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J Neurosci. Author manuscript; available in PMC 2009 March 3.
Published in final edited form as:
PMCID: PMC2650686
EMSID: UKMS3992

Novel leptin-regulated genes revealed by transcriptional profiling of the hypothalamic paraventricular nucleus

Abstract

Leptin plays a major role in coordinating the integrated response of the central nervous system to changes in nutritional state. Neurons within the paraventricular nucleus (PVN) of the hypothalamus express leptin receptors and receive dense innervation from leptin receptor-expressing neurons in the arcuate nucleus. In order to obtain new insights into the effects of circulating leptin on PVN function, we compared global transcriptional profiles of laser-captured PVN from ad libitum fed mice versus 48 hour fasted mice receiving either sham or leptin treatment intraperitoneally (i.p.).

527 PVN-expressed genes were altered by fasting in a manner which was at least partially reversible by leptin. Consistent with previous reports, thyrotrophin releasing hormone mRNA levels were decreased by fasting but restored to fed levels with leptin treatment. mRNA levels of oxytocin, vasopressin and somatostatin were also reduced by fasting and restored by leptin. Given leptin’s known effects on synaptic remodelling it is notable that among the top fifteen genes that were positively regulated by leptin were five that have been implicated in synaptic function and/or plasticity (basigin, ApoE, Gap43, Gabarap and synuclein-γ). Pathway analysis identified Oxidative Phosphorylation (OXPHOS), in particular, genes encoding complex 1 proteins that play a role in ubiquinone biosynthesis, to be the predominant gene set that was significantly regulated in a leptin dependent manner. Thus, in addition to its effects on the expression of a broad range of neuropeptides, leptin may also exert more general influences on synaptic function in, and the bioenergetic state of, the PVN.

Keywords: leptin, fasting, laser capture microdissection, hypothalamus, paraventricular nucleus, microarray, gene

Introduction

Leptin is an adipocyte-derived hormone that plays a critical role in energy homeostasis. Circulating concentrations of leptin mirror fat cell stores, being increased in overfeeding but decreased with prolonged fasting. Robust data indicate that leptin acts primarily through the central nervous system (CNS) to regulate food intake and energy expenditure (reviewed by (Coll et al., 2007; Oswal and Yeo, 2007)). Within the CNS, the hypothalamus in particular is recognized to receive and integrate neural, metabolic and humoral signals from the periphery. The hypothalamus is a heterogeneous region encompassing a number of anatomically discrete nuclei. For example, the arcuate nucleus (Arc) contains two distinct neuronal populations expressing either neuropeptides Y (NPY) and agouti-related peptide (AgRP) or pro-opiomelanocortin (POMC) and cocaine and amphetamine related transcript (CART). Both express the long form of the leptin receptor (ObRb) and are considered to be key first order neurons through which leptin exerts its effects.

Another important hypothalamic region involved in energy homeostasis is the paraventricular nucleus (PVN). In addition to containing neurons which themselves express ObRb, the PVN receives dense innervation from leptin receptor-expressing neurons in the Arc thereby allowing leptin to both directly and indirectly affect PVN neuronal activity. Further, not only does lesioning of the PVN in rodents bring about marked hyperphagia but also loss of a single allele of Sim1, a gene encoding a transcription factor critical for the normal development of the PVN (Michaud et al., 1998), causes obesity in both humans and mice (Holder et al., 2000; Michaud et al., 2001). Additionally, the reactivation of melanocortin 4-receptor (Mc4r) solely in the PVN completely corrects the hyperphagia found in Mc4r null mice (Balthasar et al., 2005), a well characterised obese mouse model of obesity resulting from disrupted central melanocortinergic signalling (Huszar et al., 1997).

The precise mechanisms by which changes in neuronal activity within these important hypothalamic nuclei are translated into changes in food intake and energy expenditure remains to be clearly established. In particular, the molecules and pathways that mediate leptin’s action in the PVN, either directly or indirectly via the melanocortin pathway, remain to be fully elucidated.

In this study, we have used laser capture microdissection (LCM) coupled with transcriptional profiling to gain insights into the leptin-dependent mechanisms at work within the PVN. Reasoning that genes with a physiological role in energy homeostasis are likely to be nutritionally regulated, we have identified genes in the PVN whose expression is a) altered in response to a substantial fast (a state of relative leptin deficiency) and b) restored towards ad libitum fed values with leptin treatment alone. To allow discrimination between changes in gene expression which may have occurred as a result of the stress of fasting rather than via a leptin-dependent mechanism, we have also analysed in the same animals the transcriptome of the cerebellum a brain region which does not express ObRb and has no known role in the control of energy balance.

Methods

In vivo murine studies

All animal studies were carried out in male SV 129 mice purchased from Charles River(Kent UK). Prior to all procedures animals were allowed to acclimatize for at least one week. Animals were kept at 22°C on a 12 hour light/dark cycle (lights on 0700-1900).The animals were fed on standard laboratory Chow (SDS diet) and had free access to water throughout. All mice were matched for body weight at the start of the experiment. All experimental procedures were in accordance with regulations and guidelines of the United Kingdom Home Office.

We used the protocol as described by Ahima et al (1996) for the maintenance of serum leptin levels during a fast. 10 weeks old mice were divided into three weight-matched groups (N = 4 in each group for microarray; N=8 for Taqman confirmation). Group one (fed) had ad libitum access to chow and group two (fasted) had all food removed at the onset of light cycle, remained fasted for 48 hours. Both groups received twice daily intraperitoneal (i.p.) injection of saline. Group three (fasted plus leptin) had all food removed at the onset of light cycle, remained fasted for 48 hours but received twice daily i.p. injection of recombinant murine leptin (Amgen) at a dose of 1μg/g total body weight. At the end of the experiment the body weights of ad libitum fed, fasted and fasted plus leptin mice were 28.1g ± 0.5g, 22.7g ± 0.3g, 22.9g ± 0.3 g, respectively. All animals were sacrificed by cervical dislocation 12 hours after the last injection. The brains were removed and immediately frozen on powdered dry ice and stored at -80°C until further processing.

Laser capture microdissection and total RNA isolation

Coronal sections of 14 μm thickness were prepared on a cryostat and mounted on RNase-free membrane-coated glass slides (P.A.L.M. Membrane Slides, P.A.L.M. MicrolaserTechnologies). Slides were kept in a slide box embedded in dry ice until sectioning was completed. Within 24 hours after sectioning, the frozen sections were thawed and fixed for 30 seconds in 95% ethanol, then rehydrated (75% and 50% ethanol, 30 seconds each). After fixation, the slides were stained with 1% cresyl violet for 1 min. The sections were then dehydrated in a graded ethanol series (50%, 75%, 95% and 2 × 100%, 30 seconds each) followed by Histoclear for 5 minutes. All the solutions were prepared with RNase-free water (Ambion). Laser microdissection was performed using a P.A.L.M. MicrolaserSystem (P.A.L.M. Microlaser Technologies). The hypothalamic PVN was microdissected covering the region from -0.7 to -1.22 mm caudal to bregma (37 sections) as defined by Paxinos and Franklin (2001). All evenly spaced sections were pooled to eliminate any potential rostrocaudal gene expression bias. Following each microdissection, the captured cells were kept in RNAlater (Ambion) prior to RNA isolation. Total RNA was isolated according to the manufacturer’s protocol using the RNAqueous®-Micro Kit (Ambion). Quality and quantity of the total RNA samples were determined by electrophoresis using the Agilent BioAnalyzer. Before RNA amplification the more sensitive Agilent BioAnalyzer PicoChip was used (Agilent; according to manufacturer’s instructions). To determine the RNA concentration a dilution series of a control with known concentration was run alongside the nuclei samples.

RNA amplification and Microarray hybridization

To minimise bias, isolated total RNA (n=4 per group) was subjected to two rounds of T7-based liner amplification. Briefly, RNA was primed with a T7 promoter-oligo (dT) primer and reverse transcribed to generate first stand cDNA, which was used as the template to synthesize second strand cDNA by DNA polymerase (Two-cycle cDNA Synthesis Kit, Affymetrix UK Ltd.) .The T7 RNA polymerase promoter contained by ds cDNA molecules was used, by T7 polymerase, to transcribe antisense amplified RNA (aRNA; MEGAscript T7 kit, Ambion). The aRNA was then randomly primed to make single stranded cDNA with a 3′poly A tail to serve as the template for second strand cDNA synthesis primed, as in the first round, with a T7 promoter-oligo dT primer to make ds cDNA containing a T7 promoter site. A second transcription step using T7 polymerase produced the second round of aRNA with biotin labelled ribonucletide (GeneChip IVT labeling Kit, Affymetrix). The biotin-labeled cRNA were than fragmented, the average fragment length determined using a Agilent BioAnalyzer 2100 and hybridized to Affymetrix Murine 430 2.0 oligonucleotide microarrays. The hybridized probe array is stained with streptavidin phycoerythrin conjugate and scanned on an Affymetrix GeneChip 7G scanner.

Microarray analysis

Raw image data was converted to CEL and pivot files using Affymetrix GeneChip Operating Software. All downstream analysis of microarray data was performed using GeneSpring GX 7.3 (Agilent). The pivot files were used in the GCOS analysis and the CEL files were used for both the RMA (Irizarry et al., 2003) and GCRMA (Wu et al., 2004) analyses. After importing the data, each chip was normalized to the 50th centile of the measurements taken from that chip and all gene expression data are reported as fold-change from the ‘Fed’ state. Genes were considered to be ‘leptin regulated’ if they were significantly up- or down-regulated by at least 1.5-fold in the fasted state and a.) returned to within 1.3-fold of the ‘Fed’ state with leptin treatment or b.) changed by greater than 3-fold from the fasted state with leptin treatment. Statistical analysis was performed using a one-sample Student’s t-test, looking for statistically differentially expressed genes within each condition. The test was applied to the mean of each normalized value against the baseline value of 1, where genes do not show any differential expression with respect to the control. We considered a p ≤ 0.05 to be significant. Only genes which met the above criteria using GCOS, RMA and GCRMA were taken forward for further study.

Gene Tree ‘heatmaps’ were implemented by GeneSpring GX 7.3 using Pearson Correlation for similarity measure and an average linkage clustering algorithm. Pathway analysis was performed using Ingenuity Pathway Analysis (Ingenuity Systems Inc., Redwood City, California, USA).

Quantitative PCR analysis

Quantitative PCR analysis was performed using TaqMan® Gene Expression assays on purified RNA samples. Total RNA were amplified as described for microarray but to minimize amplification variation, 2ng of isolated total RNA from each nucleus was subjected to two rounds of T7-based linear amplification. 100 ng of amplified RNA from laser capture microdissected samples were used in a random-primed first strand cDNA synthesis reaction, using superscript II reverse transcriptase (Invitrogen). The resulting first strand cDNA reaction was diluted 2.5-fold and 2 μl used in each 12 μl TaqMan® reaction. Quantitative PCR reactions were performed in triplicate on an ABI 7900HT (Applied Biosystems) and using ABI PCR master mix, according to manufacturer’s protocols. Expression results were normalized to 18s, β-actin and B2M. Quantitative PCR statistical analysis was performed using Microsoft Excel. P-value was calculated using a two-tailed distribution unpaired Student’s T-Test. Data is expressed as mean ± SEM.

Results

Validation of laser capture and of fasting/fed/leptin paradigm

To ensure the specificity of the PVN dissection (Fig 1a) within laser captured material, we examined expression of a number of genes which are only found in neighbouring hypothalamic nuclei. As expected, we were unable to detect expression of ARC- specific Agrp, VMN- specific Sf-1 and LH- specific melanin concentrating hormone (Mch) within any PVN sample (data not shown). In addition, we examined expression of the gene encoding thyrotrophin releasing hormone (TRH), a well characterised hypothalamic peptide known to be highly expressed within the parvocellular region of the PVN (Flament-Durand, 1980) and known to be nutritionally regulated in a leptin-dependent manner (Hakansson et al., 1998; Isse et al., 1999; Harris et al., 2001). Using Taqman quantitative PCR (Q-PCR) TRH mRNA was decreased by fasting in LCM PVN samples, with this effect being significantly blunted by leptin replacement (Fig 1b).

Figure 1a
Laser capture microdissection of the hypothalamic PVN
Figure 1b
Trh is nutritionally and leptin regulated in the PVN

Analysis of microarrays using three different algorithms

We proceeded to hybridize the PVN RNA samples to murine whole genome oligonucleotide arrays (Affymetrix, Santa Clara). In order to discriminate between PVN specific changes and a more generalised brain-wide response to stress of a prolonged fast, gene expression profiles were also obtained from samples of cerebellum removed from the same mice. All genes whose expression within the cerebellum was altered with fasting in a leptin-regulated manner, were excluded from further analysis (n=280).

To maintain maximum stringency and reduce the number of false positives, we analysed the data using three different algorithms: a.) GeneChip Operating Software (GCOS); b.) Robust Multiarray Average (RMA (Irizarry et al., 2003)) and c.) a variant of RMA that uses probe sequence coupled with GC-content background correction (GC-RMA (Wu et al., 2004)). Only genes whose expression patterns in each of the three analyses were identical were taken forward for further study.

The three analyses gave very different results from the same experimental data. GCOS indicated that the expression of 932 genes were down-regulated in fasting but returned towards fed levels with leptin (Fig 2a). The number of genes with this expression profile was 2214 with RMA and 1966 with GC-RMA, with only 438 genes having identical expression patterns across all three analytical platforms (Fig 2a; Supplementary Table 1). Similarly with genes upregulated by fasting but normalised with leptin GCOS, RMA and GC-RMA analyses determined that 382, 343 and 457 genes, respectively, followed this expression profile (Fig 2b). Only 89 of these genes satisfied the criterion of concordance across all three analyses (Supplementary Table 2).

Figure 2
Venn diagram comparing the three different analyses, GCOS, RMA & GCRMA

Figure 3a shows a heat-map of the 527 leptin-regulated genes, while Figures 33bb & c represents the same data by plotting the average normalized signal intensities of the leptin regulated genes from the fasted (Fig 3b) and fasted plus leptin (Fig 3c) group on the y-axes, respectively, against the Fed group on the x-axis.

Figure 3a
Heatmap of 527 leptin regulated genes
Figure 3b
Scatter plot of 527 leptin regulated genes in the fasting state
Figure 3c
Scatter plot of 527 leptin regulated genes when treated with leptin

Genes down regulated by fasting but normalised by leptin

The major effect of leptin was to restore towards normal genes whose expression levels were downregulated by fasting. Figure 4a lists the 25 transcripts that showed the largest downregulation in expression in the fasted state that were normalised by leptin. Consistent with our Q-PCR data (Fig 1b), the fifth gene on this list is Trh, whose expression is downregulated 10-fold in fasting and is rescued to 50% of fed levels. Among the top 25 genes positively regulated by leptin are two well known neuropeptides of the PVN, oxytocin and vasopressin. In addition, somatostatin gene expression (Supplementary Table 1) was significantly regulated in a similar fashion. These data were validated in an independent biological replicate of this experiment using Q-PCR (Fig 5a).

Figure 4
Top 25 genes that are a.) positively & b.) negatively regulated by leptin in the PVN
Figure 5
Taqman Quantitative PCR validation of genes positively regulated by leptin

In addition to its role in regulation of neuropeptide expression, leptin has recently been shown to have important structural effects on synaptic density and remodelling within the arcuate nucleus (Pinto et al., 2004). Notably, among the top 25 genes positively regulated by leptin in the PVN (Fig 4a) are several that have been implicated in synaptic function. These include the most highly leptin regulated gene that we identified, namely basigin, as well as Apolipoprotein E (ApoE), Gap43, synuclein-γ and GABA(A) receptor-associated protein (Gabarap). The effects of leptin on the expression of Bsg, ApoE, Gap43 and Gabarap were also measured by Q-PCR in an independent biological replicated experiment. The direction of the effect was confirmed for all four genes, but in the case of ApoE this did not reach statistical significance (Fig 5b).

The seventh gene on this list is neuronatin. It has been implicated to play a role in neurodevelopment and is also highly expressed in pancreatic beta-cells where it may play a role in insulin secretion (Joe et al., 2008) as well as in adipocytes (Suh et al., 2005). The expression profile of neuronatin was also validated by Q-PCR (Fig 5b).

Genes upregulated by fasting but normalised by leptin

Figure 4b lists the 25 transcripts that showed the greatest upregulation in expression in the fasted state that were normalised by leptin. The transcript at the top of the list is Neto1 (neuropilin (NRP) and tolloid (TLL)-like 1), which encodes a brain-specific transmembrane protein with structural similarity to neuropilin (Stohr et al., 2002). Sorcs1 (sortilin-related VPS10 domain containing receptor 1), the second gene on the list, has recently been implicated as a susceptibility gene in obesity-induced type 2 diabetes mellitus (Clee et al., 2006; Goodarzi et al., 2007). Cntnap2, the fourth gene on the list, encodes a member of the neurexin family which functions in the vertebrate nervous system as cell adhesion molecules and receptors (Poliak et al., 1999).

Pathway analysis

We further analyzed the data using a pathway analysis package (Ingenuity Pathway Analysis) which detects groups of functionally-related annotated genes.

The mitochondrial oxidative phosphorylation (OXPHOS) pathway was highly significantly over-represented (p=5.01 E-16) in the list of genes whose expression was down regulated in fasting and reversed by leptin (Fig 6). 26 of 158 OXPHOS genes were present in the 438 genes. In particular, 12 of these genes were from the complex I ubiquinone biosynthesis pathway. To confirm this observation, we performed Q-PCR on 8 OXPHOS genes present in a biological replicate of the experiment as described above. Three were from complex I (Ndufa8, Ndufb9 & Ndufs7), one from each of complexes II, III & IV (Sdhd, Uqcrc2 & Cox5a respectively) and 2 from complex V (Atp6v1f & Atp5g). The OXPHOS genes from complexes I-IV showed fasting induced downregulation that was reversed by leptin (Fig 7); Atp6v1f and Atp5g from complex V showed no change in expression (data not shown). In keeping with the microarray results, the fasting induced expression downregulation of these 6 genes was modest (between 1.5-2 fold downregulated) with only the down-regulation of Ndufa8, Sdhd and Cox5a reaching statistical significance (p<0.05). However, the trend to downregulation and the reversal by leptin was present in all 6 genes, supporting the pathway analysis and providing further evidence that multiple genes from the OXPHOS pathway are downregulated in the PVN in response to fasting and are regulated by leptin.

Figure 6
Ingenuity pathway analysis of 438 genes positively regulated by leptin
Figure 7
Taqman Quantitative PCR validation of OXPHOS genes

Genes involved in protein synthesis are also significantly (p=8.83E-6) over represented in our list of genes positively regulated by leptin, with 41 of the 438 genes (9.3%) involved.

Discussion

To gain insights into molecules and pathways mediating downstream signalling actions of leptin in the PVN, a key hypothalamic region involved in energy balance, we compared the expression profiles of laser captured PVN from ad libitum fed mice, 48 hours fasted mice and mice given leptin during a similar fast. In order to exclude transcripts representing non-specific neuronal stress responses to fasting we simultaneously profiled the cerebellum, a site unknown to have a regulatory role in energy balance. The specificity of the LCM could be confirmed both visually (Fig1a) and is also supported by the absence of Agrp, Sf-1 and Mch transcripts from the samples. Additionally, we confirmed using Q-PCR that the PVN samples showed the expected regulation of TRH mRNA by fasting and feeding.

In order to minimize false positives, we were stringent in handling our data. Rather than rely solely on Affymetrix GCOS software, we also analyzed our data using RMA and GC-RMA. After applying these different analyses, only 20%-30% of all the genes overlapped between all three algorithms. However, it was clear that the biggest data set (n=438) was of genes positively regulated by leptin.

Neuropeptide gene expression positively regulated by leptin

Oxytocin, vasopressin and somatostatin gene expression was reduced by fasting and restored by leptin (Fig5a). This is consistent with reports showing a fasting reduction in hypothalamic oxytocin mRNA levels that was reversed by refeeding (Kublaoui et al.,2008), and the reported role of oxytocin neurons linking hypothalamic leptin-action to caudal brainstem nuclei controlling meal size (Blevins et al.,2004). AVP expression in the PVN has been shown to be increased by leptin (Yamamoto et al.,1999). Previous reports demonstrating the presence of leptin receptors on PVN magnocellular vasopressin- and oxytocin-containing neurons (Hakansson et al.,1998) indicate that this effect could result from direct leptin action. Additionally, somatostatin has been demonstrated to modulate the efficacy of leptin-signalling in the rat hypothalamus (Stepanyan et al.,2007).

Synaptic remodelling/plasticity genes positively regulated by leptin

Four of the top 15 genes positively regulated by leptin (Basigin, ApoE, Gap43 and Gabarap) are involved in synaptic maintenance or development. Bsg is part of a transsynaptic complex regulating synaptic compartmentalization and strength, and coordinating plasma membrane and cortical organization (Besse et al.,2007). ApoE receptors act as signalling molecules in neurons, altering phosphorylation of numerous proteins after extracellular ligand binding and affecting neurite outgrowth, synapse formation and neuronal migration (Hoe et al.,2006). Gap43 is a neuronal specific gene that plays a role in actin regulation, neurite outgrowth and anatomical plasticity (Frey et al.,2000). Gabarap trafficks GABA(A) receptors to and from the cell surface, clustering these neurotransmitter receptors at the postsynaptic terminals (Chen et al.,2000; Leil et al.,2004), which is a critical requirement for efficient neurotransmission and neuronal communication.

It is becoming clear that in addition to engaging classical ‘neuropeptide/receptor’ systems within the brain, leptin also rapidly modifies synaptic connections between neurons. Leptin has been demonstrated to be necessary for both normal development of neuronal projections within the hypothalamus (Bouret et al.,2004) as well as in the regulation of synaptic plasticity (Pinto et al.,2004; Horvath and Gao,2005; Sternson et al.,2005; Gao et al.,2007). The use-dependent potentiation of excitatory synapses onto pyramidal cells in the hippocampus is a well studied form of synaptic plasticity (Kullmann and Lamsa, 2007). The identification in this study of leptin-regulated genes that play a variety of roles in synapse development or plasticity supports the notion that similar mechanisms to those seen in the hippocampus (O’Malley et al.,2007) maybe active within the hypothalamus.

Genes expressed in the brain and periphery positively regulated by leptin

Neuronatin and synuclein-γ are highly expressed in both the brain and in metabolic relevant peripheral tissues. Neuronatin was first identified in the developing mammalian brain (Joseph et al.,1994), but is also expressed in the pancreas where it plays a role in insulin secretion (Joe et al.,2008) and in adipocytes where it may have a role in adipogenesis (Suh et al.,2005). Synuclein-γ is abundant in the neuronal cytosol and enriched at presynaptic terminals (Clayton and George,1998). However, like neuronatin, it has also been found to be highly expressed in white adipose tissue, where it is coordinately expressed with leptin and increased in human obesity (Oort et al.,2008). It is intriguing that adipose tissue and leptin-responsive neurons in the brain could share some nutrient sensing mechanisms.

Genes negatively regulated by leptin

Our data indicates that there are fewer genes that are negatively regulated by leptin. However, the first (Neto1) and the fourth (Cntnap2) genes on this list also have a role in neuronal development. Neto1 encodes a brain-specific transmembrane protein, whose expression pattern and structural similarity with neuropilin suggested that it possibly played a role in the development and/or maintenance of neuronal circuitry (Stohr et al.,2002), while Cntnap2 is a member of the neurexin family which functions in vertebrate nervous systems as cell adhesion molecules and receptors (Poliak et al.,1999). Thus it appears that leptin can positively and negatively regulate genes involved in neuronal development, providing more evidence that structural changes to hypothalamic neurons may play a role in mediating leptin’s actions.

Sorcs1, another gene negatively regulated by leptin, was identified in mice as a quantitative trait locus for Type II Diabetes (T2D) affecting fasting insulin levels (Clee et al.,2006). A recent study translating these results in humans identified significant associations between SORCS1 variants and fasting insulin levels, as well as T2D risk in female subjects, in two Mexican-American populations. Goodarzi et al (2007) has hypothesized that it may play a role in the maintenance or expansion of islet vasculature during islet growth in compensation for insulin resistance. However, SORCS1 is also highly expressed in neurons where it probably plays a role in cell trafficking, with one of its major isoforms interacting with the alphaC/sigma2 subunits of the adaptor protein (AP)-2 complex (Nielsen et al.,2008). The fact that this gene is nutritionally regulated in a leptin-dependent manner warrants further investigation.

Pathway analysis

In order to identify pathways or functional annotations that maybe over-represented in the expression data we carried out pathway analyses of genes both positively and negatively regulated by leptin. We did not identify any co-ordinated pathways or functions negatively regulated by leptin. However, analysis of the 438 genes positively regulated by leptin revealed multiple genes involved in protein synthesis as well as from the mitochondrial oxidative phosphorylation (OXPHOS) pathway.

Recent evidence supports the view that protein synthesis occurs in axons, remote from the cell body, and is integral to aspects of synaptogenesis and axonal development (Piper and Holt, 2004). Thus, the fact that 9% of the genes positively regulated by leptin are involved in protein synthesis is congruent with the similar regulation of synaptic remodelling genes.

Of the 158 genes Ingenuity has categorized as being part of the OXPHOS pathway, 26 were present in the list of 438 genes. When 8 of these genes were validated using Q-PCR, all the ones from complex I-IV recapitulated the microarray data, while the two genes tested from complex V did not.

The hypothalamus integrates both hormonal and nutritional signals to achieve energy balance (Coll et al.,2007; Oswal and Yeo,2007). Thus, our finding that OXPHOS gene expression decreases in the PVN in response to fasting suggests that a switch from oxidative to non-oxidative metabolism maybe important for the hypothalamic homeostatic response to nutrient deprivation and reduced leptinergic tone. A number of studies have reported that expression of OXPHOS genes are co-ordinately decreased in skeletal muscle from patients with T2D (Mootha et al.,2003; Patti et al.,2003), a condition closely linked with obesity (Kahn and Flier,2000). Enormous interest is currently being expressed in the hypothalamus as a critical site for the co-ordinated control of both glucose homeostasis and energy balance (Obici et al.,2001; Obici and Rossetti,2003; Lam et al.,2005). Our findings raise the possibility that regulation of OXPHOS gene expression maybe a unifying mechanism important for the control of energy balance and nutrient handling in both the hypothalamus and periphery and that dysregulation of this co-ordinated pattern of gene expression might underlie both obesity and diabetes.

Caveats

Although our usage of LCM has improved our ‘resolution’ in studying gene expression in the hypothalamus, the PVN is still very heterogeneous, including both parvocellular and magnocellular neurons. Additionally, although some PVN neurons express leptin receptors, activity dependent changes in other regions, particularly the ARC are likely contributors to the observed transcriptional changes. This study did not allow us to discriminate between direct and indirect actions of leptin, which would require future studies profiling individually identified neurons.

Conclusions

Leptin, a circulating hormone produced in adipose tissue, influences the expression of a large number of genes within the PVN, most of which it positively regulates. In addition to certain classical neuropeptides, leptin also has striking effects on the expression of a number of genes implicated in synaptic function and/or plasticity. Finally leptin appears to exert a generalised positive effect on the expression of genes involved in mitochondrial OXPHOS. Further work will be required to determine which, if any, of these effects are critical for leptin’s multiple actions, including the control of bodyweight.

Supplementary Material

Supplementary Table 1

Supplementary Table 2

Acknowledgements

This work was supported by the UK Medical Research Council, the Wellcome Trust and EU FP6 EUGENE2 (LSHM-CT-2004-512013).

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