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Published in final edited form as: J Neurogenet. 2020 Jul 3;34(3-4):482–488. doi: 10.1080/01677063.2020.1777116

Neuroendocrine Control of Lipid Metabolism: Lessons from C. elegans

Supriya Srinivasan 1
PMCID: PMC7779659  NIHMSID: NIHMS1647413  PMID: 32619378

Abstract

This review article highlights our efforts to decode the role of the nervous system in regulating intestinal lipid metabolism in Caenorhabditis elegans. Capitalizing on the prescient and pioneering work of Sydney Brenner and John Sulston in establishing C. elegans as an immensely valuable model system, we have uncovered critical roles for oxygen sensing, population density sensing and food sensing in orchestrating the balance between storing lipids and utilizing them for energy in the intestine, the major organ for lipid metabolism in this model system. Our long-term goal is to reveal the integrative mechanisms and regulatory logic that underlies the complex relationship between genes, environment and internal state in the regulation of energy and whole-body physiology.

Introduction

A striking feature of humans around the world is the incredible diversity seen in aspects of physiology such as stature and body weight. When it comes to metabolism, there is a perception that we are, in the 21st century, in an environment that predisposes us towards obesity and the accumulation of body fat because of increased dietary intake and reduced energy expenditure. However, obesity and leanness have always co-existed (Davenport, 1923). This fact is perhaps most easily visualized in ancient and modern art. From the sculpture of the Venus of Willendorf dating back to about 20,000 B.C., to art in the second millennium between the 1300s-1800s, human obesity has been depicted, in co-existence with leanness (Woodhouse, 2008). In modern parlance, that is, in the post McClintock and Mendelian eras, body weight is a heritable trait. Indeed, genome-wide association studies and twin studies place the heritability of body weight between 0.4–0.7(Walley et al., 2006) commensurate with that of height, suggesting that there is a strong genetic basis that underlies the regulation of body fat storage.

General observations of human physiology began to be codified in the scientific literature in the late 1800s, in the works of Claude Bernard, Walter Cannon, Hetherington and others, who were influenced by engineering control theory, and promoted the idea of homeostasis and the body’s defense against a so-called set point (Bernard, 1927; Cannon, 1939). This idea was originally used to explain the narrow range within which parameters such as body temperature and blood glucose are maintained, but later also included body fat control and the concept of energy balance, which posits that animals placed on a high calorie diet would resist a shift in body fat stores, and return to a homeostatic set point (Figure 1A). However experimental observations in the 20th century did not agree with the set point theory, because animals with lesions in their hypothalami, ovariectomized animals, and those bearing spontaneous mutations in what would later become known as the leptin signaling pathway, rapidly gained weight with no return to a homeostatic set point (Ravussin et al., 2014; Wade and Gray, 1979; Wirtshafter and Davis, 1977). These experiments and other mathematical modeling approaches in the field soon gave rise to a ‘settling point’ model (Figure 1B), which could sufficiently account for increases in body fat stores when placed on a high-calorie diet (Wirtshafter and Davis, 1977). However this model suggested that upon returning to a regular diet, animals would reduce body weight indefinitely, which was also not been borne out by experimental observations. The ‘hybrid model’ (Figure 1C), incorporates our current understanding of the roles of the major anabolic hormones leptin and insulin, which are sufficient to explain dramatic weight gains on a high calorie diet (Tam et al., 2009). However, a strong body of evidence in both humans and rodents shows that once the weight is gained, the efficacy of weight loss is profoundly variable. Factors that control this variability are postulated to exist, but are poorly understood (Ravussin et al., 2014). Our hypothesis is that both environmental influences and genetic factors will influence the many hormones that combinatorially regulate the physiology underlying body weight control (Figure 1D).

Figure 1. Theories of body weight control.

Figure 1.

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A. The ‘set point’ model posits that an internal homeostatic sensor can detect deviations from a predetermined set point, and restore body weight back to homeostasis. HCD, high-calorie diet. B. The settling point model suggests that body weight will largely be a reflection of the environment, such that a HCD will increase body fat, and withdrawal will decrease body fat to below its original state. C. The hybrid model suggests that anabolic hormones (such as leptin, insulin) will drive body fat gain under conditions of a HCD, but that restoration to a normal diet will bring body fat back to a preset baseline value. How catabolism is effected in these conditions remains unknown. D. We propose a fluctuating model, in which body fat gain and loss occur as a result of external influences (both sensory and metabolic) and internal physiological state. There is no predetermined set point per se.

Understanding the fundamental biology of fat metabolism is of critical importance to human health given that a host of illnesses including cardiovascular disease, diabetes, metastatic cancers and perhaps even neurodegeneration have metabolic derangements as a root cause. Additionally, the prevalence of metabolic diseases has exceeded 30% of the US population and projections suggest a further increase (Ward et al., 2019). Given the complexity of the problem, it is clear that new approaches, orthogonal to the conventional view of energy balance as simple relationship between food intake and energy expenditure, are critical.

Developing C. elegans as a model system to study fat metabolism

Capitalizing on the pioneering work of Sydney Brenner and John Sulston in establishing C. elegans as a model system (Coulson et al., 1986; Sulston and Brenner, 1974), sequencing of the genome (Consortium, 1998; Waterston and Sulston, 1995) and the use of sophisticated molecular genetics including RNAi (Fire et al., 1998; Kamath and Ahringer, 2003), several groups established that the nervous system plays an instrumental role in regulating whole body lipid metabolism (Greer et al., 2008; Mak et al., 2006; Srinivasan et al., 2008). Other groups working on genes controlling the lipid composition of C. elegans deciphered the polyunsaturated fatty acid synthesis pathway, a novel class of signaling lipids called ascarosides and their many roles in C. elegans physiology (Ludewig and Schroeder, 2013; Watts and Browse, 2002; Zhu and Han, 2014), as well as roles for the major nutrient sensors (TOR, AMPK) in regulating lipid metabolism (Narbonne and Roy, 2009; Ristow and Zarse, 2010; Soukas et al., 2009). Several groups including our own have established the use of reporter assays using fluorescent proteins that would allow us, in the living worm, to capture metabolic state information (Walker et al., 2011) (Noble et al., 2013). Additional and ongoing developments in measuring food intake (Ding et al., 2020; Wu et al., 2019), energy expenditure (Koopman et al., 2016; Srinivasan et al., 2008), fat content and composition (Srinivasan, 2015) have rendered C. elegans an exceedingly sophisticated model system in which to uncover the fundamental features of body fat control.

In wild-type C. elegans feeding on E. coli, the intestine is the primary site for fat synthesis, accumulation and metabolism (Srinivasan, 2015). In reproducing adults, fertilized embryos are a second site. Under certain conditions including food deprivation, fat deposition has also been noted in the germline, presumably to ensure survival of progeny in the face of longer-term food deprivation (Lynn et al., 2015). Electron micrographs of the intestinal cells show that they contain large lipid deposits (Srinivasan, 2015), which from mass spectrometry studies primarily contain storage triglycerides (Ding et al., 2013), as seen in mammals. Additional studies have shown that beta-oxidation, a central process by which stored fats are converted to energy in the mitochondria, regulate the relationship between reduced mitochondrial activity and increased lifespan (Durieux et al., 2011).

Neurobiology of fat metabolism

In 2010 when I started my lab at TSRI, we began with the notion that, in contrast to the early discoveries of fat-accumulating hormones (such as leptin and insulin), genes and hormones regulating the conversion of stored fat to energy had lagged behind. To discover such mechanisms, we began conducting forward-genetic, candidate- and RNAi-based screens. We were also curious to explore more deeply and systematically, the role of the nervous system in intestinal fat metabolism, an endeavor that would have been Herculean without the pioneering work of John Sulston in having deciphered the complete wiring diagram of the C. elegans nervous system. Also invaluable is the deep knowledge base that had come from the work of Cori Bargmann and others in deciphering the major roles of the chemosensory neurons (Bargmann, 2006), and the remarkable ability to monitor and manipulate any neuron of choice in living worms (Chalasani et al., 2007).

Oxygen Sensing

To date, we have screened an estimated 30% of the neuronal genome (Hobert, 2013) for roles in body fat control. One of our early genetic screens was for the family of null mutants of the Gα family of G proteins (Jansen et al., 1999), that transduce sensory signals from the environment via G protein coupled receptors (GPCRs). Many Gα proteins were expressed predominantly in neurons, and null mutants were available for the viable 19 of 21 genes. Our first ‘hit’ was a Gα protein called GPA-8, which is orthologous to the mammalian gustducin family of G proteins that regulate intracellular cGMP. GPA-8 is expressed in four oxygen sensing neurons of C. elegans called AQR, PQR and the bilateral URX(L/R). These neurons had previously been studied for their role in sensing atmospheric oxygen (de Bono and Bargmann, 1998; Gray et al., 2004). We defined a role for gpa-8 in the URX neurons in regulating the metabolic response to oxygen-sensing in the following way: worms fasted at 21% oxygen metabolized more than 80% of their intestinal fat stores for energy, whereas those fasted at 10% oxygen did not. This effect was largely due to the presence of the soluble guanylate cyclase gcy-36, which was also the oxygen sensor in the URX neurons. Through molecular-genetic and live Ca++ imaging approaches, we found that in the URX neurons, gpa-8 which had emerged in our body fat screen, functions as a negative regulator of gcy-36, and modulates the cGMP-gated calcium channel, tax-4 (Witham et al., 2016). Interestingly, this work also revealed that the internal fat status of the intestine influences URX resting state, suggesting that an internal homeostatic signal regulates the extent to which environmental oxygen regulates intestinal fat metabolism (Ringstad, 2016).

In a set of parallel studies, we uncovered a role for the BAG neurons, which are sensors of low atmospheric oxygen (Zimmer et al., 2009). BAG neurons detect and respond to 5–10% oxygen via the soluble guanylyl cyclase gcy-33, which had emerged from our screen of the soluble guanylyl cyclase family in C. elegans. It had been previously established that BAG and URX neurons are tonic sensors of oxygen (Zimmer et al., 2009). In contemplating the relationship between BAG and URX neurons with respect to fat metabolism in the intestine, we discovered that BAG neurons function as tonic repressors of URX resting state (Hussey et al., 2018). When exposed to low oxygen, BAG neurons are activated, and a peptide called FLP-17 is secreted from these neurons and acts on its cognate GPCR EGL-6 (Ringstad and Horvitz, 2008), which is necessary and sufficient in the URX neurons (Hussey et al., 2018). BAG activity via flp-17-egl-6 signaling serves to repress the resting state and activity of the URX neurons, limiting fat oxidation when environmental oxygen levels are low (Hussey et al., 2018). Thus, fluctuations in environmental oxygen, sensed via the chemosensory nervous system, are an important driver of intestinal fat metabolism (Figure 2A).

Figure 2. Neuroendocrine control of lipid metabolism.

Figure 2.

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We have found that the C. elegans nervous system plays a profound role in regulating body fat stores, stored predominantly in the intestine. A. Oxygen sensing from the environment plays an important role in regulating intestinal lipid metabolism. The URX neurons, which detect environmental oxygen, drive fat oxidation in the intestine. A Gα protein called GPA-8, controls the resting state of the URX neurons, thus regulating the rate and extent to which they can be activated by environmental oxygen. On the other hand, the BAG neurons negatively regulate the URX neurons by secreting the FLP-17 peptide under conditions of low oxygen, which binds to its cognate receptor EGL-6, necessary and sufficient in the URX neurons. Thus, oxygen sensing in the nervous system regulates intestinal fat metabolism in C. elegans. B. Population-density-sensing is another driver of intestinal fat metabolism. The ascaroside pheromone ascr#3 is secreted by adults and L1 larvae. High ascr#3 concentrations within a given patch of food drive ATGL-1-dependent fat oxidation in the intestine. This process occurs via ADL neuron-mediated detection of ascr#3, and in which the Gα protein GPA-3 plays a critical sensory role. ADL communicates via downstream cholinergic neurons to the intestine to relay a signal for fat oxidation. C. The serotonergic neural circuit for intestinal fat oxidation detects food availability in the environment, and is amplified by octopamine signaling from the RIC neurons. D. Current model for the neuroendocrine control of intestinal lipid metabolism in C. elegans. The FLP-7 peptide is necessary and sufficient in the ASI neurons, and is secreted in proportion to fluctuations in oxygen, bacteria and pheromones. The FLP-7 receptor NPR-22 is necessary and sufficient in the intestine, and when activated, increases expression of the conserved triglyceride lipase ATGL-1 in the intestine. ATGL-1 then converts stored triglyceride lipids to free fatty acids, which are oxidized in the mitochondria for usable energy in the form of ATP. Thus, fluctuations in the environment, sensed and decoded by the nervous system, are a major driver of fat metabolism in C. elegans.

Population Density Sensing

The most potent hit from our Gα family screen was gpa-3, whose absence led to a profound decrease in intestinal fat stores. gpa-3 is expressed in several pairs of chemosensory neurons (Jansen et al., 1999), however we found that it is necessary and sufficient in the ADL neurons, and functions to negatively regulate the adenylyl cyclase ACY-1 which produces the second messenger cAMP. ADL neurons detect and respond to the ascaroside pheromone ascr#3, via the TRPV channel osm-9 (Jang et al., 2012). Because the effect of gpa-3 mutants was fully suppressed in the gpa-3;osm-9 mutants, we wondered whether the pheromone ascr#3, which indicates population density and structure, might be another salient environmental cue that regulates intestinal fat metabolism. A series of genetic and reconstitution studies showed that pheromone-mediated regulation of cAMP signaling in ADL neurons regulates a metabolic signal to trigger the conversion of stored fats to energy in the intestine (Figure 2B). Why would population density and pheromones regulate intestinal lipid metabolism? As an animal encounters a new patch of food, it must adjust its metabolism to reflect its environment. A food patch that contains other worms must be shared, whereas a similar patch without other worms reflects a relatively greater amount of food for a single entering worm (Hussey et al., 2017). We speculate that pheromone-sensing via ADL provides a salient ‘denominator’ to evaluate relative food availability to best optimize metabolic rate.

Food sensing and serotonin

In an independent line of research, our lab has been interested in the role of the neuromodulator serotonin (5-hydroxytryptamine, 5HT) because of its ancient roles in modulating behavior and physiology across species. In C. elegans, 5HT is synthesized by the rate-limiting enzyme tryptophan hydroxylase (tph-1), which is found predominantly in the NSM, ADF, HSN and a few other neurons (Sawin et al., 2000; Sze et al., 2000). Work from a number of groups has shown that 5HT production at each of these sites has distinct roles: NSM neurons gauge food entering via the pharynx and accordingly modulate behavioral responses to food (Rhoades et al., 2019); ADF neurons detect beneficial and pathogenic bacteria, and alter feeding behavior (Cunningham et al., 2012) and pathogen avoidance (Zhang et al., 2005); HSN neurons regulate the rate of egg-laying in proportion to food access (Brewer et al., 2019; Hardaker et al., 2001). Interestingly 5HT from both NSM and ADF neurons also transduces heat stress, detected by the AFD neurons, to the germline (Tatum et al., 2015).

We had found that neuronal 5HT was a potent modulator of fat metabolism in the intestine: loss of endogenous 5HT via genetic ablation of tph-1 increased intestinal fat stores (Noble et al., 2013), whereas ablation of mod-5 (the 5HT-specific reuptake transporter) which increases synaptic 5HT, decreased intestinal fat stores (Srinivasan et al., 2008). Through RNAi-based screens, we had found that in the intestine, neuronal 5HT led to increased mitochondrial beta-oxidation and the conversion of stored fats to energy (Srinivasan et al., 2008). In trying to understand the mechanisms by which neuronal 5HT is relayed to the intestine, we uncovered the neural circuit for 5HT-mediated fat loss (Figure 2C). We defined a role for the ADF chemosensory neurons from which 5HT signaling is required for intestinal fat loss, and interestingly, a second role for the URX neurons from which MOD-1, a 5HT-gated chloride channel, regulates intestinal fat metabolism. We also found that the RIC neuron in which octopamine (the invertebrate ortholog of adrenaline) is synthesized (Alkema et al., 2005; Horvitz et al., 1982), and the AWB sensory neurons in which the SER-6 octopamine receptor is sufficient, together modulate ADF tph-1 expression. Ultimately, food presence is relayed via the serotonergic circuit and amplified via octopamine, to drive the rate and extent of fat loss in the intestine (Noble et al., 2013). The 5HT circuit exerts its effects in the intestine via regulating the essential and highly conserved triglyceride lipase called Adipocyte Triglyceride Lipase (ATGL-1), which is expressed predominantly in the intestine (Noble et al., 2013). One notable feature of the 5HTergic fat regulatory circuit is that neither 5HT synthesis, nor the receptor that governs fat loss, nor the genes that underlie the amplifying effects of octopamine are expressed in the intestine, where the metabolic effects of 5HT occur. This observation echoed our work on oxygen sensing and pheromone sensing, in which genes necessary and sufficient in the nervous system showed large fluctuations in fat modulation in the intestinal cells. Because the C. elegans intestine is not innervated, we hypothesized that an unknown endocrine factor may relay sensory information from the nervous system, to the gut (Srinivasan, 2015).

Neuroendocrine communication and the tachykinin brain-to-gut signaling axis

In an effort to uncover such an endocrine signal, we conducted a screen of the known neuropeptide genes in C. elegans, for suppressors of 5HT-mediated fat oxidation. Our most potent suppressor was a neuropeptide called FLP-7, which we found is secreted from the ASI neurons in an AMPK-dependent manner, in response to fluctuations in neural 5HT circuit signaling (Palamiuc et al., 2017). We then found that the FLP-7 receptor, a GPCR called NPR-22 (Mertens et al., 2006; Mertens et al., 2004), is necessary and sufficient in the intestine to drive ATGL-1-mediated fat oxidation. In the flp-7;npr-22 double mutant, restoration of neither gene rescued 5HT-mediated fat oxidation without the presence of the other, suggesting that FLP-7 and NPR-22 function as a true ligand-receptor pair in vivo, and thus defining the neuroendocrine axis for 5HT-mediated lipid metabolism (Figure 2D). Notably, this ligand-receptor pair does not alter other 5HT-dependent behaviors including locomotion, reproduction and food intake (Palamiuc et al., 2017). For global modulators such as 5HT, the use of distinct peptides for each output may be a predominant strategy to achieve phenotypic selectivity. Our ongoing work suggests that the tachykinin signaling axis may represent the final common pathway that integrates oxygen sensing, population density sensing and food sensing from the nervous system, to regulate the rate and extent of fat metabolism in the intestine (Figure 2D).

Open questions

A remarkable feature of the tachykinin neuroendocrine pathway is that all of the neuronal effects on global fat metabolism occur without appreciable changes in food intake (Hussey et al., 2018; Hussey et al., 2017; Noble et al., 2013; Palamiuc et al., 2017; Srinivasan et al., 2008; Witham et al., 2016), suggesting that the regulation of body fat is indeed distinct from food intake alone. The tachykinin neuropeptides, first defined by Substance P were originally identified more than 80 years ago (Guillemin, 2013), but have not previously been associated with lipid metabolism. The tachykinin peptides and receptors have been predominantly associated with inflammation in mammals (Steinhoff et al., 2014), which has mechanistic ties to metabolic dysfunction, however the role of tachykinins in mammalian metabolism remain unknown.

By our estimates, approximately 70% of the neuronal genome remains unexplored with respect to metabolic control (Hobert, 2013). Although we have identified the roles of a handful of neurons that transmit environmental cues to regulate intestinal metabolism, the majority remain unknown in this regard. We are optimistic that the use of advanced chemo- and optogenetic tools will hasten this process. In closing, the prescient studies of John Sulston and Sydney Brenner will continue to initiate, inform and strengthen our understanding of the myriad ways in which the nervous system regulates internal physiology. In relation to models that best describe our current understanding of energy regulation, we favor one in which hormones and neuroendocrine factors such as the serotonin-tachykinin system, which fluctuate in proportion to the external environment as well as internal state, regulate body fat stores. How such factors are integrated singly and in combination to orchestrate energy states within the body, is a fascinating unanswered in biology and medicine.

Acknowledgements

I thank all current and previous members of the Srinivasan Laboratory for their dedication and sincere efforts to uncover the biology of body fat metabolism using the C. elegans model system. Work discussed in this review was funded by the NIH, and I am thankful for their support in this endeavor. We also thank the CGC, from whom we have requested many C. elegans strains.

Footnotes

Disclosures

The author declares no other competing interests.

References

  1. Alkema MJ, Hunter-Ensor M, Ringstad N, and Horvitz HR (2005). Tyramine Functions independently of octopamine in the Caenorhabditis elegans nervous system. Neuron 46, 247–260 [DOI] [PubMed] [Google Scholar]
  2. Bargmann CI (2006). Chemosensation in C elegans. WormBook, 1–29 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bernard C (1927). An introduction to the study of experimental medicine (New York, MacMillan and Co.) [Google Scholar]
  4. Brewer JC, Olson AC, Collins KM, and Koelle MR (2019). Serotonin and neuropeptides are both released by the HSN command neuron to initiate Caenorhabditis elegans egg laying. PLoS Genet 15, e1007896. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cannon W (1939). The wisdom of the body (New York, Norton & Company; ) [Google Scholar]
  6. Chalasani SH, Chronis N, Tsunozaki M, Gray JM, Ramot D, Goodman MB, and Bargmann CI (2007). Dissecting a circuit for olfactory behaviour in Caenorhabditis elegans. Nature 450, 63–70 [DOI] [PubMed] [Google Scholar]
  7. Consortium C.e.S. (1998). Genome sequence of the nematode C. elegans: a platform for investigating biology. Science 282, 2012–2018 [DOI] [PubMed] [Google Scholar]
  8. Coulson A, Sulston J, Brenner S, and Karn J (1986). Toward a physical map of the genome of the nematode Caenorhabditis elegans. Proc Natl Acad Sci U S A 83, 7821–7825 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Cunningham KA, Hua Z, Srinivasan S, Liu J, Lee BH, Edwards RH, and Ashrafi K (2012). AMP-activated kinase links serotonergic signaling to glutamate release for regulation of feeding behavior in C. elegans. Cell Metab 16, 113–121 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Davenport CB (1923). Body Build and its Inheritance. Proc Natl Acad Sci U S A 9, 226–230 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. de Bono M, and Bargmann CI (1998). Natural variation in a neuropeptide Y receptor homolog modifies social behavior and food response in C. elegans. Cell 94, 679–689. [DOI] [PubMed] [Google Scholar]
  12. Ding SS, Romenskyy M, Sarkisyan KS, and Brown AEX (2020). Measuring Caenorhabditis elegans Spatial Foraging and Food Intake Using Bioluminescent Bacteria. Genetics [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Ding Y, Zhang S, Yang L, Na H, Zhang P, Zhang H, Wang Y, Chen Y, Yu J, Huo C, et al. (2013). Isolating lipid droplets from multiple species. Nat Protoc 8, 43–51 [DOI] [PubMed] [Google Scholar]
  14. Durieux J, Wolff S, and Dillin A (2011). The cell-non-autonomous nature of electron transport chain-mediated longevity. Cell 144, 79–91 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, and Mello CC (1998). Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 391, 806–811. [DOI] [PubMed] [Google Scholar]
  16. Gray JM, Karow DS, Lu H, Chang AJ, Chang JS, Ellis RE, Marletta MA, and Bargmann CI (2004). Oxygen sensation and social feeding mediated by a C. elegans guanylate cyclase homologue. Nature 430, 317–322 [DOI] [PubMed] [Google Scholar]
  17. Greer ER, Perez CL, Van Gilst MR, Lee BH, and Ashrafi K (2008). Neural and molecular dissection of a C. elegans sensory circuit that regulates fat and feeding. Cell Metab 8, 118–131 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Guillemin R (2013). A conversation with Roger Guillemin. Interview by Greg Lemke. Annu Rev Physiol 75, 1–22 [DOI] [PubMed] [Google Scholar]
  19. Hardaker LA, Singer E, Kerr R, Zhou G, and Schafer WR (2001). Serotonin modulates locomotory behavior and coordinates egg-laying and movement in Caenorhabditis elegans. J Neurobiol 49, 303–313 [DOI] [PubMed] [Google Scholar]
  20. Hobert O (2013). The neuronal genome of Caenorhabditis elegans. WormBook, 1–106 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Horvitz HR, Chalfie M, Trent C, Sulston JE, and Evans PD (1982). Serotonin and octopamine in the nematode Caenorhabditis elegans. Science 216, 1012–1014 [DOI] [PubMed] [Google Scholar]
  22. Hussey R, Littlejohn NK, Witham E, Vanstrum E, Mesgarzadeh J, Ratanpal H, and Srinivasan S (2018). Oxygen-sensing neurons reciprocally regulate peripheral lipid metabolism via neuropeptide signaling in Caenorhabditis elegans. PLoS Genet 14, e1007305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hussey R, Stieglitz J, Mesgarzadeh J, Locke TT, Zhang YK, Schroeder FC, and Srinivasan S (2017). Pheromone-sensing neurons regulate peripheral lipid metabolism in Caenorhabditis elegans. PLoS Genet 13, e1006806. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Jang H, Kim K, Neal SJ, Macosko E, Kim D, Butcher RA, Zeiger DM, Bargmann CI, and Sengupta P (2012). Neuromodulatory state and sex specify alternative behaviors through antagonistic synaptic pathways in C. elegans. Neuron 75, 585–592 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Jansen G, Thijssen KL, Werner P, van der Horst M, Hazendonk E, and Plasterk RH (1999). The complete family of genes encoding G proteins of Caenorhabditis elegans. Nat Genet 21, 414–419 [DOI] [PubMed] [Google Scholar]
  26. Kamath RS, and Ahringer J (2003). Genome-wide RNAi screening in Caenorhabditis elegans. Methods 30, 313–321 [DOI] [PubMed] [Google Scholar]
  27. Koopman M, Michels H, Dancy BM, Kamble R, Mouchiroud L, Auwerx J, Nollen EA, and Houtkooper RH (2016). A screening-based platform for the assessment of cellular respiration in Caenorhabditis elegans. Nat Protoc 11, 1798–1816 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Ludewig AH, and Schroeder FC (2013). Ascaroside signaling in C. elegans. WormBook, 1–22 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lynn DA, Dalton HM, Sowa JN, Wang MC, Soukas AA, and Curran SP (2015). Omega-3 and −6 fatty acids allocate somatic and germline lipids to ensure fitness during nutrient and oxidative stress in Caenorhabditis elegans. Proc Natl Acad Sci U S A 112, 15378–15383 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Mak HY, Nelson LS, Basson M, Johnson CD, and Ruvkun G (2006). Polygenic control of Caenorhabditis elegans fat storage. Nat Genet 38, 363–368 [DOI] [PubMed] [Google Scholar]
  31. Mertens I, Clinckspoor I, Janssen T, Nachman R, and Schoofs L (2006). FMRFamide related peptide ligands activate the Caenorhabditis elegans orphan GPCR Y59H11AL.1. Peptides 27, 1291–1296 [DOI] [PubMed] [Google Scholar]
  32. Mertens I, Vandingenen A, Meeusen T, Janssen T, Luyten W, Nachman RJ, De Loof A, and Schoofs L (2004). Functional characterization of the putative orphan neuropeptide G-protein coupled receptor C26F1.6 in Caenorhabditis elegans. FEBS Lett 573, 55–60 [DOI] [PubMed] [Google Scholar]
  33. Narbonne P, and Roy R (2009). Caenorhabditis elegans dauers need LKB1/AMPK to ration lipid reserves and ensure long-term survival. Nature 457, 210–214 [DOI] [PubMed] [Google Scholar]
  34. Noble T, Stieglitz J, and Srinivasan S (2013). An integrated serotonin and octopamine neuronal circuit directs the release of an endocrine signal to control C. elegans body fat. Cell Metab 18, 672–684 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Palamiuc L, Noble T, Witham E, Ratanpal H, Vaughan M, and Srinivasan S (2017). A tachykinin-like neuroendocrine signalling axis couples central serotonin action and nutrient sensing with peripheral lipid metabolism. Nature communications 8, 14237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Ravussin Y, Leibel RL, and Ferrante AW Jr. (2014). A missing link in body weight homeostasis: the catabolic signal of the overfed state. Cell Metab 20, 565–572 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Rhoades JL, Nelson JC, Nwabudike I, Yu SK, McLachlan IG, Madan GK, Abebe E, Powers JR, Colon-Ramos DA, and Flavell SW (2019). ASICs Mediate Food Responses in an Enteric Serotonergic Neuron that Controls Foraging Behaviors. Cell 176, 85–97 e14 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Ringstad N (2016). A Controlled Burn: Sensing Oxygen to Tune Fat Metabolism. Cell Rep 14, 1569–1570 [DOI] [PubMed] [Google Scholar]
  39. Ringstad N, and Horvitz HR (2008). FMRFamide neuropeptides and acetylcholine synergistically inhibit egg-laying by C. elegans. Nat Neurosci 11, 1168–1176 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Ristow M, and Zarse K (2010). How increased oxidative stress promotes longevity and metabolic health: The concept of mitochondrial hormesis (mitohormesis). Exp Gerontol 45, 410–418 [DOI] [PubMed] [Google Scholar]
  41. Sawin ER, Ranganathan R, and Horvitz HR (2000). C. elegans locomotory rate is modulated by the environment through a dopaminergic pathway and by experience through a serotonergic pathway. Neuron 26, 619–631 [DOI] [PubMed] [Google Scholar]
  42. Soukas AA, Kane EA, Carr CE, Melo JA, and Ruvkun G (2009). Rictor/TORC2 regulates fat metabolism, feeding, growth, and life span in Caenorhabditis elegans. In Genes & Development, pp. 496–511 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Srinivasan S (2015). Neuroendocrine Control of Body Fat in Caenorhabditis elegans. Annual Reviews in Physiology 77 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Srinivasan S, Sadegh L, Elle IC, Christensen AG, Faergeman NJ, and Ashrafi K (2008). Serotonin regulates C. elegans fat and feeding through independent molecular mechanisms. Cell Metab 7, 533–544 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Steinhoff MS, von Mentzer B, Geppetti P, Pothoulakis C, and Bunnett NW (2014). Tachykinins and their receptors: contributions to physiological control and the mechanisms of disease. Physiol Rev 94, 265–301 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Sulston JE, and Brenner S (1974). The DNA of Caenorhabditis elegans. Genetics 77, 95–104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Sze JY, Victor M, Loer C, Shi Y, and Ruvkun G (2000). Food and metabolic signalling defects in a Caenorhabditis elegans serotonin-synthesis mutant. Nature 403, 560–564 [DOI] [PubMed] [Google Scholar]
  48. Tam J, Fukumura D, and Jain RK (2009). A mathematical model of murine metabolic regulation by leptin: energy balance and defense of a stable body weight. In Cell Metabolism, pp. 52–63 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Tatum MC, Ooi FK, Chikka MR, Chauve L, Martinez-Velazquez LA, Steinbusch HWM, Morimoto RI, and Prahlad V (2015). Neuronal serotonin release triggers the heat shock response in C. elegans in the absence of temperature increase. Curr Biol 25, 163–174 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Wade GN, and Gray JM (1979). Gonadal effects on food intake and adiposity: a metabolic hypothesis. Physiol Behav 22, 583–593 [DOI] [PubMed] [Google Scholar]
  51. Walker AK, Jacobs RL, Watts JL, Rottiers V, Jiang K, Finnegan DM, Shioda T, Hansen M, Yang F, Niebergall LJ, et al. (2011). A conserved SREBP-1/phosphatidylcholine feedback circuit regulates lipogenesis in metazoans. Cell 147, 840–852 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Walley AJ, Blakemore AI, and Froguel P (2006). Genetics of obesity and the prediction of risk for health. Hum Mol Genet 15 Spec No 2, R124–130 [DOI] [PubMed] [Google Scholar]
  53. Ward ZJ, Bleich SN, Cradock AL, Barrett JL, Giles CM, Flax C, Long MW, and Gortmaker SL (2019). Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. N Engl J Med 381, 2440–2450 [DOI] [PubMed] [Google Scholar]
  54. Waterston R, and Sulston J (1995). The genome of Caenorhabditis elegans. Proc Natl Acad Sci U S A 92, 10836–10840 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Watts JL, and Browse J (2002). Genetic dissection of polyunsaturated fatty acid synthesis in Caenorhabditis elegans. In Proc Natl Acad Sci USA, pp. 5854–5859 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Wirtshafter D, and Davis JD (1977). Set points, settling points, and the control of body weight. Physiol Behav 19, 75–78 [DOI] [PubMed] [Google Scholar]
  57. Witham E, Comunian C, Ratanpal H, Skora S, Zimmer M, and Srinivasan S (2016). C. elegans Body Cavity Neurons Are Homeostatic Sensors that Integrate Fluctuations in Oxygen Availability and Internal Nutrient Reserves. Cell Rep 14, 1641–1654 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Woodhouse R (2008). Obesity in art: a brief overview. Front Horm Res 36, 271–286 [DOI] [PubMed] [Google Scholar]
  59. Wu Z, Isik M, Moroz N, Steinbaugh MJ, Zhang P, and Blackwell TK (2019). Dietary Restriction Extends Lifespan through Metabolic Regulation of Innate Immunity. Cell Metab 29, 1192–1205 e1198 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Zhang Y, Lu H, and Bargmann CI (2005). Pathogenic bacteria induce aversive olfactory learning in Caenorhabditis elegans. Nature 438, 179–184 [DOI] [PubMed] [Google Scholar]
  61. Zhu H, and Han M (2014). Exploring developmental and physiological functions of fatty acid and lipid variants through worm and fly genetics. Annu Rev Genet 48, 119–148 [DOI] [PubMed] [Google Scholar]
  62. Zimmer M, Gray JM, Pokala N, Chang AJ, Karow DS, Marletta MA, Hudson ML, Morton DB, Chronis N, and Bargmann CI (2009). Neurons detect increases and decreases in oxygen levels using distinct guanylate cyclases. Neuron 61, 865–879 [DOI] [PMC free article] [PubMed] [Google Scholar]

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