –: no fiber, *:faint, +: a few, ++:modest, +++: strong.
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chapter 3
layer (Fig. 1C). AGRP and NPY containing cell bodies can more easily be detected
in the seME as well as in the vmARC after 48 hr fasting (Fig. 1E,F), while with a normal feeding schedule, we only observed AGRP or NPY fibers and terminals in these
two areas. This observation together with the distribution pattern of the tracer could
support the previous suggestion based on development that seME neurons are an
extension of the ARC 331. Consequently table 1 shows the retrograde and anterograde
labeling in different areas of the CNS with CTB injections into the vmARC and seME.
Control injections
Injections in the ventrolateral ARC (Fig. 1B), dorsal ARC, external zone of the ME
(Fig. 1D) and third ventricle were used as control for specificity of the projections of
the vmARC and seME and leakage of the tracer. Three rats had tracing into external
zone of the ME, three rats had ventricle injection only, two rats got ventrolateral ARC
and dorsal ARC tracing respectively.
The labeling pattern of external zone tracing was consistent with those from Wiegand and Price and Lechan 333, 334. In contrast with the seME injection, it revealed
mainly retrogradely labeled neurons in parvo-cellular paraventricular nucleus (PVN)
(Fig. 3E) and several magno-cellular neurons in PVN and supraoptic nucleus (SON)
III
Figure 2 Coronal sections of the SCN show reciprocal connection between vmARC and
SCN, after CTB injection in the vmARC. Several CTB labeled neurons are present in different
parts of the SCN, fibers and terminals cover the whole nucleus, while around the SCN the labeling is less dense, arrow indicates CTB labeled fibers. III, Third ventricle. Scale bar: 100μm.
58
chapter 3
(Fig. 3F), as well as the periventricular nucleus and magnocellular dorsal ARC. The
absence of detectable anterograde tracing confirms the external zone of ME as a pure
neurosecretory pathway of the hypothalamus. Three control injections into the third
ventricle resulted in labeling of the ependymal plexus and tanycytes or cerebrospinal
fluid contacting neurons along the third and lateral ventricles, some neurons in dorsal
raphe nucleus were also labeled. This pattern was consistent with ventricle tracing
experiments aiming at detecting cerebrospinal fluid contacting neurons in CNS by
CTB-HRP injection 335. Injections into the ventrolateral or dorsal part of the ARC had
projection patterns distinct from that of the vmARC, e.g. with ventrolateral ARC injection even when very close to the vmARC, we only observed some neurons present in
the dorsal and medial part of the SCN (Fig. 3G) and no projections to SON or NTS.
Retrograde and anterograde labeling in central nervous system with CTB
injection into the vmARC and seME.
The injection cases R122 and R173 had their injection tips localized within the
vmARC, while R121 and R144 had their injection tips in the seME. Cases R122-R173
and R121-144 showed some similar pattern of retrograde and anterograde labeling in
CNS, although with several differences exemplified by the presence of retrogradely
filled neurons and anterogradely filled fibers in a number of additional areas after
injection in the vmARC as compared to injection in the seME (see table1), and the
projections of seME area to same brain sites as vmARC are less dense as compared
to vmARC injections.
Areas with reciprocal interaction with vmARC and seME
CTB tracer injection into the vmARC and seME revealed several sites that have extensive reciprocal interaction with this area. In the anterior part of the CNS, reciprocal
connections with this area arise from the anteroventral periventricular nucleus, ventromedial preoptic nucleus and medial preoptic nucleus (lateral part) with labeled cells
and fibers scattered throughout these areas, the labeled neurons were mainly small
size. Both lateral septum and accumbens nucleus connect with vmARC reciprocally,
but labeled fibers were not visible after seME tracing.
We observed that all parts of the SCN show labeled neurons with the highest density
in the medial and dorsal parts. Moreover, abundant labeling of fibers and terminals
were found in the dorsal and ventral part. Few labeled neurons and fibers were also
observed in the area around the SCN (Fig. 2).
From rostral to caudal, the whole extension of the periventricular hypothalamic
nucleus is labeled by scattered neurons and fibers.
Consistent with previously published data about the projection from ARC to the
PVN 336, 337, with vmARC and seME tracing, the triangular shape of the PVN was full
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chapter 3
of labeled fibers and terminals (Fig. 3A,B), in contrast with the dense labeling of fibers and terminals, only few PVN neurons were labeled. While when the injection was
in the external zone of the ME, PVN labeling was characterized by the presence of
a large number of neurons that by location and appearance can easily be recognized
as neuroendocrine (Fig. 3E). Also in the SON the contrast is obvious, vmARC and
seME injection results in a dense innervation in SON (Fig. 3H) while the injection
in the external zone only shows retrogradely filled neurons (Fig. 3F). After vmARC
injection a considerable number of fibers and small sized neurons in the subPVN 338
were also labeled (Fig. 3A). More laterally, the reciprocal connection also only exists
between lateral hypothalamus (LH) and vmARC but not with seME.
Within the whole ARC many anterogradely labeled fibers as well as a few retrogradely labeled neurons were present in the dorsal and ventrolateral part of the ARC near
the border that separates the ARC and ventromedial hypothalamic nucleus (VMH)
(Fig. 1A,B), this labeling pattern of ARC was consistent from rostral to caudal.
Another important target of vmARC and seME is the dorsomedial hypothalamic
nucleus (DMH). Large number of labeled neurons, fibers and terminals visualized
throughout the DMH demonstrate the reciprocal projection between vmARC and
DMH (Fig. 3C). Interestingly, the vmARC and seME tracing revealed a very weak anatomical relationship with the VMH, with just a few neurons and fibers being labeled.
In the posterior hypothalamus, numerous labeled neurons were present in the ventral
premammillary nucleus while fibers were relatively sparse. Of the tubero-mammilary
nucleus, the dorsal part received a denser innervation from vmARC and seME than
the ventral area.
→ Figure 3 Coronal sections of the hypothalamus illustrating anterograde and retrograde
labeling in the hypothalamus after vmARC and seME injections or ventrolateral ARC and
external zone of ME injections. A, vmARC injection results at midlevel of the PVN in many
labeled terminals and few small, oval or fusiform neurons in the medial and dorsal parvocellular (p in B) subdivision, while the mango-cellular aspect (m in B) mostly contained
fibers and single large sized neurons. Note just under the triangular shape of the PVN, very
abundant small sized neurons are distributed over the whole subPVN (arrows), high magnification in B shows more details of the PVN. Nissl counterstaining of same section (D)
revealed that the magno-cellular (m) and parvo-cellular part (p) of the PVN are innervated
by CTB labeled fibers. External zone of ME control tracing resulted an abundant labeling
of the parvo-cellular PVN and several neurons in magno-cellular PVN and SON (E, F). C,
VmARC tracing results in densely labeled fibers, terminals and cell bodies in the DMH, the
central part of the DMH (c) has less labeled fibers and terminals than the dorsal and ventral
part, and the labeled neurons are denser in the ventral part. G, With ventrolateral ARC control injection, only several neurons could be detected in the SCN (arrows), labeling of fibers
was absent. H, VmARC injection results in strongly labeled terminals and fibers in the SON,
labeled neurons are only observed in the peri-nucleus area (arrow). III, Third ventricle. Scale
bar: A, C, 200μm; B, D, E, F, G, H,100μm.
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p
PVN
m
III
III
A
B
p
DMH
III
m
C
C
D
OT
F
E
III
OT
G
H
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chapter 3
In addition, neurons and some axonal terminals were observed in the other three
circumventricular organs (CVOs) after vmARC and seME injection. In subfornical
organ (SFO), neurons and fibers were spread over the vascular area (Fig. 4A). In the
organum vasculosum of the lamina terminals (OVLT), abundant labeling was present
in neurons and fibers bilaterally located in the vascular zone and peri-nucleus area.
A strong labeling of fibers as in the ependymal plexus was also seen along the wall of
the ventricle (Fig. 4B). Similarly, in the area postrema (AP), several fibers and neurons
were observed in the vascular area (Fig. 4C). At the border area between AP and NTS,
we visualized strongly labeled fibers, probably derived from the ependymal plexus
that is often labeled after injection in the seME (Fig. 4C), this labeling pattern in AP
as well as in OVLT, however, was also seen with the third ventricle control injection,
while with control incubation of anti-CTB antibody with sections from non-tracing,
we did not see any such staining, and we also have not found such labeling pattern
with lateral ARC and SCN CTB tracing animals.
In the brainstem, almost all subdivisions of the parabrachial nucleus (PB) contain
labeled neurons and terminals from the most rostral to the caudal part of the nucleus
(Fig. 4E,F). In addition scattered neurons and terminals were seen in the peri-aqueductal gray, locus coeruleus, Barrington’s nucleus and prepositus nucleus.
Similarly to the PB, another visceral integration nucleus, the NTS contained also several labeled neurons and fibers from the caudal to middle part. Consistent with a
previous study, after vmARC injection, we observed a dense labeling of fibers in a
limited area at ipsilateral part in the caudal NTS (Fig. 4H), in view of the paucity of
→ Figure 4 Coronal sections of the brain illustrate anterograde and retrograde tracing in
the CVOs, amygdaloid complex, IGL and brain stem after vmARC and seME injection. A,
Many labeled neurons with their processes are found at the border of SFO and extend to the
vascular core of this organ (arrows); the core area was rarely labeled. Similarly, CTB labeled
terminals are also present more heavily in the border area. Abundant processes within OVLT
(B) and AP (C) are oriented on both sides (double arrows) with almost same orientation on
the border. In AP the labeled fibers in vascular area were also visible (arrowhead). Moderate
number of neurons are scattered in the vascular area (arrows) of both OVLT and AP. D, Many
retrogradely labeled neurons distribute over the whole extension of the medial amygdaloid
complex with sparse labeling in the central part (Ac). E, F, Along the whole extension of
the PB, almost all subdivisions of the nucleus are labeled with CTB, E illustrates the pattern
in lateral PB sub-nucleus (LPB), the central part of the LPB (with high magnification in F)
contains the most strongly labeled neurons (arrow), fibers and terminals (double arrows).
G, Labeled fibers in intergeniculate leaflet from injection case R173 is indicated by double
arrows. H, Labeled neurons are found in both sides of the NTS, some labeled neurons were
also found in the contra-lateral DMV (arrows), dense labeled fibers and terminals are present
in the ipsilateral part (right side) of the medial NTS, arrow shows labeled neuron, double
arrows show fibers and terminals in NTS. ON: optic nerve. Scale bar: A, 50μm; B, C, F,
100μm; D, E, G, H, 200μm.
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chapter 3
PVN
A
B
III
ON
III
Ac
C
D
E
F
DMV
G
H
63
chapter 3
retrogradely labeled neurons we consider these fibers be largely due to anterograde
transport and not derived from retrogradely-labeled neurons as has been suggested
to occur with CTB tracing 339. Interestingly some small sized labeled neurons were
also found in the dorsal motor nucleus of the vagus (DMV) (Fig. 4H). These finding
corroborate our previous finding that the area of the DMV incorporates neurons are
present without an autonomic motor function 340.
Areas with only input to or output from the vmARC and seME
A few regions seem to only provide input to the vmARC and seME as demonstrated
by the presence of merely retrogradely labeled cell bodies and no clear staining of fibers. Since other brain regions at the same level do show labeled fibers, this does not
seem to be a technical limitation of the anterograde tracing. Only retrogradely filled
neurons were detected in the dorsal endopiriform nucleus, claustrum, bed nucleus of
the stria terminalis and posterior part of the paraventricular thalamic nucleus. The
whole extension of most of the medial amygdaloid complex was also strongly retrogradely labeled (Fig. 4D).
With vmARC and seME injections, a dense innervation of the SON, retrochiasmatic
area and tuber cinereum area, but without retrogradely labeled cell bodies indicate that
these areas only get input from vmARC and seME. We also found that the vmARC
and seME tracing resulted in projections to the intergeniculate leaflet (Fig. 4G).
Retrograde tracing from SCN and NTS
In order to provide further evidence for the projections of the vmARC and seME to
SCN and NTS, and to ensure that the projections are not due to uptake from passing
fibers or due to anterograde labeling by retrogradely labeled neurons341, 342, CTB was
injected into SCN and NTS .
Injections of CTB both in SCN and NTS not only revealed neurons in the vmARC
(Fig. 5A,B,D), but also retrogradely labeled neurons in the subependymal layer of the
ME with a location just under the ependymal lining of the third ventricle (Fig. 5C). We
also considered the abundant presence of fibers as evidence for the reciprocity of the
connection of vmARC and seME with SCN and NTS. The labeled neurons in seME
area were different from glia. Firstly, the location of these subependymal neurons is
just under, and very close to the ependymal layer lining the bottom of the third ventricle. In Fig. 5C we can see the difference with ependymal cells that were not labeled
by CTB; Secondly, the orientation of the oval or fusiform shaped labeled neurons was
parallel with the border of the third ventricle, while glia cells have much more processes and may extend to every orientation including the external zone; Thirdly, the
size of subependymal neurons was far larger than glia, either tanycytes or astrocytes.
After CTB injection into the SCN, fibers and terminals were abundant in the lateral
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and dorsal part of the ARC where few retrogradely labeled neurons were present (Fig.
5A,B). Also this projection pattern confirmed the vmARC and seME tracing which
resulted in labeling of neurons, fibers and terminals in SCN, and by ventrolateral and
dorsal ARC tracing which resulted in only labeled neurons in SCN without fibers or
terminals (Fig. 3G).
Functionality of the connections between vmARC and SCN
We addressed the possible role of vmARC neurons in the regulation of metabolism
in relation to their projection to the SCN by examining the induction of Fos in AGRP
III
III
A
B
III
C
III
D
Figure 5 Coronal sections of the hypothalamus illustrate the labeling pattern in vmARC
and seME after tracer injection into the SCN (A,B,C) or NTS (D); A, Labeled neurons in
vmARC after SCN injection are more abundant than in dorsal and ventrolateral ARC, while
fibers and terminals show the opposite labeling pattern. Double arrows show the border
of the vmARC and lateral ARC. B, High magnification gives details of the labeled neurons
(arrow shows the same neuron in B), fibers and terminals in vmARC (double arrows). C,
Labeled neurons (arrow) are present in the seME area after CTB injection into SCN. The
outline of the ependymal layer is visible just over the seME area; labeled fibers not only exist
in the seME area (double arrows) but also scatter in fibrous layer of the ME (arrow head).
D, Labeled neurons (arrows) and fibers (double arrows) in the vmARC and seME area after
NTS control injection.. III, Third ventricle, Scale bar: A, 100μm; B, C, D, 50μm.
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neurons after systemic administration of GHRP-6 combined with SCN tracing. In
addition we observed that GHRP-6 stimulation allowed an easier detection of AGRP
in vmARC neurons, which is normally difficult to detect. Most AGRP positive neurons also expressed Fos and some of these Fos positive AGRP neurons were shown
to project to the SCN as revealed by colocalization with CTB from SCN tracing (Fig.
6). Interestingly, both in ad libitum and feeding restricted rats, it is difficult to detect
AGRP fibers in the SCN, we only observed very thin AGRP positive fibers in the ventral SCN after 2 hr refeeding following 48 hr fasting (data not shown), which suggest
that although AGRP neurons are target of peripheral GHRP-6 and project to SCN,
the detection of this peptide is limited probably because of the low quantity of peptide
present in these nerve terminals.
Following SCN tracing, there was no obvious Fos immunoreactivity in ARC neurons and also not in intact rats ARC that were housed and perfused under the same
conditions as SCN tracing rats, which means SCN tract tracing has no effects on Fos
vmARC
III
seME
Figure 6 Confocal laser scanning micrograph of the vmARC reveals CTB-Alexa Fluor 555
(red) retrogradely labeled neurons after SCN injection are activated by systemic GHRP-6
administration. With GHRP-6 stimulation, Fos (Cy5, blue) was only strongly expressed in
vmARC cells, many of them colocalized with AGRP neurons (Cy2, green) and/or CTB-Alexa
Fluor 555 neurons, arrows show AGRP colocalized with Fos, arrowhead shows CTB-Alexa
Fluor 555 colocalized with Fos. Double arrows show AGRP colocalized with CTB-Alexa
Fluor 555 and Fos, the yellow represents the colocolization of CTB-Alexa Fluor 555 and
AGRP-Cy2. III, Third ventricle. Scale bar: 100μm.
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immunoreactivity in the ARC. Fos immunoreactivity in vmARC induced by GHRP-6
is apparent after 5μg i.v. infusion while the Ringer solution infusion remained without
any detectable Fos in the vmARC (Fig. 7A,B). In addition, Fos immunoreactivity were
also checked in geniculate area and raphe nucleus which are responsible for nonphotic input to the SCN, there were no significant difference between Ringer control
and 5μg GHRP-6 administration in both nucleus.
The number of detectable Fos positive nuclear profiles in middle portion SCN was
counted, both in controls as well as in GHRP-6 infusion animals. Negatively correlated
with the same dose of 5 μg GHRP-6 action on vmARC, the number of Fos positive
nuclei in middle portion SCN was decreased with about 40% as compared with Ringer
solution infusion (195.33 ± 14.45 vs 116.89 ± 4.7 in Ringer solution and 5μg GHRP-6,
P<0.01) (Fig. 7C,D).
III
III
A
III
C
B
III
D
Figure 7 Coronal sections of middle portion of ARC and SCN illustrate the pattern of Fos
immunoreactivity in vmARC and SCN after Ringer (A,C) or 5μg GHRP-6 systemic administration (B,D); A, Low Fos immunoreactivity in ARC after intravenously Ringer solution
infusion; B, With 5μg GHRP-6 intravenously infusion, Fos is strongly expressed by vmARC
neurons; C, Diurnal Fos immunoreactivity pattern in SCN with Ringer control infusion at
ZT1; D, 5μg GHRP-6 infusion resulted in obvious decrease of Fos immunoreactivity in SCN.
III, Third ventricle, Scale bar: A, B, 150μm; C, D, 100μm.
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Discussion
In the present study the properties of CTB as anterograde and retrograde tracer was
confirmed by the presence of tracer labeled terminals and cell bodies for example
in the NTS after injection into the vmARC, which is consistent with earlier tracing
studies on the ARC and NTS 327 and consequently allowed us to study input as well as
output of one area simultaneously.
To avoid maximally uptake of tracer by damage of fibers of passage, instead of a
Hamilton Syringe (400μm), glass pipettes with a tip around 50μm of diameter were
used for pressure injection; thus, the possibility of tracer uptake by passing fibers was
minimized.
This is demonstrated by the fact that only injection in the external zone of the median eminence resulted in retrograde labeling of neuroendocrine neurons in PVN and
SON, which confirms earlier studies 333, 334. Injections in other areas where neuroendocrine fibers pass, such as the subependymal layer- internal zone but also the lateral
ARC did not result in cell body labeling. In contrast injection in the subependymal
layer-internal zone resulted only in labeling of fiber terminals in SON and PVN. These
findings suggest, not only a high specificity of projections between the different layers
of the median eminence, but also a minimal uptake of fibers of passage by the used
method.
The present results confirm and extend previous anatomical studies of ARC and ME,
and also provide a more comprehensive view of the organization of the ARC including
its interaction with the biological clock (Fig. 8).
Moreover, we demonstrate for the first time that the vmARC and seME area, where
the blood brain barrier is operating in a modified manner as other CVOs, which has
permeable capillary networks for penetration of circulating substances 343, has extensive interaction with the SCN, the sensory CVO’s and other parts of the brain.
It is proposed that three typical sensory CVO’s, SFO, OVLT and AP have active
transport systems and receptors for blood borne molecules and play a key role in
sensing and relaying humoral information to other CNS areas 344. Our present data
demonstrate that vmARC and seME have similar specific neuronal connections to
hypothalamic neuroendocrine and autonomic centers as SFO, OVLT and AP. Early
studies already suggest that the BBB border could reside at the area between the ventromedial (or proximal) part and dorsal-lateral (or distal) part of the ARC, thus the
perivascular spaces of vmARC could communicate with the neuroheamal area of the
ME where fenestrated capillaries allow the passage of larger molecules 312-314. Therefore
the present finding that the SCN receives direct input from the vmARC and seME
suggests a route of communication between general circulation and the SCN. I.v.
injection of the ghrelin mimetic GHRP-6 results in Fos positive neurons in a narrow
band in the vmARC and seME. Of all tracer injections in the ARC (n=30), many were
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very close to the vmARC; only 4 injections that were inside and covered the same area
which is known to express Fos after GHRP-6 stimulation had reciprocal interaction
with the SCN. This suggests that a relatively small area is involved in this exchange
of information. Furthermore, injections in the SCN also resulted in the combination
of retrogradely labeled neurons and fibers only in this ventromedial area of the ARC,
which confirms the reciprocity of this connection. In view of (daily) time dependent
organization of metabolism, which depends so crucial on the presence of the SCN 345,
the interaction of vmARC and seME with SCN could serve this timing purpose and
provide the SCN with information about glucose concentration and the associated
level of hormones.
The innervations from vmARC to SCN is a novel finding, however, previous electrophysiological studies on ARC 346 already indicated this connection. Other proof
for the functional interaction between vmARC and SCN are a number of studies that
indicate the physiological and behavioral circadian rhythms are also affected by ARC
malfunction. The fact that ARC lesion by neonatal monosodium glutamate (MSG)
treatment, which mainly destroys NPY cells 347, can compromise the circadian activity
while the SCN is intact 348, 349, could be interpreted together with the present data that
the innervations from vmARC to SCN may relay peripheral hormonal information
to the SCN, and thus affect circadian activity of SCN. At the same time, input from
the SCN to the ARC 346, 350, 351 may time the activity of ARC as shown by rhythmic Fos
expression in the ARC 352 and the rhythmic activity of dopaminergic ARC neurons
negatively driven by VIP from SCN 353. Actually, such SCN-CVO reciprocal connection was already demonstrated for the SCN-SFO and SCN-OVLT interaction 354, 355.
Further evidence for a more general interaction between SCN and CVOs including the
ARC can be found in studies describing the action of prokineticin 2 that is synthesized
in the SCN and for which receptors have been shown in SFO and the vmARC 265, 356.
Together these studies suggest the capacity of the SCN to modulate the properties of
the CVOs, probably in order to control or regulate the sensitivity of CVOs to peripheral signals, and the present study indicates that not only via the SFO and OVLT but
also via the vmARC and seME these signals may be relayed to the SCN as well. In
view of the high sensitivity to peripheral metabolic hormones in vmARC, the possible
feedback pathway for these hormones to the SCN is proposed to be via this area.
Systemic administration of ghrelin mimetic GHRP-6, combined with SCN tracing
showed that AGRP neurons activated by GHRP-6 project to the SCN; at same time
the diurnal Fos immunoreactivity in the SCN was reduced by 40%, suggesting that
ghrelin mimetic GHRP-6 could interfere with the activity of the SCN via vmARC.
The obvious decrease of Fos in the ventrolateral SCN suggests a possible regulation
in the light receiving part of the SCN. The fact that the presence of AGRP in the SCN
as compared to the PVN is so sparse, may indicate that a certain selection of neurons
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project to the SCN or that collaterals of vmARC neurons may contain transmitters in
different proportions.
It is well known that most non-photic inputs to the SCN have the ability to reset the
clock when they are provided at daytime 357, 358, non-photic inputs to the SCN were
shown to arise from the intergeniculate leaflet 359 and raphe nucleus 360. In addition
non-photic inputs are also known to inhibit photic responsive Fos expression in the
SCN at night time 361. In the present study with peripheral GHRP-6 administration,
there is no obvious variation of Fos immunoreactivity in geniculate area and raphe
nucleus, which indicates that these areas are not activated. Consequently the GHRP-6
information relayed by vmARC to SCN as indicated by Fos diminishment in SCN, is
another functional support of the anatomical connection as presented here between
vmARC and SCN and suggests that pharmacological effects of ghrelin may inhibit the
activity of the SCN during the light period. This observation agrees with the fact that
with a normal feeding schedule ghrelin peaks after dark onset 347, suggesting another
central function of ghrelin such as interaction between locomotion and metabolism
362, 363
.
Since the SCN is essential for the organization of the daily metabolic activity such
that the daily rhythm of plasma glucose and metabolic hormones are driven by the
SCN 345, the present results provide an anatomical basis for our previous data that
metabolic cues indeed could influence circadian activity of e.g. vasopressin neurons
in the SCN 364. Further research is needed to elucidate the effect of the metabolism
related non-photic input on SCN functionality and the possible neurotransmitters
that are involved in the signaling.
Naturally the neuronal connections of vmARC with other areas in the CNS may
also implicate those areas as potential participants in metabolism. Here we would like
to stress the role of interaction between vmARC and CVOs, the classical CVOs are
not only engaged in monitoring changes in metabolic, osmotic, ionic and hormonal
composition but also show neuronal activation or inhibition by cytokines 365-367. Here
we show that SFO, OVLT and AP have reciprocal connections with vmARC and seME,
centers for the control of food intake, this suggests a functional interaction of CVO’s
for example in cytokine activity and sickness behavior 368, and could be the anatomical basis for anorexia and weight loss during inflammations. In addition, the present
result that amygdala complex and nucleus accumbens provide input to the vmARC
and seME, supports the significance of limbic structures in energy homeostasis. This
possibility is supported by the fact that chemical manipulation of nucleus accumbens
induced high Fos expression in ARC neuropeptide Y neurons 369.
Moreover, the vmARC and seME area also has reciprocal connections with visceral
sensory integration sites such as the PB and NTS, as was shown partially before 327,
370
. This indicates that vmARC and seME may integrate hormonal information with
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Ventromedial arcuate nucleus connection within CNS
Reciprocal
Input
Output
SFO
LSV
IGL
PVT
PAG
PB
LC
Acb
PVN
sPVN
DMH
LH
NTS AP
Am
OVLT
SCN SON
PMV
vmARC
Figure 8 Sagittal scheme illustrates the main connections of vmARC within central nervous
system. Reciprocal connections are shown with blue areas; yellow areas represent input to
vmARC; red areas represent output from vmARC. For abbreviations, see table1.
signals from first order visceral sensory centers 371, 372. Logically, the outcome of this
interaction should be signaled to many sites including the SCN and is necessary for
the multi-level central control of visceral activities.
Our present data provide the anatomical and functional basis that both humoral and
neuronal metabolic information may be relayed back to the SCN via the vmARC and
seME. Herein the vmARC and seME area is responsible for the first order integration
of circulating signals. When the normal metabolic balance is seriously disturbed, e.g.
by night-eating syndrome 373 or stress, this may influence the integrative activity of
ARC as well as the organizational activity of the SCN. Thus a slight disturbance at the
level of these essential integration sites raises a serious risk of an unbalanced energy
state and possibly obesity, diabetes or other metabolic diseases 374.
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A circulating ghrelin mimetic attenuates light-induced phase delay of mice
and light-induced Fos expression in the suprachiasmatic nucleus of rats
Eur J Neurosci. 27 (8), 1965-1972 (2008)
Chun-Xia Yi, Etienne Challet, Paul Pévet, Andries Kalsbeek, Carolina Escobar and Ruud M Buijs
Abstract
Anatomical evidence suggests that the ventromedial arcuate nucleus (vmARC) is a
route for circulating hormonal communications to the suprachiasmatic nucleus (SCN).
Whether this vmARC-SCN connection is involved in the modulation of circadian activity of the SCN is not yet known. We recently demonstrated, in rats, that intravenous
injection of a ghrelin mimetic, GHRP-6, during the daytime activated neurons in the
vmARC and reduced the normal endogenous daytime Fos expression in the SCN. In
the present study we show that i.v. administration of GHRP-6 decreases light-induced
Fos expression at ZT13 in the rat SCN by 50%, indicating that light-induced changes in
the SCN Fos expression can also be reduced by GHRP-6. Because it is difficult to study
light-induced phase changes in rats, we examined the functional effects of GHRP-6 on
light-induced phase shifts in mice and demonstrated that peripherally injected GHRP6 attenuates light-induced phase delays at ZT13 by 45%. However, light-induced Fos expression in the mice SCN was not blocked by GHRP-6. These results illustrate that acute
stimulation of the ghrelinergic system may modulate SCN activity, but that its effect
on light-induced phase shifts and Fos expression in the SCN might be species related.
Introduction
Daily rhythms of behavior and physiology of mammals are generated by the central
biological clock located in the suprachiasmatic nucleus (SCN). The activity of the SCN
can be entrained by external photic stimuli as well as adjusted by non-photic factors.
Under a normal 12/12 (light/dark (LD)) cycle, the circadian rhythm of locomotor
activity is synchronized with the LD cycle 375. Light exposure during the (subjective)
dark period will shift the endogenous activity rhythm backward or forward, depending on the timing of the light. Most non-photic stimuli producing behavioral arousal,
such as novel wheel access and social interaction, can only shift the locomotor activity
during the subjective daytime and are less effective during the subjective night 376, 377.
However, non-photic stimuli can interfere with the photic response during the subjective night, and behavioral arousal has been shown to attenuate light-induced phase
shifts 378-381. The most important areas relaying non-photic information to the SCN,
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by their serotonergic or NPYergic and GABAergic afferents, respectively, are thought
to be the midbrain raphe and the intergeniculate leaflet of the thalamus (IGL) 360, 382386
. NPY can inhibit photic phase shifts both in vivo and in vitro 387-390, and this effect
was confirmed in NPY-/- mice in which such influence is abolished 391. Furthermore,
application of Y5 receptor antagonists can reverse the inhibitory effect of NPY 387, 392.
Systemic administration of the ghrelin mimetic GHRP-6, whose physiological analogy
to ghrelin has been well confirmed 328, 393, can activate ARC NPY neurons of such different species as rat, mouse and hamster 394-396. The recent finding that in the ventromedial
arcuate nucleus (vmARC) Agouti-related protein (AGRP)/NPY neurons project to
the SCN-opened up the possibility that part of the NPY terminals in the SCN might
be derived from another source than the IGL and may come from the ARC 243. The
importance of ghrelin-induced feeding via the ARC was confirmed by intranuclear
injection 397, although several other hypothalamic nuclei also express abundant ghrelin
receptors 398. Circulating GHRP-6 reduces daytime endogenous Fos immunoreactivity
in the rat SCN 243, suggesting that ghrelin might be able to influence the activity of the
SCN as a non-photic stimulus. Indeed, a recent study on mice showed ghrelin-induced
phase advance when applied at circadian time 6, both in in vitro cultured SCN slices
and in in vivo fasting condition 399. This raises the question whether ghrelin, as a strong
hunger signal, can disturb light entrainment effects on the biological clock.
In the present study, we confirmed the activation of the vmARC AGRP/NPY neurons after i.v. injection of GHRP-6 by Fos expression in these neurons. In order to
investigate whether GHRP-6 could also modulate the photic activation of the SCN
first we studied the light-induced Fos immunoreactivity pattern at ZT13 in the rat
SCN, with or without a prior i.v. injection of GHRP-6. To confirm that the reduced
light-induced Fos expression after prior GHRP-6 treatment was an indication of a
reduced capacity of light to shift the phase of the SCN, we also examined, at ZT 13,
the effect of GHRP-6 on the light-induced phase shift in locomotor activity. Since rats
are known to be less reliable for determining light-induced phase shifts, these studies
were performed in mice.
Materials and Methods
Animals
Experiments 1 and 2 were aimed at investigating the effect of GHRP-6 on light-induced changes in SCN activity. These experiments were conducted in the Netherlands,
with the approval of the Animal Care Committee of the Royal Netherlands Academy
of Arts and Sciences. Sixteen male Wistar rats weighing 250–350g (Harlan Nederland,
Horst, The Netherlands) were housed at room temperature with a 12hr/12hr light/
dark regimen (lights on at 7:00 AM.). Animals were housed in separate cages one week
before their operation. Food and water were available ad libitum.
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Experiments 3 and 4 were performed with mice in accordance with the principles
of laboratory animal care set forth in NIH publication 86-23 (revised 1985) and the
French national laws. Forty-two male C57BL/6J mice (Charles River laboratories,
L’arbresle, France) were purchased when 8 weeks old, housed at room temperature
and exposed to a 12hr/12hr light/dark cycle for 3 weeks before the start of the experiments. Food and water were available ad libitum.
Rat experiments
To administer GHRP-6 systematically, and to avoid stress due to handling, restraint or
anesthesia, an intravenous silicone catheter was implanted through the right jugular
vein according to the method of Steffens 400, when the body weight of the rats reached
300g. After surgery, the rats were given at least 10 days to recover. Handling, vehicle
(saline) injection and sham blood sampling (i.e., blood was withdrawn and immediately returned) were carried out regularly, starting three days before the experiment,
to familiarize the rats with the experimental procedures. On day 9, the rats were connected permanently to a drug administration catheter for 24 hrs, which was attached
to a metal collar and kept out of reach of the rats by means of a counterbalanced beam.
This allowed all manipulations to be carried out without handling the rat. All of the
experiments were performed in the rat’s home cage. On day 10, the drug administration catheter was connected to a syringe containing the infusion solution.
Experiment 1 investigated the activation of AGRP/NPY neurons by GHRP-6. Eight
rats were divided into two groups, one receiving a GHRP-6 (0.5ml; 50μg /300g body
weight, n=4) and the other receiving vehicle (Saline, 0.5ml/300g body weight, n=4)
by infusion into the jugular vein catheter both at ZT2. The dose of 50μg GHRP-6 was
derived from similar studies showing activation of ARC neurons with intravenous
injection 401, 402. The physiological relevance of this dose was validated by their common
effects on Fos induction and growth hormone releasing hormone 328, 393. Moreover, in
our previous experiments, a higher dose, e.g. 100μg/300g, did not induce more Fos
immunoreactivity in the ARC. The infusion speed was kept at 0.1ml/min. Ninety min
after the i.v. infusion, all rats were sacrificed by intra-atrial perfusion under deep
anesthesia preceded by a lethal dose of i.v. sodium pentobarbital i.v. with saline, followed by a solution of 4% paraformaldehyde in 0.1M phosphate buffer (pH 7.4) at
4°C.
For Experiment 2, 8 rats were randomly divided in two groups. Ten min before
ZT13, one group was infused with GHRP-6 (0.5ml; 50μg /300g body weight, n=4)
and the other with vehicle (Saline, 0.5ml/300g body weight, n=4) into the jugular vein
catheter. At ZT13, 200 lux light exposure was applied to all the rats for 10 min. Ninety
min after the light exposure all rats were sacrificed under the same conditions as the
animals in Experiment 1.
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After perfusion, all the brains were removed and kept in 4% paraformaldehyde at
4°C for overnight post-fixation. After equilibration for 48 hrs with 30% sucrose in
0.1M Tris-buffered saline (TBS), brains were cut with a cryostat into three series of
30μm sections, and one series of sections dedicated to immunocytochemical staining
were collected and rinsed in 0.1 M TBS.
To visualize the action of GHRP-6 on AGRP/NPY neurons in vmARC, we used
double-labeling immunofluorescence. Sections were incubated overnight at 4°C with
goat anti-Fos (1:1500; Santa Cruz Biotechnology, Inc., Santa Cruz, CA) and rabbit
anti-AGRP (1:1000; Phoenix Pharmaceuticals, Belmont, CA) primary antibody. Sections containing the SCN were incubated only with rabbit anti-AGRP (1:1500).
For Fos and AGRP double staining, sections were then rinsed in 0.1M TBS, incubated for 1 hr in biotinylated horse anti-goat IgG, and then in streptoavidin-Cy5 (for
Fos) and donkey anti-rabbit-Cy3 (for AGRP) also for 1 hr, rinsed, mounted on gelatincoated glass slides, dried, covered with glycerol in 0.1M PBS (pH 9.0), and put under a
confocal laser scanning microscope. For AGRP immunostaining in the SCN, sections
were rinsed and incubated in biotinylated secondary antibody and then incubated in
avidin–biotin complex (ABC, Vector) for 1 hr. The reaction product was visualized by
incubation in 1% diaminobenzidine (DAB) (0.05% nickel ammonium sulfate was added to the DAB solution to darken the reaction product, DAB/Ni) with 0.01% hydrogen
peroxide for 5-7 min. Sections were mounted on gelatin-coated glass slides, dried,
run through ethanol and xylene and covered for observation by light microscope.
To assess Fos immunoreactivity in the central nervous system (CNS), brain sections were incubated with goat anti-Fos primary antibody overnight at 4°C, tissues
were rinsed and incubated in biotinylated secondary antibody (horse anti-goat IgG)
for 1 hr; rinsed and incubated in avidin–biotin complex (ABC, Vector) for 1 hr, and
visualized by DAB reaction.
For counting the Fos-immunoreactive neurons in the SCN, tiled images were captured by a computerized image analysis system consisting of an Axioskop 9811-Sony
XC77 black and white video camera (Sony Corp., Tokyo, Japan). In the images, both
sides of the middle portion of the SCN were manually outlined. The Fos-positive
nuclear profiles were automatically segmented by a dedicated macro written within
the ImagePro programming environment. For each rat, three sections were measured
90μm apart (from bregma -1.20 to -1.40 mm); the mean number of Fos positive nuclear profiles from these three sections was calculated. All values are expressed as the
mean ± SEM/per section, and data were analyzed using one-way ANOVA. Statistical
significance was set at P < 0.05.
Mice experiments
After adaptation to their cages, equipped with a running wheel, forty-two mice were
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transferred to constant darkness by not allowing the lights to come on at the normal
time, which was designated as ZT0, the onset of the subjective day.
In Experiment 3, twenty-four mice were divided at random into 4 groups to investigate the effect of GHRP-6 on photic phase shifts. On the first day of darkness, group 1
received an i.p. saline injection (0.2 ml, n=6), and group 2 a GHRP-6 (0.2 ml, 1000μg/
kg; n=6) i.p. injection 15 min before being exposed to 100 lux of light for 10 min at
ZT13. In order to investigate the GHRP-6 or saline effect per se, the control groups
3 and 4 received the same volume and dose of GHRP-6 or saline respectively by i.p.
injections 15 min before ZT13 without light exposure.
Wheel running activity data were recorded by a PC equipped with an acquisition
card (Dispsi Industrie, Chatillon, France). Phase shifts were calculated by projecting
the phase of onset of nocturnal locomotor activity during the first 10 days in constant
darkness to the mean onsets during the last 10 days under a light-dark cycle (Clocklab
software, Actimetrics, Evanston, IL). All values are expressed as mean ± SEM.
In Experiment 4, eighteen mice were divided into 4 groups to study the GHRP-6
effect on light-induced Fos expression in SCN. On the first day of darkness half of the
animals were exposed to 100 lux of light for 10 min at ZT13. Within both groups (i.e.
light exposed (n=5) and animals maintained in darkness (n=4)), half of the animals
received the i.p. GHRP-6 pretreatment, whereas the remaining animals received vehicle. This part of the protocol was similar to that of Experiment 3. Mice were then
all perfused within 60 min after the onset of light or without light. Perfusion, postfixation, immunocytochemical staining all followed the same methods as in experiment 2. For counting Fos immunoreactivity positive cells, three adjacent sections of
30μm were measured in the mid area of the SCN.
Both phase-shifting and Fos counting data in mice were analyzed by a two-way
ANOVA (Group (2 levels), i.e., light versus dark; and Treatment (2 levels), i.e., GHRP-6
versus saline). If significant main or interaction effects were detected, it was followed
by a post-hoc LSD test. The differences were considered significant when P values
were lower than 0.05.
Results
Experiment 1 GHRP-6 activates AGRP/NPY neurons in the arcuate nucleus.
Following the i.v. saline control injections into the circulation via the jugular vein,
almost no Fos-immunoreactive neurons in the ARC could be detected. Furthermore,
AGRP-immunoreactive cell bodies in the vmARC were also difficult to visualize. Only
AGRP-immunoreactive fibers were visible in the vmARC and other areas receiving
a vmARC projection. In contrast, after GHRP-6 injections, not only many vmARC
neurons showed strong Fos expression but also many of them were clearly AGRPimmunopositive, confirming the activating effect of ghrelin on AGRP/NPY neurons
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III
Figure 1 Systemic administration of GHRP-6 activates AGRP neurons in vmARC which
project to ventral SCN. Double-labeling immunofluorescence showing AGRP cell bodies
(Cy3-red) in the ventromedial part of the ARC after GHRP-6 stimulation, the same area
also presents most of the GHRP-6 inducible Fos immunoreactivity (Cy5-blue), the majority
of AGRP cell bodies being colocalized with Fos. The arrow shows a typical double labeled
neuron. Scale bar: 100μm.
. The co-localization of Fos and AGRP could be more readily shown by confocal immunofluorescent microscopy (Fig. 1). Consistent with previous studies in the
hypothalamus, Fos activation by GHRP-6 stimulation was limited to the vmARC and
was not observed in other areas such as PVN, dorsomedial and ventromedial nuclei.
In the brain stem, Fos positive cells in the area postrema were observed after GHRP-6
stimulation but not in the saline control animals. This latter observation is consistent
with other studies using a similar dose of GHRP-6 395, 403. However, since the area postrema has no direct projection to the SCN, this area was not further processed. Under
these conditions, with GHRP-6 induced Fos expression in the hypothalamus limited
to vmARC neurons, several AGRP terminals were also found in the ventral SCN
(data not shown), as further evidence for the vmARC-SCN projection 243. Due to the
dense IGL-NPY projection, it was not possible to identify whether these AGRP fibers
also contain NPY or whether the amount of NPY staining in the SCN had changed.
328, 329
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III
III
A
B
Figure 2 GHRP-6 interferes with light-inducible Fos immunoreactivity in the rat SCN.
90 min following a 10-min light stimulation of 200 lux at ZT13, saline control pre-treated
animals show many Fos immunoreactive cells in SCN (A). The light-induced Fos reaction is
attenuated by around 50% by the GHRP-6 pretreatment (B). Scale bar: 100μm.
Therefore we only applied the AGRP staining in our study, with the knowledge that
AGRP nearly completely co-exists with NPY in vmARC 332.
Experiment 2 GHRP-6 reduces light- induced Fos expression in rat SCN in the
early subjective night
Light exposure at ZT13 resulted in a large amount of Fos expression in the SCN,
Fos positive neurons were mainly clustered in the ventral part of the SCN. Along
the rostral - caudal axis, Fos positive neurons were mainly distributed in the middle
part of the nuclei (therefore we selected sections from bregma -1.20 to -1.40 for cell
counting) (Fig. 2). The light-induced number of Fos immunoreactive cells was 60.0 ±
9.9 per section after saline control injections, while after 50μg GHRP-6 injection, the
light-induced number of Fos immunoreactive cells was significantly reduced to 28.8
± 3.0 per section, (P= 0.02; Fig. 3).
Figure 3 GHRP-6 inhibited light-induced
Fos expression in rat but not mouse SCN
(mean ± SEM.), * The GHRP-6 + light group
is significantly different from the saline +
light group, P=0.02
Fos positive cells per section
180
150
Saline
GHRP-6
120
90
60
*
30
0
Rat
Mouse
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0
Hours
24
48
0
Hours
24
48
Days
LD
DD
Light + Saline
0
24
Light + GHRP6
48
0
24
48
Days
LD
DD
Dark + Saline
Dark + GHRP6
Figure 4 Phase shifts of wheel-running activity rhythms of mice treated with various combinations of light, dark, saline and GHRP-6 at ZT13. Saline or GHRP-6 were injected i.p.
at ZT12.7 prior to light exposure. GHRP-6 treatment attenuates light-induced phase delays
compared to saline injections. Without light, GHRP-6 or saline injections have no obvious
effect on circadian rhythm.
Experiments-3 and -4 GHRP-6 decreases photic phase-shifts but not SCN Fos
expression in the early subjective night in mice
Photic stimulation at ZT13 following saline administration resulted in a phase delay of
63.6 ± 6.5 min; administration of GHRP-6 prior to light exposure resulted in a lightinduced phase delay of 34.8 ± 2.2 min. Injection of saline or GHRP-6 alone at ZT13
(i.e. without light exposure) did not result in a phase shift (5.0 ± 9.5 min vs 3.6 ± 9.0
min) (Fig. 4). The two-way ANOVA indicated a significant effect of Group (i.e. light
vs dark exposure) (F(1,17)=48.3; p<0.001), but the effect of Treatment did not reach
statistical significance (F(1,17)=3.8; p=0.07), nor did the interaction of Treatment x
Group (F(2,17)=3.2; p=0.09). The light-induced phase-shift was significant in both
the saline-treated (p<0.001) and the GHRP-6 treated (p=0.002) animals. On the other
hand, the light-induced phase shift was significantly smaller in the GHRP-6 group
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20
Phase shifting (min)
Figure 5 Phase shift of locomotor activity
rhythms (mean ± SEM.) in mice with GHRP6 or saline pretreatment with or without a
light pulse at ZT13.
* Saline + light is different from saline + dark
(P=0.002);
** GHRP-6 + light is statistically different
from GHRP-6 + dark (P<0.001);
^ GHRP-6 + light is statistically different
from saline + light (P=0.019).
0
Light
Dark
-20
-40
*^*
-60
-80
Saline
GHRP-6
*
than in the saline group (p=0.02). These results demonstrate that GHRP-6 reduced
the light-induced phase delay (Fig. 5).
Light-induced Fos immunoreactive cells in mice SCN with saline injection was
114.1 ± 11.5 per section, with GHRP-6 injection, 121.4 ± 9.3 per section. Without light
treatment, there is sparse endogenous Fos expression in SCN with GHRP-6 or saline
treatment (16.33 ± 1.42 vs 15.58 ± 1.89 per section). Two-way ANOVA indicated a
significant effect of Group (i.e. light exposure vs dark) (F(1,14)=124.20; p<0.001), but
no effect was showed with Treatment (F(1,14)=2.65; p=0.13), also no effect of Treatment x Group (F(2,14)=2.9; p=0.11), which means GHRP-6 pretreatment can not
interfere light induced Fos expression in mice SCN.
Discussion
VmARC relays circulating ghrelin signal to SCN
In our previous study, we showed that the efferent projections of the arcuate nucleus
also reach the SCN. In addition, we showed that animals kept in LD, that received a
GHRP-6 injection in the early daytime (i.e. ZT2) showed a reduction of endogenous
Fos expression in the ventral SCN. Considering that the vmARC can sense circulating
GHRP-6, and has projections to the SCN, we assumed that this Fos reduction in the
SCN was due to a direct GHRP-6 stimulation on vmARC neurons and subsequent
vmARC signaling to the SCN. In the present study we therefore aimed at investigating the possibility that circulating GHRP-6 can indeed inhibit SCN activity and thus
may counteract the effect of nocturnal light exposure. Indeed GHRP-6 pretreatment
at ZT13 significantly reduced (50%) the light induced Fos activation in rat. In addition, light-induced phase-shifts experiment with mice showed likewise that the light
induced phase shift had decreased by 45% after GHRP-6 injection. However, in spite
of the GHRP-6 induced reduction of the light-induced phase shifts, mice did not show
a reduction in SCN Fos expression. Interestingly this observation agrees with a study
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of Edelstein et al.378 showing a reduction of a light-induced phase shift by non-photic
stimuli in hamsters, but no reduction of the light-induced Fos or PER1 expression.
The present observation that in contrast to the mouse, in the rat, GHRP-6 interferes
with the light-induced Fos activity may indicates that the mechanisms of non-photic
interference with SCN activity may be species-related.
Ghrelin receptors are present in many areas in the central nervous system, including
in the SCN. Recently, evidence has been presented that ghrelin injected into the general circulation may also pass the blood brain barrier 404. In addition, there are reports
that ghrelin is produced within the hypothalamus 405-407. However, considering the
sensitivity to ghrelin, clearly the neurons in the vmARC are the most prominent group
in the brain that are activated by both peripheral and central ghrelin stimulation 329, 397,
408
, which supports the proposal that the vmARC may be viewed as a hormonal sensor
in the hypothalamus 316, 317. In addition, ghrelin-driven feeding behavior is independent
of the feeding schedule, which means animals may respond to ghrelin with or without
food deprivation. Herein the function of GHRP-6 is not different from insulin, leptin
and glucose - all substances that have been shown to be able to influence vmARC
neuronal activity 319, 320, 409, 410. By its efferent projections the vmARC can subsequently
affect the SCN and other structures within and outside of the hypothalamus 243. It is
important to consider that ghrelin receptors have been described in other areas of
the CNS, including the SCN 321, 398, indicating that if GHRP-6 is able to penetrate the
blood brain barrier it may also affect these other brain areas directly.
Several arguments favor an explanation of the present data whereby GHRP-6 acts at
the level of the vmARC. Firstly, since the vmARC is outside the blood brain barrier 313,
411, 411, 412, 412
, the Fos expression of its neurons more than likely indicates a direct activation by circulating GHRP-6, a result which is supported by in vitro electrophysiological recordings of vmARC neurons 413. Indirect evidence supporting this explanation
comes from a recent study on accessibility of circulating leptin to the hypothalamus,
which showed that ARC neurons expressing the long form of the leptin receptor have
more specific and direct contact with circulating leptin compared to other hypothalamic neurons that have no direct access to the circulation 414; Secondly, injection of
GHRP-6 into the cerebral ventricles not only results in Fos expression in the vmARC
but also Fos expression in the paraventricular nucleus (PVN), dorsomedial nucleus
(DMH), lateral hypothalamus, and the nucleus of the solitary tract 415. Because this
response cannot be observed after i.v. injections, these data indicate that ghrelin receptors in other CNS areas other than circumventricular organs 344 such as the vmARC
321, 398
cannot be easily reached by peripheral ghrelin or GHRP-6. Thirdly, binding of
GHRP-6 to its receptor, either in the CNS from intracerebral administration, or in
the ARC from the peripheral circulation, only activates neurons as indicated by Fos
induction or by electrophysiological recording of activity 416. Since the activation of
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the vmARC is known to induce an inhibitory effect in its projection areas, such as the
lateral ARC 417, 418, it is likely that also the projection of the vmARC to the SCN has an
inhibitory effect on its target neurons. Consequently, the inhibition of Fos expression
in the SCN after i.v. administration of GHRP-6 can be considered as an indirect effect
from circulating GHRP-6 stimulation, via the vmARC. Lastly, the modulating effect of
the blood brain barrier is also illustrated by a recent publication by Yannielli et al. 399,
who observed a direct phase shifting effect of ghrelin on the SCN in vitro, but failed
to observe a similar phase shift in vivo.
Circulating ghrelin indirectly affects the SCN as a non-photic stimulus
Fos is a well-known neuronal marker that reflects the activation of SCN neurons
after a light stimulus. However, the decreased light-induced Fos expression following
GHRP-6 pretreatment does not necessarily mean that the effect of light on the circadian activity of SCN neurons is blocked. Therefore, we examined to what extent a
GHRP-6 injection was able to prevent the light-induced phase shift at ZT13. Clearly,
the bolus injection of GHRP-6 into the circulation in mice had a functional consequence, i.e. it caused a reduction of the light-induced phase delay at ZT13, without
effect on Fos expression in SCN. Consequently just like other non-photic stimuli,
such as locomotor activity 378, ghrelin may modulate the light-induced phase shift of
the SCN without affecting Fos expression. The mechanisms for this influence on the
locomotor outcome via the SCN still needs to be further understood. Clearly there
must be slight differences among rodents’ SCN organization that need to be explored
in order to understand this interesting effect in mice.
A non-photic stimulus either results in a phase shift during the subjective day, or in
a blocking of the light effect during the subjective night. In laboratory animals, most
of these well known non-photic inputs to the SCN are related to locomotion, either by
direct behavioral manipulation such as wheel running or by non-photic inputs mimicked by neurotransmitters injected into the SCN. The attenuation of the light-induced
phase delay by circulating GHRP-6 indicates that it can be categorized as a non-photic
stimulus, which might reach the SCN via sensory circumventricular organs such as the
ARC. Several arguments plead for an important “relay” role of the ARC AGRP/NPY
neurons. Firstly, NPY and GABA can interfere with and suppress the light-induced
phase shifting via direct actions on SCN neurons. Secondly, AGRP/NPY neurons of
the vmARC project to the SCN and are activated by circulating GHRP-6. Thirdly,
NPY/AGRP in the vmARC is also colocalized with GABA 419. Fourthly, since NPY
innervation is still observed in the SCN after lesioning of the IGL 382, 420, the vmARC
is another possible source for NPY innervation of the SCN. The small caliber of the
AGRP fibers derived from the vmARC may indicate why after IGL lesioning some of
us observed the loss of all NPY innervation in the SCN of rats 421. The total amount
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of the IGL-derived NPY terminals may by far outnumber NPY terminals originating
from the vmARC, but together NPY and GABA may disrupt the stable pacemaker
organized by the cellular synchrony across the SCN 422.
The observed reduction of light-induced phase delays by GHRP-6 agrees with the previously observed reduction in light-induced phase delays due to direct NPY injections
into the SCN, i.e 45% reduction with GHRP-6 versus 70% with NPY 423. The lesser inhibition can be explained by the fact that NPY injected directly in the SCN will reach all
NPY receptors, including those from the IGL, while the endogenous neurotransmitter
released from vmARC terminals in the SCN will only reach a selection of these receptors.
The present results provide an anatomical basis by which metabolic stimuli can affect
the functionality of the SCN. Light induced phase shifts have already been shown to
be modulated by changes in glucose availability, such as observed during diabetesrelated hyperglycemia, insulin-induced hypoglycemia, blockade of glucose utilization
or caloric restriction 424-426. Yet it has been difficult to specify the mechanism by which
these changes in glucose availability affected the SCN. Gold-thioglucose lesions of the
glucose-receptive neurons in the VMH and ARC prevent the metabolic modulation
of photic resetting during shortage of glucose availability 427, Thus these data also
suggest an effect on the SCN via a relay in the VMH and/or ARC and consequently,
give support to our hypothesis for an NPYergic vmARC-SCN projection that would
be specifically activated by metabolic stimuli.
Although the environmental light/dark cycle provides the principal entrainment
to circadian rhythms, many more factors can also influence the phase of the SCN
or its outputs via direct effects on SCN. For a nocturnal animal, this means the light
inhibition on its locomotion must be removed to allow the motivation of feeding be
expressed through active behavior. Several studies indicate the importance of sensory
circumventricular organs for communication with the SCN 344, 355, 428, 428, 429. The present
study allows us to hypothesize that after sensing blood borne metabolic signals, the
output from one of the circumventricular organs, for instance the vmARC may send
this metabolic feedback information to the SCN, which could influence the synchrony
of the SCN on physiology and behavior. For example the suppression of light information to the SCN by the “hunger signal” ghrelin may allow the animal to become
more active in order to search for food. This hypothesis is supported by the results of a
study on leptin, the natural antagonist of ghrelin, which demonstrates that its normal
signaling in the hypothalamus, especially in the vmARC, is necessary to maintain
a normal level of locomotion at night 430. The present study would indicate that the
vmARC-SCN connection may also be involved in the effect of leptin on locomotion.
In conclusion, the demonstration that intravenously injected GHRP-6 modifies the
response of the SCN to light is evidence for the existence of neuronal pathways that
transmit peripheral circulating information to the SCN.
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Chapter 5
Dorsomedial hypothalamic neuropeptide FF neurons project to the retinal
termination site of the suprachiasmatic nucleus
Submitted
Chun-Xia Yi, Jan van der Vliet, Michael Proper, Manuel Angeles-Castellanos, Valeri Goncharuk,
Jack H.Jhamandas, Andries Kalsbeek, Carolina Escobar & Ruud M.Buijs
Abstract
Food anticipation results in enhanced locomotor activity in rodents, also during periods when the biological clock normally signals inactivity. In our search for hypothalamic mechanisms involved in inducing this activity, we examined the possible role
of neuropeptide FF (NPFF) neurons and the suprachiasmatic nucleus (SCN). Food
anticipatory locomotor activity in rats entrained to food restriction during the day
period resulted in Fos expression in NPFF neurons located in the ventral part of the
dorsomedial hypothalamus (DMH). Retrograde tracing from the ventral SCN suggests that the NPFF terminals in the SCN originate from the DMH-NPFF cell bodies.
Co-staining of NPFF with SCN neuropeptides revealed that NPFF terminals mainly
target gastrin-releasing peptide neurons in the SCN. Labeling retinal projections in
combination with NPFF revealed a close association between retinal and NPFF terminals in the SCN. Simultaneous with food anticipation-induced Fos expression in the
DMH, Fos expression in the ventral SCN decreased, suggesting that DMH input may
inhibit neurons in the light-receiving part of the SCN. Since daytime as well as lightinduced neuronal activity in the SCN is known to inhibit locomotor activity in rodents,
it is proposed that, under food anticipatory conditions, activation of the DMH–NPFF
input to the ventral, retinal termination site of the SCN is involved in inhibiting SCN
neuronal activity, allowing increased locomotor activity during the light period.
Introduction
The suprachiasmatic nucleus (SCN) is responsible for the organization and synchronization of the 24 hour activity/inactivity-cycle in all mammals. Neuronal activity of
the SCN in night active rodents coincides with the locomotor-inactive daytime, while
SCN neuronal inactivity coincides with increased locomotor activity in the dark phase
431
. Light stimulates neuronal activity of the ventral, light input-receiving part of the
SCN, and this light input inhibits locomotor activity also during the active phase of
the animal 432-434. This light-induced inhibition of locomotor activity can only be observed in SCNintact animals, suggesting that (light-induced) electrical activity of SCN
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neurons is directly responsible for the inhibition of locomotor activity, also during the
subjective light phase 435, 436. Interestingly, the reverse, i.e. stimuli that are able to induce
activity during the light period and thus interfere with normal (locomotor) inactivity,
are often associated with metabolism. For example, animals entrained to food being
available only during the day (light) period become active just before the food is made
available 437-439; apparently in these animals the normal inhibition of locomotor activity
by light is prevented. We hypothesized that the SCN should be involved in this behavioral activity and we therefore examined the input to the SCN. Specifically, retrograde
tracer injections into the ventral SCN resulted in labeled neurons in an area of the
ventral DMH that corresponds with the area that is activated during food anticipatory
activity (FAA) at daytime 330, 440, 441. The DMH is well known for its The involvement
of the DMH in wakefulness and sleep is a well-known fact 441, 442, while one of the few
peptides known to be present in the ventral DMH is neuropeptide FF (NPFF) 443, 444.
Interestingly, NPFF activity has been related to feeding behavior 445-447. This observation suggested the involvement of the DMH in the organization of FAA. In the present
study, the FAA-activated DMH neurons appeared to be positive for neuropeptide FF
(NPFF). We subsequently showed these DMH-NPFF neurons to project to the SCN.
In the SCN, we observed NPFF fibers terminating exclusively in its ventral part, and
targeting preferentially gastrin-releasing peptide (GRP) and vasoactive-intestinal peptide (VIP) neurons. After labeling projections from the retina we also demonstrated
a close association between NPFF and retinal terminals. Next we showed that FAA
during the light period induced Fos immunoreactivity in NPFF neurons in the DMH
area and simultaneously a diminishment of Fos in the ventral part of the SCN. We propose that the activation of NPFF neurons in the DMH is responsible for the decrease
of Fos in the ventral SCN during food anticipation, which may reflect a decrease in
electrical activity of these SCN neurons, thus allowing for increased locomotor activity.
Results
Retrograde tracing revealed ventral SCN innervated by DMH
In order to identify structures that project to the ventral SCN, CTB-AF555 injections
were placed into the ventral SCN. Pressure injection of nano-liter amounts of CTBAF555 resulted in labeling restricted to the SCN when the tip of glass pipette was
confined to within the ventral SCN (Fig. 1A). As soon as the tip was outside the SCN,
no labeling of the SCN itself was observed, only of the area around it. Such injections
just outside the SCN were compared with injections inside the SCN in order to determine whether the retrograde labeling was indeed derived from the SCN and not from
the area around the nucleus. Injections into the dorsal SCN nearly always resulted in
leakage of tracer outside the SCN but still this did not result in labeling of neurons in
the DMH. Interestingly, as observed earlier 330, 448, 449, depending on the injection site
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DMH
III
III
VMH
ARC
ox
A
B
Figure 1 NPFF neurons in the DMH project to the ventral SCN. A, A CTB-AF555 injection
site that was restricted to the ventral SCN and optic nerve. B, Ipsilateral CTB-AF555 labeling
from ventral SCN injection demonstrates labeled neurons at the level of the dorsomedial
hypothalamic area. The dense CTB labeling of neurons in the ventral part of the DMH also
delineates the non-labeled ventromedial hypothalamus (VMH) area. In addition, labeled
neurons are found in the arcuate nucleus (ARC), i.e., a brain area also known to project to
the SCN 235. OX: optic chiasm, III: third ventricle. Scale bar: A, 100μm, B, 200μm.
in the SCN (dorsal, lateral or ventral), a different pattern in anterograde-labeled fibers
and retrograde-labeled cell bodies was observed. Labeling of cell bodies in the DMH
was only reliably obtained when injections of tracer included the ventral SCN. Our
series of ventral injections (5 animals) all showed clear retrogradely labeled neurons
in the DMH area (Fig. 1B). The neurons in the DMH were distributed especially in
the ventral part of the DMH.
DMH-NPFF neurons project to the SCN
Since the ventral part of the DMH contains NPFF neurons 444, 450 we examined whether
DMH-NPFF neurons project to the SCN and investigated possible co-localization of
NPFF with CTB-AF555 injected into the ventral SCN. Clearly, in all animals every
section of the DMH that contained NPFF neurons showed several NPFF neurons containing CTB-AF555, providing evidence for their projection to the ventral SCN (Fig.
2A). The injections just outside or even in the dorsal part of the SCN did not result in
any labeling in the DMH-NPFF neurons. A further confirmation of the projection of
NPFF neurons to the SCN was obtained by analyzing the innervation pattern of NPFF
in the SCN; a distribution of very thin NPFF fibers can be detected in the ventral part
of the SCN (Figs. 3A-C). In the nucleus of the solitary tract (NTS), the only other site
of NPFF neurons in the brain 451, no evidence was obtained for the presence of CTB87
chapter 5
AF555 in NPFF neurons, indicating that the NPFF neurons in the DMH are the sole
source of the fiber terminals in the SCN.
Refeeding during the light period activates DMH-NPFF neurons which project to
the SCN
This study showed that injection of CTB tracer into the ventral SCN in combination
with a 48h fast followed by 2h refeeding resulted in the presence of NPFF neurons that
also contain CTB and Fos (1-3 per brain) (Fig. 2C), confirming the view that NPFF neurons projecting to the SCN can be activated by refeeding in this paradigm. The number
of neurons showing Fos-NPFF co-localization was approximately 2-3 per section, illustrating a modest activation of this NPFF- containing cell group. Since Fos activation
was detected after refeeding, also the availability of food and the food intake itself might
serve as an important stimulus for Fos immunoreactivity. However, these possibilities
were countered by the observation that refeeding at night after a 48h fast did not result
in activation of NPFF neurons in the DMH, thus indicating that food intake alone
or locomotion during the dark period does not activate the DMH-NPFF neurons.
Food anticipation activates NPFF neurons in DMH
The experiment in which animals anticipated food but were not allowed to eat showed
a high locomotor activity pattern in the hours before sacrifice, which coincided with
a large number of Fos-positive neurons in the DMH as was demonstrated before 452.
Many of these Fos-positive neurons were co-localizing NPFF (Fig. 2B), indicating
that NPFF neurons were activated. Since Fos protein peaks 60-90 minutes after the
stimulus, the presence of Fos consequently shows the activation of neurons 60-90
minutes prior to sacrifice. With meal expectancy at ZT5, animals in general start to
show anticipation to food between ZT3-4. Without feeding, with perfusion at ZT5,
→ Figure 2 Food anticipation activates DMH-NPFF neurons that project to the ventral SCN.
A, After CTB injection in SCN, NPFF-containing and CTB labeled neurons can be found
in the ventral DMH. NPFF neurons (green) are mainly located in the ventral DMH, while
CTB-labeled neurons (red) from the SCN tracing also cover more dorsal parts of the DMH.
Arrows indicate two neurons that show NPFF and CTB co-localization (yellow). B, NPFF and
Fos co-expression in DMH neurons with food anticipation, rats were perfused at ZT6, i.e. 60
min after food would have become available. Many of the NPFF neurons (green) express Fos
(red) as shown by arrows. C, Illustration of CTB-AF555, NPFF and Fos co-localization in the
ventral DMH. CTB tracing combined with fasting-refeeding not only resulted in a similar
NPFF and CTB-AF555 distribution pattern as shown by Fig. 2A, but neurons co-localizing
NPFF (green, C1) and CTB-AF555 (red, C2) were also activated by the refeeding stimulus,
as indicated by Fos immunoreactivity (blue, C3). Arrows in C1-4 indicate the same neuron
in the ventral DMH area. C4 shows the triple labeling. Double arrows in C3 illustrate another
Fos- positive neuron. Scale bar: A, 200μm; B and C, 100μm.
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Fos
NPFF
CTB - SCN
NPFF
p
III
III
A
B
NPFF
CTB - SCN
III
III
III
III
C1
C2
Fos
C3
C4
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Fos in the DMH was already clearly increased as compared to control (i.e., nonrestricted) animals, where Fos could hardly be detected. In the DMH this resulted
in the detection of Fos in NPFF neurons in about 1-2 Fos-NPFF co-localizations per
section. Animals perfused at ZT6 showed Fos in the DMH (Fig. 4B) at the height of
behavioral activity during food anticipation. At this time point we detected Fos in
NPFF neurons with a higher frequency of about 5-8 Fos-NPFF co-localizations per
section, which meant often that all NPFF neurons were Fos positive, in control rats,
only few Fos could be detected in the same area. Interestingly, the NPFF neurons in
the NTS area did not show any co-localization of Fos with NPFF, although the NTS
clearly shows Fos during FAA, thus illustrating the difference in response of these two
NPFF systems in our experimental paradigm. These results show that the peak of Fos
activity in DMH-NPFF neurons reflects the activity of neurons at the height of the
behavioral activity in the anticipation of food.
NPFF and retinal terminals innervate the same SCN region
Next we analyzed the presence of NPFF fibers in the SCN. In the ventral SCN a
dense termination of NPFF fibers was found with a distribution that resembled the
distribution of retinal terminals. In order to investigate this further we examined the
distribution of NPFF together with SCN peptidergic neurons known to receive retinal
input. Indeed, NPFF terminals were found in very close apposition to GRP and VIP
neurons (Fig. 3A), while hardly any NPFF fibers could be detected in the vicinity of
arginine-vasopressin (AVP) neurons (Fig. 3B). To demonstrate further the overlap
with retinal termination in the SCN, we performed the NPFF staining in the SCN
of animals that received a CTB-AF488 injection into the retina. Retinal fibers were
always found in very close association with NPFF fibers present in the ventral, light
input receiving part of the SCN (Fig. 3C).
FAA-induced Fos in the DMH correlates with a decrease of Fos in the SCN
In view of the importance of the retinal input for the light activation of SCN neurons we
analyzed further the presence of Fos staining in the SCN of control animals as compared
to those perfused during food anticipation. FAA not only increased the expression of Fos
in the DMH 452, it also changed the expression of Fos in the SCN, but in a mirror image
of that in the DMH. The SCN of ad libitum fed control animals perfused between ZT5
and ZT6 expresses Fos over the whole SCN, but with an emphasis on the ventral (light
receiving) part. In contrast, all the 8 animals with (food anticipatory) locomotor activity during the light period show a strongly reduced Fos activity, especially in the ventrolateral SCN (76±8 in control and 42±3 in food anticipation, P=0.007; Figs. 4C and 4D).
Compared with the ventrolateral SCN, Fos activity in the dorsomedial SCN did not
show a significant change (139±18 in control and 125±7 in food anticipation, P = 0.54).
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Discussion
The present study demonstrates that NPFF-containing neurons of the DMH project to
the SCN and terminate in close association with retinal terminals. Moreover, DMHNPFF neurons are activated during food anticipation, and this activation coincides
with a decrease of Fos in the ventral light receiving part of the SCN.
NPFF neurons in the DMH are labeled after CTB-AF555 injection in the ventral
SCN, suggesting that the NPFF terminals in the SCN come from the DMH. This is
confirmed by the fact that NPFF neurons in the NTS, the only other region of NPFF
neurons in the forebrain, do not show CTB-AF555 after injection of this tracer into
the SCN. The close proximity of DMH-NPFF terminals and retinal terminals in the
SCN indicates that the region within the SCN where information from the retina is
integrated is the same site where non-photic food anticipation information from the
DMH is transmitted to SCN neurons. Consequently, the role of DMH-NPFF in the
SCN could be functionally related to that of the light input to the SCN. The diminishment of Fos staining in the ventral SCN in the daytime during FAA reflects an
inhibition of daytime SCN neuronal activity. We propose that inhibition of the lightreceiving part of the SCN is essential for the expression of (anticipatory) activity of
the animal during the light period.
The presence of Fos in the DMH only during the day and not during the night when
animals are active or anticipating food, suggests a ‘gating’ mechanism for which the
strong input from the SCN to the DMH 453 is proposed to be responsible. Consequently
we propose that DMH-NPFF-SCN interaction is essential for a normal expression of
FAA.
The SCN organizes locomotor activity according to the light/dark cycle
The synchronization of the rest-activity cycle of mammals to the light/dark cycle is
organized by the SCN. However, it should be possible that, under certain circumstances, signals of the biological clock may be overruled or modified such that activity
occurs at circadian times when activity is normally inhibited. The other condition
also holds: i.e., the inhibition of activity at times when the animal would normally
be active. This, for example, is achieved by a light stimulus during the dark (active)
period of the animal. The light signal activates ventral SCN neurons, resulting in an
increase in electrical activity 454, the induction of Fos protein (27), and an inhibition
of locomotor activity 455, 456. The proof that the lightinduced inhibition of locomotor
activity is mediated by the SCN, is that in SCN-lesioned animals no such inhibition
of locomotor activity is seen 435, 436.
On the other hand, the presence of food during the light period after a long period
of fasting results in voluntary activity during the normally inactive period. The fact
that only refeeding during the light period and no refeeding during the dark period
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results in Fos labeling in DMH-NPFF neurons projecting to the SCN suggests that,
together with the SCN, the DMH-NPFF neurons are implicated in the organization of
feeding related activity in the light cycle. In order to investigate this further we chose
another stimulus, the restricted feeding paradigm, in which animals learn to anticipate
food at a moment they normally do not eat, i.e., during the light period. This protocol
does not only result in a period of intense locomotor activity in the hours preceding
the presentation of food, but also in the activation of neurons in the DMH 452. The
present study shows that many of these Fos-stained neurons contain NPFF, and that
NPFF-containing fibers terminate in close association with retinal terminals in the
SCN. In contrast with the increase of Fos-expressing neurons in the DMH, in the SCN
a diminishment of Fos staining is seen in the ventral part, suggesting an inhibition of
activity of the ventral SCN neurons. As an explanation, two observations are important. First, the DMH is also known to contain a large number of GABA-ergic neurons
457, 458
It is plausible that some of these neurons, either with or without NPFF as a cotransmitter, also project to the SCN. In addition, NPFF is also known to reduce glutamatergic activation and the electrical activity of neurons in the parabrachial nucleus
by presynaptic mechanisms 459. These properties of NPFF and the putative presence of
GABA in these neurons may provide a powerful mechanism to reduce the electrical
activity of the ventral (retinal input receiving) neurons of the SCN. In this way the
DMH may decrease the activity of the ventral SCN in order to allow the animal to
become active during its normal period of inactivity. It is interesting to consider which
neurotransmitters of the SCN might mediate this light output. Light preferentially
activates GRP but also VIP- containing neurons 460 These SCN neurons target preferentially the MPO, Sub PVZ and DMH, where locomotor activity, temperature regulation and corticosterone secretion are organized 461-465, suggesting that these peptides
and their co-transmitters could be involved in the light output pathway of the SCN.
→ Figure 3 NPFF distribution pattern in the SCN. A, NPFF, GRP and VIP distribution
pattern in the SCN. NPFF fibers (red) are present in the ventral SCN, VIP neurons (green)
cover mainly the medial SCN, and partially overlap with the area that contains GRP (blue)
neurons. NPFF synaptic buttons can be found mainly on GRP (arrow) neurons but also on
VIP (double arrows) neurons. B, Illustration of NPFF, GRP and AVP distribution pattern in
the SCN at a lower magnification. NPFF fibers (red) are mainly present in the ventral SCN
in close apposition to GRP neurons and fibers (blue) which are mainly present in the ventral
SCN. The part in the dorsomedial SCN that contains AVP neurons (green) does not receive
NPFF fibers. C, NPFF and retinal fibers terminate in the same area of the ventral SCN.
CTB-labeled retinal terminals (green) are distributed very close to NPFF fibers (red) in the
ventral SCN. Since it is well known that retinal terminals do not contain any NPFF peptide,
the yellow spots which normally indicate co-localization are evidence of the close proximity
of retinal and NPFF terminals. Due to the close proximity the CLSM image shows overlapping red and green (i.e., yellow) fluorescence signals. Scale bar: A, 100μm; B and C, 200μm.
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NPFF
GRP
VIP
p
III
A
NPFF
GRP
AVP
NPFF
CTB-Retina
B
C
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The DMH integrates circadian and feeding-related information
The present study shows that food availability after fasting resulted in a marked increase in the number of NPFF neurons in the DMH that express Fos. It is remarkable
that an identical situation, i.e. fasting for 48 hours and fed at night (at the normal time
of activity) does not result in Fos in NPFF neurons. The explanation for this discrepancy should be sought for in the massive input of SCN fibers to the DMH. In order to
analyze this situation we need to consider what information is essential for the DMH
and where this information is coming from. First, fasting associated with FAA has
been shown to result in lower blood glucose and in the resetting of liver metabolism
associated with food presentation 466. In addition, FAA entrains a glucocorticoid peak
just prior to food presentation 439. This information will reach the DMH via those areas
that are implicated in the integration of circulating and visceral information such as
the NTS, parabrachial nucleus and ARC 243, 370. This is emphasized by the observation
of FAA Fos activity in the NTS 467.
Thus, the present results show that day-time activation of circuits that relay nonphotic information to the SCN coincides with changes in locomotor activity and with a
decrease of Fos activation in the ventral SCN. This observation suggests that neuronal
circuits originating in the DMH and projecting to the SCN have the capacity to change
SCN activity, and thus its output, in order to allow changes in SCN-dictated activity
patterns, such that the behavior of the animal can be adapted to meet the (metabolic)
demands of the organism.
The location of the food-entrained oscillator(s)
The recent investigations on the role of the DMH in food-entrainable circadian
rhythms 441, 468-470 and the fact that the SCN is not essential for FAA 471, warrant a careful interpretation of the results of the present study. The Fos expression in the DMH
441, 469
suggests that activity of DMH neurons is important for a correct display of this
FAA. Since many studies have demonstrated that the SCN is not essential for FAA, the
question is: what is the role of the DMH? The answer to this problem is that in intact
animals the normal function of the SCN is to organize the daily activity/inactivity cycle. Therefore its outputs, also to the DMH, will inhibit or activate the structures in the
hypothalamus that are responsible for the execution of these functions. Consequently,
in our view an absence of SCN activity will in fact facilitate the expression of FAA during the day, since the active SCN is no longer present to inhibit activity. This is clearly
illustrated in experiments with SCN-lesioned animals that are active at all moments
of the light-dark cycle and with SCN-lesioned animals that are perfectly entrained for
FAA 471. We propose that in circumstances in which the SCN is lesioned, metabolic
signals (such as the food entrained liver metabolism and the decreasing glucose levels) are sufficient to activate the DMH and initiate FAA via the efferent projections of
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DMH
III
III
VMH
A
B
III
III
DM
V
C
D
Figure 4 Food anticipation correlates with Fos reactivity in DMH and SCN. Animals were
sacrificed at ZT5, which reveals the induction of Fos to take place at the beginning of the
anticipatory phase, or at ZT6, which reveals the induction of Fos taking place during the peak
of anticipation. Fos is strongly expressed in the DMH (ZT6, B) as compared with ad libitum
fed control animals (ZT6, A), while in the ventral SCN Fos expression decreases significantly
in feeding-restricted animals (ZT6, D) as compared with ad libitum fed control animals (ZT6,
C). DM: dorsomedial SCN; V: ventral SCN. Scale bar: A and B, 200μm, C and D, 100μm.
the DMH. It is clear that the DMH is essential for the expression of wakefulness and
many activity related behaviors 472, but the many lesion studies performed since the
first seminal studies of Stephan et al. 473, 474 clearly show that the occurrence of FAA is
not the sole responsibility of one brain area. Although recently the study of 468 seemed
to make a strong case for a unique and essential role of the DMH in the organization
of FAA, follow-up studies have clearly proved otherwise 470, 475, 476.
The present results indicate that an important function of the DMH in order to allow FAA to occur is the removal of the inhibitory influence of the SCN (on locomotor
activity) at that time of the day. Of all brain structures involved in FAA, the DMH
might be the most efficient one to shut down the activity of the SCN. This essential
interaction with the SCN might be an example of how a number of brain structures
interact to organize FAA.
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Methods
All experiments were executed with Wistar rats weighing 250-350 g. Animals were
kept in a humidity and temperature-controlled environment with free access to water
and food, with lights on from 07:00-19:00. All experiments were conducted with the
approval of the animal experimental committee of the Royal Netherlands Academy
of Arts and Sciences.
Experimental design
1. SCN tracing: Investigating DMH projections to the SCN and their colocalization with NPFF
For anesthesia a mixture of 0.8 ml/kg Hypnorm (Janssen, High Wycombe, Buckinghamshire, UK), im, and 0.4 ml/kg Dormicum (Roche, Almere, The Netherlands), sc.
was used. Thirty-three animals were mounted in a David Kopf stereotact and received
a 50nl 0.25% fluorophore conjugated cholera toxin B (CTB-AF555, Molecular Probes,
Eugene, OR). CTB-AF555 was taken up in the glass capillary (80μm diameter) by
capillary force (max. 50nl), and pressure injected (10 mbar, 5 seconds) into the ventral
part of the SCN using the following coordinates: toothbar +5; 1.4 rostral from bregma;
0.05 lateral and 0.86 ventral from dura under an angle of 2o. Animals were allowed to
survive for at least one week, after which they were sacrificed by perfusion fixation to
validate tracing and consequently NPFF co-staining.
2. SCN tracing in combination with a fasting-refeeding protocol: examining whether the SCN-projecting NPFF neurons in the DMH have a
relationship with feeding
In this study, SCN tracing was carried out in animals that were voluntarily active in
the daytime. After a minimum period of 10 days after ventral SCN tracer injection, 16
rats were deprived of food for 48h starting at ZT1 (ZT0 = onset of light period). Two
hours after food had become available again, the rats were perfused (i.e., at ZT3). Three
intact rats without tract tracing underwent the same fasting and refeeding protocol and
were sacrificed to check whether tract tracing into the SCN influenced Fos expression
in the brain. In order to examine whether refeeding also induced Fos expression in the
DMH during the dark period, another group of three rats underwent the same 48h
fasting process from ZT12 onwards. These were refed 48h later, starting at the onset
of the dark period (i.e., ZT12) and perfused at ZT14.
3. Food anticipation: to study the neurochemical character of anticipation-activated neurons in the DMH as well as Fos-immunoreactive
patterns in the SCN
Eight rats were entrained to a restricted feeding schedule (RFS), with food available
for only 2h each day, from ZT5-ZT7. After three weeks of food restriction, four RFS
rats were perfused at ZT5 and four at ZT6 without food becoming available (see also
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Angeles-Castellanos et al. 452 for the detailed experimental protocol). Four normal ad
libitum rats were perfused at ZT6 as controls. Considering the time needed for Fos
protein expression (for a minimum of 60-90 minutes), the Fos immunoreactivity at
ZT 5 represents activity in the neurons no later than ZT4 and the animals perfused
at ZT6 show Fos of neurons that became active no later than ZT5. Fos and NPFF colocalization were carried out in DMH and NTS with all animals. Fos immunoreactive
nuclei in the SCN were quantified by an automated cell counting program.
4. Retinal tracing and analysis of NPFF innervation in the SCN: to explore
the possible functionality of NPFF in the SCN
In order to investigate the relationship between NPFF and retinal innervation in the
SCN, CTB-AF488 (Molecular Probes, Eugene, OR) 0.2% 0.1μl was injected into the
vitreous of the left eye, under brief isofluorane gas anesthesia, to label the retinal
terminals in combination with NPFF staining in the SCN. Animals were allowed to
survive for at least one week, after which they were sacrificed by perfusion fixation.
To analyze NPFF target neurons in the SCN, NPFF staining was combined with
staining for GRP, VIP or AVP, by immunocytochemistry and confocal laser scanning
microscopy (CLSM) in the ventral part of the SCN.
Immunocytochemical staining
All animals were perfused under a lethal sodium pentobarbital anesthesia, first with
100ml saline, followed by 4% freshly prepared paraformaldehyde in 0.1 M phosphate
buffered saline (PBS, pH 7.2). Post-fixation took place in the same buffer for 24h, after
which the brains were immersed for at least 24h in 30% sucrose in 0.1 M PBS (pH 7.2).
Sections of 30um were made on a cryostat, collected and stained for tracer or other
markers that were detected by means of immunocytochemistry.
Free-floating sections from rats after SCN tracing were rinsed in 0.1M Tris buffered
saline (TBS, pH7.2) and then incubated overnight at 4°C with primary rabbit anti-CTB
antibody (1:100,000, Sigma-Aldrich Corp., St. Louis, MO); following incubation in the
primary antibody, sections were incubated with biotinylated anti-rabbit IgG made in
goat for 1h and avidin–biotin–peroxidase complex (ABC Vecta Stain Kit, Vector Laboratories, Burlingame, CA) 1h; following incubation with the ABC reagents, sections
were visualized with 0.025% 3,3’-diaminobenzidine (DAB)/Tris–HCl together with
0.01% H2O2 and 8% NiCl2. Sections were rinsed, mounted, dehydrated and covered
for light microscopic observation.
For RFS rats, goat anti-Fos (1:1500, Santa Cruz Biotechnology, Inc., Santa Cruz,
CA) antibody was used to examine neuronal activation in the DMH, NTS and SCN
with the DAB/NiCl2 staining protocol as described above.
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Analysis of Fos immunoreactivity
For identification and display of Fos immunoreactivity in the SCN, tiled images were
captured by a computerized image analysis system consisting of a Zeiss Axioskop and
a 9811-Sony XC77 black and white video camera (Sony Corp., Tokyo, Japan). In the
images, both sides of the middle portion of the SCN were manually outlined. The Fospositive nuclear profiles were automatically segmented by a dedicated macro written
within the ImagePro programming environment. For each rat, three sections were
measured every 90 μm (from bregma -1.20 to -1.40 mm); the automatic segmentation (see Fig. 4) were divided into ventral SCN (v) and dorsomedial (dm) SCN and
the mean number of Fos-positive cells per section of these two separated regions was
calculated. All values are expressed as the means ± SEM. Data were analyzed using
one-way ANOVA. Statistical significance was set at P < 0.01.
Confocal laser scanning microscopy
All multi-labeled fluorophores conjugated with second antibodies and streptoavidin
conjugated with Cy2, Cy3 or Cy5 were obtained from Jackson Immuno Research
Laboratories (Westgrove, PA). Sections from the rats with a successful injection of
CTB-AF555 into the ventral SCN were incubated overnight at 4°C in a polyclonal
antiserum against the neuropeptides NPFF (1:1500, kindly provided by Dr Yang H-YT,
NIMH, Washington, DC) 435, 477-480. Afterwards donkey anti-rabbit-Cy2 was applied
to examine the co-localization of CTB-AF555 and NPFF neurons in DMH. Sections
from RFS and SCN tracing-refeeding rats were incubated overnight at 4°C in rabbit
anti-NPFF and goat anti-Fos, and sections were further incubated with second horse
anti-goat IgG for 1h. For RFS sections, donkey anti-rabbit-Cy2 and streptoavidin-Cy3
were co-incubated for 1h to check colocalization of NPFF in DMH or NTS with Fos.
For SCN tracing-fasting-refeeding sections, donkey anti-rabbit-Cy2 and streptoavidin-Cy5 were used to check colocalization of NPFF and Fos in neurons in the DMH
projecting to the SCN (containing CTB-AF555).
By combining NPFF anti-rabbit antibody either with a monoclonal mouse antiAVP (1:2000, NP-AVP, PS41, a generous gift from Drs Gainer H and Key SH, NIH,
Bethesda, MD) 480, a sheep anti-VIP or a goat anti-GRP (Charles River Laboratories,
Southbridge, MA), then using a goat anti-rabbit-Cy3 (for NPFF) in combination with
respectively goat anti-mouse-FITC (for AVP), goat anti-sheep-FITC (for VIP), or
sheep anti-goat-Cy5 (for GRP), enabled us to examine the NPFF staining in combination with AVP/GRP or VIP/GRP peptides of the SCN from intact rats.
The relation of NPFF with retinal terminals in the SCN was investigated in sections
with CTB-AF488 injection in the retina. After overnight incubation with primary
rabbit anti-NPFF antibody, the combination of NPFF with CTB-AF488 in retinal
terminals in SCN was detected by goat anti-rabbit-Cy3 incubation.
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Hypothalamic modulation
of glucose metabolism
Chapter 6
A major role for perifornical orexin neurons in the control of glucose metabolism in rats
Based on: Diabetes 58 (9), 1988-2005 (2009)
Chun-Xia Yi, Mireille J. Serlie, Mariëtte T. Ackermans, Ewout Foppen, Ruud M. Buijs,
Hans P. Sauerwein, Eric Fliers & Andries Kalsbeek
Abstract
Objective The hypothalamic neuropeptide orexin influences (feeding) behaviour as
well as energy metabolism. Administration of exogenous orexin-A into the brain
has been shown to increase both food intake and blood glucose levels. In the present
study, we investigated the role of endogenous hypothalamic orexin release in glucose
homeostasis in rats.
Research Design and Methods We investigated the effects of the hypothalamic orexin
system on basal endogenous glucose production (EGP) as well as hepatic and peripheral insulin sensitivity by changing orexinergic activity in the hypothalamus combined
with hepatic sympathetic or parasympathetic denervation, two step hyperinsulinemiceuglycemic clamps, and RT-PCR studies.
Results Hypothalamic disinhibition of neuronal activity by GABA-receptor antagonist
bicuculline (BIC) increased basal EGP, especially when BIC was administered in the
perifornical area where orexin-containing neurons, but not melanocortin concentrating hormone-containing neurons, were activated. The increased BIC-induced EGP
was largely prevented by i.c.v. pretreatment with the orexin-1 receptor antagonist. I.c.v.
administration of orexin-A itself caused an increase in plasma glucose and prevented
the daytime decrease of EGP. The stimulatory effect of i.c.v. orexin-A on EGP was
prevented by hepatic sympathetic denervation. Plasma insulin clamped at 2x or 6x
basal levels did not counteract the stimulatory effect of perifornical BIC on EGP, indicating hepatic insulin resistance. RT-PCR showed that stimulation of orexin neurons
increased the expression of hepatic glucoregulatory enzymes. I.c.v. administration of
SB-408124 suppressed the diurnal increase of glucose appearance only around dawn.
Conclusions Hypothalamic orexin plays an important role in EGP, most likely by
changing the hypothalamic output to the autonomic nervous system. It also indicates
that activation of perifornical orexin neurons is a necessary link in the control of the
biological clock over the daily rhythm in glucose production. Disturbance of this
pathway may result in unbalanced glucose homeostasis.
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Introduction
The hypothalamic neuropeptide orexin is involved in arousal and energy homeostasis
212
. Lack of orexin results in narcolepsy and hypophagia. Despite the reduced food
intake, both narcoleptic patients with orexin deficiency and the animal model with
genetic ablation of orexin neurons tend to be obese 481, 482. These findings indicate that
the link between orexin and energy homeostasis is not only via appetite stimulation
483, 484
, but also involves additional mechanisms in the control of energy metabolism.
In keeping with this notion, orexin-ataxin-3 transgenic mice show reduced metabolic
rate, independent of other behavioural changes induced by orexin, such as arousal,
locomotion and food intake 485.
Orexin-A can regulate plasma glucose concentrations via both central and peripheral mechanisms 486, 487, but the neurotransmitter(s) responsible for controlling the endogenous activity of the orexin neurons is (are) not evident. Besides the glutamatergic
input that is derived from a local neuronal network 488, orexin neurons also receive
GABAergic inputs from a variety of brain areas such as arcuate nucleus (ARC) NPY
neurons 488, basal forebrain 489 and preoptic area 490. During the light period, i.e. the
sleeping/fasting period of rats, orexin neurons in the perifornical area are inhibited
by GABA inputs originating from the biological clock neurons located in the suprachiasmatic nucleus (SCN) 491. Interestingly hypothalamic application of the GABAa
receptor antagonist bicuculline (BIC) not only activates orexin neurons 492, but also
increases plasma glucose concentrations 48, 493, 494.
To test the hypothesis that GABA acts as an inhibitory neurotransmitter in upstream
brain areas to control the glucoregulatory function of orexin, we activated the orexin
neurons in the perifornical orexin area (PF-Oa) of rats by retrodialysis of GABAa
receptor antagonist and investigated its effect on endogenous glucose production
(EGP), using the stable isotope technique. The effect of BIC on hepatic and peripheral
insulin sensitivity was investigated by performing euglycemic clamps at two different
levels of hyperinsulinemia. The specific involvement of orexin neurons in the response
of EGP to BIC was confirmed in several ways: 1) by comparing the EGP response
from BIC administration in the PF-Oa with that in two nearby brain areas that do
not contain orexin neurons, i.e. the dorsal part of the dorsomedial hypothalamus
(dDMH) and the hypothalamic paraventricular nucleus (PVN), 2) by comparing EGP
responses with and without i.c.v. co-infusion of orexin-1 receptor (OX-1R) antagonist
SB-408124 during BIC administration in the PF-Oa, 3) by investigating the effects
of i.c.v. administration of orexin-A and melanin-concentrating hormone (MCH) on
EGP. To investigate the possible involvement of the autonomic nervous system in the
glucoregulatory actions of orexin-A, we combined the i.c.v. administration of orexinA with specific hepatic sympathetic or parasympathetic denervations. Furthermore,
to elucidate the metabolic signalling pathway utilized by the orexin system to control
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hepatic insulin sensitivity, we also examined several hepatic glucoregulatory factors
by quantitative real time-PCR (RT-PCR). Both GABA signaling and orexin activity
seem to be timed by the central pacemaker in the suprachiasmatic nuclei (SCN), as
on the one hand GABAergic input to the orexin neurons is most pronounced during the daytime 490, 492, and on the other hand the content and release of orexin in the
central nervous system shows a pronounced day/night rhythm 495, 496. To investigate
the involvement of endogenous orexin release in the daily rhythm of plasma glucose
concentrations, we performed a loss-of-function experiment by blocking the OX-1R
from the middle of the light period until the early dark period and measured the rate
of glucose appearance.
Research design and methods
Animals
All experiments were conducted under the approval of the animal care committee
of the Royal Netherlands Academy of Arts and Sciences. Male Wistar rats weighing
300-350 g (Harlan Nederland, Horst, The Netherlands), were housed in individual
cages (25x25x35 cm), with a 12/12-h light-dark schedule (lights on at 07.00 h). Food
and water were available ad libitum, unless stated otherwise.
Surgery preparation
Animals underwent surgeries according to the different experimental designs under
anaesthesia with 0.8 ml/kg Hypnorm (Janssen, High Wycombe, Buckinghamshire,
UK), i.m., and 0.4 ml/kg Dormicum (Roche, Almere, The Netherlands), s.c.
Silicon catheters were inserted into the right jugular vein and left carotid artery
for i.v. infusions and blood sampling, respectively. With a standard Kopf stereotaxic
apparatus, bilateral microdialysis probes 48 were placed into the PF-Oa, dDMH and
the PVN. I.c.v. guiding probes were placed into the lateral cerebral ventricle. All coordinates were adapted from the atlas of Paxinos and Watson 497 (see supplemental
data.1, table.1). All catheters and probes were fixed on top of the head and secured
with dental cement.
Hepatic sympathetic or parasympathetic branches were denervated according to
our previously published methods 48. The effectiveness of the hepatic sympathetic
denervation was checked by measurement of noradrenaline content in the liver as
described before 196.
After recovery, animals were connected to a multi-channel fluid infusion swivel
(Instech Laboratories, PA, USA) one day before the experiment for adaption. Food was
removed at the beginning of the light period to exclude intestinal glucose absorption.
The first experimental blood samples were collected 4 hours later.
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Tracer dilution study
To study glucose kinetics [6.6-2H2] glucose (as a primed (8.0 μmol in 5 min)-continuous (16.6 μmol/h) infusion) was used as tracer (>99% enriched; Cambridge Isotopes,
Andover, USA). In Experiment 1 to 4, blood samples were taken at t=-5 min for
measuring background enrichment of [6.6-2H2] glucose, at t=90, t=95 and t=100 for
determining enrichment during the equilibration state, and at t=210, 220, 230, 240
and 250 for determining enrichment during the retrodialysis and/or i.c.v. infusion of
different drugs according to the different experimental designs.
In Experiment 1, Ringer’s dialysis (vehicle, 3μl/min) was started together with [6,62
H2] glucose infusion in both BIC and vehicle groups. After the t=100 blood sample,
the Ringer’s solution was changed to a BIC solution (100μmol/L, 3μl/min, Sigma, USA)
or Ringer’s (vehicle control, 3μl/min) again. After t=250 blood sampling, to validate
the placement of the microdialysis probes, animals were perfused by 4% paraformaldehyde and went through Nissl and immunohistochemical staining.
In Experiment 2, the primed-continuous [6,6-2H2] glucose infusion and Ringer’s
dialysis (vehicle) were started (after primary background blood sampling) together
with OX-1R antagonist 1-(6,8-difluoro-2-methyl-quinolin-4-yl)-3-(4-dimethylamino-phenyl)-urea (SB-408124), (50mmol/L, 5μl/hr, Sigma-Aldrich Corp., St. Louis,
MO, USA) or 20% DMSO (vehicle, 5μl/hr), the dose of SB-408124 was adapted from
SB-334867 in previously reported data 498, 499. At the end of the equilibration state, BIC
retrodialysis was applied in both groups. After the t=250 min sampling animals were
perfused, i.c.v. and microdialysis probe placements were validated as described above.
In Experiment 3 with liver nerve intact rats and in Experiment 4 with liver sympathetic, parasympathetic or sham denervated rats, after the t=100 blood sample, a
continuous i.c.v. infusion of orexin-A (1mmol/L, 5μl/hr, Bachem, Germany), MCH
(1mmol/L, 5μl/hr, Bachem, Germany) (only in Experiment 3) or purified water (MilliQ water, vehicle, 5μl/hr) (only in Experiment 3) 158 was started. After t=250 blood
sampling, animals were then deeply anaesthetized and 2 μl colored dye was injected
via the i.c.v. guiding probe to validate the probe placement.
In Experiment 5, both hyperinsulinemic clamp-1 and clamp-2 consisted of a basal
Ringer’s (vehicle) equilibration period (t=0 – t=100), a primary Ringer’s – hyperinsulinemic - euglycemic clamp period (t=110 – t=140) and a secondary BIC – hyperinsulinemic - euglycemic clamp period (t=140 – t=250). At t=100, insulin was
administered in a primed (7.2mU/kg·min in 4min for clamp-1, and 21.6mU/kg·min
in 4min for clamp-2) - continuous (3mU/kg·min for clamp-1 and 9mU/kg·min for
clamp-2) i.v. infusion. A variable infusion of a 25% glucose solution (containing 1%
[6,6-2H2] glucose) was used to maintain euglycemia (5.5±0.2mmol/L), as determined
by 10 min carotid catheter blood sampling. Thirty min after the start of the primary
insulin infusion, Ringer’s perfusion of the microdialysis probes was replaced by the
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BIC solution in BIC group. At the end of the clamp, five blood samples were taken
with a 10 min interval from t=210 to t=250. Liver tissue was then collected under deep
anaesthesia for RT-PCR study, and animals were perfused for Nissl and immunohistochemical staining.
In Experiment 6, animals provided with catheters and i.c.v. probe were divided into
two groups, with ad libitum access to food and water. Group 1 received i.c.v. infusion with SB-408124 (50mmol/L, 5μl/hr). Group 2 received 20% dimethyl sulfoxide
(DMSO, 5μl/hr, as vehicle and volume control for the SB-408124). Both groups had
a primed-continuous [6,6-2H2] glucose i.v. infusion started at ZT2 and 0.1ml blood
samples were taken every 60 min from ZT4 until ZT15. The i.c.v. infusion of SB408124 or vehicle was applied from ZT6 till ZT12. Food intake was measured every
hour (after each blood sampling).
Immunohistochemistry
For immunohistochemical staining, animals were sacrificed by an intra-atrial perfusion with saline, followed by a solution of 4% paraformaldehyde in 0.1M phosphate
buffer (pH 7.4) at 4°C. After post-fixation and equilibration for 48hrs with 30% sucrose
in 0.1M Tris-buffered saline (TBS), the brain tissue was cut into 30 μm sections and
divided into three equal groups for Fos and orexin or MCH immunostaining (Supplemental data.2).
Quantitative real-time PCR
Total RNA from liver tissue was isolated with Trizol (Invitrogen) and single-stranded
complementary DNA was synthesized. One μl of each cDNA was incubated in a final
volume of 20μl RT-PCR reaction containing 1X SYBR-green master mix (Applied
Biosystems) and 3 pmol reverse and 3 pmol forward primers (Supplemental data.3,
table 2). Efficiency of primer was determined on the basis of a cDNA dilution series. Quantitative RT-PCR was performed in an Applied Biosystems (Model ABI7300
Prism Sequence Detection System). Standard PCR conditions were used. The data
were acquired and processed automatically by Sequence Detection Software 33 (Applied Biosystems Inc).
Analytical methods
Blood samples were immediately chilled on ice in tubes containing a 5μl heparin
solution and centrifuged at 4°C. Plasma was then stored at -20°C for analysis. Plasma glucose concentrations were determined using a glucose/glucose oxidase-perid
method (Boehringer Mannheim, Mannheim, Germany). Plasma insulin, glucagon and
corticosterone concentrations were measured using radioimmunoassay kits [LINCO
Research (St. Charles, MO, USA and ICN Biomedicals, Costa Mesa, CA, respectively).
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Plasma [6,6-2H2] glucose enrichment was measured by gas chromatography-mass
spectrometry (GCMS), EGP was calculated by the methods of Steele 500.
Statistics
From Experiment 1 to 5, results are expressed by averaging values from three plasma
samples at the end of the equilibration state, and five plasma samples at the end of the
experimental period. In Experiment 6 the results are expressed by averaging values
from four different time periods. ANOVA and Student’s t-test was used to test orexin-A
or BIC effects on EGP, by comparing the mean of the equilibration state with the mean
of the experimental period, and were also performed to evaluate the BIC effects of different hypothalamic nuclei and to compare the different states of (hyper)insulinemia,
as well as evaluate the OX-1R effects on profile of glucose metabolism during different
time periods in Experiment 6.
Results
Removal of the endogenous GABA inhibition of perifornical orexin neurons
stimulates endogenous glucose production (Experiment 1)
Experiment 1 was performed to investigate whether activation of orexin neurons
during the light period would affect glucose metabolism. Histological analysis of the
probe placements showed that the tip of the microdialysis probes was located either in
the lateral part of the PVN (Fig. 1A2), at the upper borders of the PF-Oa (Fig. 1A3),
or in the dDMH (Fig. 1A4).
→ Figure 1 GABAa receptor antagonist BIC administration in the paraventricular (PVN),
dorsal part of the dorsomedial (dDMH) or perifornical orexin area (PF-Oa) causes different
EGP responses that are independent of changes in plasma insulin and corticosterone. A,
Representative microdialysis probe placements in PVN, PF-Oa and dorsal DMH. The left and
right panels of graph A1 are located at AP coordinates -3.30mm and -1.88mm, respectively.
Graphs A2, A3 and A4 show a Nissl stained example of each placement. PVN, DMH and
VMH are outlined by a white dotted line. B, C, D and E display the plasma glucose concentration, EGP, plasma insulin and corticosterone concentration before (equilibration state,
light gray bars) and after BIC (or vehicle, dark gray bars) in different hypothalamic nuclei.
F, Average EGP before (light gray bars) and after a 2-h infusion of BIC in the PF-Oa (dark
gray bars), with i.c.v. vehicle or orexin-1 receptor antagonist SB-408124 (pre)treatment. I.c.v.
(pre)treatment with the SB-408124 blocks the BIC-induced EGP increase. c: compact zone
of DMH, DM: dorsomedial DMH, f: fornix, VL: ventrolateral DMH, III: third ventricle. Data
are presented as mean±SEM. # P<0.05 vs. equilibration state; *P<0.05 vs. Vehicle control;
^P<0.05 vs. dorsal DMH and PVN.
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Rats with Ringer’s retrodialysis (n=6, vehicle) showed no changes in plasma glucose
levels as compared with their own equilibration state (Fig. 1B), however, it showed a
clear decline in EGP (Fig. 1C). This steady decline most likely is due to absence of food
in the cages, and not to the different brain infusions, as it was not observed in animals
that remained in ad libitum conditions (supplemental data.4, supplemental Fig. 1).
A
B 12
DM
C
VL
1
2
4
3
*#^
EGP (umol/kg.min)
125
*
100
*
75
#
50
2
Veh
PVN
dDMH
PF-Oa
dDMH
PF-Oa
2.0
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Veh
PVN
dDMH
#
300
0.0
PF-Oa
E
*
F
200
#
150
*
#
*
100
50
Veh
PVN
150
125
250
EGP (umol/kg.min)
Plasma corticosterone (ng/ml)
4
2.5
25
0
*#
6
D 3.0
150
0
*#
8
0
Plasma insulin (ng/ml)
C
*# ^
10
Plasma glucose (mmol/L)
f
#
100
75
50
25
Veh
PVN
dDMH
PF-Oa
0
Vehicle SB-408124
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Figure 2 Fos immunoreactivity around the microdialysis probes in the PF-Oa and dDMH
area (A,B,C,D). Fos and orexin double stainings are shown for BIC administration in the
PF-Oa (A) and dDMH (B). Fos and MCH double staining after BIC administration in the
PF-Oa is shown in C. D illustrates the Fos and orexin double staining in a Ringer’s control.
After BIC administration in the PF-Oa, Fos immunoreactivity is also present in orexin target
areas such as PVN (E), F shows the absence of Fos-ir in PVN with Ringer’s dialysis in PF-Oa
area. The photos shown are representative for all the other animals in the same group, which
are 4 to 6 rats depending on individual groups. III, third ventricle, f: fornix, Scale bar: A-D:
100μm, E, F: 200 μm.
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Figure 3 Fos immunoreactivity is present in extra-hypothalamic orexin target areas. Sections
A through F are double stained for Fos and orexin. Fos immunoreactivity is present in locus
coeruleus (A), central amygdaloid nucleus (C) and intermediolateral cell column of the sacral
spinal cord (E). The panels on their respective right side show the absence of Fos-ir in these
areas with Ringer’s dialysis in PF-Oa area (B, D and F). IV: fourth ventricle, OT: optic tract.
Scale bar: A, B: 100μm, C-F: 200 μm.
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chapter 6
Retrodialysis of BIC in the PF-Oa (n=5) caused a significant hyperglycemic response
and a pronounced increase in EGP as compared to its own equilibration state as well
as to that of the Ringer’s infusion. Retrodialysis of BIC into the dDMH (n=6) and
PVN (n=4) also caused a significant, albeit smaller hyperglycemic response. Different
from the PF-Oa group, both the dDMH and PVN group did not show a significant
increase in EGP as compared to their own equilibration, but both groups differed
significantly from the Ringer’s group at the end of their BIC administration period.
Plasma insulin levels were not affected by the BIC treatment (Fig. 1D). In addition,
BIC, but not Ringer’s, significantly increased plasma corticosterone levels, without
significant differences between the three groups (Fig. 1E). Moreover, no correlation
was found between the area under the curve of the corticosterone response and the
EGP increase in BIC treated rats (r=0.55, p=0.10).
Immunohistochemical staining with the Fos antibody showed that in BIC treated
brains (n=4-6) the major part of the activated neurons (as indicated by the expression of Fos in their nucleus) was limited to a restricted area around the dialysis probes
(±500μm spread from the edge of the dialysis probe). Double immunohistochemical
stainings with Fos and orexin (n=4-6) showed that when the Ringer’s dialysis probes
ended in the upper part of the PF-Oa, very few Fos positive nuclei (1-5/sections)
were observed, no colocalization of orexin and Fos was found. On the other hand, in
animals with BIC dialysis probes ending in the upper part of the PF-Oa, double immunohistochemical stainings showed that most of the orexin neurons (81±14 single
labelled neurons/section) were activated (58±9 Fos/orexin double labelled/section, i.e.
~71%; Fig. 2A). With the same BIC stimulation, most of the MCH neurons that are
interspersed among the orexin neurons were not activated (Fig. 2C). However, when
dialysis probes were placed in the dDMH, only a few orexin neurons (104±6 single
labelled neurons/section) were activated (21±2 Fos/orexin double labelled neurons/
section, i.e. ~20%; Fig. 2B) (p<0.001 vs. PF-Oa group). Fos expression after BIC administration into the PVN did not engage the orexin neurons. This specific activation
of orexin neurons by BIC is consistent with a previous study that targeted BIC to the
perifornical area 492. In addition, when most of the orexin neurons were Fos positive,
Fos immunoreactivity was also found in orexin targeting areas, such as PVN (Fig.
2E), locus coeruleus (Fig. 3A), central amygdaloid nucleus (Fig. 3C) and even as far
as the intermediolateral cell column of the sacral spinal cord (Fig. 3E) 501, confirming
the intensive activation of orexin neurons. Although the ARC has been suggested to
be involved in the appetite stimulating actions of orexin 502, 503, BIC administration
into the PF-Oa did not result in different numbers of Fos immunoreactive neurons
in this nucleus as compared to the Ringer’s control group (6.6±1.5 vs 3.3±0.5 per/
section, p=0.14).
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chapter 6
Antagonizing the central orexin-1 receptor prevents the increase in EGP induced
by BIC administration in the PF-Oa (Experiment 2)
Retrodialysis of BIC in the PF-Oa, combined with i.c.v. vehicle treatment, significantly
increased EGP (Fig. 1F) as well as plasma glucose concentration (6.1±0.1 vs 7.8±0.3
mmol/L, p<0.001), i.e. similar to the results of Experiment 1. However, i.c.v. (pre)treatment with SB-408124 prevented the BIC-induced increase in EGP. The BIC-induced
increase in plasma glucose concentration was also attenuated, but it was still significantly higher than its own equilibration state (5.9±0.1 vs 6.9±0.2 mmol/L; p=0.002),
and showed a trend to be significantly different from the BIC-induced increase in
plasma glucose in the vehicle group (p=0.055).
Central administration of orexin-A stimulates endogenous glucose production
(Experiment 3)
To confirm that orexin neurons are indeed involved in the BIC induced increase in
EGP, in Experiment 3 we performed an i.c.v. infusion of either orexin-A or vehicle.
I.c.v. administration of vehicle had no effect on plasma glucose levels (Fig. 4A). However, a clear decline in EGP (Fig. 4B) and metabolic clearance rate (MCR) (EGP/
plasma glucose concentration) (Fig. 4C) was apparent, i.e. similar to what was found in
the Ringer’s animals of Experiment 1. I.c.v. infusion of orexin-A increased the plasma
glucose level. In contrast to the vehicle group, no decrease in EGP and MCR was
observed. EGP at the end of the orexin-A infusion was also significantly higher than
that in the vehicle group at the end of the infusion state, thus i.c.v. orexin-A prevented
the endogenous decline of EGP. Plasma insulin concentrations did not change during
i.c.v. infusion of either vehicle or orexin-A (Fig. 4D). In line with the absence of Fos
immunoreactivity in MCH neurons after BIC stimulation, no significant effects of i.c.v.
administered MCH (n=5) on either plasma glucose levels, EGP or MCR as compared
to the vehicle control animals were found (Fig. 4A, B and C).
Hepatic sympathetic but not parasympathetic denervation blocks the effect of
i.c.v. orexin-A infusion on EGP (Experiment 4).
Successful hepatic sympathetic denervation (HSX) was validated by a significant
decrease of liver noradrenaline concentrations as compared to sham denervation
(shamX) (Fig. 4E). After HSX, i.c.v. infusion of orexin-A no longer could prevent the
endogenous decline of EGP and MCR as shown in Experiment 3 (compare 4H and I
with 4B and C). However, after hepatic parasympathetic denervation (HPX) or sham
denervation (ShamX) the i.c.v. infusion of orexin-A was as effective as in liver-intact
animals to prevent the endogenous drop in EGP and MCR (Fig. 4H and I). Plasma
glucose changes on the other hand, were not affected by any of the denervation procedures, i.e. plasma glucose levels increased after i.c.v. orexin-A infusion in all three
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chapter 6
B
A8
C
100
6
15.0
*
75
4
2
12.5
#
#
^
50
MCR (mL/kg.min)
*
EGP (umol/kg.min)
Plasma glucose (mmol/L)
#
#
10.0
#
7.5
5.0
25
2.5
0
Vehicle
Orexin-A
0
MCH
Orexin-A
0.0
MCH
E
F
2.0
40
100
1.5
30
1.0
0.5
Vehicle
Orexin-A
MCH
80
Plasma glucagon (pg/ml)
Liver noradrenaline (ng/g)
Plasma insulin (ng/ml)
D
Vehicle
20
10
60
40
20
#
0.0
Vehicle
0
Orexin-A
G
0
ShamX
H
#
75
EGP (umol/kg.min)
#
6
4
ShamX
*
#
12.5
50
#
10.0
7.5
5.0
25
2
0
*
#
HPX
15.0
MCR (mL/kg.min)
8
HSX
I
100
10
Plasma glucose (mmol/L)
HSX
2.5
HSX
HPX
ShamX
0
HSX
HPX
ShamX
0.0
HSX
HPX
ShamX
Figure 4 Involvement of the autonomic nervous system in the EGP increase induced by
bicuculline administration in the PF-Oa. A-C, Average plasma glucose concentration, EGP
and MCR before (light gray bars) and after a 2-h infusion of vehicle, orexin-A or MCH into
the lateral cerebral ventricle (dark gray bars). D, Average plasma insulin concentration before
(equilibration state, light gray bars) and after i.c.v. vehicle or orexin-A infusion (dark gray
bars). E, Hepatic sympathetic denervation abolishes 96% of the noradrenaline content in
the liver. F-I, Plasma glucagon concentration, EGP, MCR and plasma glucose concentration
before (light gray bars) and after i.c.v. orexin-A infusion (dark gray bars) with HSX, HPX
and shamX. Data are presented as mean±SEM. # P<0.05 Infusion state vs. Equilibration state
(or shamX vs. HSX in E); *P<0.05 vs. Vehicle control in A and B and vs. HSX in H; ^P<0.05
MCH vs. orexin-A group.
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chapter 6
groups (Fig. 4G). No differences were found in plasma glucagon concentrations as a
result of the i.c.v. orexin-A infusion or the denervation procedure (Fig. 4F).
Removal of the endogenous GABA inhibition of perifornical orexin neurons
reduces hepatic insulin sensitivity (Experiment 5)
During clamp-1 (3mU/kg.min) retrodialysis of BIC in the PF-Oa (n=6) and dDMH
(n=4) after the equilibration state still induced a significant increase in EGP in both
groups, despite the presence of peripheral hyperinsulinemia (Fig. 5A). Furthermore,
EGP in the dDMH group was significantly lower than in the PF-Oa group. Thus the
insulin mediated suppression of EGP, i.e. hepatic insulin sensitivity, was significantly
attenuated in both BIC groups as compared to their vehicle control groups (Fig. 5B),
but the effect was significantly more pronounced in the PF-Oa group than in the
dDMH group. The rate of glucose disappearance (Rd) was significantly increased by
BIC in the PF-Oa group, but not in the dDMH group (Fig. 5C) as compared to their
respective control groups.
To explore the effect of BIC on peripheral insulin sensitivity, clamp-2 with a higher
plasma insulin level was performed. Despite the higher insulin levels, which resulted
in a significant further decrease in EGP in the two Ringer’s control groups, BIC still
caused a significant increase in EGP in both the PF-Oa (n=7) and the dDMH (n=4)
group as compared to their respective control groups (Fig. 5A). Again the effect was
more pronounced in the PF-Oa group than in the dDMH group. With regard to Rd,
the two Ringer’s groups showed a significant higher Rd as compared to clamp-1 and
both BIC groups showed a significantly higher Rd than the control groups (Fig. 5C).
The RT-PCR study on the liver tissue revealed that BIC treatment significantly diA
A 175
B
B
100
175
100
150
150
#
#*
#*
#
#**
25
25
0
^^
PF-Oa dDMH
PF-Oa dDMH
Clamp-1
Clamp-1
^^
PF-Oa dDMH
PF-Oa dDMH
Clamp-2
Clamp-2
0
#*
#*
-50
-50
^
#
250
#*
#*
0
#
300
250
200
Rd (umol/kg.min)
#
50
50
0
#
#
#
50
50
100
100
75
75
#
Rd (umol/kg.min)
#
#
%
Suppression
% Suppression
EGP (umol/kg.min)
EGP (µmol/kg.min)
125
125
C
C
^
200
150
150
#
#
^
#
^
^
^
^
^
#
100
100
50
50
-100
-100 PF-Oa dDMH
PF-Oa dDMH
Clamp-1
Clamp-1
^^
^^
PF-Oa dDMH
PF-Oa dDMH
Clamp-2
Clamp-2
0
0 PF-Oa dDMH
PF-Oa
Clamp-1dDMH
Clamp-1
PF-Oa dDMH
PF-Oa
Clamp-2dDMH
Clamp-2
Figure 5 Average EGP (A), insulin suppression of EGP (B) and Rd (C) under hyperinsulinemic-euglycemic clamp-1 (3 mU/kg.min) and clamp-2 (9 mU/kg.min) conditions. BIC administration in the PF-Oa induced the strongest increase in EGP as well as in Rd. Light gray
bars, vehicle retrodialysis group; dark gray bars, BIC retrodialysis group. Data are presented
as mean±SEM. # P<0.05 vs. Ringer’s control; *P<0.05 vs. PF-Oa; ^P<0.05 vs. clamp-1.
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minished the inhibitory effect of hyperinsulinemia on the expression of phosphoenolpyruvate cerboxykinase (Pepck) and Glucose-6-Phosphatase (G6Pase), as well as
its stimulatory effect on the expression of glucokinase (Fig. 6A-C). In addition to these
glucoregulatory genes, we also checked three genes that have previously been associated with the development of hepatic insulin resistance 199. However, the BIC-induced
activation of orexin neurons had no significant effects on the expression level of either
tumor necrosis factor alpha (TNFα), interleukin-6 (IL-6), or suppressor of cytokine
signaling-3 (SOCS-3) (Fig. 6D-F).
A
B
7
4
Pepck
C
G6Pase
2.0
Glucokinase
6
#
3
5
#
4
2
3
1.0
#
#
*
2
1
#
*^
1
0
*^
1.5
Non-clamp Clamp-1
Clamp-2
D
0.04
0
*^
*^
Non-clamp Clamp-1
Clamp-2
E
0.04
TNF alpha
#
0.0
0.03
0.3
0.02
0.02
0.2
0.01
0.01
0.1
Non-clamp Clamp-1
Clamp-2
0.00
Non-clamp Clamp-1
Clamp-2
F
0.4
IL-6
0.03
0.00
*^
0.5
Non-clamp Clamp-1
Clamp-2
0.0
SOCS-3
Non-clamp Clamp-1
Clamp-2
Figure 6 Effects of BIC and hyperinsulinemia on the hepatic expression level of Pepck,
G6Pase, glucokinase, TNF-alpha, IL-6 and SOCS-3 mRNA. BIC administration in the perifornical orexin area counteracts the effects of hyperinsulinemia on the hepatic expression
level of the Pepck, G6Pase and glucokinase genes, and has no effects on that of the TNFα, IL-6
and SOCS-3 genes. Light dray bars: Ringer’s control, dark gray bars, BIC groups. Data are
presented as mean±SEM. # P<0.05 vs. Ringer’s, * P<005 vs. non-clamp, ^ P<0.05 vs. clamp-1.
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Antagonizing the orexin-1 receptor suppresses the daily increase of glucose
appearance at dawn (Experiment 6)
If an increased activity of orexin neurons results in an increase in EGP, a suppression
of the endogenous increase in central orexin activity is expected to change glucose
metabolism in the opposite direction. The rhythmic activity of orexin along the light/
dark cycle, with lowest levels during the light period and an acrophase during the
dark period in rats, is well known 495, 496. In Experiment 6 we administered the OX-1R
antagonist SB-408124 i.c.v. from the early light period until the early dark period and
measured the 12 hours profile of plasma glucose concentration and rate of glucose
appearance (Ra). Since long term fasting is known to activate orexin neurons 212, this
study was carried out under ad libitum conditions in order not to disturb the physiological release pattern of orexin. Starting with a similar basal Ra (P=0.90, Fig. 7A),
the OX-1R antagonist SB-408124 or vehicle was infused i.c.v. from ZT6 onwards
A
B
225
Ra (umol/kg.min)
200
175
ZT4-6
ZT6-11
ZT11-12
ZT12-15
#
150
8
7
#
^
^
*
125
*
100
75
Plasma glucose (mmol/L)
250
6
5
4
3
2
50
1
25
Vehicle
0
SB-408124
C 30
D
#
MCR (ml/kg.min)
25
#
20
*
15
*
10
5
0
Vehicle
5
SB-408124
Vehicle
SB-408124
^
^
Plasma insulin (ng/ml)
0
4
3
2
1
Vehicle
SB-408124
0
ZT5
7
Light
9
11
13
Dark
15
Figure 7 I.c.v. infusion of OX-1R antagonist SB-408124 suppresses the increase of Ra and
MCR from dawn (ZT11-12) until the first hours of the dark period (ZT12-15), without influencing the plasma glucose and insulin concentration. Data are presented as mean±SEM.
# P<0.05 vs. ZT4-6, ^ P<0.05 vs. ZT6-11. *P<0.05 vs. the same period in the vehicle group.
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continuously. From basal until the dark period, repeated-measures ANOVA detected
significant effects of Time in the vehicle group on Ra (F (3,19)=13.0, p<0.001). During
both dawn and dark period Ra was significantly higher than basal rates (p=0.002 and
p=0.003 respectively) and during the light period (p=0.002 for both periods), but this
effect was not found in the i.c.v. SB-408124 group (F(3,23)=1.47,p=0.25). Between
the two groups, no significant effects of the OX-1R antagonist on Ra were detected
(p=0.90 and p=0.58) during the basal and light period (i.e. ZT6-ZT11). The first and
also most significant difference was seen just before the dark period (i.e. ZT11-ZT12),
with the SB-408124 group having a significantly lower Ra than the vehicle group
(P<0.001). This difference extended into the dark period from ZT12 (P=0.03). Plasma
glucose levels, however, showed no Time difference between any of the time points
within either the vehicle (F(3,19)=1.15, p=0.36) or SB-408124 group (F(3,23)=1.11,
p=0.34). Furthermore, no difference was found between vehicle and SB-408124 groups
(F (1,9)=1.0, p=0.33) (Fig. 7B). Consequently, repeated-measures ANOVA detected
significant effects of Time in the vehicle group on MCR (F(3,19)=9.76, p=0.001), with
both the dawn and dark period showing a significantly higher MCR than the basal (p=0.002 and p=0.003 respectively) and light period (p=0.002 for both periods).
No effect of Time was detected in the i.c.v. SB-408124 group (F(3,23)=1.22, p=0.33).
Moreover the SB-408124 group had a significantly lower MCR than the vehicle group
during the dawn (P=0.003) and dark periods (P=0.02, Fig. 7C).
These results show a significant inhibitory effect of i.c.v. SB-408124 on a physiological increase in Ra and MCR starting around the light-dark transition (dawn) period
and extending in the first part of the dark period. Furthermore, no differences were
detected between the two groups with regard to their total food intake during this
12 h study (8.95±1.64 vs. 7.93±1.76, p=0.68) and plasma insulin concentration (Fig.
7D), thus excluding an indirect effect of the OX-1R antagonist on Ra via a reduction
in food intake or influence on insulin level. The fact that the time related effects of
i.c.v. OX-1R antagonist were only seen shortly before and during arousal indicates
that under physiological conditions the orexin system affects glucose metabolism in
a time-dependent manner.
Discussion
Plasma glucose concentrations are kept within a narrow physiological range by dynamically balancing glucose production and utilization to avoid hypoglycaemia and
hyperglycemia and to guarantee substrate availability for energy production. Disturbances in the regulation of glucose metabolism can result in insulin resistance
and diabetes mellitus type 2. Accumulated animal data of recent years indicate that
derangements of hypothalamic neural networks may act as a critical factor responsible for an unbalanced glucose metabolism 504. The present study identifies orexin as
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one of the critical players in such a glucoregulatory hypothalamic network. Activation of orexin neurons in the hypothalamic perifornical area increases blood glucose
concentrations via a stimulation of endogenous glucose production. Moreover, daily
rise in endogenous orexin activity is involved in an increased blood glucose appearance at dawn. For the stimulatory effect of orexin on glucose production to become
apparent an intact autonomic outflow from brain to liver via the hepatic sympathetic
innervation is essential.
DMH and PVN have both been defined as being part of the endocrine and autonomic hypothalamic output network, with the general concept that the PVN functions
as the hypothalamic integrating center for autonomic and endocrine information and
serves as the final neuroendocrine and autonomic output nucleus from the hypothalamus 64, whereas the DMH has a more specific role in controlling the stress response and
circadian rhythms of sleep 274. In comparison with the PVN, the separation between
DMH and PF-Oa is less obvious. The rat DMH is a large complex nucleus, with its
dorsomedial and ventrolateral parts divided by a compact central zone. Unlike the
PVN, the different divisions of the DMH do not show a clear neurochemical separation. For instance, a large part of the PF orexin neurons extends into the ventrolateral
DMH. In fact, in some (lesion) studies the DMH was considered as one area, often
including part of the PF-Oa 505. In the present study, the glucoregulatory effects of BIC
markedly differed between PF-Oa, dDMH and PVN with respect to its effects on EGP
and peripheral glucose uptake. Removal of the GABAergic inhibition clearly separated
the PF-Oa, dDMH and PVN.
Within the PF-Oa area, the distribution of orexin and MCH neurons strongly overlaps, without any co-localization. MCH and orexin both have been characterized as
orexigenic peptides 506 and both orexin and MCH neurons receive GABAergic inputs
507
, as well as being sensitive to other metabolic inputs such as leptin 508, NPY/AGRP
and POMC 509, 510. Nevertheless, our and other studies 492 show that during the sleep
period only orexin, but not MCH neurons can be activated by removal of the GABAergic inhibition, indicating that the stimulatory effect of BIC on EGP probably involves
activation of orexin, but not MCH, neurons. Indeed i.c.v. orexin, but not i.c.v. MCH,
was able to affect EGP and i.c.v. administration of the orexin antagonist blocked a
major part of the EGP stimulatory effect of BIC. Together, these data indicate that in
the PF-Oa area, orexin neurons play a prominent role in the control of endogenous
glucose production.
Both neuronal and hormonal factors have been considered to relay the orexin signal
to the periphery. Central administration of orexin can activate the hypothalamopituitary-adrenal axis and consequently increase plasma corticosterone levels 511. Corticosterone is able to stimulate hepatic glucose production, but in the present study
EGP responses to BIC were site specific whereas the corticosterone responses were
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not, suggesting that corticosterone is not the major factor responsible for the increase
in EGP. In addition, also an altered pancreatic release of glucagon does not seem to be
the determining factor. An alternative pathway for relaying orexin signaling to the liver
is via the autonomic nervous system. Indeed, orexin can influence liver function via a
multilevel sympathetic output pathway 512. Previous studies have already shown that
denervation of the sympathetic input to the liver abolishes a hypothalamic induced
increase in EGP 48, 158, Also in line with other studies 513, 514, a purely hormonal effect
of orexin on EGP is therefore not very likely. In the present study, we showed that
central administration of orexin-A can only affect EGP when an intact sympathetic
innervation of the liver is present, indicating a stimulatory effect of central orexin on
sympathetic neuronal outflow. Remarkably, the sympathetic denervation of the liver
did not prevent the stimulatory effect of i.c.v. orexin-A on plasma glucose concentrations. The separation of the plasma glucose and EGP responses indicate that increased
central orexin signalling might affect plasma glucose concentrations not only through
changes in the hepatic glucose production, but also by affecting peripheral glucose
uptake. A central control of peripheral glucose uptake, mediated by the autonomic
nervous system, is also supported by previous studies showing that the increased
glucose uptake in skeletal muscle and brown adipose tissue after the central administration of NMDA and leptin is abolished by sympathetic denervation 515, 516. Since
plasma insulin is not affected by orexin-A administration and hepatic sympathetic
denervation 48, and our experiments were performed under fasting condition, the
effect on glucose in Experiment 4 seems to be mediated by a change in non-insulin
dependent glucose uptake.
The GABAergic input to the orexin neurons is timed by the central biological clock
located in the suprachiasmatic nucleus (SCN), with the most prominent inhibition
occurring during the sleep period 492, 517. This timed GABA input probably is responsible for switching the orexin activity on and off in its target areas, thereby controlling the sleep/wake cycle 495, 496. Since the SCN not only times glucose metabolism
518
, but also controls sympathetic pre-autonomic neurons 519, very possibly the SCN
utilizes GABA as a timing signal to control orexin activity and consequently influence sympathetic outflow and regulate glucose metabolism. On the other hand, it is
well accepted that insulin signalling in the arcuate AGRP/NPY neurons accounts for
approximately 40% of the insulin mediated suppression of EGP via the autonomic
output to liver 157, 158, 520. Therefore it is possible that removal of GABA inhibition at
the level of the PF-Oa could also block central insulin signalling by antagonizing the
arcuate NPY/GABA projection to the orexin neurons, or by activating the orexinergic
projection to the arcuate NPY neurons (counteracting the suppressive effect of insulin
on NPY neurons) 158, 502, 521. However, most of our experiments were performed under
basal insulin conditions, making the contribution of such a pathway less prominent.
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Nevertheless, the present data support the conclusion from other studies using the
orexin knock-out mice model, by showing that orexin is indeed an essential factor for
maintaining hypothalamic insulin sensitivity for glucose metabolism 522. However, at
which hypothalamic area and under which situation this interaction takes place needs
further investigation.
GABAergic input to the orexin neurons is timed by the central biological clock
located in the suprachiasmatic nucleus (SCN), with the most prominent inhibition occurring during the sleep period 492, 517. This timed GABA input probably is responsible
for switching the orexin activity on and off in its target areas, thereby controlling the
sleep/wake cycle 495, 496. Glucose metabolism in the rat is also well timed by the SCN
output 518. Data obtained from both human and rat studies strongly suggest that the
rise in plasma glucose concentrations during the dawn period is primarily caused by
an increased hepatic glucose production controlled by the endogenous clock located
in the central nervous system 523-526.
With the present data, we propose that the orexin system in the PF area is an important intermediate between the biological clock and at least one aspect of the dawnphenomenon, i.e. increased glucose production. Although the hypothalamic administration of BIC also clearly enhanced peripheral glucose uptake, we have not been able
to link it to a specific nucleus or neurotransmitter system and the intermediate neural
mechanism between the biological clock and peripheral glucose uptake is therefore
still unknown at present.
In conclusion, we identified orexin as an important hypothalamic regulator of glucose homeostasis. The hypothalamic orexin system is possibly involved in incorporating timing information from the master brain clock into the control mechanism of
endogenous glucose production and also provides a possible molecular explanation for
the previously observed correlation between short sleep duration and an increased risk
for insulin resistance 527. The present results show that the inappropriate activation of
orexin neurons during sleep deprivation will induce an increase in basal endogenous
glucose production and a reduction in hepatic insulin sensitivity.
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Supplemental data.1
Table 1 Stereotactic coordinates for placements of microdialysis and i.c.v. probes.
(mm) PF-Oa
dDMH
PVN
i.c.v.
Antero- posterior
Lateral
Ventral
Angle
-2.4
-2.4
-1.6
-0.8
2.5
2.0
2.0
2.0
-8.1
-7.9
-7.9
-3.2
10
10
10
0
Tooth bar was set as -3.2 mm. The ventral coordinates were standardized for 300g BW, every
additional 25g BW will be placed 0.1 mm deeper.
Supplemental data.2
Immunocytochemistry
Two groups of brain sections were incubated overnight at 4°C with goat anti-Fos
(1:1500; Santa Cruz Biotechnology, Inc., Santa Cruz, CA) and rabbit anti-orexin or
rabbit anti-MCH (1:2000; Phoenix Pharmaceuticals, Belmont, CA) primary antibodies. Sections were then rinsed in 0.1M TBS, incubated 1 hr in biotinylated horse
anti-goat IgG, and then 1 h in avidin–biotin complex (ABC, Vector Laboratories, Inc.,
Burlingame, CA), the reaction product was visualized by incubation in 1% diaminobenzidine (DAB) (0.05% nickel ammonium sulphate was added to the DAB solution
to darken the reaction product, DAB/Ni) with 0.01% hydrogen peroxide for 5-7 min.
After Fos immunostaining, sections were rinsed in 0.1M TBS, incubated 1 h in biotinylated goat anti-rabbit IgG, and then 1 h in ABC, the reaction product was visualized
by DAB staining only. Sections were mounted on gelatine-coated glass slides, dried,
run through ethanol and xylene and covered for observation by light microscopy.
Supplemental data.3
Table 2, RT-PCR primer
Gene
Forward primer
Reverse primer
Pepck
TGCCCTCTCCCCTTAAAAAAG
CGCTTCCGAAGGAGATGATCT
G6Pase
CCCATCTGGTTCCACATTCAA GGCGCTGTCCAAAAAGAATC
Glucokinase TCCTCCTCAATTGGACCAAGG TGCCACCACATCCATCTCAA
IL-6
TGCCCTTCAGGAACAGCTATG
TGTCAACAACATCAGTCCCAAGAA
TNF-a
CTAACTCCCAGAAAAGCAAGCAA
CCTCGGGCCAGTGTATGAGA
SOCS3
CCTCCAGCATCTTTGTCGGAAGAC TACTGGTCCAGGAACTCCCGAATG
Ubi*
CTCCAACAGGACCTGCTGAAC CTGAAGAGAATCCACAAGGAATTGA
* Ubi: ubiquitin conjugate enzyme, as reference gene.
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Supplemental data.4
EGP (umol/kg.min)
Ringer's retrodialysis into
Supplemental Figure 1 EGP response to
hypothalamus (fasting)
Ringer’s retrodialysis into hypothalamus or
Purified water i.c.v. (fasting)
purified water i.c.v. infusion. Food was reBrain intact (fasting)
100
Brain intact (ad libitum)
moved from the rat’s home cage at the beginning of the light period. Experiments started
90
five hours later, after the baseline samples for
calculating the equilibration of isotope tracer
80
[6.6-2H2] glucose were taken between 90-100
min. Rats received either Ringer’s retrodialy70
sis into the hypothalamus (3μl/min) or purified water i.c.v. (5μl/hr), blood samples were
60
taken continuously during 2 hrs with a 50
min intervals. With similar basal EGP, both
50
groups show similar decline of EGP along
Basal
i.c.v or diaylysis infusion
the 2 hrs sampling period and also ended
state
state
40
up with similar EGP’s at the last time point
90
150
200
250
(t=250 min, 54.9±0.74 vs 54.8 ± 2.52 μmol/
(Time (min)
kg.min, p=0.65). Another group of rats that
went through a similar fasting protocol but without any brain infusion showed a similar
EGP on each time point. Under ad libitum conditions, without any brain infusion, EGP does
not show a declining trend. This indicates that the decline of EGP is an endogenous process
resulting from the removal of food from rats’ home cage at the beginning of the light period,
and not from the brain infusion.
Supplemental data.5
Supplemental Figure 2 Orexin neurons (dark brown) and Fos positive orexin neurons were
counted in the rectangle box outlined in a Nissl staining (blue) section (1.5 mm x 1 mm).
III, third ventricle, f: fornix. Scale bar: 500 μm.
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Chapter 7
Pmch expression during early development is a critical determinant of energy
homeostasis
The American Journal of Physiology – Endocrinology and Metabolism (under revision)
Joram D. Mul, Chun-Xia Yi, Pim W. Toonen, Martine C.J. van der Elst, Bart A. Ellenbroek,
Andries Kalsbeek, Susanne E. la Fleur, and Edwin Cuppen
Abstract
Postnatal development and puberty are times of strong physical maturation and require large quantities of energy. The hypothalamic neuropeptide Melanin-Concentrating Hormone (MCH) is known to stimulate nutrient intake and regulate energy
homeostasis, but the underlying mechanisms are largely not understood. Here we
used a novel rat knockout model in which the Pmch gene has been inactivated to
study the effects of loss of MCH on energy regulation in more detail. Pmch-/- rats
were found to be lean, confirming earlier findings in MCH knockout mice. While
endocrine parameters were changed in pmch-/- rats, endocrine dynamics were normal,
indicating an adaptation to new homeostatic levels rather than disturbed metabolic
mechanisms. Detailed analysis of feeding behavior revealed that pmch-/- animals are
hypophagic during early development and switch to hyperphagia after entering adulthood. Moreover, our data show that loss of Pmch results in a 20% lower set point for
body weight that is determined solely during the first 8 postnatal weeks and remains
unchanged during adulthood. Although the final body weight depends on the diet,
the Pmch knockout effect is similar for all diets tested in this study. Current findings
show an important role for Pmch in energy homeostasis determination during early
development, and indicate that the MCH-Melanin-Concentrating Hormone Receptor 1 (MCH1R)-system is a plausible target for childhood obesity treatment, currently
a major health issue in first world countries.
Introduction
Childhood obesity is now widely recognized as a severe public health issue 528. Treatment with drugs aimed at neural systems involved in the determination of the energy
balance could potentially result in a lower energy balance during puberty as well as
later in adulthood. Therefore, neuropeptides involved in body weight regulation during early development and puberty are attractive targets for anti-childhood obesity
drugs.
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The neuronal metabolic systems in humans and primates develop prenatally while in
rodents these systems develop during the first three postnatal weeks 529, 530. This results
in the activation and optimization of neuronal systems during early rodent development. A second important metabolic period is puberty, a period of major growth,
hormonal changes, and sexual maturation. In the rat, puberty is characterized by
different responses of young-adolescent (day 40) and young-adult (day 60) male rats
to environmental cues like stress and cold 531, 532. In addition to these age-dependent
behavioral differences, the amount of food consumed during early rodent life plays
an important role in determining subsequent food intake in later life 533. Following
this initial observation, many studies have shown that postnatal nutrition is important
for the regulation of appetite in adult rodents, suggesting that the energy balance is
predominantly determined during early development 534.
MCH has been shown to be a critical mammalian hypothalamic effecter of energy
homeostasis by various genetic and pharmacological studies 535. The MCH precursor
gene (Pmch) is expressed predominantly in neurons of the lateral hypothalamic area
(LHA) and the incerto hypothalamic area (IHy), which project throughout the brain
536, 537
. Pmch is also expressed in some peripheral tissues, such as the testis, although
at lower levels than in brain 538. Processing of the preprohormone Pmch results in the
production of three neuropeptides: neuropeptide glycine-glutamic acid (N-GE), neuropeptide glutamic acid-isoleucine (N-EI) and MCH 539. However, most studies have
focused on MCH. Pmch mRNA is up regulated after fasting or leptin deficiency 540, 541,
3rd ventricle ICV injections of MCH increase food intake and body weight 542-546, Pmch
knockout mice are lean due to a decreased food intake and an increased metabolic
rate 547, 548, and overexpression of MCH causes obesity 549. In rodents MCH binds to
MCH1R, a G-protein coupled receptor expressed throughout the brain 550-553. MCH1R
is particularly enriched in the nucleus accumbens shell (AcbSh) 551, 552, 554, thus forming
a potential hypothalamic-limbic circuit modulating the hedonic, or rewarding, aspects
of feeding 554, 555. Rodents only express MCH1R, whereas humans also express a second
MCH receptor, MCH2R 556. Recent studies have focused on MCH1R, demonstrating
that MCH1R-antagonism decreases food intake and weight gain in adult rodents 557-561.
Most MCH-related studies using genetic models or MCH antagonists have primarily
focused on the function of MCH during adulthood. Therefore the effect of loss of Pmch
expression on energy regulation during early development is largely unexplored. To
study nutrient intake during this period, we utilized a novel rat knockout model that
was generated recently using an ENU-driven target-selected mutagenesis approach
562
. Preliminary studies in young-adult animals showed that the caloric intake of pmch/rats was unchanged compared to control littermates when nutrient intake data was
normalized for body weight. Following this initial observation we have analyzed the
metabolic characteristics of this knockout (KO) rat model on three different diets
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(maintenance [M], semi-high-protein [SHP], and high-fat [HF]) by following body
weight and food intake during development and adulthood, and by measuring endocrine values. Our results show that Pmch plays an important role in the energy balance
determination during the first 8 postnatal weeks, and that loss of Pmch results in a
20% decreased body weight during adulthood regardless of the diet.
Methods
Animals
The Animal Care Committee of the Royal Dutch Academy of Science approved all
experiments according to the Dutch legal ethical guidelines. The Pmch KO rat (Pmch1Hubr
) was generated by target-selected ENU-driven mutagenesis (see 562). Briefly, highthroughput resequencing of genomic target sequences in progeny from mutagenized
rats revealed an ENU-induced premature stopcodon in exon 1 (K50X) of Pmch in a
rat (Wistar/Crl background). The heterozygous mutant animal was backcrossed to
wild type Wistar background for six generations to eliminate confounding effects from
background mutations induced by ENU. Assuming that the total amount of coding
DNA in a male rat is approximately 28.6 x106 bp 536 and the used ENU treatment
resulted in a mutation frequency of 1 per 1.5x106 bp 562, approximately 19 mutations
can be expected in protein-coding sequences of the founder animal. Backcrossing six
times would therefore decrease the total number of random background mutations to
1. Furthermore, the maximal number of nonsense inducing mutations (NIMs) is much
lower than 19, i.e. 3 563. However, as part of the donor chromosome harboring the Pmch
mutation is still present after six backcrosses 564, we cannot fully exclude the presence
of tightly linked confounding mutations in our model. To further control for possible
contributions of confounding mutations, we have repeated several measurements in
different outcross generations and could replicate previous findings in each generation. Additionally, we have always generated experimental KO and wild type animals
by crossing pmch+/- animals. Experimental animals were obtained at the expected
Mendelian frequency. Furthermore, littermates (with similar genetic backgrounds)
were used as much as possible for experiments. Pmch-/- rats were viable into adulthood
and fertile, and appeared phenotypically normal despite their decreased body weight.
Two rats were housed together, unless noted otherwise, under controlled experimental conditions (12 h light/dark cycle, light period 0600-1800, 21±1°C, ~60% relative
humidity). Standard fed diet (semi high-protein chow: RM3, 27% CP and 12% F, 3.33
kcal/g AFE, SDS, Witham, United Kingdom) and water was provided ad libitum unless noted otherwise (maintenance chow: RM1, 17% CP and 7% F, 3.29 kcal/g AFE,
SDS, Witham, United Kingdom; high-fat chow: 45%-AFE, 20% CP and 45% F, 4.54
kcal/g AFE SDS, Witham, United Kingdom). Only male animals were used in the
present study.
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Genotyping
Genotyping was done using the KASPar SNP Genotyping System (KBiosciences, Hoddesdon, United Kingdom 565) using gene-specific primers (forward common, TTAAT
ACATT CAGGA TGGGG AAAGC CTTT; reverse wild type, GAAGG TGACC
AAGTT CATGCT CGATC TTTCT GCGGT ATCTT CCTT; reverse homozygous,
GAAGG TCGGA GTCAA CGGAT TCGAT CTTTC TGCGG TATCT TCCTA). All
pups were genotyped during week 3. Genotypes were reconfirmed when experimental
procedures were completed.
Northern Blot analysis
Northern Blot analysis 566 was done using a Pmch specific radiolabeled PCR-derived
probe covering the first exon of the gene. The following primers were used for probe
generation: forward primer: ATTCT CCTTC GGCTT TACG; reverse primer: TCCAG
AGAAG GAGCA ACAAC.
Immunohistochemistry
A detailed description of the immunohistochemistry procedure is provided in the
Supplemental Material and Methods section.
Body weight and nutrient intake monitoring
Pups were housed individually 3 weeks after birth. Until weaning, pups had access
to SHP diet in their maternal home cage. Body weight, water intake, and food intake
was monitored biweekly for 18 weeks (n = 10-16 per group). Water was freely available, and food (M, SHP, or HF diet) was provided ad libitum. At 8 and 17 weeks of
age, nutrient intake was measured for 6 days at 06:00 (dark phase intake) and at 18:00
(light phase intake).
Body composition
A WAT fat pad sample (containing the right side of the subcutaneous WAT pad, the
whole epididymal WAT pad, the right side of the perirenal WAT pad, the whole mesenteric WAT pad), liver, adrenals, and the thymus were isolated from 26-week old
animals (n = 3-6 per group).
Jugular vein catheter placement
At 22 weeks of age, animals were anaesthetized with isoflurane and equipped with a
jugular vein catheter (headpiece: Connector Pedestal 20GA, Plastics One, Roanoke,
VA, USA). Before surgery, animals received one dose of Temgesic® (0.05 mg/kg, subcutaneous; Schering-Plough, Utrecht, the Netherlands). Animals were allowed to recover
for 7 days during which they were handled to minimize stress.
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Six time point blood plasma measurements
Blood samples (0.3 ml) were obtained at 24:00, 04:00, 08:00, 12:00, 16:00, and 20:00
(n = 9-13 per group). Blood was collected in EDTA tubes (BD Vacutainer tubes, Plymouth, United Kingdom) containing 20µl aprotinin (Sigma-Aldrich, Zwijndrecht,
the Netherlands). Samples were collected on ice and instantly centrifuged at 2150 rcf
for 15’ at 4°C. Samples were then aliquoted and stored at -80°C until analysis. Plasma
leptin levels were determined in duplo using a leptin ELISA (EZRL-83K, Linco Research, St. Charles, Missouri, USA). The assay sensitivity limit was 0.04 ng/ml. The
intra- and interassay coefficients of variation were 2.17 and 3.40%, respectively. Plasma
insulin levels were determined in duplo using an insulin ELISA (EZRMI-13K, Linco
Research, St. Charles, Missouri, USA). The assay sensitivity limit was 0.2 ng/ml. The
intra- and interassay coefficients of variation were 1.91 and 7.63%, respectively. Plasma
glucose levels were determined in duplo using an OneTouch® Ultrameter® (LifeScan
Benelux, Beerse, Belgium). Plasma corticosterone levels were determined in duplo using a Corticosterone EIA (DSL Deutschland GMBH – Benelux, Assendelft, NL). The
assay sensitivity limit was 1.6 ng/ml. The intra- and interassay coefficients of variation
were 3.23 and 4.77%, respectively.
Hyperinsulinemic-euglycemic clamp
A detailed description of the hyperinsulinemic-euglycemic clamp procedure is provided in the Supplemental Material and Methods section.
Statistics
Data are expressed as mean ± S.E.M. Fig. 2B-E, 3A, 3E, 4A-D, S1A-D, S2, S4A, and
S6F were analyzed using a two-tailed Students’ t-test. In Fig. 2A, 3B-D, S3A-B, S4B,
S5A-C, and S6A overall results were analyzed using a two-way repeated-measure
ANOVA with a Tukey-HSD post hoc correction for multiple comparisons, followed by
a two-tailed Students’ t-test analysis for each time point if the ANOVA showed mean
differences. All data were analyzed using a commercially available statistical program
(SPSS for Windows, version 15.0). The null hypothesis was rejected at the 0.05 level.
Results
Generation of the Pmch KO rat
In a large ENU-driven target-selected mutagenesis screen we identified a rat carrying a
heterozygous mutation in Pmch 562. The mutation (K50X) resulted in a premature stop
codon in exon 1 (Fig. 1A). Northern blot analysis showed that Pmch mRNA is almost
completely absent in pmch-/- animals, most likely as a result of nonsense-mediated
decay (Fig. 1B). Furthermore, there is a gene dose-dependent reduction in Pmch expression in pmch+/- rats. The KO phenotype was confirmed by immunohistochemistry,
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which showed that all three neuropeptides derived from Pmch, N-GE, N-EI, and
MCH, are absent in sections of the lateral hypothalamus of pmch-/- animals (Fig. 1C).
Pmch KO rats are lean and hypophagic
The body weight of pmch-/- animals and wild type siblings was monitored on three
different diets (M, SHP, and HF) for 18 weeks starting at postnatal week 3. Pmch-/animals showed a reduced body weight and a lean phenotype compared to wild type
siblings on all three different diets. A difference in body weight between genotypes
was1not present at birth, or between birth and the 3rd postnatal week (data not shown),
Fig.
and only became visible approximately 3 weeks after birth. When the monitoring was
Figure 1 Confirmation of the Pmch KO rat. A, Sequencing revealed an induced premature
stop codon in the first exon (K50X) in the MCH precursor gene (indicated in schematic
overview). The light grey bar indicates the probe used for the Northern Blot analysis. B,
Northern Blot analysis of whole brain tissue demonstrated that the premature stopcodon
results in almost complete loss of Pmch mRNA in animals homozygous for the mutation, and
showed a gene dose-dependent reduction in Pmch expression in heterozygous animals (53%
expression compared to WT). C, Immunohistochemistry (250x enlargement) revealed that
all three neuropeptides derived from the Pmch precursor, N-GE, N-EI, and MCH, are absent
in hypothalamic sections derived from pmch-/- animals. Abbreviations: 3V, third ventricle; ic,
internal capsule; f, fornix; IHy, incerto hypothalamic area; LHA, lateral hypothalamic area.
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stopped after 18 weeks, relative body weight of the pmch-/- animals was 78% (M), 79%
(SHP), and 82% (HF) compared to wild type siblings (Fig. 2A). Interestingly, not only
wild type animals on HF diet showed a strong increase in body weight compared to
wild type animals on M or SHP diet (109% and 112% increase, respectively), also
pmch-/- animals on HF diet showed a strong increase in body weight compared to
pmch-/- animals on M or SHP diet (114% and 117%, respectively), thus indicating that
pmch-/- animals are capable of increasing their body weight when presented with a HF
diet (Fig. 2A). Caloric intake (24-hr) was recorded at 8 and 17 weeks of age showing
that pmch-/- animals are significantly hypophagic at both ages on all three diets (Fig.
2B). The reduction in caloric intake occurred both during the light and dark phase (see
Supplementary Data, Fig. S1A). Water intake was also monitored showing that pmch-/animals drink significantly less water at 8 weeks on all diets (Fig. 2D, S1C). However,
at 17 weeks of age, water intake was unchanged (M diet), decreased (SHP diet), or
increased (HF diet) in pmch-/- animals (Fig. 2D, S1C). Furthermore, pmch-/- animals
showed a small but significant decrease in naso-anal body length at 6 and 13 weeks
(M, SHP diet) and 12 weeks (HF diet) of age (Fig. S2), suggesting a slightly impaired
growth that could be a secondary effect of the decreased caloric intake.
Body analysis and endocrine profile of Pmch KO rats
Body composition analysis of 26-week old pmch-/- animals (M, SHP, and HF diet)
revealed significantly decreased WAT fat pad weights and liver weights (Fig. 3A). However, no difference was found when liver weights were normalized for body weight,
indicating that liver weights are proportional to the body weight (Fig. 3A). Six-time
point analysis in 24-week old pmch-/- animals revealed strongly decreased plasma leptin concentrations on all three diets (Fig. 3B). Pmch-/- animals on M diet did not have
altered plasma glucose concentrations, whereas pmch-/- animals on SHP diet showed
slightly elevated but not significantly changed plasma glucose concentrations, and
pmch-/- animals on a HF diet showed significantly elevated plasma glucose concentrations (Fig. 3C). Plasma insulin concentrations were significantly decreased in pmch/animals on M or SHP diet, whereas no differences in insulin concentrations were
found between pmch+/+ and pmch-/- animals on HF diet (Fig. 3D). Interestingly, plasma
insulin concentrations in pmch-/- animals were strongly decreased on all three diets
during the end of the dark phase (04:00; Fig. 3D). A hyperinsulinemic-euglycemic
clamp study revealed no significant difference between body weight-matched pmch+/+
and pmch-/- animals in basal plasma glucose levels (pmch+/+: 5.73 ± 0.09 mmol/L;
pmch-/-: 5.50 ± 0.12 mmol/L; P = 0.14 by two-tailed Students’ t-test, n = 6 per group)
and basal insulin levels (pmch+/+: 1.23 ± 0.15 ng/ml; pmch-/-: 1.00 ± 0.18 ng/ml; P =
0.36 by two-tailed Students’ t-test, n = 6 per group) during an equilibrium state in the
early afternoon. However, pmch-/- animals did show a significant lower basal endog129
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enous glucose production (EGP) compared to pmch+/+ animals, reflecting a decreased
metabolic clearance rate (MCR) (Fig. 3E). When basal insulin was clamped at approximately two fold of the normal level (pmch+/+: 2.16 ± 0.08 ng/ml; pmch-/-: 2.24 ±
0.09 ng/ml; P = 0.25 by two-tailed Students’ t-test, n = 6 per group), both pmch-/- and
Fig. 2 +/+
pmch animals showed a similar EGP (Fig. 3E) and similar rate of glucose disappear-
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ance (Rd) (pmch+/+: 94.21 ± 5.43 μmol/kg.min; pmch-/-: 99.01 ± 5.74 μmol/kg.min; P
= 0.56 by two-tailed Students’ t-test, n = 6 per group). Additionally, insulin suppression on the EGP also showed no difference (pmch+/+: -63.07 ± 3.67%; pmch-/-: -62.13
± 2.86%; P = 0.84 by two-tailed Students’ t-test, n = 6 per group). This indicates that
pmch-/- animals have a functional and dynamic insulin system for maintaining the basal glucose production and utilization. In line with this, intravenous insulin-tolerance
tests (IVITT) revealed no difference between genotypes in whole-body insulin sensitivity (Fig. S3A). Interestingly, intravenous glucose-tolerance tests (IVGTT) showed
a trend towards a slightly delayed glucose removal in response to a glucose bolus in
pmch-/- animals on SHP or HF diet (Fig. S3A). The Hypothalamic-Pituitary-Adrenal
(HPA) axis activity was also investigated in the 26-week old pmch-/- animals, and the
thymus weight of pmch-/- animals on SHP diet was found to be decreased (pmch+/+:
0.351 ± 0.018 g, pmch-/-: 0.263 ± 0.014 g; P < 0.05 by two-tailed Student’s t-test; n =
3-4 per group) but did not differ on the other two diets (data not shown). Weight of
the adrenals did not differ on any diet (data not shown). Plasma corticosterone levels
at 08:00 and 20:00 also showed no differences between pmch+/+ and pmch-/- animals
on M diet (data not shown).
← Figure 2 Pmch KO rats show a decreased body weight and decreased 24-hr caloric intake
on three different diets. A, Male pmch-/- animals showed a decreased body weight over time
compared to pmch+/+ control animals on M diet (squares; P < 0.001), SHP diet (triangles; P <
0.001), and HF diet (circles; P < 0.001). HF diet increased body weight over time compared
to animals on M or SHP diet, both in pmch+/+ and pmch-/- animals (WT HF vs. WT M: P
< 0.001; HOM HF vs. HOM M: P < 0.001; WT HF vs. WT SHP: P < 0.001; HOM HF vs.
HOM SHP: P < 0.001). Animals on M or SHP diet showed no difference over time in body
weight within genotype (WT M vs. WT SHP: P = 0.23; HOM M vs. HOM SHP: P = 0.29).
All overall longitudinal body weight data were analyzed using a repeated-measure ANOVA.
Pmch-/- animals started showing a reduced body weight per individual measurement after
22 days of age (SHP and HF diet; P < 0.05 by two-tailed Students’ t-test) or 26 days of age
(M diet; P < 0.05 by two-tailed Students’ t-test). B, Pmch-/- animals ingested fewer calories
compared to control animals (M: -26% and -21%, 8 and 17 weeks of age, respectively; SHP:
-24% and -17%, 8 and 17 weeks of age, respectively; HF: -22% and -15%, 8 and 17 weeks of
age, respectively). C, The hypophagic character of pmch-/- animals fades at a younger age, and
completely disappears at an older age when data are normalized for body weight (M: -6% and
+0%, 8 and 17 weeks of age, respectively; SHP: -3% and +5%, 8 and 17 weeks of age, respectively; HF: -2% and +2%, 8 and 17 weeks of age, respectively). D, Pmch-/- animals consumed
less water than control animals, except for 17-week old rats on HF diet (M: -24% and -7%, 8
and 17 weeks of age, respectively; SHP: -19% and -6%, 8 and 17 weeks of age, respectively;
HF: -13% and +10%, 8 and 17 weeks of age, respectively). E, Pmch-/- animals drink equal or
increased amounts of water compared to control animals when data are normalized for body
weight (M: -3% and +18%, 8 and 17 weeks of age, respectively; SHP: +2% and +19%, 8 and
17 weeks of age, respectively; HF: +8% and +31%, 8 and 17 weeks of age, respectively). *P <
0.05 by two-tailed Student’s t-test. Data are expressed as mean ± S.E.M. (n = 10-16 per group).
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Fig. 3
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Basal locomotor activity and body core temperature
Basal locomotor activity measured during 72 hours in 10-week old (M, SHP, HF)
or 19-week old (HF) animals using a home-cage monitoring system did not differ
between pmch+/+ and pmch-/- animals (Fig. S4A). Body core temperature measured
using telemetry did not reveal a significant difference between adult pmch+/+ and pmch/animals on SHP diet (Fig. S4B).
Pmch KO rats show relative hypophagia during early development and relative
hyperphagia during adulthood
The hypophagic characteristic of the pmch-/- rats is obvious when comparing caloric
intake data (Fig. 2B, S1A). However, if caloric intake data are normalized per body
weight, this clear pattern disappears and although the differences are very small,
­pmch-/- animals seem slightly hypophagic at 8 weeks of age, and somewhat hyperphagic
at 17 weeks of age (Fig. 2C, S1B). As the 24-hr monitoring only showed caloric intake
behavior during two short time windows, we decided to longitudinally monitor caloric
intake of male pmch-/- animals and wild type siblings on M and SHP diet, starting at
weaning at 3 weeks of age and ending during adulthood at 18 weeks of age.
In line with our initial data, caloric intake corrected for body weight data of ­pmch-/animals on M diet showed a decreased caloric intake compared to control animals
← Figure 3 Pmch KO rats show a changed endocrine profile on three different diets although
dynamics are intact. A, Pmch-/- animals showed decreased body-, total WAT fat pad-, and
liver weights compared to pmch+/+ animals on three different diets (M, SHP, and HF) (n =
3-6 per group). Relative body weight is 78% (M), 80% (SHP), and 77% (HF). Relative total
WAT fat pad weight is 48% (M), 51% (SHP), and 54% (HF). Relative liver weight is 71% (M),
75% (SHP), and 74% (HF). However, if liver weights were normalized for body weight, no
difference was found between genotypes. B, Pmch-/- animals showed decreased plasma leptin
levels during 24 hrs on M, SHP, and HF diet (§, P < 0.05 by repeated-measure ANOVA; *P <
0.05 by two-tailed Students’ t-test; n = 8-12 per group). C, Pmch-/- animals showed unchanged
plasma glucose levels on M diet (P = 0.98 by repeated-measure ANOVA), an elevated trend
on SHP diet (P = 0.06 by repeated-measure ANOVA), and elevated glucose levels on HF
diet (§, P < 0.05 by repeated-measure ANOVA; *P < 0.05 by two-tailed Students’ t-test) (n =
9-13 per group). D, Pmch-/- animals showed decreased plasma insulin levels on M and SHP
diet (§, P < 0.05 by repeated-measure ANOVA; *P < 0.05 by two-tailed Students’ t-test), but
unchanged insulin levels on HF diet (P = 0.24 by repeated-measure ANOVA) (n = 8-12 per
group). E, Pmch-/- animals body weight-matched to pmch+/+ animals showed a decreased
basal endogenous glucose production (EGP) and a decreased basal metabolic clearing rate
(MCR) compared to pmch+/+ animals during a hyperinsulinemic-euglycemic clamp analysis
(n = 6 per group). EGP levels under hyperinsulinemic conditions did not differ significantly
between genotypes (P = 0.33 by two-tailed Students’ t-test; n = 6 per group). *P < 0.05 by
two-tailed Students’ t-test. Data are expressed as mean ± S.E.M. The black bars on the x-axes
in panels’ B, C, and D indicate the dark phase.
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7
Fig.
Fig.
44
Figure 4 Pmch KO animals show a switch
in caloric intake and a stabilization in relative body weight during development. A,
Pmch-/- animals showed a switch in relative
caloric intake normalized for body weight
compared to pmch+/+ animals on M diet (n
= 10-12 per group). Average relative caloric
intake from day 40 till day 57 is 94%. However, average relative intake from day 61 till day
145 is 103%. B, Pmch-/- animals showed a switch in relative water intake normalized for body
weight compared to pmch+/+ animals on M diet (n = 10-12 per group). Average relative water
intake from day 33 till day 57 is 95%. However, average relative intake from day 61 till day
145 is 118%. C, Pmch-/- animals showed a switch in relative caloric intake normalized for body
weight compared to pmch+/+ animals on SHP diet (n = 10-11 per group). Average relative
caloric intake from day 40 till day 57 was 96%. However, average relative intake from day 61
till day 145 was 104%. D, Pmch-/- animals showed a switch in relative water intake normalized for body weight compared to pmch+/+ animals on SHP diet. Average relative water intake
from day 33 till day 57 was 98%. However, average relative intake from day 61 till day 145
was 113%. E, Pmch-/- animals showed a stabilization of relative body weight difference during
week 8 (day 50-56) on all three diets (M, SHP, and HF) compared to pmch+/+ animals (n = 1016 per group). *P < 0.05 by two-tailed Students’ t-test. Data are expressed as mean ± S.E.M.
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before week 8, but an increased caloric intake compared to control animals after week
8 (Fig. 4A). A same ‘biphasic’ pattern was observed for relative water intake (Fig. 4B).
These changes result in increased relative nutrient intake behavior in pmch-/- animals
compared to wild type siblings during adulthood. The same ‘biphasic’ patterns were
also observed for animals on SHP diet (Fig. 4C, 4D). Remarkably, the observed switch
in nutrient intake occurred around the moment the young male rats enter sexual adulthood (approximately between day 55 and day 65). Although caloric intake measurements obtained from animals on HF diet started at day 45 and were not collected on
regular intervals as the obtained data from the other two diets, a ‘switching’ pattern
resembling the pattern observed with animals on M and SHP diet was also observed
with the animals on HF diet (data not shown). However, water intake normalized
for body weight at day 45 of male pmch-/- animals on HF diet was already strongly
increased compared to wild type siblings, increasing further till week 8, stabilizing
during week 8 and remaining strongly elevated after week 8 (data not shown).
Pmch KO rats have an altered energy balance set point
The relative body weight of pmch-/- animals on all diets decreases with approximately
20% during the first 7 weeks compared to wild type siblings, but this difference stabilized quite abruptly during week 8 (Fig. 4C). After this abrupt stabilization the relative
body weight difference stayed stable during the remainder of the study and the average remained approximately 79%, 79%, and 83% (M, SHP, and HF respectively; Fig.
4C). Surprisingly, the observed stabilization occurred exactly during the same week
of age, postnatal week 8 (days 50-56), with all three diets. These results indicate that
the energy balance is set differently in pmch-/- animals when entering adulthood and is
maintained at a lower level during adulthood. Interestingly, the observed deviation in
body weight between pmch+/+ and pmch-/- animals during the first 8 weeks is mirrored
by the weekly body weight growth rate, which is strongly decreased in pmch-/- animals
during the first 8 weeks compared to pmch+/+ animals on all three diets, but approaches
the level of pmch+/+ animals during adulthood (Fig. S5A, B, C). This indicates that
the body weight growth rate is decreased in pmch-/- animals during the first 8 weeks,
again suggesting that Pmch has a critical role during this period, and that loss of Pmch
during this period lowers body weight growth.
Testosterone does not induce the observed stabilization of relative body weight
As the observed stabilization of relative body weight and ‘switch’ in nutrient intake
behavior were observed around the end of rat puberty, we tested the hypothesis that
changes in blood testosterone levels induced our observed phenotype. Orchiectomy
during postnatal week 5 reduced the body weight of pmch+/+ and pmch-/- animals compared to sham-operated pmch+/+ and pmch-/- animals (Fig. S6A). Both orchiectomized
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pmch+/+ and pmch-/- animals show a decrease in relative body weight compared to
sham-operated animals, although no clear stabilization pattern is observed around
week 8 (Fig. S6B, S6C). Sham-operated pmch-/- animals showed a clear stabilization
of relative body weight compared to sham-operated pmch+/+ animals around week 8,
confirming observations from untreated animals (Fig. 4C, S6D). Interestingly, orchiectomized pmch-/- animals also showed a stabilization of relative body weight compared
to orchiectomized pmch+/+ animals around week 8 (Fig. S6E). Serum free testosterone
levels showed no difference between pmch+/+ and pmch-/- animals on SHP diet around
day 40, while orchiectomy resulted in almost undetectable levels in both genotypes
(Fig. S6F).
Discussion
Here, we show that loss of Pmch in the rat causes relative hypophagia during early rat
development and puberty, resulting in a 20% decreased energy balance that is maintained during adulthood. While the role of MCH in food intake regulation is well established, it should be noted that the entire Pmch gene is inactivated in our model and
that also the less well-characterized neuropeptides N-GE and N-EI are not expressed
in these animals. Although N-GE so far does not seem to have a biological function,
N-EI is implicated in modulatory action on anxiety- and sexual-related behavior in
female rats 567, increases luteinizing hormone (LH) release 568, and stimulates grooming, locomotion, and rearing in male rats 569. These additional neuropeptides could
perform as of yet unknown functions, thereby contributing to phenotypes observed
in this study.
In this study, we show that pmch-/- animals have a changed endocrine profile while its
dynamics are intact. As pmch-/- rats are lean and hypophagic with strongly decreased
adipose tissue, the decreased plasma leptin and insulin levels are as expected. Pissios
and colleagues recently showed that MCH is a positive regulator of insulin release 570,
thus loss of Pmch expression could explain the decreased basal plasma insulin levels
and the delayed glucose clearance in the IVGTT studies. It is also interesting to note
that basal insulin levels seem to be lowered especially at the end of the dark phase. This
could be the effect of a combination of decreased caloric intake and a loss of MCHstimulated insulin release. The hyperinsulinemic-euglycemic clamp showed decreased
basal EGP levels in the pmch-/- animals compared to pmch+/+ animals (78% in pmch/as compared to pmch+/+ animals). Interestingly, under hyperinsulinemic conditions
EGP levels did not differ significantly anymore between both genotypes, although
mean levels were still lower in pmch-/- animals (84% compared to pmch+/+ animals
under hyperinsulinemic conditions). However, as the inhibition of EGP levels by the
hyperinsulinemic conditions was equal between genotypes, these data do not support
the idea that pmch-/- animals are slightly insulin resistant. Moreover, IVITT studies
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also showed no difference between genotypes. Because the observed decreased basal
EGP level (22%) is not body weight related, as animals were body weight-matched, it
is therefore tempting to speculate that the basal EGP levels in pmch-/- animals reflect
the energy balance level, which is also decreased by approximately 20%. As plasma
leptin, insulin, and glucose levels showed normal circadian patterns in general and
insulin sensitivity seemed to be unchanged between genotypes, this suggests that
the system dynamics in pmch-/- animals are intact and functional, although adapted
to new homeostatic levels. Additionally, thymus weight, adrenal weight, and plasma
corticosterone levels showed no clear differences between pmch+/+ and pmch-/- animals,
suggesting that the HPA axis is not severely affected in male Pmch-deficient rats.
In mice it was observed that the loss of Pmch (on a mixed genetic background)
resulted in hypophagia 548; however this was characterized in adult mice only. More
detailed analysis of feeding behavior in Pmch-deficient rats revealed a more complex phenotype. When caloric intake is normalized for body weight, only a slight
hypophagia is detectable at a young-adult age (8 weeks), while at an adult age (17
weeks), the hypophagia disappeared completely (M and HF diet) or even inverted to
hyperphagia (SHP diet). This would indicate that at these ages, pmch-/- animals consumed approximately an equal amount of calories per kg body weight as wild type
animals. While longitudinal food intake experiments confirmed these findings, they
also revealed a clear relative hypophagia in Pmch KO rats, but only until approximately
60 days of age, a time-period including puberty. After leaving puberty, around day 60,
pmch-/- animals started consuming slightly elevated amounts of chow per body weight,
indicating that they are actually slightly hyperphagic. The observed switch occurred in
the same week for all three diets, suggesting that the effect is a genetic effect, and is not
affected by diet. As the relative body weight of wild type and Pmch KO rats only diverts
during the first 8 postnatal weeks and the difference in relative body weight remains
stable during the remainder of the study, the observed slight hyperphagia might be
indicative of a possible increase in metabolic rate, similar as has been shown for 20week old mice with a loss of Pmch and 17-week old transgenic mice with a severe loss
of MCH neurons 548, 571. As basal locomotor activity was unchanged in pmch-/- animals,
the relative reduced caloric intake of the pmch-/- animals during the first 8 weeks and
an increased metabolic rate rather than increased basal locomotor activity seem to be
the main contributors to the lean phenotype in Pmch KO rats.
The current findings have an interesting correlate in the effects of lesions of the
lateral hypothalamus, which also show a reduced body weight 572. However, their phenotype is much more extreme than that of the pmch-/- rat, probably because it involves
the loss of a more extended population of orexigenic neurons (i.e. also those containing orexin). Animals with a dorsomedial hypothalamic nucleus (DMH) lesion also
regulate and actively defend their body weight at a reduced level as well. In addition,
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they show a reduced linear growth, have a normal body composition, hormone levels,
metabolism and respond normally to numerous body weight challenges 573. Because
part of the Pmch neuron population is found close to the DMH, loss of these neurons
during a DMH lesion is a strong candidate for causing the similarities between both
phenotypes.
The switch at the end of puberty is very interesting, as both MCH and N-EI are
known to stimulate LH release in rats 568, 574 and a functional interaction between
Pmch and gonadal steroids, such as testosterone, thus seems plausible. However, free
testosterone levels measured in pmch+/+ and pmch-/- animals around day 40 did not
differ. Additionally, orchiectomy during postnatal week 5 did lower the body weight
of orchiectomized animals compared to sham-operated animals within genotypes,
but did not affect the observed stabilization in relative body weight between pmch+/+
and pmch-/- animals around week 8. This suggests that testosterone is not essential to
induce the observed stabilization of body weight. Although only males were used in
the present study, it is important to note that female pmch-/- rats also show a stabilization of relative body weight around week 8 compared to female pmch+/+ rats (data not
shown).
Hypothalamic rat Pmch mRNA expression increases slowly during early development, increasing more rapidly after weaning, and stabilizes in 8-week-old young adult
rats 575. Pmch is also expressed in Sertoli cells in rat testis, increasing strongly between
15-day old rats and adult animals 538. Both expression gradients could potentially affect
gonadal steroid expression directly or indirectly, although regulation of Pmch expression levels by sex steroids is possible as well.
Our observations are in line with a role of Pmch in increasing energy reserve levels,
a process that is important during times of rapid growth like early development and
puberty. Interestingly, relative Pmch expression in food-restricted as compared to
control rats changes during early development 576, suggesting the presence of a metabolic feedback mechanism during this time period. Moreover, nest-size induced food
restriction of pups until day 25 decreases relative body weight, and this difference in
relative body weight diminishes again when animals are given ad libitum access to
chow after day 25 577. Interestingly, the catch-up growth is incomplete as relative body
weight stabilizes around week 9, reflected by an increased growth velocity in restricted
rats until week 8 and no difference in growth velocity after week 8 577. It is however
important to note that the body weight of pmch-/- rats starts to differentiate during
postnatal week 3.
The body weight of adult humans is normally relatively stable, with only a very small
variance over a long period of time 578, 579. Classic studies in rodents have shown that
stable body weights are actively maintained when animals receive caloric restriction
or when the rat’s body weight is experimentally elevated; animals quickly restored
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their body weight to the level appropriate for their age and gender when returned to
standard conditions 580. In humans, dieting strategies combining energy restriction and
physical activity have shown moderate success for the reduction of body weight 581, 582.
However, many individuals who have lost weight using a dieting strategy will regain a
large proportion or all of the weight lost within 5 years from the end of the treatment
583-585
, although low-fat intake in combination with high activity can successfully slow
the regain of weight 586, 587. Even though ‘short-term’ (≤ 4 weeks) MCH1R-antagonism
studies are successful in decreasing body weight in adult rats and mice 557-560, it would
be very interesting to see if ‘long-term’ (> 4 weeks) MCH1R antagonism can chronically alter the energy balance of adult animals successfully. Because our data indicate
that loss of Pmch can lower the energy balance, and that Pmch expression is important
during early development and puberty, it would be even more interesting to study the
effect of MCH1R-antagonism on the determination of the energy balance in young
animals.
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Supplemental
Fig.data
1
Supplemental
Supplemental Figure 1 Pmch KO rats show a decreased nutrient intake during light and
dark phase on three different diets. A, Caloric intake is decreased in pmch-/- animals on
three diets (M, SHP, and HF) during both light (L) and dark phase (D) at age week 8 and
age week 17. B, The hypophagic character of pmch-/- animals is lost if data is normalized for
body weight, except for dark phase caloric intake on M or SHP diet at age week 8. C, Pmch/animals drink less water on all three diets during both light and dark phases at age week 8.
However, this pattern is lost at age week 17. Only the water intake during the dark phase on
SHP diet remains decreased, while the other differences disappear. Surprisingly, animals on
a HF diet at age week 17 drink more water during the dark phase then pmch+/+ siblings. D,
Pmch-/- animals drink equal or increased water quantities of water at age week 8 when water
intake is normalized for body weight, with the exception of water intake during the dark
phase on M diet. At age week 17, pmch-/- animals on all three diets drink more water during
light and dark phase. *P < 0.05 by two-tailed Students’ t-test. Data are expressed as mean ±
S.E.M. (n = 10-16 per group).
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Supplemental Fig. 2
chapter 7
Supplemental Figure 2 Pmch KO rats have a decreased body length. Pmch-/- animals showed
a decreased body length compared to pmch+/+ animals on three different diets (M, SHP, and
HF) at a different age (M, SHP: 6 and 13 weeks; HF: 12 weeks). Relative body length was
94.2% (M) and 94.9% (SHP) at 6 weeks of age, and 93.8% (M), 94.2% (SHP), and 95.4% (HF)
at 12/13 weeks of age. *P < 0.05 by two-tailed Students’ t-test. Data are expressed as mean ±
S.E.M. (n = 10-16 per group).
Supplemental Figure 3 Pmch KO rats show no change in whole-body insulin sensitivity. A,
No difference in whole-body insulin sensitivity is observed between adult pmch+/+ and ­pmch-/animals on three different diets (M, SHP, and HF) during an IVITT (n = 5-9 per group). B,
Pmch-/- animals on SHP or HF diet showed a trend towards slower glucose removal during
an IVGTT (n = 3-5 per group). Data are expressed as mean ± S.E.M.
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chapter 7Fig.
Supplemental
Fig.
Supplemental
44
Supplemental Figure 4 Pmch KO rats show no
change in locomotor activity and body core temperature.
A, Locomotor activity of pmch-/- animals on three
different diets at a different age (M and SHP: 11
weeks; HF: 10 and 19 weeks) during 72 hours
was unchanged compared to pmch+/+ animals (n
= 7-8 per group). B, No statistical difference was
found in body core temperature measured during
24 hours between adult pmch-/animals and pmch+/+ animals on
SupplementalSHP
Fig.diet
5 (P = 0.60 by repeatedmeasure ANOVA; n = 7-10 per
group). Measurement is average
of 6 days. Data are expressed as
mean ± S.E.M. The black bar in
panel B indicates dark phase.
Supplemental Fig. 5
Supplemental Figure 5 Pmch KO rats
show a decreased growth rate during early
development and puberty. A, The weekly
body weight growth is strongly decreased
in pmch-/- animals on M diet during the
first 8 weeks. After week 8, this difference
in weekly body weight growth between
genotypes fades. The same effect is observed for pmch-/- animals on SHP diet (B)
or HF diet (C). Data are expressed as mean
± S.E.M. (n = 10-16 per group).
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Supplemental Fig. 6
chapter 7
Supplemental Figure 6 Testosterone is not critical to induce relative body weight stabilization around week 8. A: Orchiectomy during postnatal week 5 (indicated by the arrowhead)
decreased the body weight of pmch+/+ animals compared to sham-operated pmch+/+ animals (P < 0.005 by repeated-measure ANOVA; n = 8-10 per group). Orchiectomy also lowered the body weight of pmch-/- animals (P < 0.05 by repeated-measure ANOVA; n = 9-14
per group) compared to sham-operated pmch-/- animals. Orchiectomized animals started
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showing a reduced body weight per individual measurement after 49 days of age (pmch+/+;
P < 0.05 by two-tailed Students’ t-test) or 60 days of age (pmch-/-; P < 0.05 by two-tailed Students’ t-test). At 16 weeks of age, the body weight of orchiectomized pmch+/+ animals is 81%
compared to the body weight of sham-operated pmch+/+ animals. During the same week,
the body weight of orchiectomized pmch-/- animals is 87% compared to the body weight of
sham-operated pmch-/- animals. All overall longitudinal body weight studies were analyzed
by repeated-measure ANOVA. B: The relative body weight of orchiectomized pmch+/+ animals showed no clear stabilization around week 8 compared to sham-operated pmch+/+
animals (n = 8-10 per group). C: The relative body weight of orchiectomized pmch-/- animals
showed no clear stabilization around week 8 compared to sham-operated pmch-/- animals (n
= 9-14 per group). D: The relative body weight of sham-operated pmch-/- animals showed
a stabilization of relative body weight around week 8 compared to sham-operated pmch+/+
animals (n = 8-9 per group). E: The relative body weight of orchiectomized pmch-/- animals
showed a stabilization of relative body weight around week 8 compared orchiectomized
pmch+/+ animals (n = 10-14 per group). F: Serum free testosterone levels did not differ
between pmch+/+ and pmch-/- animals on day 40 (n = 14 per group) or day 60 (n = 8-10
per group), but were decreased on day 120 (P < 0.05 by two-tailed Students’ t-test n = 8 per
group). Serum free testosterone levels were undetectable in orchiectomized pmch+/+ and
pmch-/- animals on day 120 (n = 10-14 per group). Data are expressed as mean ± S.E.M.
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Chapter 8
Pituitary adenylate cyclase-activating polypeptide stimulates glucose production through glycogenolysis and via the hepatic sympathetic innervation
in rats
Diabetes (under revision)
Chun-Xia Yi, Ning Sun, Mariëtte T Ackermans, Anneke Alkemade, Ewout Foppen, Jing Shi,
Mireille J Serlie, Ruud M Buijs, Eric Fliers & Andries Kalsbeek
Abstract
Objective The unraveling of the elaborate brain networks that control glucose metabolism presents one of the current challenges in diabetes research. Within the central
nervous system the hypothalamus is regarded as the key brain area to regulate energy
homeostasis. The present study aimed to investigate the hypothalamic mechanism
involved in the hyperglycemic effects of the neuropeptide Pituitary Adenylyl CyclaseActivating Polypeptide (PACAP).
Research Design and Methods Endogenous glucose production (EGP) was determined
during intracerebroventricular (i.c.v.) infusions of PACAP-38, VIP or their receptor
agonists. The specificity of their receptors was examined by co-infusions of receptor
antagonists. The possible neuronal pathway involved was investigated 1) by retrograde
neuronal tracing from the thoracic spinal cord to hypothalamic pre-autonomic neurons together with Fos immunoreactivity, and by 2) specific hepatic sympathetic or
parasympathetic denervation to block the autonomic neuronal input to liver.
Results I.c.v infusion of PACAP-38 increased EGP to a similar extent as a VIP/PACAP-2 (VPAC2) receptor agonist, the increase being mainly caused by stimulation of
glycogenolysis. I.c.v. administration of VIP had significantly less influence on EGP. The
PACAP-38 induced increase of EGP was significantly suppressed by pre-infusion of a
VPAC2 but not a PAC1 receptor antagonist; as well as by hepatic sympathetic but not
parasympathetic denervation. In the hypothalamus, Fos immunoreactivity induced
by PACAP-38 was co-localized within autonomic neurons projecting to preganglionic
sympathetic neurons in the spinal cord.
Conclusions This study demonstrates that PACAP-38 signaling via sympathetic preautonomic neurons is an important component in the hypothalamic control of hepatic
glucose production.
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Introduction
In order to maintain glucose homeostasis, a complex glucose sensing and regulatory
system has developed within the central nervous system (CNS), involving hypothalamic and hindbrain areas 68, 70. Also a recent study in humans evidenced the exquisite
sensitivity of the hypothalamus to small changes in blood glucose levels 588. Despite
clear evidence from animal data for a role in glucose homeostasis of several hypothalamic nuclei such as the arcuate nucleus (ARC), ventromedial hypothalamus (VMH)
and paraventricular nucleus (PVN), the major part of the neurochemical make-up of
this hypothalamic network is still largely unknown.
Pituitary Adenylyl Cyclase-Activating Polypeptide (PACAP) 589 is a highly conserved
peptide from the secretin-glucagon superfamily, which exerts a plethora of peripheral
and central effects. PACAP has been found to have affect food intake and glucose and
lipid metabolism 590, 591. PACAP-immunoreactive neurons and their receptors (5), however, are distributed widely, not only in the CNS but also in peripheral tissues such as
adipose tissue and pancreas. Highest concentrations in the CNS are found in the hypothalamus 592, where PACAP-38 is produced abundantly in VMH neurons, whereas
high release rates are reported for the PVN 592-594. PACAP from retinal ganglion cells
is released primarily in the hypothalamic suprachiasmatic nuclei (SCN) 595. However,
since tissue specific knock-out animals are not yet available, it is not clear whether
the effects of PACAP on glucose metabolism are mediated via central or peripheral
pathways.
PACAP is structurally related to vasoactive intestinal peptide (VIP). PACAP and
VIP receptors have been classified as 3 different subtypes: PACAP-1 receptors (PAC1R)
596
, VIP/PACAP-1 (VPAC1R) and -2 receptors (VPAC2R) 597, 598. VIP and PACAP have
a comparable affinity for VPAC1 and VPAC2 599, while PACAP also has a high affinity
for the PACAP-specific PAC1 receptor 600. Both PAC1R and VPAC2R are broadly expressed in the brain, including the hypothalamus, while VPAC1R is mainly expressed
in the cerebral cortex and the hippocampus 601. The demonstration that central administration of PACAP-38 not only induces clear Fos immunoreactivity in several
brain areas, including the PVN 602, but also increases plasma glucose levels 603, suggests
that central PACAP-38 may indeed play an important role in (glucose) metabolism.
However, it is not clear which receptor attributes mostly to the metabolic effects of
PACAP in the central nervous system.
In order to determine the importance of central PACAP signaling in regulating
glucose metabolism, we combined central administration of PACAP-38, VIP and/or
their receptor specific agonists and antagonists, with quantification of plasma glucose
concentrations and endogenous glucose production (EGP). In order to delineate further the hypothalamic output pathway we combined the intracerebroventricular (i.c.v.)
administration of PACAP-38 with Fos immunohistochemistry and retrograde tracing
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from the intermediolateral column of the thoracic spinal cord, and we performed i.c.v.
infusions of PACAP-38 in rats that had undergone a specific hepatic sympathetic or
parasympathetic denervation.
Research design and methods
Animals
All experiments were conducted with the approval of the animal care committee of
the Royal Netherlands Academy of Arts and Sciences. Male Wistar rats weighing 300350 g (Harlan Nederland, Horst, The Netherlands) were housed four per cage at room
temperature with a 12/12-h light-dark schedule (lights on at 07.00 h). Food and water
were available ad libitum, unless stated otherwise.
Surgery preparation
Animals underwent surgery according to the different experimental designs under
anesthesia with 0.8 ml/kg Hypnorm (Janssen, High Wycombe, Buckinghamshire, UK),
i.m., and 0.4 ml/kg Dormicum (Roche, Almere, The Netherlands), s.c.
Silicon catheters were inserted into the right jugular vein and left carotid artery for
i.v. infusions and blood sampling, respectively. With a standard David Kopf stereotaxic
apparatus, i.c.v. guiding cannula were placed into the lateral cerebral ventricle, double
i.c.v. cannulations were applied for i.c.v. pre-infusion studies (see below). Coordinates
were adapted from the atlas of Paxinos and Watson 497 (Anteroposterior: -0.8mm,
Lateral: 2.0mm, Ventral: 3.2mm, Angle: 0). Correct placement of the i.c.v. probe was
validated by a colored dye injection at the end of the experiment. Fixation, anti-clotting
and connection of catheters and probes were applied as described before 604.
Hepatic sympathetic and parasympathetic denervation was performed as described
previously 48, sham surgery without denervation was used as surgery control.
For visualizing the PVN pre-autonomic neurons, a retrograde neuronal tracer, i.e.,
cholera toxin subunit B (CTB) was injected into the IML. The spines of the rats were
stabilized and exposed, with a small laminectomy revealing the spinal cord, after
which an injection of 0.05-0.1μl fluorophore-conjugated CTB (with Alexa Fluor 555,
CTB-AF555, Molecular Probed, Eugene, OR) was given with a micro-needle. The
injections were given unilaterally between T6 and T7 (where the highest density of
liver-projecting sympathetic motor neurons is found). After the injection the microneedle was left in place for 1-2 minutes to minimize leakage.
After surgery, all animals were allowed at least 10 days for recovery. Experiments
were performed only when they had regained at least their pre-surgery bodyweight.
To exclude intestinal glucose absorption during experiments, food was restricted
overnight at 20g. In addition, during the experimental day food was withheld from
lights-on onwards, and experimental blood sampling was started 5 hours later.
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Stable isotope tracer dilution, i.c.v infusions and blood sampling schedule
To study glucose kinetics stable isotope tracers were used. To compare the effects of the
different PACAP-38 and VIP (ant)agonists on total EGP, the isotope dilution method
was applied, using [6.6-2H2]glucose (as a primed (8.0 μmol in 5 min) - continuous (16.6
μmol/h) infusion (>99% enriched); Cambridge Isotopes, Andover, USA). To dissect the
separate contributions of gluconeogenesis (GNG) and glycogenolysis to total EGP, in an
additional vehicle and i.c.v. PACAP-38 infusion group, the MIDA method was applied
using U-13C6-glucose and 2-13C1–glycerol (U-13C6-glucose 3.53 mg/ml, 2-13C1-glycerol
22.8 mg/ml (bolus 2910μl/hr for 5 min, and continuous infusion 500μl/hr). Blood
samples were taken at t=-5 min for background tracer enrichment, and at t=90, t=95
and t=100min for determining basal plasma parameters and isotope enrichment after
having reached isotope equilibrium (data are presented by averaging these three time
points). Single i.c.v. infusions of different drugs (and vehicle) were started immediately
after t=100 min (infusion speed 5 μl/hr). From t=120 - 220 min 6 blood samples were
taken with 20 min interval for determining enrichment during the experimental state.
In experiments that needed co-infusion of receptor antagonists, a pre-infusion of
the receptor antagonist was started immediately after t=100min through the left i.c.v.
canula, 10 min later the PACAP-38 infusion was started via the right i.c.v. cannula.
To check Fos immunoreactivity after i.c.v. infusion and the labeling by the CTBAF555 tracer in the brain, single immunohistochemical staining or double-labeling
immunofluorescence staining were performed (supplemental data.1).
Analytical methods
Blood samples were chilled on ice in tubes containing 5 μl heparin and centrifuged
at 4°C. Plasma was then stored at -20°C for analysis. By using radioimmunoassay
kits, plasma insulin (t=100, 140, 180, 220 min), glucagon (t=90, 120, 160, 200 min)
[LINCO Research (St. Charles, MO, USA) and corticosterone concentrations (all time
points) (ICN Biomedicals, Costa Mesa, CA) were measured. Plasma isotope enrichments were measured using gas chromatography-mass spectrometry (GCMS) and
GNG was calculated by mass isotopomer distribution analysis (MIDA) 605, 606. Liver
noradrenalin was measured by HPLC with fluorescence detection after derivatisation
of the catecholamines with diphenylethylene diamine. Glycogen content was measured
by spectrophotometry 607 .
Statistics and calculation
Data from all experiments are presented as means±SEM. EGP was calculated from
isotope enrichment using adapted Steele equations 500. Glucose concentration and EGP
were analyzed using a repeated-measures analysis of variance (ANOVA), to test for the
effects of peptide infusions and time. Plasma corticosterone, glucagon and insulin, as
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well as liver noradrenalin and glycogen content were analyzed using one way ANOVA
to compare the average between each experimental group and the vehicle group.
Results
I.c.v. PACAP-38 induces hyperglycemia by stimulating endogenous glucose
production
To investigate the possible contribution of the hypothalamic PACAP/VIP systems
to peripheral glucose metabolism, in a first series of experiments we administered
PACAP-38 and VIP, as well as specific VPAC1-R agonist (K15, R16, L27VIP/GRF) 608 and
VPAC2-R agonist (Hexa-His’ VIP (2-27) 609, by i.c.v. infusion into the lateral cerebral
ventricle (5μl/hr). Upon i.c.v. infusion of PACAP-38 for 2-h (1nmol/hr, n=6), both
plasma glucose concentration and EGP were increased in comparison with basal state
at t=100min (~70% and ~100%, respectively). ANOVA detected a significant effect of
Time (difference between time points is expressed by Time effects Pt) (pt<0.001 for both
parameters). The PACAP-38 induced increase was also significant as compared to the
vehicle control group (n=6) (difference between groups is expressed by Group effects
Pg) (pg=0.001 and pg<0.001 for plasma glucose and EGP, respectively) (Figs. 1A and B).
I.c.v. infusion of VIP at the same concentration (1nmol/hr, n=4) did not significantly
change plasma glucose concentrations (pt =0.15), but did cause a significant increase
of EGP (pt=0.004). This increase was slightly higher than vehicle control (pg=0.049),
but significantly lower than PACAP-38 (pg=0.04). When a 5-fold higher concentration
of VIP (5nmol/hr, n=5) was administered, a clear hyperglycemia was induced (~50%,
pt<0.001), which was significantly higher than that in the 1nmol/hr group (pg=0.03)
and vehicle group (pg<0.001), and not significantly different from PACAP-38 (pg=0.22).
EGP also increased significantly (pt<0.001) in the 5nmol/hr group, it was significantly
higher than that of the vehicle control group (pg=0.02), but did not differ from 1nmol/
hr VIP (pg=0.93) and was still significantly lower than the PACAP-38 group (pg=0.03).
PACAP-38 induces hyperglycemia via VPAC2R
I.c.v. infusion of the VPAC1R-agonist (1nmol/hr, n=5) or the VPAC2R-agonist
(1nmol/hr, n=6) resulted in quite different effects on plasma glucose concentration
and EGP. I.c.v. infusion of the VPAC2R agonist caused a significant increase of plasma
glucose concentrations (~40%, pt<0.001), which was higher than the effect of vehicle (pg<0.001) or the VPAC1R agonist (pg=0.001); it also significantly increased EGP
(~65%, pt<0.001), an effect which was again significantly stronger than that of vehicle
(pg<0.001) and VPAC1R agonist (pg=0.02). Although the effects were shorter lasting and less pronounced than those of PACAP-38, no significant differences were
found between the VPAC2R agonist and PACAP-38 with regard to their effects on
either plasma glucose concentration (pg=0.08) or EGP (pg=0.48). I.c.v. infusion of the
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A
A
B
B
16
16
140
140
i.c.v. infusion
i.c.v. infusion
120
120
100
100
80
80
60
60
10
10
8
8
6
6
4
4
40
40
C
C
D
D
16
16 PACAP-38
PACAP-38
1nmol/hr
1nmol/hr
140
140
14
VPAC1R
VPAC1R
agonistagonist
1nmol/hr
1nmol/hr
VPAC2R
agonistagonist
1nmol/hr
1nmol/hr
14 VPAC2R
Vehicle
Vehicle
12
12
10
10
8
8
6
6
4
4
E
16
14
12
E
16 PACAP-38
PACAP-38
1nmol/hr
1nmol/hr
HSX + PACAP-38
HSX + PACAP-38
1nmol/hr
1nmol/hr
HPX + PACAP-38
HPX + PACAP-38
1nmol/hr
1nmol/hr
14 ShamXShamX
+ PACAP-38
+ PACAP-38
1nmol/hr
1nmol/hr
VehicleVehicle
120
120
100
100
80
80
60
60
40
40
F
F
140
140
120
120
100
100
80
80
60
60
40
40
100
12
10
10
8
8
6
6
4
4
100
150
EGP (umol/kg.min)
12
EGP (umol/kg.min)
12
Plasama glucose (mmol/L)
Plasama glucose (mmol/L)
14
PACAP-38
PACAP-38
1nmol/hr
1nmol/hr
VIP 1nmol/hr
VIP 1nmol/hr
VIP 5nmol/hr
14 VIP 5nmol/hr
VehicleVehicle
100 140
140180
180220
Time (min)
Time (min)
220
100 140
140180
180220
Time (min)
Time (min)
220
chapter 8
VPAC1R agonist also increased plasma glucose concentrations, especially during later
stages (pt=0.002) and differed significantly from vehicle (pg=0.02), but this increase was
significantly lower than that of PACAP-38 (pg=0.01), as well as of that of the VPAC2R
agonist (pg=0.001). On the other hand, the VPAC1R agonist did not significantly
change EGP (pt=0.10), its effect did not differ significantly from the vehicle group
(pg=0.52), and was significantly lower than that of the VPAC2R agonist (pg<0.001)
and PACAP-38 (pg=0.004) (Figs. 1C and D). VPAC1- and VPAC2-receptors are also
expressed in peripheral tissues, such as the pancreas and adipose tissue 610. In order
to exclude the possibility that glucoregulatory effects of PACAP/VIP resulted from
leakage of brain infusates into the systemic circulation, we also infused the VPAC1R
and VPAC2R agonists (with the same dose and time period as used for the i.c.v. administration, i.e. 5nmol/hr, in 200µl vehicle, 2hrs) directly into the systemic circulation. These control infusions did not result in any significant changes in either plasma
glucose concentrations or EGP (supplemental data.2, supplemental Figs. 1A and B).
Because no specific PAC1 agonist was available, we tested the possible involvement of
the PAC1 receptor in the glucoregulatory effects of PACAP-38 by i.c.v. pre-infusion of
the PAC1 specific antagonist PACAP 6-38 611 (5nmol/hr) and co-infusion (5nmol/hr)
together with PACAP-38 (1nmol/hr) (n=4). The co-infusion of PACAP 6-38 together
with PACAP-38 still significantly increased plasma glucose concentrations (pt<0.001)
and EGP (pt<0.001) (Figs. 2A and B).
To test further the role of the VPAC2 receptor, also the VPAC2R specific antagonist
myristoyl-K12-VIP(1-26)-KKGGT 612 was pre-infused (5nmol/hr) and co-infused
(5nmol/hr) together with PACAP-38 (1nmol/hr) (n=6). Plasma glucose levels did
not rise significantly (pt=0.15), EGP, however, still showed a significant increase over
time (pt=0.003). Compared with the single i.c.v infusion group, the co-infusion almost
completely blocked the increases of plasma glucose (pg=0.03) and EGP (pg<0.001)
← Figure 1 The effects of central administration of PACAP-38, VIP and/or their receptor
agonists and antagonists on plasma glucose concentration and EGP. A and B, I.c.v. infusion
of PACAP-38 increases both plasma glucose concentrations and EGP. Similar responses could
not be obtained with equimolar or 5 times higher concentrations of VIP. C and D, I.c.v. infusion of the VPAC2R agonist resulted in significantly higher plasma glucose levels and EGP
responses than the VPAC1R agonist, especially in the first half of the infusion period. The
almost similar responses induced by the VPAC2R agonist and PACAP-38 indicate that the
plasma glucose and EGP changes induced by PACAP-38 are predominantly mediated via
the VPAC2R. E and F, Selective denervation of the sympathetic, but not parasympathetic,
innervation to the liver largely blocks the hyperglycemic and EGP stimulatory effects of
PACAP-38. The starting time point for the i.c.v. infusion of the different drugs in all groups
is illustrated in B, i.e., immediately after t=100 min. The gray symbols and lines in figures
C-F are a repeat of the PACAP-38 and vehicle data in figures A and B. Data are presented
as mean±SEM.
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A
16
a b
i.c.v. infusion
120
EGP (umol/kg.min)
14
Plasma glucose (mmol/L)
B 140
PACAP-38 1nmol/hr
+VPAC2R antagonist 5nmol/hr
+PAC1R antagonist 5nmol/hr
+MC3/4-R antagonist 5nmol/hr
Vehicle
12
10
8
100
80
60
6
4
40
100
150
190
Time (min)
230
100
150
190
Time (min)
230
Figure 2 Co-infusion of PACAP-38 with the PAC1R or VPAC2R antagonist shows that
antagonizing VPAC2R, but not PAC1R, blocks a large part of the plasma glucose (A) and
EGP (B) responses evoked by PACAP-38, thus confirming that PACAP-38 mainly acts on
central VPAC2Rs to regulate plasma glucose concentrations and EGP. Co-infusion of PACAP-38 with the MC3R/MC4R antagonist Shu9119 still induces responses of plasma glucose
and EGP. Thus the melanocortin signaling pathway is not likely to be involved in central
PACAP-38 effects on glucose production. Antagonist infusions were started at time point
“a” through the left i.c.v. cannula and the PACAP-38 infusion was started 10 min later at
time point “b” through the right i.c.v. cannula. The gray symbols and lines are a repeat of the
PACAP-38 and vehicle data in Figures 1A and 1B.
evoked by PACAP-38. The plasma glucose level was still significantly higher than the
vehicle control group (pg=0.003), but EGP was not significantly different from the
vehicle control group (pg=0.09) (Figs. 2A and B).
The hyperglycemic action of PACAP-38 does not involve POMC neurons
It has been reported that the inhibitory effect of i.c.v. administered PACAP-38 on
food intake is mediated via an effect of PACAP-38 on the POMC containing neurons
in the ARC, and can be blocked by the co-administration of the MC3-R/MC4-R
specific antagonist SHU9119 603. In order to investigate whether the above-described
glucoregulatory effects of PACAP-38 were mediated via the ARC POMC neurons,
we pre-infused and co-infused the MC3-R/MC4-R antagonist SHU9119 (5nmol/hr)
with PACAP-38 (1nmol/hr). However, this co-infusion group still showed increases
over time of the plasma glucose level (pt<0.001) and EGP (pt <0.001) and did not
significantly change the hyperglycemic and EGP stimulatory effects of single i.c.v.
PACAP-38 (pg=0.52 and pg=0.53 respectively) (Fig. 2A and B).
I.c.v. administration of the PAC1 (n=4), the VPAC2 (n=5) or the MC3-R/MC4-R
specific antagonists (n=6) on their own did not significantly affect plasma glucose
concentrations or EGP (supplemental data.2, supplemental Figs. 1C and D).
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Glycogenolysis is the major contributor to the hyperglycemic action of PACAP-38
By using a dual-isotope tracer infusion method in combination with the i.c.v. administration of either vehicle (n=5) or PACAP-38 (n=6), we determined the metabolic
sources of the increase in plasma glucose. In this new group of animals, i.c.v. administration of PACAP-38 again significantly increased plasma glucose concentrations and
EGP (pt<0.001 and pt<0.002, respectively). These results were very much comparable
to the previous results with the [6.6-2H2]glucose method (compare Figs. 3A and C and
Figs. 1A and B). In the vehicle group, EGP slightly decreased during the study period
(pt=0.034). In both groups (i.e., vehicle and PACAP-38), the fractional contribution
from GNG to EGP slowly increased along the 2-hr experiment (from 19% to 28%
in vehicle, pt=0.002; and from 18% to 23% in the PACAP group, pt=0.008), without
significant differences between the two groups (Fig. 3B). The absolute rate of GNG,
however, increased significantly more in the PACAP-38 group than in the vehicle
group (pg=0.027). In the PACAP-38 group, glycogenolysis significantly increased by
61% (pt<0.001), whereas in the vehicle group glycogenolysis significantly decreased
by 27% (pt=0.005) (Fig. 3C). In line with the increased glycogenolysis, liver glycogen
stores were significantly lower in the PACAP-38 animals (Fig. 3D).
PACAP-38 induces Fos immunopositive nuclei in sympathetic pre-autonomic
PVN neurons
I.c.v. administration of PACAP-38, the VPAC2R specific agonist or VIP (only in
5nmol/hr group), but not the VPAC1R specific agonist or vehicle infusions, caused a
pronounced increase of hypothalamic Fos-ir. Fos-ir was found mainly in the PVN, Pe
and ARC, as well as in the nucleus incertus (NI) in the pons (Fig. 4, Fig. 5A). In the
PVN, the PACAP-38 and VPAC2R-agonist induced Fos-ir nuclei mainly located in its
rostro-medial part, with considerable fewer labelled nuclei extending into the lateral
magnocellular compartment of the PVN. Indeed double staining of Fos and AVP
showed that few of the VPAC2R agonist-induced Fos-ir neurons contained AVP-ir
(Fig. 5A). By contrast, VIP induced strong Fos-ir both in the rostro-medial and lateral
magnocellular compartment and co-localization with AVP (Fig. 5B).
In order to identify the pre-autonomic PVN neurons that project to the sympathetic
preganglionic neurons in the IML, rats were injected with CTB-AF555 in the IML.
Three animals showed clear CTB labeling in the CNS. The main labelling included
the corticospinal projection neurons, lateral hypothalamus, PVN, locus coeruleus,
parabrachial nucleus, and the nucleus ambiguous. In the PVN, CTB-labelled neurons
were concentrated in the dorsomedial subdivision. Several CTB-labelled neurons colocalized Fos-ir induced by PACAP-38. This co-localization was not observed in other
brain areas (Fig. 5C).
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50 50
BB
Plasma glucose (mmol/L)
Plasma glucose (mmol/L)
[U13C6]glucose
[U13C6]glucose
/ [2-13C1]glycerol
/ [2-13C1]glycerol
method
method
15 15
PACAP-38
PACAP-38
1nmol/hr
1nmol/hr
Vehicle
Vehicle
PACAP-38
PACAP-38
1nmol/hr
1nmol/hr
Vehicle
Vehicle
Fractional gluconeogenesis (%)
Fractional gluconeogenesis (%)
A 18
A 18
40 40
30 30
12 12
20 20
9 9
10 10
6 6
0 0
CC
150150
Absolute flux (umol/kg.min)
Absolute flux (umol/kg.min)
125125
140140
180180
Time
Time
(min)
(min)
100100
220220
PACAP-38
PACAP-38
EGP
EGP
Vehicle
Vehicle
EGP
EGP
PACAP-38
PACAP-38
glycogenolysis
glycogenolysis
Vehicle
Vehicle
glycogenolysis
glycogenolysis
PACAP-38
PACAP-38
GNG
GNG
Vehicle
Vehicle
GNG
GNG
100100
DD
0.40.4
140140
180180
Time
Time
(min)
(min)
220220
Vehicle
Vehicle
PACAP-38
PACAP-38
1nmol/hr
1nmol/hr
Liver glycogen (absorption /mg)
Liver glycogen (absorption /mg)
100100
0.30.3
0.20.2
75 75
50 50
0.10.1
25 25
# #
0.00.0
0 0
100100
140140
180180
Time
Time
(min)
(min)
220220
Figure 3 Fractional contributions of gluconeogenesis and glycogenolysis to the hyperglycemic action of i.c.v. PACAP-38. A, The changes in plasma glucose concentration in animals
with the dual-isotope tracer experiment are very much comparable to those of the singleisotope tracer experiments. B, The fractional GNG of the PACAP-38 group increases slightly,
but not significantly, slower than that in the vehicle group. C, The absolute flux of GNG and
glycogenolysis contribute very differently to the PACAP-38-induced changes in total EGP.
D, Liver glycogen content at the end of the experiment is significantly lower in PACAP-38
as compared to vehicle treated animals, indicating more pronounced glycogen depletion in
the PACAP-38 treated animals. Data are presented as mean±SEM. # P<0.05.
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PACAP-38 1nmol/hr
VIP 5nmol/hr
III
III
OT
A
VPAC1R agonist 1nmol/hr
Vehicle
III
C
III
OT
PACAP-38 1nmol/hr
OT
D
Vehicle
IV
E
OT
B
IV
F
Figure 4 I.c.v. infusion of PACAP-38, VIP or their receptor agonists result in different Fos-ir
patterns in different brain areas. A, PACAP-38 (1nmol/hr) induced Fos-ir in PVN and Pe. B,
C & D, A similar Fos-ir pattern can be seen after VIP (5nmol/hr) (B) and VPAC2R (1nmol/
hr) (Fig.5A), but not VIP (1nmol/hr) (not shown), VPAC1R (1nmol/hr) (C) or vehicle (D).
E & F, I.c.v. administration of PACAP-38 (E), VIP (5nmol/hr) and VPAC2R agonist, also
induced Fos-ir in the nucleus incertus (NI) located in the pons. No such Fos-ir was visible
in the NI with vehicle (F) or VPAC1R agonist infusion. OT: optic tract, III: third cerebral
ventricle, IV: fourth cerebral ventricle. Scale bar: A-D, 400 μm; E and F, 200 μm.
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VPAC2R agonist 1nmol/hr
III
A
AVP/FOS
VIP 5nmol/hr
III
B AVP/FOS
PACAP-38 1nmol/hr
CTP/FOS
III
C
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Hepatic sympathetic denervation blocks the hyperglycemic action of PACAP-38
Basal plasma glucose concentrations and EGP were not influenced by hepatic sympathetic denervation (HSX), parasympathetic denervation (HPX) or sham denervation
(shamX) (Figs. 1E and F). After HSX, the hyperglycemic and EGP stimulatory effect
of PACAP-38 were significantly reduced. Plasma glucose concentrations no longer
showed a significant increase (pt=0.53) and remained at the same level as that of vehicle-treated non-denervated animals (pg=0.58). In addition, the PACAP-38-induced
increases in plasma glucose in HSX animals were significantly lower than those in
shamX (pg=0.01) and HPX animals (pg=0.02). Although EGP still showed a significant
increase (pt<0.001) in the HSX group and was higher than that of vehicle-treated nondenervated animals (pg=0.02), it was also significantly lower than that of PACAP-38
treated non-denervated (pg=0.005), shamX (pg=0.036) and HPX (pg=0.036) animals.
In addition, no differences were found between HPX and shamX animals in plasma
glucose concentration (pg=0.71) and EGP (pg=0.55), nor between shamX or HPX and
the PACAP-38 treated non-denervated animals in Experiment 1 (pg=0.26 & pg=0.40
for plasma glucose and pg=0.55 & pg=0.96 for EGP, respectively). The effectiveness of
the HSX was validated by a significantly reduced noradrenalin (NA) content in the
liver of HSX (26.17±1.32ng/g) as compared to HPX (57.93±5.88ng/g) (p<0.001), as
well as shamX (58.00±4.30ng/g) (p<0.001). No difference in hepatic NA content was
found between HPX and shamX groups (p=0.99). In addition, NA in both HPX and
shamX was not different from intact rats without abdominal surgery (58.96±9.24ng/g).
Plasma glucoregulatory hormones
The average concentration of plasma glucagon increased significantly after PACAP-38,
VIP (5nmol/hr) as well as the VPAC2R agonist infusion, but not with lower concentrations of VIP (1nmol/hr; not shown), VPAC1R agonist or vehicle infusion (Fig. 6A).
Furthermore, no significant difference was found between the glucagon responses of
the VIP (5nmol/hr), PACAP-38 and VPAC2R-agonist treated groups. Mean plasma
insulin concentrations were mildly elevated upon i.c.v. administration of PACAP-38
and the VPAC2R agonist, but neither of them reached statistical significance (Fig.
6B). After hepatic sympathetic, parasympathetic and sham denervation, PACAP-38
← Figure 5 Fos-ir neurons induced by PACAP-38 and VPAC2R agonist mainly locate in the
medial PVN, VIP induced Fos-ir also extends to the lateral PVN. A, Few of the VPAC2R
agonist induced Fos-ir neurons contain AVP-ir. B, VIP induced strong Fos-ir both in the
rostro-medial and lateral magnocellular compartment with considerable co-localization with
AVP (arrow). C, CTB injection into the thoracic IML retrogradely labelled pre-autonomic
neurons in PVN (red, as pointed by arrow head), some of them are activated by the i.c.v.
administration of PACAP-38 as indicated by the co-localized Fos-ir (green, pointed by arrow). III: third cerebral ventricle. Scale bar: A and B 100 μm; C, 50 μm.
157
158
PA
*
8
#
P- 3
8
*
CA
P- 3
#
X+
#
am
8
*
CA
P- 3
*
PA
CA
*
Sh
X+
PA
#
HP
*
X+
#
is t
*
on
#
HS
ag
is t
#
2R
on
200
AC
#
VP
r)
150
ag
l/h
#
1R
150
mo
8
#
AC
P- 3
le
Plasma glucagon (ng/ml)
100
(5n
CA
h ic
Plasma insulin (ng/ml)
A 200
VP
VIP
PA
Ve
Plasma Corticosterone (ng/ml)
chapter 8
Basal State
i.c.v. infusion state
*
*
#
2.5
#
*
#
100
50
#
0
*
50
0
B 4.0
3.5
3.0
#
2.0
1.5
1.0
0.5
0.0
C 250
*
*
chapter 8
infusion increased plasma glucagon concentrations to a similar level as did PACAP-38,
VIP or VPAC2R-agonist in non-denervated animals. After HSX, mean plasma insulin levels were not increased during the administration of PACAP-38. In HPX and
shamX animals only the increase in the shamX group reached significance. Plasma
corticosterone concentrations showed a significant increase in all groups. However,
all drug-induced responses were significantly higher than those of the vehicle controls
and no significant differences were found between PACAP-38, VIP and their receptorspecific agonists, or between HSX, HPX and shamX groups (Fig. 6C).
Discussion
The present results clearly show that hypothalamic PACAP signalling is tightly involved in the control of glucose metabolism. The i.c.v. administration of PACAP-38
caused a pronounced increase in EGP and a lasting hyperglycemia by stimulating
glycogenolysis. Follow-up experiments using co-infusions of specific VIP/PACAP
receptor (ant)agonists, Fos immunohistochemistry, retrograde tracing and specific
denervations of the autonomic liver input, suggest a role for the hypothalamic PACAP
system in the control of glucose metabolism by a specific central pathway involving
VPAC2R and pre-autonomic neurons.
Although PACAP and VIP share several similar functions, including that of stimulating the release of prolactin and other pituitary hormones 589, they are basically
distinct peptides, with different origins and distributions in both brain and periphery.
Hypothalamic VIP immunoreactive fibers, including those in the PVN, are almost
solely derived from the SCN 613, 614. On the other hand, PACAP immunoreactive fibers
are widely distributed within the hypothalamus, especially in the medial part of the
PVN 615. Moreover, the hypothalamic PACAP innervation is derived from different
origins, including intra-hypothalamic sources such as the VMH, and extra-hypothalamic sources such as the bed nucleus of the stria terminalis (BNST), the brainstem 594,
615-617
and the retina 595. Despite the equal affinity of PACAP and VIP for the VPAC2R
Figure 6 Plasma insulin, glucagon and corticosterone responses to the i.c.v infusion of
PACAP-38, VIP and their receptor agonists, in liver intact and denervated animals. A, I.c.v.
infusion of PACAP-38, VIP and VPAC2R agonist significantly increased plasma glucagon
concentrations as compared to the basal state as well as compared to the vehicle control. Hepatic sympathetic, parasympathetic or sham denervation has no influence on the stimulatory
effect of PACAP-38 on plasma glucagon. B, In the same animals only the plasma insulin increase in the sham-denervated animals reached statistical significance. C, All groups showed
increased plasma corticosterone concentrations (as compared to basal), but no difference was
found between the different drug infusion groups, although all differed significantly from
the vehicle infusion. Data are presented as mean±SEM, # P<0.05 vs. Basal state, *P<0.05 vs.
Vehicle control.
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as shown by in vitro receptor binding studies 598, we found quite different actions on
glucose metabolism, i.e., at least 5-fold doses of VIP were incapable of inducing similar
increases in plasma glucose concentration and EGP as PACAP-38. This difference did
not depend on their effects on peripheral glucoregulatory hormones. For instance, VIP
had the strongest effect on plasma glucagon but its effects on plasma glucose and EGP
were much weaker than those of PACAP-38 and the VPAC2R-agonist. Moreover, similar increases of corticosterone were associated with very different effects on plasma
glucose and EGP. Therefore our data implicate a different central effect of PACAP-38
and VIP on hepatic glucose production. Similar differences were observed in other
studies. In the adrenal, PACAP is approximately 100-fold potent more than VIP in
evoking secretion of catecholamines 618, and in SCN, PACAP is 1000-fold more potent
than VIP at altering the phasing of the circadian rhythm 595.
Specific denervation of the sympathetic input to the liver profoundly obliterated
the EGP increase produced by i.c.v. administration of PACAP-38, despite an unimpaired plasma glucagon increase. These results indicate that PACAP-38 stimulation
of hepatic glucose production largely depends on an intact sympathetic autonomic
innervation of the liver. PACAP activation of the thoracic IML projecting pre-autonomic neurons in the PVN strongly suggest that the EGP stimulating action involves
activation of liver projecting pre-autonomic neurons by PACAP-38 47. This idea is
supported by the presence of VPAC2R-immunoreactivity in the dorsal and ventral
PVN 619. On the other hand, the PACAP-38 activated pre-autonomic neurons might
also control other (visceral) organs. Thus, besides the liver, PACAP-38 information
might also reach the adrenal to stimulate adrenalin, noradrenalin and/or corticosterone release, and the pancreas to stimulate pancreatic glucagon release and/or inhibit
the insulin response to hyperglycemia. In fact, the i.c.v. treatment with PACAP-38,
VIP and VPAC2R-agonist all increased glucagon levels while the expected insulin
release upon the induction of hyperglycemia did not occur suggesting an inhibitory
effect on insulin secretion. The combination of an increase in glucagon, increase in
EGP with a presumed inhibitory effect on insulin suggests a role for PACAP-38 and
the VPAC2R in the counter-regulatory response to hypoglycaemia or in maintaining
plasma glucose during fasting. Glucose is produced in the liver by glycogenolysis and
by gluconeogenesis (GNG). It is still far from clear which specific signals, besides
circulating glucoregulatory hormones, control the balance between glycogenolysis
and GNG. The present study shows that the PACAP-38 induced increase in EGP can
be almost entirely attributed to an increased glycogenolysis. These findings are completely in line with early studies on the stimulatory effects of electrically stimulated
sympathetic nerves on liver glycogenolysis 151, 154.
What cannot be ignored is that besides the PVN also the nucleus incertus (NI) in the
pons was consistently activated by the i.c.v. administration of PACAP-38, VIP and the
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chapter 8
VPAC2R agonist. The NI abundantly expresses the CRH receptor 620. Whether the Fosir is a direct response to PACAP, VIP and VPAC2R agonist, or an indirect response to
CRH release from the PVN is not clear at present. The NI uniquely expresses relaxin-3,
an orexigenic neurotransmitter belonging to the insulin superfamily, with its receptor
being predominantly expressed in the PVN 621, 622. We can thus certainly not exclude
that the NI, too, participates in the presently observed glucoregulatory effects of VIP
and PACAP-38 through a complex forebrain-hindbrain network.
At present it is not clear which group(s) of PACAP-containing neurons are responsible for the effects described. PACAP-deficient animals have been shown to have an impaired counterregulatory response to hypoglycemia 623. Recovery from hypoglycemia
is believed to be mainly processed by the VMH and the sympathoadrenal pathway 624.
As PACAP mRNA is highly expressed in the VMH 615, it is possible that activation of
PACAP neurons in the VMH, and subsequently the PACAP-containing projection to
the PVN, are involved in the hypothalamic mechanism necessary to stimulate hepatic
glucose production upon a hypoglycemic challenge. PACAP is also involved in both
acute and chronic stress responses via the PVN-CRH neurons, the HPA-axis and the
sympathetic nervous system 625-628. The PACAP system could thus be an important
gateway to control hepatic glucose production during stress 625-628. Finally, as PACAP
expression in the VMH is also under the influence of estrogen 629, the currently revealed glucoregulatory effects of PACAP might also be part of a brain circuit that
connects the reproductive system with energy metabolism.
In summary, we present a neuronal pathway by which PACAP-38 activates hypothalamic pre-autonomic neurons that control sympathetic nerves innervating the
liver, resulting in a hyperglycemia almost entirely due to an increase in hepatic glycogenolysis. Future experiments should reveal the specific physiological stimuli and
PACAP neurons responsible for the activation of these glucoregulatory sympathetic
pre-autonomic neurons.
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Supplemental data.1
Immunohistochemistry
Animals were deeply anaesthetized after the final blood sample and 1 μl colorful dye
was injected via the i.c.v. guiding probe to validate the probe placement. Animals were
transcardially perfused with saline, followed by a solution of 4% paraformaldehyde
in 0.1M phosphate buffer (pH 7.4) at 4°C. Tissues were cryoprotected for 48hrs with
30% sucrose in 0.1M Tris-buffered saline (TBS), the brain tissue was cut into 35 μm
coronal sections and divided into five equal groups for single immunohistochemical
staining or double-labeling immunofluorescence staining. For single Fos immunohistochemistry, sections were incubated overnight at 4°C with goat anti-Fos (1:1500;
Santa Cruz Biotechnology, Inc., Santa Cruz, CA) primary antibodies. Sections were
then rinsed in 0.1M TBS, incubated 1 hr in biotinylated horse anti-goat IgG, and then
1 hr in avidin–biotin complex (ABC, Vector Laboratories, Inc., Burlingame, CA). The
reaction product was visualized by incubation in 1% diaminobenzidine (DAB) (0.05%
nickel ammonium sulphate was added to the DAB solution to darken the reaction
product, DAB/Ni) with 0.01% hydrogen peroxide for 5-7 min. Sections were mounted
on gelatin-coated glass slides, dried, run through ethanol and xylene and covered for
evaluation by light microscopy. To check whether the Fos-ir was co-localized within
arginine vasopressin (AVP) containing neurons in the PVN, adjacent sections were incubated with both goat anti-Fos and rabbit anti-AVP (1:1000, Boehringer Mannheim,
Indianapolis, IN) primary antibodies. After Fos staining with DAB/Ni, sections were
rinsed and incubated with horse anti-rabbit IgG and ABC, and only DAB staining was
applied to visualize the AVP-ir.
Double-labeling immunofluorescence was applied to characterize the relation between
the pre-autonomic neurons in the PVN that project to the spinal cord and the PACAP-38-induced Fos-ir. Sections were incubated overnight at 4 °C with goat anti-Fos
primary antibody, rinsed in 0.1M TBS, incubated 1 hr in biotinylated horse anti-goat
IgG, and rinsed and incubated with streptoavidin-Cy2 for 1 hr, rinsed, mounted on
gelatin-coated glass slides, dried and covered with glycerol in 0.1 M PBS (PH 9.0) and
evaluated using confocal laser scanning microscopy.
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chapter 8
Supplemental data.2
A
B
12
140
VPAC1R agonist 1nmol/hr
VPAC2R agonist 1nmol/hr
Vehicle
i.c.v. infusion
120
10
100
80
6
4
C
12
VPAC2R antagonist 5nmol/hr
PAC1R antagonist 5nmol/hr
MC3/4-R antagonist 5nmol/hr
Vehicle
10
EGP (umol/kg.min)
Plasama glucose (mmol/L)
8
60
40
D
140
120
100
8
80
6
60
40
4
100
140
180
Time (min)
220
100
140
180
Time (min)
220
Supplemental Figure 1 Control infusion of VPAC1R and VPAC2R agonists into the systemic circulation or i.c.v. infusion of PAC1R, VPAC2R and MC3/4-R antagonists without
PACAP-38 had no effects on either plasma glucose concentrations (A & B) or EGP (C & D).
Data are presented as mean±SEM.
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Chapter 9
Glucocorticoid signaling in the arcuate nucleus is involved in the control of
hepatic insulin sensitivity
In preparation
Chun-Xia Yi, Ewout Foppen, Mireille J. Serlie, Eric Fliers, Ruud M. Buijs & Andries Kalsbeek
Abstract
Objective Glucocorticoid receptors are, amongst others, highly expressed in the hypothalamic paraventricular (PVN) and arcuate nucleus (ARC). As glucocorticoids
have pronounced effects on neuropeptide Y (NPY) expression, and NPY neurons
projecting from the ARC to the PVN are pivotal in feeding behaviour and glucose
metabolism, we investigated the effect of glucocorticoid signaling in the ARC and PVN
on endogenous glucose production (EGP) and hepatic insulin sensitivity.
Research Design and Methods We investigated the acute effects of local administration of the glucocorticoid receptor agonist dexamethasone (Dex) in the PVN or ARC,
by retrodialysis, on EGP and hepatic insulin sensitivity. EGP was measured by the
stable isotope dilution method, and hepatic insulin sensitivity was studied during a
hyperinsulinemic-euglycemic clamp.
Results Retrodialysis of dexamethasone for 90 min into the PVN, the ARC, or the
brain area surrounding the PVN and ARC (misplacement control, MC) had no significant effects on basal plasma glucose concentration. EGP showed a decline over
time in all groups (i.e., dexamethasone and vehicle), but only in the Dex-ARC and
Dex-MC group this decline reached significance. No significant differences were found
between the six treatment groups, nor when each dexamethasone group was compared
to its own vehicle control group. During the hyperinsulinemic-euglycemic clamp,
retrodialysis of dexamethasone into the ARC, but not into the PVN or MC, largely
prevented the suppressive effect of peripheral hyperinsulinemia on EGP. Circulating
plasma corticosterone levels were inhibited in all dexamethasone, but not vehicle,
treated groups.
Conclusions Dexamethasone administration in the ARC, but not in the PVN, induces hepatic insulin resistance. Whereas glucocorticoids profoundly affect glucose
metabolism through their signalling in specific hypothalamic nuclei, their inhibitory
effect on the hypothalamus-pituitary-adrenal (HPA) axis is much more widespread
in the hypothalamus.
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chapter 9
Introduction
Clinical conditions with glucocorticoid excess such as Cushing’s syndrome are accompanied by a disturbed glucose metabolism, including hepatic insulin resistance,
which is reversible after treatment 630. Several hypothalamic nuclei including the arcuate nucleus (ARC) and the paraventricular nucleus (PVN) have recently been proven
to be involved in regulating hepatic glucose production and insulin sensitivity 158, 193,
196, 631, 632
. Thus in addition to their well known direct peripheral effects on glucose
metabolism, glucocorticoids may also affect glucose metabolism through their binding in the central nervous system (CNS).
Glucocorticoid signaling involves two receptor systems, i.e., the mineralocorticoid
receptor (MR), which in the CNS is mainly restricted to the septum, hippocampus
and amygdala 633, and the glucocorticoid receptor (GR), which is localized throughout the brain including the hypothalamus. In the hypothalamus, GRs are expressed
abundantly in the PVN and in the ARC as demonstrated by immunohistochemistry,
in situ shybridization and receptor autoradiography studies 318, 633-636, while MRs show
weak immunoreactivity in the PVN and its mRNA expression is not detectable by in
situ hybridization methods 637. The strong expression of GRs in the PVN, especially
in the parvocellular subdivision 634, 635, is thought to be mainly involved in the negative feedback of corticosterone on the hypothalamus-pituitary-adrenal (HPA) axis.
However, the PVN is not only responsible for neuroendocrine regulation, but it is also
an important hypothalamic centre for the control of the autonomic nervous system
(ANS) by virtue of the local abundance of pre-autonomic neurons. Recently the ANS
has been strongly implicated in the regulation of glucose metabolism and hepatic
insulin sensitivity 157, 158, therefore glucocorticoids might affect glucose metabolism
through their action on pre-autonomic neurons in the PVN.
Interestingly, i.c.v. infusion of dexamethasone (i.e., a glucocorticoid receptor agonist) stimulates food intake and body weight gain 638, while it decreases glucose uptake
639
. The specific neuronal target area(s) for these i.c.v. administered dexamethasone
effects have not been clearly identified yet. One possibility is that it involves glucocorticoid signaling in the ARC, thereby antagonizing the effects of insulin on neuropeptide
Y (NPY) containing neurons in the ARC 640, 641. This is supported by the observation
that peripheral administration of dexamethasone or corticosterone increases NPY
mRNA expression in the ARC 642, 643.
In the present study we investigated whether modulation of hypothalamic glucocorticoid signaling specifically in the ARC or the PVN would influence peripheral glucose
metabolism. By using the retrodialysis technique we delivered dexamethasone locally
into the ARC and PVN under stress-free experimental conditions. EGP was measured
by the stable isotope dilution method and hepatic insulin sensitivity was determined
by combining it with a hyperinsulinemic-euglycemic clamp.
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chapter 9
Materials and Methods
Animals
All experiments were conducted under the approval of the animal care committee of
the Royal Netherlands Academy of Arts and Sciences. Male Wistar rats weighing 300350 g (Harlan Nederland, Horst, The Netherlands) were housed in individual cages,
with a 12/12-h light-dark schedule (lights on at 07.00 h, as Zeitgeber time 0 (ZT0)).
Food and water were available ad libitum, unless stated otherwise.
Surgery preparation
Animals underwent surgeries according to the different experimental designs under
anaesthesia with 0.8 ml/kg Hypnorm i.m. (Janssen, High Wycombe, Buckinghamshire,
UK), and 0.4 ml/kg Dormicum s.c. (Roche, Almere, The Netherlands).
Silicon catheters were inserted into the right jugular vein and left carotid artery
for i.v. infusions and blood sampling, respectively. With a standard Kopf stereotaxic
apparatus, bilateral microdialysis probes 48 were placed into the ARC and PVN. Coordinates were adapted from the atlas of Paxinos and Watson 497 (see supplemental
data.1; table.1). All catheters and probes were fixed on top of the skull and secured
with dental cement. After recovery, animals were connected to a multi-channel fluid
infusion swivel (Instech Laboratories, PA, USA) one day before the experiment for
adaption. Food was restricted at 20g on the night prior to experiments. The start of
the experiment (i.e., t=0) was at ZT3.
Glucose kinetics
To study glucose kinetics, [6.6-2H2] glucose as a primed (8.0 μmol in 5 min) followed by a continuous (16.6 μmol/h) infusion was used as a tracer (>99% enriched;
Cambridge Isotopes, Andover, USA). A first blood sample was taken at t=-5 min for
measuring background enrichment of [6.6-2H2] glucose. The [6.6-2H2] glucose infusion started at t=0 min. After an equilibration time of 90 minutes, blood samples were
taken at t=90, t=95 and t=100 min for determining glucose enrichment and plasma
glucose and corticosterone concentrations. Thereafter the [6.6-2H2] glucose infusion
was continued for another 110 min where after blood samples were taken at t=200,
t=205 and t=210 min for determining glucose enrichment during the retrodialysis
of dexamethasone and vehicle (Ringer’s solution). Thereafter, the insulin infusion
started (prime 7.2mU/kg·min for 4 min followed by a continuous infusion (3mU/
kg·min) from T= 210 min until T=370 min (vide infra). At t=210 min an additional
and variable infusion of a 25% glucose solution (enriched 1% with [6,6-2H2] glucose)
was started to maintain euglycemia (5.5±0.2mmol/L), as determined by 10 min carotid
catheter blood sampling. At the end of the clamp, five blood samples were taken with
a 10 min interval from t=330-370 min 632.
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chapter 9
Retrodialysis
Retrodialysis probes were aimed to be placed into PVN and ARC. We included animals in which the probes appeared to be misplaced upon histological examination as
a separate post-hoc misplacement control (MC) group, thus animals were divided into
six groups: vehicle-PVN, dexamethasone-PVN (Dex-PVN), vehicle-ARC, Dex-ARC,
vehicle-MC and Dex-MC. From t=0-100 min, all six groups received retrodialysis
of vehicle (Ringer’s, 3μl/min). After taking the blood samples for the calculation of
basal EGP, i.e., from t=100 min onwards, in the dexamethasone groups (Dex-PVN,
Dex-ARC and Dex-MC) the retrodialysis of Ringer’s was replaced by dexamethasone
retrodialysis (200 μM, 3μl/min). In the vehicle group the retrodialysis of Ringer’s
was continued until the end of the study. At the end of the experiments, brains were
removed for Nissl staining to validate the probe placements.
Analytical methods
Plasma glucose concentration was measured by a handheld glucometer (Freestyle
Flash, Abbott), plasma corticosterone concentrations were measured using radioimmunoassay kits [LINCO Research (St. Charles, MO, USA). Plasma [6,6-2H2] glucose
enrichment was measured by gas chromatography-mass spectrometry (GCMS) 605.
Statistics and calculations
Results are expressed by averaging values from three plasma samples at the end of
the equilibration state (t=90-95-100 min), the end of the dexamethasone infusion state
(t=200-205-210 min), and five plasma samples at the end of the clamp experimental
period (t=330-340-350-360-370 min). ANOVA and post-hoc Student’s t-tests were
performed to compare the group differences. EGP was calculated using the modified
forms of the Steele Equations (ref Finegood) 500.
PVN
ARC
168
Figure 1 Schematic drawing illustrating the correct
placement zones for of retrodialysis probes. If probes
were inside the PVN and ARC nuclei or within the
boundaries of the gray dotted lines (≈200μm around
the nuclei), rats were categorized as vehicle/Dex-PVN
(Dex-PVN is illustrated by gray triangles) or vehicle/
Dex-ARC (Dex-ARC is illustrated by gray circles)
groups. Rats with probes outside of the gray dotted
lines were grouped as misplacement control (Vehicle/
Dex-MC).
chapter 9
Results
Glucose metabolism in the basal state
Probe placements were examined in Nissl stained sections. For the ARC and PVN
groups, rats were included if bilateral probes were placed either inside the nuclei or
within the direct vicinity of the nucleus, i.e., not beyond 200μm distance from the
borders of the nuclei. Rats with probes exceeding these ranges were categorized as
misplacement control. The anatomical criteria are illustrated in Fig. 1.
Basal plasma glucose levels did not differ between the six experimental groups
(F(5,28)=0.74, p=0.60) and glucose concentration did not change within any of the
groups during the retrodialysis of vehicle or dexamethasone; also no difference in plasma glucose level was found between the six groups after retrodialysis (F(5,28)=0.80,
p=0.56) (Fig. 2).
Basal EGP showed no significant difference between all groups (F(5,28)=0.42,
p=0.83) (Fig. 3). Also after 90 min of dexamethasone or vehicle treatment, EGP was
not different between the 6 treatment groups (F(5,28)=1.03, p=0.42). In all groups
mean EGP decreased (average 27%) during the retrodialysis of vehicle or dexamethasone. As we demonstrated previously (6), this decline of EGP is caused by the removal
of food from the rat home cage before the start of the experiment and fasting along
the experimental period. Only in the Dex-ARC and Dex-MC groups, this decrease
reached significance (p=0.03 for both groups).
Basal state
Dex
6
4
-MC
n=5
Dex
-MC
n=4
Ve h
C
n=5
-AR
Dex
C
n=4
-AR
Veh
n=7
-PVN
D ex
Ve h
0
n=4
2
-PVN
Plasma glucose (mmol/L)
8
Figure 2 Plasma glucose concentrations at the end of the equilibration state (basal) and at
the end of the 90-min dexamethasone treatment (before the start of the clamp).
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chapter 9
Hepatic insulin sensitivity
Insulin significantly suppressed EGP in the three vehicle groups, as well as in the
Dex-PVN and the Dex-MC groups (P<0.01 for all five groups, compared to their own
basal state, and P<0.05 for five all groups, compared to their own Dex state) (Fig. 3).
Mean suppression of EGP in those groups was 64%. However, in the Dex-ARC group,
severe hepatic insulin resistance was found with no significant suppression of EGP by
insulin infusion (P= 0.43 vs. Basal state, and P=0.54 vs. Dex state). Indeed ANOVA
detected a significant effect of Group (F(5,28)=5.66, p=0.002) during the clamp condition. Post-hoc testing showed that EGP during hyperinsulinemia was significantly
higher and suppression significantly less in the Dex-ARC group than in the other five
groups (P<0.01 for all groups).
The rate of glucose disappearance (Rd) was not significantly different between the
six groups (F(5,28)=1.41, p=0.26), however, Rd in Dex-PVN was significantly higher
than in vehicle-PVN (p=0.02) as well as in Dex-ARC group (p=0.01) (Fig. 5).
The present study used a freely moving, non-stressed animal model, and during the
basal state (i.e., before dexamethasone administration) plasma corticosterone concentrations of all animals were in the normal daytime range, i.e., 0 – 25 ng/ml (Fig.
6), without significant differences between any of the groups (F(5,28)=0.78, p=0.80).
After dexamethasone or vehicle treatment in the basal state no significant difference
Basal vehicle state
Dex or Vehicle
Dex or Vehicle + Clamp
125
75
*
#
#
50
^
^
-MC
#
Dex
C
Veh
-M
C
C
Dex
-PVN
Veh
-P
0
VN
25
^
#
^
-AR
#
#
D ex
^
-AR
#
Veh
EGP (umol/kg.min)
100
Figure 3 Endogenous glucose production (EGP) at the end of equilibration state (basal
vehicle state), at the end of the 90-min dexamethasone or vehicle treatment and at the end
of the hyperinsulinemic-euglycemic clamp. # p<0.05 vs. basal vehicle state; ^ p<0.05 vs. Dex
state; * p<0.05 vs. other five groups during clamp.
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chapter 9
was found between the 6 groups (F(5,28)=2.63, p=0.17). A clear rise in the plasma
corticosterone concentration was observed in the three vehicle groups at the end
of the hyperinsulinemic clamp (ZT9-10 ) compared to their basal state (p=0.01 for
vehicle-PVN; p=0.04 for vehicle-ARC; p=0.006 for vehicle-MC); no difference was
found between the end of the dexamethasone period and the clamp period (p=0.064
for vehicle-PVN; p=0.26 for vehicle-ARC); p=0.007 for vehicle-mc), i.e., nicely in
line with the daily rhythm in plasma corticosterone concentrations that show a pronounced circadian peak before the onset of the dark period (i.e., ZT12). This rise in
corticosterone at the end of the hyperinsulinemic period was completely absent in
0
PVN
MC
ARC
Suppression of EGP (%)
-20
#
Figure 4 Percentage suppression of EGP by
hyperinsulinemia at the end of the clamp.
# p<0.05 vs. Vehicle-ARC;
* p<0.05 vs. Dex-PVN and Dex-MC.
*
-40
-60
-80
-100
175
Vehicle
Dex
Vehicle
Dex
Clamp Rd (umol/kg.min)
150
125
#
Figure 5 Rd at the end of the euglycemic
hyperinsulinemic clamp.
# p<0.05 vs. Vehicle-PVN,
* p<0.05 vs. Dex-ARC.
*
100
75
50
25
0
PVN
ARC
MC
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chapter 9
Plasma corticosterone (ng/ml)
175
Basal vehicle state ZT4-5
Dex or Vehicle ZT7-8
Dex or Vehicle + Clamp ZT9-10
150
#
125
#
100
*
#
*
*
75
50
-MC
D ex
-MC
Veh
C
-AR
D ex
C
-AR
Veh
-PVN
D ex
Veh
0
-PVN
25
Figure 6 Plasma corticosterone concentration at the end of equilibration state (basal vehicle
state), at the end of the 90-min dexamethasone or vehicle treatment (before the start of the
clamp) and at the end of the hyperinsulinemic-euglycemic clamp. * p<0.05 vs. basal vehicle
state.
all three dexamethasone treated groups (p=0.12 for Dex-PVN; p=0.87 for Dex-ARC;
p=0.48 for Dex-mc). ANOVA detected a significant effect of Group (F(5,28)=12.31,
p<0.001), (p<0.01, for each vehicle group vs. dexamethasone group). No differences
were found between the three vehicle groups (F(2,11)=3.35, p=0.99), nor between the
three dexamethasone-treated groups (F(2,16)=3.35, p=0.07).
Discussion
To investigate whether glucocorticoids are able to affect glucose metabolism via a
central mechanism and whether this modulation is mediated within the hypothalamus by the ARC or the PVN, we delivered the glucocorticoid receptor agonist dexamethasone or vehicle locally into the ARC as well as in the PVN. After 90 min of
treatment, dexamethasone appeared to have no effects on either basal plasma glucose
concentrations or basal EGP in comparison with the vehicle control groups. However,
dexamethasone treatment into the ARC during hyperinsulinemia induced severe hepatic insulin resistance. Peripheral corticosterone concentrations were similar in all
groups, but the endogenous rise in plasma corticosterone before the onset of the dark
period was absent in all dexamethasone treated animals. These results show that glucocorticoids acting specifically in the ARC reduce hepatic insulin sensitivity, whereas
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their inhibitory effect on the HPA-axis is not different between ARC and PVN or the
areas around these two nuclei. Therefore, contrary to its feedback action on the HPAaxis, the antagonistic effect of glucocorticoids on the insulin-induced inhibition of
EGP appears to be localized specifically in the ARC. Moreover, the insulin-resistance
promoting effect of hypothalamic glucocorticoids is independent from its effects on
circulating glucocorticoids.
Due to a locally leaky blood brain barrier, the ARC neurons represent a neuron
population in the brain with an easy access to many blood born signals, including
hormones such as insulin, leptin, thyroid hormone, ghrelin and glucocorticoids as well
as other circulating metabolic factors. Moreover, the receptors for these hormones are
abundantly expressed in this nucleus 318-321, 644. The clearest evidence for glucocorticoids
to act on the ARC are the changes induced by glucocorticoids in NPY expression and
release 642, 643, in conjunction with the presence of glucocorticoid binding elements in
the NPY gene 645. In addition, the effects of ghrelin, which is released by the stomach
and also acts within the ARC to alter food intake depend on glucocorticoids because
none of these actions of ghrelin can be induced after adrenalectomy (ADX). In addition, we found that during fasting, which increases circulating plasma corticosterone
levels 646, Fos-ir is induced in the ARC neurons that express the GR (see supplemental
data.2 and supplemental Fig. 1). Together these data indicate that glucocorticoids are
able to interact with ARC signaling and that this interference may act as an important
integrative element for ARC neurons in the control of glucose metabolism. In our
previous study, i.c.v. infusion of NPY induced hepatic insulin resistance via the hepatic
sympathetic innervation 158. Therefore, it is tempting to speculate that in the present
study the main action of dexamethasone in the ARC was to increase NPY activity and
release, thereby inducing hepatic insulin resistance via an increased sympathetic input
to the liver.
Chronic (2 days) i.c.v. infusion of dexamethasone increases food intake and decreases muscle tissue glucose uptake, and both effects need an intact subdiaphragmatic vagus nerve in order to occur 639. Interestingly, some of the metabolic effects of
chronic i.c.v. infusions of NPY depend on the presence of circulating corticosterone
because bilateral adrenalectomy prevents the effects on muscle glucose uptake and
insulin sensitivity of adipose tissue. Moreover these effects also dependent upon an
intact subdiaphragmatic vagus nerve 647. Taken together, these data support a synergy
between NPY and corticosteroids in the ARC in the control of metabolism.
To further clarify the effects of central dexamethasone on glucose disappearance,
plasma insulin concentrations representing ~6 times physiological levels 632 are needed. Moreover, such studies will also enable us to separate possible direct effects of
dexamethasone on glucose metabolism from indirect effects via changes in food intake
and other aspects of energy balance.
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chapter 9
Interestingly, although it has been suggested that dexamethasone poorly penetrates
the brain 648, by using radioautographic studies in ADX rats, it has been shown that
“small amounts” of dexamethasone do selectively reach the ventral part of the ARC
649
. Whether the observed specificity of dexamethasone in the ARC on glucoregulation
in the present study has a clinical implication and thus whether peripherally administered dexamethasone can act via the ARC to regulate hepatic insulin sensitivity needs
further investigation.
In summary, by delivering dexamethasone via retrodialysis into specific hypothalamic nuclei, we showed that increasing glucocorticoid signaling in the ARC induces
severe hepatic insulin resistance while it had no effect on basal endogenous glucose
production. This centrally mediated effect of dexamethasone cannot be attributed to
increased circulating plasma corticosterone concentrations. Moreover, the hypothalamic system responsible for the glucocorticoid feedback on the HPA-axis seems much
more widespread than the one responsible for the inhibitory effect on EGP.
Supplemental data.1
Table 1 Stereotactic coordinates for placements of microdialysis probes.
(mm) PVN
ARC
Antero- posterior
Lateral
Ventral
Angle
-1.88
-3.30
2.0
2.0
-7.9
-9.7
10
8
Tooth bar was set as -3.2 mm. The ventral coordinates were standardized for 300g BW, every
additional 25g BW will be placed 0.1 mm deeper.
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chapter 9
Supplemental data.2
Methods
To examine whether ARC neurons that express GR can be activated by long-term
fasting, food (but not water) was removed at ZT1 from three intact rats for 48 h. Rats
were then deeply anesthetized with a lethal dose of sodium pentobarbital and perfused
with saline, followed by a solution of 4% paraformaldehyde in 0.1M PBS (pH 7.4) at
4 C. The brains were removed and kept in fixative at 4 C for overnight post-fixation,
equilibrated 48h with 30% sucrose in 0.1M Tris-buffered saline (TBS; pH 7.2). Brains
were coronally cut in a cryostat into 30 μm sections; sections were rinsed in 0.1M
TBS and incubated overnight at 4°C in goat anti c-Fos antibody (1:1500; Santa Cruz
Biotechnology, Inc., Santa Cruz, CA) and rabbit anti-GR antiserum (1:2000). Sections
were then further incubated with horse anti-goat IgG for 1h, thereafter, donkey antirabbit-Cy2 and streptoavidin-Cy3 were co-incubated for 1h to check colocalization
of c-Fos and GR by confocal laser scanning microscopy.
Supplemental Figure 1 c-Fos expression (red), induced by 48 hours fasting, in the ventromedial part of the ARC is co-localized with glucocorticoid-receptor staining (green) in the
same neurons (yellow) (arrow). III: third cerebral ventricle.
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Chapter 10
Floating rhythms in plasma glucose concentration and glucose appearance
-a technical note-
Introduction
Although the daily rhythm in plasma glucose concentration is not determined by food
intake but by the central biological clock located in the suprachiasmatic nucleus (SCN)
518, 650
, the rhythmic physiology and behavior of animals can be influenced by changing
feeding conditions, as evidenced by food anticipation studies. Most of the studies on
day-night fluctuations of glucose metabolism have been done by measuring plasma
glucose concentration. The plasma glucose pool is determined by input –rate of glucose appearance (Ra) and output – rate of glucose disappearance (Rd). Any influence
on either of these two fluxes will affect the final plasma glucose concentration. The
main contributions to Ra come from endogenous glucose production and the direct
glucose intake by feeding. Rd is the sum of the insulin-dependent (mainly muscle and
adipose tissue) and insulin-independent (mainly liver and brain) glucose uptake. In
the present study we aimed to map the Ra along the day/night-cycle under 3 different
experimental conditions, including groups of animals that were: 1) fed ad libitum (with
food pellets on floor of the cage); 2) fasted for 24-hours; 3) trained to eat only during
the 12-h dark period (food pellets available in food hoppers). The reason to include
the third group was due to the consideration, that in studies of glucose metabolism,
food is always removed from the rats’ home cage either in advance or temporarily, to
avoid feeding derived glucose entering the circulation. In our lab, we observed a slight
increase in food seeking behavior when the rats notice that food has been removed
from the cage. Despite the fact that rats don’t eat big meals when food is present in the
cage during this time of the day, i.e., the light, thus sleep, period for rats. Therefore,
when we observed that the endogenous glucose production (EGP) was continuously
decreasing shortly after the food was removed (as shown in the following results), we
reasoned this could be an immediate response of the animal in order to save energy,
as the animals did not know of course when the food would become available again.
Remarkably, previously we observed a similar response when we were studying daily
changes in plasma glucagon concentrations, i.e., upon removal of food during the light
period there was an immediate decrease in plasma glucagon concentrations (Ruiter et
al., unpublished observations). Group 3 animals thus were adapted to the presence of
food only during the dark period (and its absence during the light period) for at least
10 days before we did the actual experiment.
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chapter 10
Experimental preparation
Silicon catheters were inserted into the right jugular vein and left carotid artery for
intravenous (i.v.) infusions and blood sampling, as described in previous chapters.
Group-1: Ad libitum, food present inside the cage all the time.
Group-2: Fasting, food was removed at ZT0 of the experimental day till the end of the
blood sampling (totally 28 hours).
Group-3: Food availability restricted to the dark period.
For Ra measurement, a tracer dilution technique was applied, in which the enrichment (tracer/tracee ration) of [6,6-D2] glucose (Cambridge Isotope Laboratories,
Cambridge, USA) was measured, with continuous intravenous infusion. A primed
(8.0 μmol in 5 min)-continuous (16.6 μmol/h) [6,6-D2] glucose intravenous infusion
started at ZT2 (ZT0=7am) (t=0), blood samples were taken at t=-5 min for background
[6,6-D2] glucose enrichment measurement, and at ZT3.5 for determining enrichment
after the equilibration state, from ZT3.5, hourly sampling was performed, in group1-2
till ZT2.5 the next day, and in group 3 till ZT14.5 of the first day. The volume of each
blood sampling was limited to 0.1ml.
Results
1. The plasma glucose concentration of all three groups showed a significant fluctuation along the light/dark-cycle. In ad libitum fed animals plasma glucose concentration slowly increased from ZT3.5 onwards till a peak was reached at ZT12.5 in the
dark period. In fasting animals plasma glucose concentrations also slowly increased
from ZT3.5 onwards, but only until ZT 9.5, i.e, the peak was reached 2.5 hours before
the start of the dark period. In the dark-fed animals, plasma glucose concentrations
at ZT3.5 were very much comparable to those of the ad libitum fed animals. These
animals also showed a slow increase from ZT3.5 onwards, and reached peak levels
at ZT13.5 in the dark period. However, the peak level of the dark-fed animals was
much lower than that of the ad libitum fed animals. In fact, during the light period
the increase did not reach significance (Fig. 1).
2. Because in group 1, glucose appearance probably is not only derived from the endogenous production (as it is in groups 2 and 3), i.e., despite the low feeding activity
during the light period we can not exclude that some of the glucose is coming from
food intake in these animals, we used Ra instead of EGP for all groups.
As can be clearly observed in Fig. 2, the pattern of Ra does not follow closely the pattern of plasma glucose concentrations. In the ad libitum rats, the peak of Ra was found
at ZT16.5. In the fasted animals of group 2, Ra is continuously decreasing. Remarkably the starting point is virtually equal for all 3 groups, i.e., despite the decreased
plasma glucose concentrations at this time Ra is not affected yet. The Ra pattern in
the dark-fed animals of group 3 closely follows the pattern of the fasting rats, with a
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chapter 10
continuous decrease during the light period. At the start of the dark period, however,
a strong increase in Ra is observed due the onset of feeding. A comparison of Figs.
1 and 2 shows that the Ra increase at ZT12.5, is followed by an increase in plasma
glucose concentrations at 13.5.
9
Ad libitum
Feeding in dark
Fasting
Plasma glucose (mmol/L)
8
7
6
5
4
3.5
11.5
Zeitgeber Time
23.5
2.5
Figure 1 Plasma glucose concentration along the light/dark-cycle.
300
Ad libitum
Feeding in dark
Fasting
Ra (umol/kg.min)
250
200
150
100
50
0
3.5
11.5
Zeitgeber Time
23.5
2.5
Figure 2 Rate of glucose appearance (Ra) along the light/dark-cycle.
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chapter 10
Ad libitum
Feeding in dark
Fasting
MCR (mL/kg.min)
40
30
20
10
0
3.5
11.5
Zeitgeber Time
23.5
2.5
Figure 3 Metabolic clearance rate (MCR) along the light/dark-cycle.
3. Because the differences between plasma glucose concentrations and Ra might be
caused by a different glucose disappearance (i.e., Rd), we also calculated the metabolic
clearance rate (MCR). But as there were no major differences between the patterns of
MCR and Ra, apparently no profound changes in Rd occurred during the different
experiments (Fig. 3).
4. Total food intake during this 25.5 hours sampling period did not differ between
group 1 and group 3 (22.6 ± 2.2 g vs. 25.4 ± 1.3 g, p=0.30).
Conclusion
We conclude that:1) different patterns of energy intake will influence the effects of the
SCN timing information on glucose homeostasis, i.e., all 3 groups showed a different
peak time in their daily plasma glucose rhythm; 2) a short-time training of the animals
to adapt them to feeding in the dark period does not change the daily patterns of Ra
and MCR as compared to acutely fasted animals, but it does affect the daily rhythm
in plasma glucose concentration, i.e., trained rats do not show the steep decrease
in plasma glucose concentrations before the end of the light period as observed in
fasted animals. Whether after a longer training period with only feeding in the dark
period, a closer approximation of the ad libitum situation can be accomplised will
need further testing.
180
General discussion
General discussion
Metabolic feedback to the SCN
The dramatic metabolic phenotypes of some mice with clock gene mutations 254 and
the association of other clock gene mutations with type 2 diabetes in humans 651 have
snowballed the interest for the circadian control of energy metabolism in recent years.
The circadian timing information is coming from the central biological clock, which is
presented in the suprachiasmatic nuclei (SCN) located in the anterior hypothalamus,
and synchronizes the daily patterns in locomotor activity, feeding behavior and energy
homeostasis. The zeitgeber properties of photic and behavioral inputs to the clock
are well established, but the renewed interest has evoked the question whether the
central biological clock also receives (feedback) information about the bodily energy
homeostasis and fuel supply. This question is all the more relevant as other evidence
has emerged recently showing that diet itself affects circadian rhythms and clock gene
expression 426, 652-657. Thus, in spite of all the evidence that the light-entrainable oscillator and the feeding-entrainable oscillator are separate entities, for instance, because
SCN lesions do not eliminate food anticipatory behavior 437, 658, it is also evident that
energy metabolism and nutrition influence SCN activity. For instance, SCN neurons
express receptors for metabolic hormones, such as insulin 319, 659, leptin 660 and ghrelin
321
, and they are also sensitive to glucose 661. Therefore, a direct input of metabolic
information to the SCN seems possible, but little information is available and it is not
clear how well this metabolic information can pass the blood-brain-barrier. Leptin
informs the brain about the body’s nutritional status and its secretion can be modulated by feeding, glucocorticoids and insulin, but its daily rhythm is timed by the SCN
662
. In vitro studies have shown that leptin can phase advance the circadian rhythm of
SCN neurons at most circadian times, except at the late subjective night 663, 664. Ghrelin, the natural antagonist of leptin, with its daily changes in plasma concentrations
also being timed by the SCN 665, 666, can phase advance the circadian rhythm of SCN
neurons, when applied in vitro at circadian time 6 399. The limited evidence for direct
and effective metabolic inputs onto the SCN might implicate that this is not a wellstudied mechanism or that this is not the major metabolic feedback mechanism. A
plausible explanation for the latter might be that in order to reach the SCN an active
transport system should be present for these hormones in order to be able to pass the
blood-brain-barrier and reach the SCN. Therefore, we hypothesized that the metabolic
feedback to the SCN would depend on indirect pathways, involving the circumventricular organs. For instance, in the hypothalamic arcuate nucleus (ARC), circulating
metabolic information is already highly integrated, as insulin, leptin, ghrelin, glucose
and glucocorticoids all have their specific effects on the ARC neurons. The data pre183
general discussion
sented in Chapters 3 and 4 show that indeed the ARC-SCN pathway may be important
for relaying metabolic information to the SCN. The results of Chapter 5 show that next
to the circumventricular organs, metabolic information might also reach the SCN
through the dorsomedial hypothalamus (DMH). Clearly the metabolic information
from the DMH is different from that provided by the ARC as it probably consists of
the integrated inputs from circumventricular organs, the brainstem and sleep centers.
DMH-NPFF neurons are mainly sensitive to feeding signals such as food anticipation
and fasting-refeeding. We hypothesize that the NPFF-SCN projection onto the lightsensitive VIP neurons is necessary to lift the inhibitory effect of the SCN on daytime
vigilance and feeding behavior.
Clock perspectives
We propose that through the ARC the SCN has the ability to selectively sense circulating metabolic information representing the peripheral energy status. In addition, the
SCN keeps itself informed about the energetic status of the body in a broader sense
via the DMH. In this way the SCN guarantees to time the whole body physiology and
behavior in the most efficient way.
Hypothalamic neuropeptides and the control of glucose homeostasis
Our present studies, but also recent studies from others, have evidenced the involvement of several hypothalamic neuropeptides in the control of hepatic insulin sensitivity and glucose production. Each of these peptides has its own divergent physiological
function in the control of food intake and energy homeostasis, but in addition they
seem to share common signaling pathways and to target similar brain areas and brain
output pathways.
Neuropeptide Y (NPY)
Best known among these hypothalamic neuropeptidergic networks are the NPY-containing neurons in the ARC with their projections to several hypothalamic brain areas
including the PVN. The first report on the glucoregulatory effects of the hypothalamic
NPY system appeared in the mid nineties when it was shown that i.c.v. administration of NPY increases endogenous glucose production in rats, probably by decreasing
hepatic insulin sensitivity 667, 668. Later on these results were confirmed in mice 201. In
view of the inhibitory effects of hypothalamic insulin receptors on hepatic glucose
production 193, 669, the abundant expression of insulin receptors in the ARC 319, the
inhibitory effect of insulin on NPY neuronal activity 670, and the effects of i.c.v. NPY
on sympathetic activity 158, 671-673, we decided to test whether NPY could be the hypothalamic intermediate between the insulin receptors in the ARC and the pre-autonomic
neurons in the PVN. Hereto we combined the euglycemic hyperinsulinemic clamp
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general discussion
technique with the i.c.v. administration of NPY, and performed these experiments in
hepatic sympathetic-, hepatic parasympathetic- and hepatic sham-denervated rats.
Our results confirmed that i.c.v. NPY is able to block (partially) the inhibitory effects
of peripheral hyperinsulinemia on hepatic glucose production, but they also showed
that a specific denervation of hepatic sympathetic nerves blocks the effect on hepatic
insulin sensitivity of NPY. Therefore, the brain-mediated inhibitory effect of insulin
on hepatic glucose production is probably effectuated via an inhibition of NPY neuronal activity in the ARC. Subsequently, the resulting diminished release of NPY will
decrease the stimulatory input to the sympathetic pre-autonomic neurons in the PVN
and thus reduce the sympathetic stimulation of hepatic glucose production. The results
of Pocai et al. 157, however, show that also the parasympathetic innervation of the liver
is involved in the inhibitory effect of insulin on hepatic glucose production. This means
that in addition to the effect of NPY on the sympathetic pre-autonomic neurons there
is probably another neurotransmitter that is responsible for the transmission of insulin’s effects in the ARC to the parasympathetic pre-autonomic neurons in the PVN.
Moreover, the effects of NPY also seem to be specific for glucose production as in none
of the above experiments there was a significant effect on whole body glucose disposal.
Pro-opiomelanocortin (POMC)
Next to the orexigenic NPY/AGRP neurons, the ARC also contains a population of
anorexigenic POMC/CART-containing neurons. The most important POMC-derived
peptide with respect to feeding and metabolism is alpha-MSH. The antagonistic function of the NPY/AGRP and POMC/CART cell populations is most clearly illustrated
by the fact that AGRP acts as an endogenous antagonist of the melanocortin receptors 3 and 4 674. The antagonizing mechanism of these neuropeptides are extremely
important to adapt the hypothalamic–pituitary–thyroid (HPT) axis to the prevailing
food/energy status, i.e., the fasting-induced suppression of TRH mRNA in the PVN
needs the reduction in alpha-MSH and the increase in AGRP 675. Surprisingly, this
antagonistic cell population does not seem to be involved in the inhibitory effect of
hypothalamic insulin on EGP, as co-administration of a melanocortin antagonist failed
to block the decrease in EGP induced by central insulin 210. Blocking alpha-MSH signaling via i.c.v. infusion of the melanocortin 3/4 receptor (MC3R/MC4R) antagonist
SHU9119 has no effects on glucose metabolism, but i.c.v. infusion of alpha-MSH
itself has a clear stimulatory effect on EGP via gluconeogenesis (GNG) which can
be antagonized by SHU9119. In the liver, the stimulation of GNG is confirmed by
the increased expression of G6Pase and PEPCK 203. These central manipulations had
no effect on peripheral glucose uptake. It has been proposed that the hypothalamic
MC3R/MC4R signaling pathway mediates the effect of systemic leptin on EGP 676.
Central administration of leptin has been proven to be involved in the autoregulation
185
general discussion
of hepatic glucose output, i.e. an increase in GNG with a concomitant decrease in
glycogenolysis without changing total glucose production 208, 209. Recently, it was nicely
shown that the adenoviral-induced expression of leptin receptors in the ARC of leptin
receptor knock-out animals improves glucose tolerance via enhanced suppression of
EGP 677. The ARC-induced expression of the leptin receptor was associated with a
reduced hepatic expression of G6Pase and PEPCK, but again, no significant changes
in the insulin-stimulated whole body glucose utilization were apparent. Moreover, the
effects of hypothalamic leptin signaling on hepatic insulin sensitivity could be blocked
by a selective hepatic vagotomy, providing further supportive evidence for the idea
that ARC projections to pre-autonomic neurons (in the PVN) are important for the
transmission of the effect of leptin on EGP.
Orexin
The neuropeptides orexin-A and orexin-B (also known as hypocretin-1 and hypocretin-2) were initially identified as the endogenous ligands for orphan receptors involved
in the pathogenesis of narcolepsy 678, 679. They were recognized as regulators of feeding
behavior and energy metabolism because of the exclusive localization of their cell
bodies in the lateral hypothalamus (LH), the induction of feeding upon their i.c.v.
administration, their responsiveness to peripheral metabolic cues such as leptin and
glucose, and the metabolic phenotype of the knock-out animals. More recent studies suggest that the orexin system is particularly important for the maintenance of
wakefulness. However, the experiments described in Chapter 6 clearly revitalize the
concept of the metabolic control function of the orexin system. Our data show that
an increased availability of orexin in the central nervous system, either by i.c.v. infusion, or by local activation via removal of GABA inhibition, increases plasma glucose
concentrations through an increase in hepatic glucose production. As with NPY also
the stimulatory effect of orexin on EGP could be blocked by a hepatic sympathetic
but not parasympathetic denervation. From the results described in Chapter 6 it is
not entirely clear yet where in the brain orexin is acting to stimulate EGP. The i.c.v.
infusion experiments and the presence of a pronounced orexin-containing fiber network in the PVN suggest that its main action is again at the level of the sympathetic
pre-autonomic neurons in the PVN, but in view of the electrophysiological data of Van
Den Top et al 512, a direct effect of orexin at the level of the sympathetic pre-ganglionic
neurons in the intermediolateral column of the spinal cord can also not be excluded.
Unfortunately, the selective liver denervations do not allow for a distinction between
these 2 options. In addition, it is not exactly clear yet what the endogenous triggers
are for the stimulatory effect of orexin on EGP, but we propose at least 2 possible
pathways: 1. The orexin neurons could be an alternative pathway for the ARC to affect
EGP, i.e., in addition to a direct projection to the pre-autonomic neurons in the PVN.
186
general discussion
Indeed viral tracing studies have shown second order labeling in orexin neurons after
tracer injections in the liver, i.e., orexin neurons are also pre-autonomic neurons 512.
2. In addition, the orexin neurons might also integrate circadian information. Our
and other studies clearly showed that the activity of the orexin neurons is under tight
control of a GABAergic input that is probably derived from the circadian system 492, 680.
These data indicate that the circadian rhythm in orexin release 681 might be implicated
in the genesis of the circadian rhythm in plasma glucose concentrations. In order to
test this hypothesis, we administered the orexin antagonist SB-408124, either i.c.v. or
i.v., during the final 8 hours of the light period and simultaneously measured glucose
appearance (Ra) from ZT3-ZT15 with the isotope dilution technique. The i.c.v. administration of the orexin-antagonist completely blocked the endogenous increase in
Ra until the start of the dark period. Once the animals start eating, in the dark period,
Ra also increases in the i.c.v. orexin-antagonist treated animals. This i.c.v. administration of the orexin-antagonist did not inhibit food intake. Together these data strongly
suggest that the perifornical orexin neurons are an important link in the circadian
control of the daily peripheral glucose rhythm. Hereby the orexin system provides an
example of hypothalamic integration, as the increased activity of the orexin system at
the end of the light period not only initiates the wake state but at the same time also
ensures a sufficient supply of energy. This may also explain the recently discovered
correlation between sleep duration and type 2 diabetes 682-684. We hypothesize that short
sleep may cause an over activation of the orexin system, and thereby a disproportionate increase in EGP (Chapter 6).
Melanin-concentrating hormone (MCH)
MCH is a cyclic 19-amino-acid polypeptide the expression of which is limited to the
lateral hypothalamus, zona incerta and perifornical area, very similar to orexin. However, despite the almost complete overlap in their distribution, the two peptides do
not co-localize. The MCH neurons have been implicated as an additional important
regulator of food intake, because the central administration of MCH promotes feeding, MCH mRNA levels rise as a result of starvation and leptin deficiency, knock-out
animals are hypophagic and lean 506, 685, 686, and MCH neurons are essential for the
leptin-deficient phenotype 687. Also over expression of MCH results in hyperglycemia
688
. Despite these earlier observations, we found no effect on glucose metabolism of
either i.c.v. administered MCH in wild type rats (Chapter 6) or of the MCH knock-out
in the MCH knock-out rat (Chapter 7). In fact, the reduced metabolic rate we found
in the MCH knock-out rats was perfectly adapted to the leaner body composition of
these animals. Of course, these data do not exclude a role for MCH in glucose metabolism; however, apparently at present we have not been able to find the right stimulus
to reveal its function in glucose homeostasis.
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general discussion
Pituitary adenylate cyclase activating peptide (PACAP)
PACAP is a 38-amino acid, C-terminally α-amidated neuropeptide, that was originally
isolated from the ovine hypothalamus on the basis of its ability to stimulate adenyl
cyclase activity in rat anterior pituitary cells 589. Studies conducted in rodents have
shown that PACAP exerts a wide array of biological activities both in the CNS and
in peripheral organs. Again the results from knock-out studies indicated the involvement of PACAP in glucose metabolism. However, these studies did not reveal which
part of the metabolic phenotype could be attributed to central signaling pathways of
PACAP, although some evidence for central effects on energy metabolism was available. Amongst others it has been shown that in the brain PACAP decreases food intake
689, 690
and increases plasma glucose 603. The data presented in Chapter 8 clearly show
that i.c.v. administered PACAP causes a strong increase of EGP. The additional experiments described in Chapter 8 provide strong evidence that also the effects of PACAP
are mediated through the pre-autonomic neurons in the hypothalamus. Contrary to
the neuropeptidergic systems discussed above, PACAP-producing neurons do not
show a restricted localization, but are widespread throughout the CNS. Prominent
populations of PACAP neurons can be found in the ARC and the VMH, but the PACAP innervation in the PVN is also derived from other sources such as the brainstem
and the BNST. Since, at present only little is known about the stimuli that modulate
PACAP release, it is not clear yet what the physiological function of PACAP could be.
In Chapter 8 we speculate that it could be involved in the counter-regulatory response
to hypoglycemia, but it could also be involved in the hyperglycemic stress response or
in the effects of estrogen on glucose metabolism.
Glucagon-like peptide 1 (GLP-1)
GLP-1 is preproglucagon-derived hormone that is secreted from the L-cells in the distal
gut in response to meals and is known to decrease food intake in rodents and humans
691, 692
. In addition, GLP-1 also serves as an incretin as it potently augments the release
of insulin during food intake 140. The anorectic effects of GLP-1 are probably mediated
through both peripheral and central mechanisms, as a population of GLP-1 positive
neurons is located in the brainstem and projects to hypothalamic and brainstem areas
important in the control of energy homeostasis 693, 694. GLP-1 is also involved in glucose
metabolism and may lower plasma glucose levels through multiple mechanisms 695,
including central mechanisms. First, Knauf et al 696 demonstrated that during hyperglycemia i.c.v. administered GLP-1 decreases non-insulin-dependent muscle glucose
uptake. Although the hypothalamic GLP-1 projections from the brainstem target both
the PVN and the ARC 693, it was shown that direct administration of GLP-1 in the
ARC, but not in the PVN, reduces EGP 135. On the other hand, GLP-1 administration
in the PVN causes a decrease in food intake. Interestingly, GLP-1 receptor mRNA is
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general discussion
also expressed in ~70% of the ARC-POMC neurons. These data seem to suggest that
both central and peripheral GLP-1 can work synergistically to regulate food intake and
glucose homeostasis. Moreover, they provide a nice example of how the same molecule can work in the periphery as a hormone, and in the CNS as a neurotransmitter.
Interestingly, the results of the dexamethasone infusions described in Chapter 9
show a similar differentiation of the function of PVN and ARC in glucose metabolism.
Dexamethasone administration in the ARC, but not in the PVN, decreases hepatic
insulin sensitivity. One obvious difference between NPY, orexin and PACAP at the
one hand, and GLP-1 and dexamethasone at the other hand, is of course that the first
three are (hypothalamic) neurotransmitters that serve as an afferent input to the PVN
from other brain areas (amongst which probably the ARC), whereas the latter two are
(agonists of) circulating factors acting on the ARC via the systemic circulation. In fact,
the PACAP, NPY or orexin might be involved in signaling the effects of peripheral
changes in GLP-1 or glucocorticoids via the ARC to the PVN.
Liver perspectives
Most of the neuropeptides just discussed regarding their role in the control of EGP
share a common effective hypothalamic area, the PVN, although not for all of them it
has been proven yet that they regulate glucose metabolism specifically via the PVN.
But, in our studies and studies of others, central administration of orexin-A (Chapter
6), PACAP-38 (Chapter 8), NPY 697 and synthetic MC3R and MC4R agonist 698 are all
associated with Fos immunoreactivity in this nucleus. Moreover, for the PACAP-38
induced Fos-ir neurons in the PVN we have shown that they project to the sympathetic
pre-ganglionic neurons in the spinal cord. Since some of these peptides are orexigenic
(orexin, NPY, MCH), while others (POMC, PACAP) are anorexigenic, this suggests
that the mechanism of feeding regulation is separated from that of glucoregulation.
Secondly, sympathetic and parasympathetic pre-autonomic neurons in the PVN are
separated 699; this brings about the question, whether the neuropeptidergic effects we
just described can be categorized into two groups, depending on their specific effects
on either sympathetic or parasympathetic output pathways. In our studies, the orexinA and PACAP-38 induced hyperglycemia can only be blocked by hepatic sympathetic
but not parasympathetic denervation. Also in the case of NPY, although it does not
influence basal glucose turnover, the suppressive effect on hepatic insulin sensitivity
is only blocked by hepatic sympathetic denervation. On the other hand, it has been
shown that insulin and leptin signaling in ARC influence hepatic insulin sensitivity
also via the vagal nerves, supposedly via another type of neurotransmission from the
ARC (to the PVN) to influence pre-autonomic neurons in the hypothalamus. Clearly,
further studies combining neuroanatomy and physiology are necessary to reveal this
“parasympathetic pathway”.
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general discussion
Clinical implications
Obesity, insulin resistance and type 2 diabetes represent a primary health and economic threat for modern societies. How obesity interferes with glucose metabolism is
still matter of debate, but it is clear from the above that disorders in autonomic nervous activity or hypothalamic neuropeptidergic signaling may contribute in a major
way to hepatic insulin resistance. Future pharmacologic treatments therefore could
aim to restore the neuropeptidergic milieu of the hypothalamus or the balance of the
hypothalamic outputs to the sympathetic and parasympathetic branch of the autonomic nervous system.
190
Summary
This thesis deals with the role of the central nervous system in two different aspects of
glucose homeostasis. In chapters 3-5, experiments are described that investigated the
question how the mammalian biological clock, located in the suprachiasmatic nuclei
(SCN) of the anterior hypothalamus, keeps itself informed about the metabolic status
of an organism. Chapters 6-10 involve experiments that were aimed at revealing (part
of) the hypothalamic brain areas and neurotransmitter systems that are in control of
glucose production by the liver. The dual interest of this thesis is already visible in the
Introduction. First we review the history and current knowledge on the role of the
autonomic liver innervation in the control of glucose and lipid metabolism (Chapter 1)
and, secondly, we give an overview of the output mechanisms used by the mammalian
biological clock to control hormonal and metabolic day/night rhythms (Chapter 2).
The search for the neuro-anatomical pathways that provide metabolic (feedback) information to the biological clock is described in Chapters 3-5 of this thesis. In Chapter
3, we describe in detail the efferent projections of the so-called “window-of-the-brain”
located in the hypothalamic arcuate nucleus (ARC). This study showed that the ARC
has direct projections to the SCN, that the projecting neurons mainly express agoutirelated peptide (AGRP), and that these SCN-projecting ARC neurons are sensitive to
circulating ghrelin. In Chapter 4 we provide further functional evidence for the relevance of this ARC–SCN connection. Normally light exposure during the dark period
will activate SCN neurons. However, when during the nocturnal light exposure ARC
neurons are activated by a peripheral injection of ghrelin, i.e., the hormone related
the preparation for a meal, the light-induced activation of SCN neurons is prevented.
Combining these physiological experiments with the neuro-anatomical evidence from
Chapter-3 indicates that AGRP-containing neurons in the ARC are the most likely
candidates to transmit the information from an increase in circulating ghrelin levels
to the SCN. Chapter 5 provides the first evidence for an additional pathway for the
SCN to receive metabolic (feedback) information via the dorsomedial hypothalamus
(DMH). We report a new hypothalamic neuronal input to the SCN, i.e., by way of
the neuropeptide FF (NPFF)-containing neurons in the DMH. This NPFF projection
is believed to play an important role in regulating food anticipatory behavior, i.e., by
virtue of the inhibitory effect of NPFF on neuronal activity in the SCN, animals may
be able to wake up in the middle of their sleep and prepare for a meal at this extraordinary time of day.
Together these data indicate that by means of the ARC and the DMH the biological clock is able to receive feedback information about the daily rhythms it induces
in metabolic hormones such as, insulin, leptin and ghrelin. By way of this feedback
191
information the SCN can adjust its timely output to its target areas and consequently
balance, amongst others, energy intake and energy expenditure.
Chapters 6-10 of the thesis describe our search for the hypothalamic pathways that
are in control of hepatic glucose production. Clearly these data support the highly
differentiated organization of the hypothalamus. In Chapters 6 and 7, we studied the
possible involvement of two transmitters located in the lateral hypothalamus, that have
recently been shown by others to be involved in the control of energy metabolism, i.e.,
the neuropeptides orexin and melanin-concentration hormone (MCH). Our experiments show that activation of the perifornical orexin system during the sleep period of
the rats increases hepatic glucose production. Within the perifornical area the MCH
neurons are intermingled with the orexin neurons. Although we found no evidence
for the involvement of MCH neurons during the sleep period in the control of either
hepatic glucose production or glucose uptake (Chapter 6), we did see that MCHknockout rats had a lower basal glucose turnover (Chapter 7). Probably this peptide
uses other mechanisms to exert its influence on glucose homeostasis. In Chapter 8
we investigated another neuropeptide that is abundantly expressed in the hypothalamus, i.e., pituitary adenyl cyclase-activating polypeptide (PACAP). Just as for orexin
and MCH, also in the case of PACAP, experiments with knock-out mice produced a
clear metabolic phenotype. Our experiments showed that at least part of this metabolic phenotype can be attributed to the hypothalamic effects of PACAP on glucose
metabolism, as the intracerebroventricular (i.c.v.) administration of PACAP caused a
pronounced increase in hepatic glucose production. By combining the i.c.v. administration of orexin and PACAP with a liver-specific denervation of either the sympathetic
or the parasympathetic autonomic input to the liver, we found that orexin and PACAP
“use” the pre-autonomic neurons in the hypothalamus to modulate hepatic insulin
sensitivity and glucose production. It is not clear yet under which physiological conditions these neuropeptidergic systems are activated, but we propose that the orexin
system may be an important target for both the SCN and the ARC to mediate their
effects on glucose homeostasis, whereas the PACAP innervation to the PVN might
be activated by stimuli such as hypoglycemia, stress and sex hormones. In Chapter
9 we describe the site-specific effects within the hypothalamus of the activation of
glucocorticoid receptor signaling on glucose homeostasis. By way of retrodialysis, the
glucocorticoid receptor agonist dexamethasone (Dex) was administered into either
the ARC or the PVN. We found that an activation of glucocorticoid signaling in the
ARC caused hepatic insulin resistance, whereas administration of the same amount
of Dex in the PVN had no such effect.
Together, these studies provide clear evidence that different hypothalamic nuclei can
regulate different aspects of glucose metabolism and that hypothalamic neuropepides
are important for the maintenance of glucose homeostasis. These data also support
192
the idea that a dis-functioning of these hypothalamic peptide systems can be one of
the mechanisms behind brain-induced insulin resistance, which appears to be one of
the major pathophysiological mechanisms in type 2 diabetes.
In the Discussion, we draw several conclusions but also raise a number of new questions. First of all, we conclude that besides the possible direct action of leptin, ghrelin
and glucose in the SCN, a large part of the metabolic feedback information to SCN
is derived from ARC and DMH where the information has already been integrated
with other information. An important remaining question is how metabolic sensing
information is processed in brain areas outside the hypothalamus. For instance, how
does metabolic information reach the limbic system and cortex to influence emotion
and cognition?
Comparing the pathways utilized by the SCN and the ARC to control peripheral
glucose metabolism, we conclude that various neuropeptidergic systems are involved
in the hypothalamic control of the autonomic output pathways, either sympathetic
or parasympathetic. This fits with the concept that via the autonomic nervous system
the brain has an elegant mechanism to balance catabolism and anabolism. However,
which particular neuropeptidergic signals in these pathways are responsible for the
control of the sympathetic and parasympathetic branch, or for the control of liver gluconeogenesis or glycogenolysis is still an open question. But certainly this knowledge
will contribute to our understanding of the role played by brain in the development
of diabetes mellitus.
193
Samenvatting
Dit proefschrift gaat over de rol van het centraal zenuwstelsel bij twee verschillende
aspecten van glucose homeostase. In Hoofdstukken 3-5 worden experimenten beschreven waarmee de vraag werd onderzocht hoe de biologische klok van zoogdieren,
die gelokaliseerd is in de suprachiasmatische kern (SCN) in het voorste deel van de
hypothalamus, informatie ontvangt met betrekking tot de metabole status van het
organisme. Hoofdstukken 6-10 gaan over experimenten die werden uitgevoerd met
het doel om gebieden en neurotransmittersystemen te identificeren in de hypothalamus die de productie van glucose door de lever controleren. De aandacht voor deze
twee aspecten wordt in het proefschrift reeds duidelijk in de Inleiding. In Hoofdstuk 1
wordt een overzicht gegeven van de geschiedenis en de huidige kennis van de rol van
de autonome innervatie van de lever bij de regulering van het glucose- en vetmetabolisme. Hoofdstuk 2 geeft een overzicht van de output-mechanismen die gebruikt
worden door de biologische klok van zoogdieren om hormonale en metabole dag/
nacht-ritmes te reguleren.
De zoektocht naar de neuro-anatomische routes die metabole (feedback) informatie
leveren aan de biologisch klok wordt beschreven in Hoofdstukken 3-5. Hoofdstuk 3
beschrijft in detail de efferente projecties van het zogenaamde ‘venster van de hersenen’, gelokaliseerd in de nucleus arcuatus (ARC). Deze studie toonde aan dat de
ARC directe projecties heeft naar de SCN, dat de projecterende neuronen voornamelijk agouti-gerelateerd peptide (AGRP) tot expressie brengen en dat deze SCNprojecterende ARC neuronen gevoelig zijn voor ghreline uit de circulatie. Hoofdstuk
4 beschrijft additioneel functioneel bewijs voor de relevantie van de ARC-SCN connectie. Normaliter zal blootstelling aan licht tijdens de donkerperiode SCN neuronen
activeren. Echter, wanneer gedurende de nachtelijke blootstelling aan licht de ARC
neuronen worden geactiveerd door de perifere toediening van ghreline, het hormoon
dat is gerelateerd aan de voorbereiding op een maaltijd, dan wordt de lichtgeïnduceerde activering van SCN neuronen voorkomen. Deze fysiologische experimenten
gecombineerd met de neuro-anatomische evidentie uit Hoofdstuk 3 geven aan dat
AGRP-bevattende neuronen in de ARC de meest waarschijnlijke kandidaten zijn voor
het overbrengen van de boodschap van verhoogde ghreline spiegels in de circulatie
aan de SCN. Hoofdstuk 5 levert de eerste evidentie voor een additionele route voor
de SCN om metabole (feedback) informatie te ontvangen en wel via het kerngebied
genaamd de dorsomediale hypothalamus (DMH). Wij rapporteren een nieuwe neuronale input naar de SCN afkomstig van neuropeptide FF (NPFF)-bevattende neuronen
in de DMH. Deze NPFF projectie wordt verondersteld een belangrijke rol te spelen in
de regulering van het anticiperend gedrag voor een maaltijd. Dankzij het remmende
194
effect van NPFF op de neuronale activiteit in de SCN zijn dieren in staat om wakker
te worden middenin hun slaap en zich voor te bereiden op een maaltijd op een oneigenlijk tijdtip gedurende hun slaapperiode.
Gezamenlijk geven deze data aan dat via de ARC en de DMH de biologisch klok
instaat is om feedback informatie te ontvangen over de dagelijkse ritmes die het zelf
induceert in metabole hormonen zoals insuline, leptine en ghreline. Door middel van
deze feedback informatie kan de SCN de output naar zijn doelgebieden aanpassen en
hierdoor, samen met andere informatie, een balans aanbrengen in de inname en het
gebruik van energie.
Hoofdstukken 6-10 beschrijven de zoektocht naar de neuronale routes waarlangs
de hypothalamus de productie van glucose door de lever kan controleren. De gegevens laten zien dat de organisatie van de hypothalamus zeer gedifferentieerd is. In de
Hoofdstukken 6 en 7 onderzoeken we de mogelijke betrokkenheid van 2 neurotransmitters die geproduceerd worden in het laterale deel van de hypothalamus: orexine
en melanine-concentrerend hormoon (MCH). Eerder was reeds aangetoond dat deze
neurotransmitters betrokken zijn bij de controle van het energie metabolisme. Onze
experimenten laten zien dat de activering van het perifornicale orexine systeem tijdens de slaapperiode in ratten een toename in de glucose productie door de lever
veroorzaakt. In dit perifornicale gebied zijn de MCH neuronen vermengd met orexine
neuronen. We vonden echter geen aanwijzingen voor de betrokkenheid van MCH
neuronen bij productie van glucose door de lever, nog de glucose opname, tijdens
de slaapperiode (Hoofdstuk 6). Wel zagen we dat MCH-knockout ratten een lagere
basale glucose turnover hadden (Hoofdstuk 7). Mogelijk worden door dit peptide
andere mechanismen gebruikt om de glucose huishouding te beïnvloeden. In Hoofdstuk 8 onderzochten we een ander neuropeptide dat uitbundig tot expressie komt in
de hypothalamus: hypofyse adenyl cyclase-activerend polypeptide (PACAP). Net als
geldt voor orexine- en MCH-knockout muizen vertonen ook PACAP-knockout muizen een duidelijk metabool fenotype. Onze experimenten toonden aan dat tenminste
een deel van dit fenotype kan worden toegeschreven aan de hypothalame effecten
van PACAP op het glucose metabolisme. Intracerebroventriculaire (i.c.v.) toediening
van PACAP veroorzaakt namelijk een sterke toename van de glucoseproductie door
de lever. Door de i.c.v. toediening van orexine en PACAP te combineren met leverspecifieke denervatie van of de sympathische of de parasympathische innervatie van de
lever vonden we dat orexine en PACAP ‘gebruikmaken’ van pre-autonome neuronen
in de hypothalamus om de insuline-gevoeligheid en de glucoseproductie van de lever
te moduleren. Het is nog niet duidelijk onder welke fysiologische omstandigheden
deze neuropeptiderge systemen worden geactiveerd, maar we veronderstellen dat
het orexine systeem een belangrijk doelwit is van zowel de SCN als de ARC om hun
invloed op de glucose huishouding uit te oefenen, terwijl de PACAP innervatie van
195
de PVN geactiveerd zou kunnen worden door stimuli zoals hypoglycaemie, stress en
geslachtshormonen. In Hoofdstuk 9 beschrijven we de effecten van activatie van de
glucocorticoïde receptor signalering op specifieke plaatsen in de hypothalamus op de
glucose homeostase. Door middel van retrodialyse werd de glucocorticoïde receptor
agonist dexamethason (Dex) toegediend in of de ARC of de PVN. Toediening in
de ARC veroorzaakte insulineresistentie in de lever terwijl toediening van eenzelfde
hoeveelheid Dex in de PVN niet een dergelijk effect had.
Gezamenlijk tonen deze studies duidelijk aan dat verschillende kerngebieden in de
hypothalamus verschillende aspecten van het glucose metabolisme kunnen reguleren
en dat de peptiderge neurotransmitters in de hypothalamus een belangrijke rol kunnen
spelen in het handhaven van glucose homeostase. Deze gegevens ondersteunen ook
de idee dat een dysfunctie van bepaalde peptide-systemen in de hypothalamus een
van de mechanismen zou kunnen zijn bij hersen-geïnduceerde insulineresistentie, één
van de belangrijkste pathofysiologische mechanismen bij type 2 diabetes.
In de discussie trekken we verschillende conclusies maar worden ook een aantal
nieuwe vragen opgeworpen. Ten eerste concluderen we dat naast de mogelijke directe
werking van leptine, ghreline en glucose op de SCN, een groot deel van de metabole
feedback informatie naar de SCN afkomstig is vanuit de ARC en de DMH. De toegevoegde waarde van deze extra route is de integratie met andere informatie die in
de ARC en DMH plaatvindt. Een resterende vraag is hoe metabole informatie wordt
verwerkt in hersengebieden buiten de hypothalamus. Hoe worden bijvoorbeeld het
limbische systeem en de cortex bereikt zodat metabole informatie ook een effect kan
hebben op emotie en cognitie?
Uit het vergelijken van de routes die gebruikt worden door de SCN en de ARC
om het perifere glucosemetabolisme te controleren concluderen we dat verschillende
neuropeptiderge systemen van invloed zijn op de hypothalame aansturing van het
autonome zenuwstelsel, hetzij sympathisch, hetzij parasympatisch. Dit past bij het
concept dat de hersenen middels het autonome zenuwstelsel een elegant mechanisme
hebben om een homeostatische balans aan te brengen tussen katabolisme en ana­
bolisme. Resterende vragen zijn onder andere welke specifieke neuropeptiderge signalen in deze routes verantwoordelijk zijn voor de controle van de sympatische danwel
parasympathische activiteit, en welke voor de controle van de gluconeogenese en de
glycogenolyse in de lever. Deze kennis zal bijdragen aan een beter begrip met betrekking tot de rol die de hersenen spelen bij het ontstaan van diabetes mellitus.
196
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232
Authors
Andries Kalsbeek Hypothalamic Integration Mechanisms, Netherlands Institute for
Neuroscience; Department of Endocrinology and Metabolism, Academic Medical
Center (AMC), University of Amsterdam, The Netherlands
Anneke Alkemade Department of Endocrinology and Metabolism, Academic Medical Center (AMC), University of Amsterdam, The Netherlands
Bart A. Ellenbroek Department of Cognitive Neuroscience, Psychoneuropharmacology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
Carolina Escobar Instituto Invest. Biomedicas, Universidad Nacional Autónoma de
México, México
Cathy Cailotto Division of Gastroenterology and Hepatology, Academic Medical
Center (AMC), Amsterdam, The Netherlands
Chun-Xia Yi Hypothalamic Integration Mechanisms, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
Edwin Cuppen Hubrecht Institute for Developmental Biology and Stem Cell Research & University Medical Center Utrecht, Utrecht, The Netherlands
Eric Fliers Department of Endocrinology and Metabolism, Academic Medical Center
(AMC), University of Amsterdam, The Netherlands
Etienne Challet Department of Neurobiology of Rhythms, Institute for Cellular and
Integrative Neurosciences, CNRS, Université Louis Pasteur, France
Ewout Foppen Hypothalamic Integration Mechanisms, Netherlands Institute for
Neuroscience, Amsterdam, The Netherlands
Guangfu Yin Department of Neurobiology, Tongji Medical College of Huazhong
University of Science and Technology, Hubei, China
Hans P. Sauerwein Department of Endocrinology and Metabolism, Academic Medical Center (AMC), University of Amsterdam, The Netherlands
Jack H. Jhamandas Department of Medicine (Neurology), and Centre for Alzheimer
and Neurodegenerative Research, University of Alberta, Edmonton, Alberta, T6G
2S2, Canada
Jan van der Vliet Hypothalamic Integration Mechanisms, Netherlands Institute for
Neuroscience, Amsterdam, The Netherlands
Jiapei Dai Hypothalamic Integration Mechanisms, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
Jing Shi Department of Neurobiology, Tongji Medical College of Huazhong University of Science and Technology, Hubei, China
Joram D. Mul Hubrecht Institute for Developmental Biology and Stem Cell Research
& University Medical Center Utrecht, Utrecht, The Netherlands
233
Liqiang Ru Department of Neurobiology, Tongji Medical College of Huazhong
­University of Science and Technology, Hubei, China
Manuel Angeles-Castellanos Department of Anatomy, Universidad Nacional
­Autónoma de México, Mexico
Martine C.J. van der Elst Department of Cognitive Neuroscience, Psycho­neuro­
pharmacology, Radboud University Nijmegen Medical Center, Nijmegen, The
Netherlands
Mariëtte T. Ackermans Department of Clinical Chemistry, Laboratory of Endocrinology, Academic Medical Center (AMC), University of Amsterdam, The
Netherlands
Michael Proper Hypothalamic Integration Mechanisms, Netherlands Institute for
Neuroscience, Amsterdam, The Netherlands
Mireille J. Serlie Department of Endocrinology and Metabolism, Academic Medical
Center (AMC), University of Amsterdam, The Netherlands
Ning Sun Department of Neurobiology, Tongji Medical College of Huazhong
­University of Science and Technology, Hubei, China
Paul Pévet Department of Neurobiology of Rhythms, Institute for Cellular and
­Integrative Neurosciences, CNRS, Université Louis Pasteur, France
Pim W. Toonen Hubrecht Institute for Developmental Biology and Stem Cell ­Research
& University Medical Center Utrecht, Utrecht, The Netherlands
Ruud M. Buijs Instituto de Investigaciones Biomedicas UNAM, Ciudad Universitaria,
Mexico
Susanne E. la Fleur Department of Endocrinology and Metabolism, Academic
­Medical Center (AMC), University of Amsterdam, The Netherlands
Valeri Goncharuk Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
234
Publications
1. Chun-Xia Yi, Jan van der Vliet, Jiapei Dai, Guanfu Yin, Liqiang Ru and Ruud M
Buijs. 2006. Ventromedial arcuate nucleus communicates peripheral metabolic
information to the suprachiasmatic nucleus. Endocrinology, 147:283-294.
2. Ruud M Buijs, Frank A Scheer, Felix Kreier, Chun-Xia Yi, Nico Bos, Valeri Goncharuk, Andries Kalsbeek. 2006. Organization of circadian functions: interaction
with the body. Prog Brain Res, 153:341-60.
3. Chun-Xia Yi, Etienne Challet, Paul Pévet, Andries Kalsbeek, Carolina Escobar &
Ruud M Buijs. 2008. A circulating ghrelin mimetic attenuates light-induced phase
delay of mice and light-induced Fos expression in the suprachiasmatic nucleus of
rats. Eur J Neurosci, 27:1965-1972.
4. Chun-Xia Yi, Mireille J. Serlie, Mariëtte T. Ackermans, Ewout Foppen, Ruud M.
Buijs, Hans P. Sauerwein, Eric Fliers & Andries Kalsbeek. 2009. A major role for
perifornical orexin neurons in the control of glucose metabolism. Diabetes, 2009,
58:1998-2005.
5. Chun-Xia Yi, Susanne E. la Fleur, Eric Fliers & Andries Kalsbeek. The role of liver
innervation in the control of metabolism. Biochimica et Biophysica Acta. In press.
6. Andries Kalsbeek, Chun-Xia Yi, Cathy Cailotto, Susanne E. la Fleur, Eric Fliers &
Ruud Buijs. Mammalian Clock Output Mechanisms. Essays in Biochemistry. In
press.
7. Andries Kalsbeek, Chun-Xia Yi, Susanne E. la Fleur & Eric Fliers. The hypothalamic clock and its control of glucose homeostasis. Trends in Endocrinology and
Metabolism. In press.
8. Joram D. Mul, Chun-Xia Yi, Pim W. Toonen, Martine C. van der Elst, Bart A.
Ellenbroek, Andries Kalsbeek, Susanne E. la Fleur, and Edwin Cuppen. Absence
of Pmch lowers energy homeostasis and body weight. The American Journal of
Physiology - Endocrinology and Metabolism. In press
235
9. Chun-Xia Yi, Ning Sun, Mariëtte T Ackermans, Ewout Foppen, Jing Shi, Ruud M
Buijs, Mireille J Serlie, Eric Fliers & Andries Kalsbeek. Pituitary adenylate cyclaseactivating polypeptide (PACAP) signaling to the pre-autonomic neurons of the
hypothalamic paraventricular nucleus (PVN) controls hepatic glucose. Diabetes,
under revision.
10.Chun-Xia Yi, Jan van der Vliet, Michael Proper, Manuel Angeles-Castellanos,
Valeri Goncharuk, Jack H.Jhamandas, Andries Kalsbeek, Carolina Escobar & Ruud
M.Buijs. Dorsomedial hypothalamic neuropeptide FF neurons project to the retinal
termination site of the suprachiasmatic nucleus. Submitted.
11. Chun-Xia Yi, Ewout Foppen, Mireille J. Serlie, Ruud M. Buijs, Eric Fliers & Andries
Kalsbeek. Glucocorticoid signaling in the arcuate nucleus is involved in the control
of hepatic insulin sensitivity. In preparation.
12.Mirjam Langeveld, Sjoerd van den Berg, Nora Bijl, Silvia Bijland, Cindy PAA van
Roomen, Judith HPM Houben-Weerts, Roelof Ottenhoff, Sander M Houten, Andries Kalsbeek, Chun-Xia Yi, Albert K Groen, Johannes MFG Aerts & Peter J
Voshol. Treatment of genetically obese (ob/ob) mice with the iminosugar N-(5adamantane-1-yl-methoxy-pentyl)-deoxynojirimycin (AMP-DNM) acutely increases fat oxidation and decreases food intake. Submitted.
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Acknowledgements
My thesis is the result of six years of research that has been done as a visiting student and later work as a PhD student in the Hypothalamic Integration Mechanisms
group. I have worked with a great number of people who have contributed in assorted
ways to my research. It is a pleasure to convey my gratitude to them in my humble
acknowledgments.
First and foremost I offer my sincerest gratitude to my supervisor, Dr. Andries
Kalsbeek. Dear Dries, your knowledge, guidance, support and patience enable me to
develop an understanding of my PhD project, and gave me the opportunity to work in
my Chinese way. Your truly scientific intuition has inspired and enriched my growth
as a researcher. After years of your training, I learned to look at the curves and bars of
glucose metabolism as they are ‘alive’. Although you are one of the quietest scientists,
your quietness has very a powerful meaning to me: passions in science do not need to
be always very loud and noisy. Thank you for shaping me up to become a researcher.
I own my deepest gratitude to my promoters, Prof. dr. Eric Fliers and Prof. dr. Ruud
Buijs, you both made wonderful support to me in so many different ways.
Dear Eric, your wisdom and kind smiling are the best support for all your students
and the best treatment for all your patients! You did much more for me than simply being my promoter. I am indebted to many of your inspiring suggestions to my research
and my writing (not only for thesis but also for other ‘writing for survive’). Each time
when I was running into your room to ask for your help, you always said ‘why not sit
down first’, and then you start to deal with my problems. I appreciate very much this
magic ‘calming-down procedure’, and I realize (step by step) that actually most of the
‘urgent things’ can be better done in a more peaceful and efficient way. I learned not
to ‘run’ but to ‘walk’ to the destination, to avoid unnecessary mistakes generated by
my ‘big hurry’.
Dear Ruud, I have benefited so much from your training on morphology. If I have
a chance to train a student to be a neuroscientist, I will definitely start with histochemistry, because I felt so much motivation to continue when I saw those beautifully
stained neurons labeled by tracer: you can read their history in the brain. After you
left to Mexico, I am still insisting on combining morphology with physiology, and I
hope people appreciate our data more than usual with this combination. A second
important thing you taught me is criticizing any hypothesis we generated. I also like
to ask ‘why’ more often when I face a hypothesis, because we will never lose our
direction if we know very well why we start a project and many failures will become
less disappointing. Thanks for telling me everything I needed to know as a beginner.
I wish you have a wonderful time in Mexico.
237
Special thanks to Prof. dr. Hans Sauerwein and Dr. Mireille Serlie. Dear Hans, I
should be more patient to teach you to speak Chinese: you deserve it because of
your great knowledge to help me to understand the ‘metabolism’. Dear Mireille, my
co-promoter, many thanks for your valuable advice, your precious time to read my
manuscript and your critical comments. I have benefited a lot from all the advice and
the kind support from everybody from the Department of Endocrinology & Metabolism in AMC, Peter and Maarten, thanks for the discussions. Marlies and Birgit, thank
for your kind help.
I am grateful to Dr. Mariëtte Ackermans and the Department of Clinical Chemistry, Lab Endocrinology in AMC who have provided me the support and equipment I
needed to produce and complete my thesis. Dear Mariëtte, thanks for your excellent
support and all the education to get our beautiful data. I promise in my future work,
I will also keep in mind all the laboratory rules you have taught me. Dear An, thanks
for kindly helping me to handle all the daily problems in the lab and your supervision.
Yvette and Cecilia, thanks for your technical support.
Dear Susanne, in the past six years, I don’t remember how many times I have read
and cited your articles. Thank you so much for your advice and inspiration. You are a
real example for me in my scientific adventure.
It is an honor for me to thank Prof. dr. Dick Swaab. Dear Dick, in China, I should call
you our grand-supervisor. Thank for the wisdom you spread in the air of this institute
as well as in the public. In those dark days made by the depressive Dutch weather or
by bad data, your waving hand from the distance certainly brought sunlight to me. ­I
hope you didn’t mind to be bothered by my unintelligent questions about the brain.
This thesis would not have been possible unless everybody in our group created a
pleasant working atmosphere. Ewout, Jan, Nico and Caroline, you are the best technicians I have known, I think every student owns your excellent technical training and
help. Dear Ewout, thanks to be my paranymph, our daily march to the coffee machine
and discussions were the best emotional support to my research and thesis. Thanks for
your sparkling technical suggestions to my work. Dear Jan, although you are not working with us anymore, you remain for me the first teacher in my ‘Journey in the brain’.
It is never too late to find a true friendship. Six years ago, when I came here, I heard
people talking about Anneke Alkemade, an excellent PhD student with a powerful
Dutch mind. I have showed only once my appreciation to her beautiful confocal images
from postmortem human brain tissue. Now, six years later, Dr Alkemade is working
as a postdoc with us, and offers me great friendship by being my paranymph. Dear
Anneke, it is a great pleasure to work with you, I wish you can tell me more about human brain before I leave. ‘Fantastic Felix’, long long ago, when I was alone in the lab,
you arrived from the sky and brought me to numerous places outside the lab. I cannot
remember them all anymore. You brought me to the beach (in an almost broken car), I
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think that was the first time I saw the sea, and to a church, that might be also the first
time I was in a church. Thank you for taking care of me like a big brother. You are one
of the most intelligent persons I have met; I still don’t know how you can shift from a
computer man to a pediatrician. Dear Cathy, in the first years, you and Marie Laure
influenced me so much, that finally someone was surprised by my English with a heavy
French accent, thanks for your generous help in these years. Lars, thanks for accompanying me in tackling all those problems in animal studies. Marieke, Ajda and all others,
thanks for your kind and generous help in my first years in the lab. Elodie and Eveline,
thanks for keeping me warm and active by sitting on two sides of me, Elodie, thanks
for all your fashion advice, shopping with you is always my festival. Rianne, thanks
for the ‘toeter’ you bought for me, it is my first Dutch toy. José, Charlene, Barbara,
Joan, Clementine, Anke and Lesly, good luck to your work. Cathalijn, Nico and Els,
wish you good luck with your ‘coming soon’ thesis. Matthijs and Ruud, thank for your
help. ­Yinghui, Jun Lei, Ning Sun, Li Zhao, Ji Liu, Lei Pei, Ling Shan, Xin-Rui Qi, Juan
Zhao, Tian Zhou and Shanshan Wang, Sabina, Alicia, Thijs, I wish you lots of success.
I can not imagine how a PhD student can survive without the help from the supporting groups in the institute. Dear Chris and Nanneke (DEC), I appreciate very much all
your advice and the supervision of my animal studies; your efforts have improved my
animal handling skills. Chris, also thanks for writing the cell counting program, which
is a great contribution to all my publications. For the cell counting and image collection
and analysis, I also want to thank the great help from Joop van Heerikhuize. Dear Joop,
you are the happiest person I know because of your daily cheerful laughing. Although
I am a bit clumsy to follow the image analysis programs you made, and always ask for
your help, the photos we produced are very much appreciated by the journals. In my
future working places, I hope I can find a similar place we have in the institute: the mechanics department. Dear Rinus, Ruud and Martin, thank for the all the excellent technical supports, it is amazing how beautiful the small things you made for our research.
Adriaan, Maarten, Marcel and Dirk (‘the supermen’), thanks for keeping my computer
working. Each time when I thought I lost my data, you could help me to find them.
People from other research groups have also offered me great help, Corbert, Ronald
and Valerie, I wish I can learn more from you to improve my research skills, thank for
all the kind help and knowledge which is definitely only available from seniors. Arja,
Rawien, Unga, Jasper and Barbara, thanks for your help. Dear Bart, it was very wise
of you to give up smoking, not only for yourself. Your health is vital for every foreign
student who does not want to sleep in the Church. Thanks for helping me to settle
down at the beginning.
Although I have never worked in Strasbourgh, my thesis got essential support from
the French chronobiologists Prof.dr. Paul Pévet and Dr. Etienne Challet, Dear Paul
and Etienne, although I am not always focusing on chronobiology, the knowledge I
239
got will be kept in my mind and will be brought back now and then, because I still
consider the biological clock as the most mysterious thing in this world. I wish I will
have a chance to work with you in the future.
I wish to thank everybody at the other side of the world: Mexico. Dear Carolina,
thanks for allowing me to work in your lab as well as staying with you and enjoying your charm, elegance and intelligence. Manuel Angeles, Mari Carmen Miñana,
­Roberto Salgado, Oscar Rodriguez, Hans Viloria and Katia Rodriguez, I enjoyed very
much your friendship as hot as Mexican chili. Dear Daniela and Nadia, I wish you a
lot of success.
Dear Joram, Pim, Edwin and others, thanks for all the fun we had while working
together in Hubrecht laboratory. Surgery on knock-out rats is not an easy job, but I
enjoy it very much. Joram, I wish you lots of success with finishing your thesis and
finding a beautiful postdoc job.
The people who work in the animal facility have provided essential support in my
daily work. Jilles, wij promovendi zijn ons misschien niet altijd bewust van het belang
van de dagelijkse verzorging van de proefdieren. Wij weten echter dat wanneer het
in de dierverblijven een puinzooi is, dit komt door jouw afwezigheid. Ik schrijf dit in
het Nederlands omdat jij nooit Engels tegen mij sprak en mij daardoor dwong mijn
povere Nederlands te oefenen, bedankt voor je ‘Dutch effort’.
Wilma, thank you for polishing my English, I realize that sooner or later, I have to
handle my Chinese English without your help, so for the first time, I tried to write
this acknowledgement without your polishing. Heidi and Ernita, thank you for taking care of my ‘Chinese’ problems. Same thanks to Tini for helping me with the thesis
and other unnoticeable but essential things. Marcia and Wil, thanks for the pleasant
reception work, Marcia, I wish I can explain to you more about your questions about
China and Chinese.
Dear Hans, my ‘supervisor at home’, it is impossible for me to finish the thesis without you, thank for your truly persistent support for my study. Nobody else can do the
same things you did for me: taking me to work on rainy days and picking me up at
midnight because of the chronobiology studies, cooking delicious food everyday and
keeping it warm till I am home, making our garden beautiful to compete with the
neighbours, and sharing numerous moments with interesting scientific stories and
beautiful nature.
Lieve Ko en Dieuwertje, ik ben jullie ontzettend dankbaar voor alle liefde.
亲爱的爸爸妈妈, 感谢你们的养育之恩, 特别感谢爸爸为我设计的论文封面。
希望你们天天快乐,祝你们健康长寿。
240

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