PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Exp Gerontol. Author manuscript; available in PMC 2017 December 15.
Published in final edited form as:
PMCID: PMC5001925
NIHMSID: NIHMS785490

Gene-diet interactions and aging in C. elegans

Abstract

Diet is the most variable aspect of life history, as most individuals have a large diversity of food choices, varying in the type and amount that they ingest. In the short-term, diet can affect metabolism and energy levels. However, in the long run, the net deficiency or excess of calories from diet can influence the progression and severity of age-related diseases. An old and yet still debated question is: how do specific dietary choices impact health- and lifespan? It is clear that genetics can play a critical role — perhaps just as important as diet choices. For example, poor diet in combination with genetic susceptibility can lead to metabolic disorders, such as obesity and type 2 diabetes. Recent work in Caenorhabditis elegans has identified the existence of diet-gene pairs, where the consequence of mutating a specific gene is only realized on specific diets. Many core metabolic pathways are conserved from worm to human. Although only a handful of these diet-gene pairs has been characterized, there are potentially hundreds, if not thousands, of such interactions, which may explain the variability in the rates of aging in humans and the incidence and severity of age-related diseases.

Keywords: Diet-gene pairs, C. elegans, Metabolism, E. coli

1. C. elegans is a powerful model organism for studying dietary effects on animal physiology

Whether to fulfill biosynthetic deficiencies or to fuel growth and essential cellular functions, food is essential for all organisms. Although food is universally indispensable, types of diets are never universally equal. Despite the lack of a defined diet, recent work in Caenorhabditis elegans is still able to demonstrate the role diet plays on organismal physiology, as seen in studies uncovering several diet-dependent effects (Shtonda and Avery, 2006; Soukas et al., 2009; Maier et al., 2010; Macneil and Walhout, 2013; MacNeil et al., 2013; Pang and Curran, 2014; Pang et al., 2014; Gracida and Eckmann, 2013). Diet can exert immediate as well as long lasting effects on animal physiology, and remarkably, diet can also influence the physiology of future generations (Greer et al., 2014; Greer et al., 2011; Maures et al., 2011; Pang and Curran, 2012). But what can studies of C. elegans diet tell us about human metabolism? C. elegans is an attractive model for studying metabolism and aging for many reasons. First, it is cultured in laboratory settings using bacterial species, such as Escherichia coli, making it easy to study the effects of different diets through the use of different species/strains of bacteria as its food source. Second, it is characterized by short developmental and reproductive periods and a lifespan that averages three weeks, facilitating the rapid identification of effects that diet plays on these traits (Brenner, 1974; Sulston and Brenner, 1974). Third, despite their small 1 mm size, worms are complex multicellular organisms, whose transparency allows facile visual investigation of systems-level changes with age under different experimental conditions, such as diet. Fourth, genetic, RNA interference (RNAi), and chemical screening approaches are well-established in this system, facilitating fast discovery with these high-throughput approaches (Dillin et al., 2002; Lee et al., 2003; Hamilton et al., 2005; Hansen et al., 2005a; Curran and Ruvkun, 2007; Desalermos et al., 2011). Lastly, and perhaps most importantly, the C. elegans genome shares 60–80% of all human genes (Kim, 2013; Arvanitis et al., 2013; Zheng and Greenway, 2012; Marsh and May, 2012; Fontana et al., 2010; Rose and Archer, 1996; Brignull et al., 2006; Reis-Rodrigues et al., 2012; Lee et al., 2008a; Williams et al., 2012), and many of the core metabolic pathways in humans are conserved in C. elegans, including: the AMPK pathway (Greer et al., 2007), the TOR pathway (Vellai et al., 2003; Jia et al., 2004; Hansen et al., 2007), SREBP regulator of lipid homeostasis (Yang et al., 2006), insulin/IGF-1 (IIS) signaling pathway (Kenyon et al., 1993; Libina et al., 2003; Morris et al., 1996; Iser et al., 2007), nuclear hormone receptors that mediate energy homeostasis (Maglich et al., 2001), etc. For all these reasons, C. elegans is an excellent model for studying dietary effects on animal physiology.

2. Worm dieting, obesity, and food choice

A significant body of work exists that document how dietary restriction leads to increased life- and healthspan across many species, including C. elegans (Houthoofd et al., 2002a; Houthoofd et al., 2005a; Houthoofd et al., 2007; Houthoofd et al., 2003; Houthoofd et al., 2005b; Houthoofd et al., 2002b; Burnell et al., 2005; Braeckman et al., 2002; Mair and Dillin, 2008; Braeckman et al., 2006; Greer and Brunet, 2009; Lee and Longo, 2011; Hansen et al., 2005b; Panowski et al., 2007; Bishop and Guarente, 2007). However, our understanding of how ad libitum fed – the standard dietary regimen – diets impact basal metabolism requires further study. In addition, an examination of diets that would be classified as “unhealthy” in the context of those basal metabolic measurements is needed to allow better comprehension of their physiological effects on an animal and how the animal responds to diets of varying quality.

In contrast to worms in the wild, where food of high nutritional value may not always be present, humans living in developed countries are presented with easy and unhindered access to food that are often highly processed and whose composition is high in fats and carbohydrates (Odermatt, 2011). Excess ingestion of these diets can lead to obesity (Zheng and Greenway, 2012; Miller et al., 1994; Ma et al., 2005; Pereira et al., 2005; Rosenheck, 2008). In fact, obesity has become a worldwide epidemic (Popkin, 2006; Ogden et al., 2014). Body mass index (BMI) is a measurement used to estimate body fat content (calculated by dividing weight in kg by height in m2). In a report that took data from 900,000 participants from 57 different studies, it was shown that an increase in BMI is associated with higher risks of cardiovascular diseases, high blood pressure, type 2 diabetes, and other undesirable ailments (Prospective Studies et al., 2009). However, the negative effects on health from increased BMI are controversial as some studies have reported that higher BMI can be beneficial (Flegal et al., 2013; Sandholt et al., 2012; Conus et al., 2007; Asghar et al., 2012). As such, a clearer understanding of disease risk associated with obesity combined with information on diet is needed to better elucidate mechanisms of how organisms adapt to diets of varying nutritional value.

How does the C. elegans diet in the wild compare to that in the lab? C. elegans are free-living nematodes that were first isolated in soil and compost (Hodgkin and Doniach, 1997). To date, C. elegans have been found worldwide, primarily in humid temperate areas that include farmlands, woods, and decomposing fruits and stems (Kiontke et al., 2011; Andersen et al., 2012; Frezal and Felix, 2015). In the wild, C. elegans feeds on various soil bacteria species including Bacillus megaterium, Pseudomonas medocina, Comomonas sp., other various bacterial species, fungi, and as well as yeast, most likely as a source of cholesterol (Avery and Shtonda, 2003; Duveau and Felix, 2012; Felix and Duveau, 2012; Montalvo-Katz et al., 2013). When Sydney Brenner isolated C. elegans for study in the laboratory, he selected the uracil auxotroph E. coli B strain OP50 as the laboratory diet to limit the bacterial growth on plates, making it easier for microscopic analysis (Brenner, 1974; Sulston and Brenner, 1974). Like all model organisms, a worm's dietary composition in the wild is quite different than that in the laboratory. A worm's diet in the wild can be a mixture of many different bacterial species, while in laboratory its diet is usually a selected bacterial species/strain. In light of this, the use of multiple bacterial diets in studies can assist with the realization of previously unidentified genetic pathways perhaps masked by using the standard OP50 diet.

Even in the laboratory, diverse microbial diets have been found to have varying effects on the rate of development and reproduction when compared to the standard OP50 diet (Shtonda and Avery, 2006). Coonlon et al. demonstrated that different bacterial species found in soil, which are able to be cultured in the lab and fed to worms, have divergent impacts on physiology. Their study identified a total of 372 genes that are differentially expressed in C. elegans when exposed to the standard laboratory diet E. coli OP50 versus the three bacterial species that they isolated from the Konza prairie grasslands: Micrococcus luteus, B. megaterium, and Pseudomonas species (most identical to P. fluorescens). Among these identified genes, many are involved in metabolism, including: acdh-1 which encodes for acyl-CoA dehydrogenase that catalyzes first step of fatty acid beta-oxidation, elo-5 which encodes for polyunsaturated fatty acid elongase in the fatty acid biosynthesis pathway, fat-2 which encodes for delta12-desaturase in the polyunsaturated fatty acid synthesis pathway, gei-7 which encodes for a isocitrate lyase/malate synthase that functions in the glycoxylate cycle used in the production of glucose from fatty acids, and cyp-37A1 which encodes for cytochrome P450 (Coolon et al., 2009). Therefore, the bacterial diet a worm eats can elicit a metabolic response that changes according to the available nutrients in that diet.

The biological basis for the changes in development rate, fitness, and lifespan that result from the feeding of different microbes is likely complex, due to the fact that they may differ in nutritional content and produce different metabolites that can be taken up by the worm. As such, recent work has focused on a handful of E. coli strains that are commonly cultured and used for C. elegans research. These include E. coli B strain OP50, E. coli K12 strain HT115, and E. coli B and K12 hybrid strain HB101. These three diets have relatively similar overall protein and fat content, but HB101 and HT115 both contain a much higher level of carbohydrate when compared to OP50 (Brooks et al., 2009). Worms fed the OP50 diet show differential fat storage when compared to HB101 and HT115. Remarkably, feeding these diets has minimal impact on lifespan (Brooks et al., 2009). This demonstrates that ingesting different bacterial diets can induce changes in a worm's metabolic pathways to maintain homeostasis and is an example of metabolic adaptation — the capacity to effectively utilize various diets to fuel cellular and organismal functions.

Previous studies on the effect of consumption of different bacterial species on C. elegans have emphasized the idea that the calories are dissimilar between different diets and that different diets can affect fat metabolism, development, fertility, and lifespan of an animal (Shtonda and Avery, 2006; Soukas et al., 2009; Maier et al., 2010; Macneil and Walhout, 2013; MacNeil et al., 2013; Pang and Curran, 2014; Pang et al., 2014; Gracida and Eckmann, 2013; Coolon et al., 2009). The measurement of food intake is itself varied among studies. Classically, pharyngeal pumping has been used as a surrogate to estimate how much food is being ingested but recent studies using fluorescently labeled bacteria provide a more accurate measure (Avery and Shtonda, 2003; Chiang et al., 2006; Paek et al., 2012). When coupled with bacterial clearance assays (Gomez-Amaro et al., 2015), these two measures of “ins and outs” provide a nice correlation of food consumption. Recently, mass-spectrometry based methods to measure food consumption allow for higher resolution identification of ingested material (Gomez-Amaro et al., 2015; Liang et al., 2014). These more recent measures are of particular importance as they could be adapted to quantify the differences between ingestion of bacterial species, which can contain varied amounts of macronutrients that are important for generating energy for cellular processes, growth, and reproduction. In a study by Brooks et al., they found that worms fed OP50 or DA837, an OP50 derived strain, have a much higher amount of triacylglycerol (TAG) when compared to worms fed HB101 or HT115. Correspondingly, these worms also have larger and more intensely stained lipid droplets than those fed HB101 or HT115, as indicated by fixed Nile Red staining. Therefore, the fatty acid composition of the worm reflects the levels, and likely, the type of fatty acids in the diet.

Interestingly, C. elegans display behaviors that indicate a preference for bacterial diets that contribute to better fitness, as measured through growth, reproduction, and lifespan (Shtonda and Avery, 2006; Coolon et al., 2009; Abada et al., 2009). When presented with a choice between two different E. coli strains, HB101 and DA837, worms consistently choose the “higher quality” food HB101, which better supports growth (Shtonda and Avery, 2006; Avery and Shtonda, 2003). Furthermore, worms that are previously fed a higher quality diet display a strong tendency to leave poorer diet more readily, in search of a better choice (Shtonda and Avery, 2006). Along these lines, it was also discovered that C. elegans exhibit a dietary choice behavior that drives them to seek out the bacterial food source that confers the highest fitness, as measured by age-specific development, fecundity, and lifespan (Coolon et al., 2009). Taken together, these studies reveal that, similar to mammals, when given the choice, worms will seek out higher quality foods to support future life history events. The evolutionary pressures underlying these behaviors are clear, but the molecular mechanisms that drive these choices have yet to be uncovered, but will be of significant interest.

3. Gene-diet interactions

It is clear that diet and genetics play important roles in the regulation of metabolism, healthspan, and lifespan (Lynn and Curran, 2015). However, our understanding of these interactions is limited by studies that only query single gene mutations on one particular diet. For example, dietary restriction (DR) is one of the most effective and well-studied environmental manipulations that can influence the rate of aging and healthspan. The genetics underlying the effects of dietary restriction are multifaceted (Lakowski and Hekimi, 1998) but several genetic loci have been identified that are central to the response. In C. elegans, the benefits of dietary restriction require at least two transcription factors: the cytoprotective cap'n'collar transcription factor SKN-1 (Bishop and Guarente, 2007; Paek et al., 2012) and the FoxA transcription factor PHA-4 (Panowski et al., 2007). Early work suggested that the FoxO transcription factor DAF-16 was not required for the longevity response to dietary restriction (Lakowski and Hekimi, 1998). However, it was later found that DAF-16 and AMPK are key regulators of the DR response under specific methods of nutrient limitation (Greer and Brunet, 2009). As such, it is clear that genetics play an important role in the DR response.

While the above mentioned examples define a role for specific genes in regulating behaviors tied to the amount of food ingested, recent studies have uncovered genes that are specific to also the type of diet ingested (Pang and Curran, 2014; Pang et al., 2014; Khanna and Curran, 2015; Khanna et al., 2014) (Table 1). These diet-gene pair interactions emphasize the complexity of this system. Soukas et al. found that rict-1, a component of the Target of Rapamycin complex 2 (TORC2) influences fat metabolism and lifespan in a diet-dependent manner (Soukas et al., 2009). When fed HB101 or HT115, rict-1 mutant worms are leaner than those fed OP50. This was surprising because HB101 and HT115 have similar overall levels of protein and fat as OP50, while their carbohydrate levels are 3–5 times higher than that of OP50 (Brooks et al., 2009). Perhaps rict-1 mutant animals sense the three diets differently, altering their feeding behavior. Further investigation revealed that rict-1 mutant animals spend less time on the HB101 diet when compared to animals fed the OP50 bacteria; these mutant animals actually eat less when fed HB101. Therefore, rict-1 seems to play a role in regulating feeding behavior when an animal encounters diets of different qualities. This further demonstrates the importance of diet quality and how new roles for genes can be discovered through the usage of different bacterial diets. In addition, when compared to the wildtype animals, rict-1 mutant animals also show shortened lifespan when fed OP50, but are long lived on HB101 (Soukas et al., 2009). This seems to be mediated through dietary restriction since a rict-1; skn-1 double mutant is no longer long lived on HB101, and skn-1 is known to be required for dietary restriction (Bishop and Guarente, 2007). Soukas et al. also found that insulin signaling through akt-1 and daf-2 is required for the shortened lifespan on OP50 because double mutants rict-1; akt-1 and rict-1; daf-2 are no longer short-lived. Additionally, a rict-1; daf-16 double mutant has an even shorter lifespan than either single mutant, indicating that insulin signaling appears to contribute to rict-1 regulation of lifespan (Soukas et al., 2009). This study shows that the way an animal senses food and the specific downstream signaling pathways can be important for regulating the animal's adaptive capacity to different diets. However, we still do not know how this signaling occurs and the nature of the specific signals from variable diets that cause rict-1 mutant animals to have altered fat metabolism, feeding behavior, and lifespan.

Table 1
Diet-gene pair induced physiological changes in C. elegans.

Typically, researchers focus on glucose and lipids supplied by diet. However, recent research has now added dietary amino acids to the list of regulators of animal lifespan (Pang and Curran, 2014; Pang et al., 2014; Gracida and Eckmann, 2013; Schulz et al., 2007; Lee et al., 2009; Wang et al., 2008). For example, the role of the gene alh-6, a mitochondrial proline metabolism gene that encodes for 1-pyrroline-5-carboxylate dehydrogenase (P5CDH), in regulating lifespan on different diets was recently discovered (Pang and Curran, 2014; Pang et al., 2014). P5CDH is a mitochondrial enzyme that is needed to catalyze P5C to glutamate. Interestingly, alh-6 mutants were found to age prematurely when fed the OP50 strain of E. coli, but not HT115; a direct consequence of impaired mitochondrial function and organelle collapse (Pang and Curran, 2014). This represents a more recently defined dietgene pair. Furthermore, the reduced lifespan phenotype only occurs when worms are exposed to the OP50 diet during the developmental period between larval stage 3 and larval stage 4 and requires exposure throughout adulthood, suggesting that there may be critical stages in life where diet plays a more prominent role in aging. alh-6 mutants exhibit a shortened lifespan when proline was supplemented to the HT115 diet, but do not display a further reduced lifespan when proline was added to the OP50 diet; this implies that the accelerated aging was caused by the activation of the proline catabolism pathway and the accumulation of P5C, resulting in an increase in ROS (reactive oxygen species) and altered mitochondrial morphology (Pang and Curran, 2014; Pang et al., 2014). This suggests that specific diets have differential capacity to induce changes in organelle morphology as we age.

Another example of a specific genetic response induced by the type of diet is found in the tissue distribution of lipids in aged SKN-1 gain-of-function mutants (SKN-1 gf) when fed specific diets. When fed the OP50 diet, SKN-1 gf animals display a lipid depletion phenotype at the end of their reproductive period where their somatic lipid stores are mobilized to and retained in the germline, also called age-dependent somatic depletion of fat (Asdf). Conversely, this phenotype is not observed when the animals are fed an HT115 diet (Lynn et al., 2015). Similarly, alh-6 mutant animals fed OP50 deplete fat rapidly through the activation of SKN-1 during acute starvation, while those fed HT115 do not (Pang et al., 2014). Together, these studies show how genes involved in lipid metabolism can elicit a diet-dependent physiological response in an animal.

While the above examples emphasize overall dietary intake, small changes in diet, such as its micronutrient content, can also impact an organism. Micronutrients are vitamins and trace elements that are used as metabolites or cofactors in metabolic pathways, which can ultimately affect the health of an organism. Recent work done by MacNeil et al., has shown that C. elegans develops faster while consuming a diet of Comamonas DA1877 compared to E. coli OP50, even though the two bacterial species have similar macronutrient levels. In addition, by just adding a small amount of Comamonas DA1877 into E. coli OP50, they were able to recapitulate the accelerated development, suggesting that there is some signaling molecule from the Comamonas diet that induced this change. This was later identified as vitamin B12 (Macneil and Walhout, 2013; MacNeil et al., 2013). This shows that it is important to consider the entire nutritional content of a diet, rather than just looking at calories and macronutrient levels.

A greater appreciation and acknowledgement for the type of food sources used has emerged in the design of experiments to help uncover genetic pathways that modulate aging through dietary effects. This is the most prominent in feeding RNAi assays. The development of feeding RNAi libraries in bacteria has resulted in copious usage of this tool to perform large-scale genetic screens. Traditionally, RNAi in worms is routinely performed by feeding the E. coli K-12 strain HT115 because they are deficient in the dsRNA specific endonuclease RNAse III (Timmons and Fire, 1998; Wang and Barr, 2005; Timmons et al., 2001). However, usage of the HT115 bacteria as the food source raises the question of whether phenotypic screens, which were previously thought to be saturated, are truly penetrant. Recently, the development of an OP50 strain, engineered for delivering RNAi (Xiao et al., 2015), has proven to reveal new results in experiments previously performed with the HT115 RNAi strain. A push for using RNAi in both OP50 and HT115 background in laboratories is needed to fully flush out the genetic pathways that underlie diet-dependent regulation of development, reproduction, metabolism, and aging.

4. How are nutrients in diets sensed?

Dietary composition affects animal physiology, but the signaling pathways that are involved in helping an animal adapt to various diets are unclear. Since diets of variable quality can induce gene expression changes in the metabolic network, thus affecting the physiology state and life history traits of C. elegans, worms must have a way to sense and respond to these dietary cues. The physiological responses initiated at olfaction, and the smell of different bacteria can impact physiological outputs including behavior and reproduction (Sowa et al., 2015; Matsuki et al., 2006; Glater et al., 2014). Worms sense environmental stimuli through their sensory neurons, which contain specialized receptors that recognize various types of cues, including mechanical, thermal, gustatory, and olfactory stimuli (de Bono and Bargmann, 1998). Worms use their chemosensory amphid neurons to detect the volatile and water-soluble compounds metabolized and produced by E. coli and exhibit either attractive or repellant chemotaxis (Ward, 1973; Bargmann and Horvitz, 1991; Bargmann et al., 1993; Zhang et al., 2005). Once food is ingested, glucose levels rise, which in turn stimulates the release of insulin-like peptides, resulting in the increased uptake of glucose by cells. Insulin signaling is needed in both the nervous system and intestine for proper development, reproduction, and lifespan (Iser et al., 2007; Wolkow et al., 2000). The insulin/IGF-1 signaling pathway was the first longevity pathway to be discovered in C. elegans (Kenyon et al., 1993; Klass and Hirsh, 1976). Reduced expression of the DAF-2/IGF-1 receptor or the direct downstream kinase AGE-1/PI3K inactivates the downstream kinase signaling cascade, which results in the transcription factor DAF-16/FOXO translocating into the nucleus to turn on its target genes, ultimately extending the lifespan of the animal (Kenyon et al., 1993; Morris et al., 1996; Kimura et al., 1997; Lin et al., 1997; Ogg et al., 1997). Furthermore, mutations in the other three downstream targets of DAF-2 also cause extension of lifespan: AKT-1, PDK-1, and SGK-1 (Kimura et al., 1997; Paradis and Ruvkun, 1998; Paradis et al., 1999; Hertweck et al., 2004; Ashrafi et al., 2003).

Although neuroendocrine signaling pathways are important for food-seeking behaviors and for satiety (Iser et al., 2007; Bargmann and Horvitz, 1991; Wolkow et al., 2000; Kimura et al., 1997; Ren et al., 1996; Gallagher et al., 2013a; Gallagher et al., 2013b), their roles in lipid storage and mobilization are less clear. To test the role of these pathways in lipid metabolism, Watts and colleagues measured lipid levels in the daf-2 insulin receptor mutants and daf-7/TGF-β mutants fed HB101 or OP50 diet. Like wild type animals, these mutants contained lower levels of stored fat on HB101 when compared to on OP50. As such, the insulin/IGF and TGFβ signaling pathways do not seem to be directly involved in the diet-induced changes in fat storage in worms. This study identified pept-1, a gene that encodes an intestinal peptide transporter, to be essential for the differential fat storage in worms fed different diets (Brooks et al., 2009). The signaling events following exposure to different diets are sensed by pept-1 and result in the downstream changes in fat metabolism and reproductive output. This study shows that some nutritional cues can be sensed directly by the intestine. Further assessment of the roles that specific tissues, or even cells, play in mediating diet-dependent behaviors will be of critical importance.

Recent work from Maier et al. identified nmur-1, a mammalian homolog of the neuromedin U receptor, to be involved in the sensing of dietary cues from different food types and the regulation of lifespan through the neurosensory system in a diet-dependent manner. nmur-1 mutants live longer on OP50, but not on HT115 — another example of a diet-gene pair interaction (Maier et al., 2010). Remarkably, nmur-1 is also required for alh-6 in regulating lifespan in a food-dependent manner (Pang and Curran, 2014; Pang et al., 2014). However, we do not currently know the downstream targets of nmur-1 or its connection to the alh-6 pathway that allows the animal to appropriately respond to OP50 versus HT115. It will be interesting to see if there are other neuropeptide signaling pathways involved in the processing of different bacterial diet signals.

Nuclear hormone receptors (NHRs) are ligand-activated transcription factors that sense environmental signals and regulate many fundamental physiological processes, including metabolism, development, and reproduction (Aranda and Pascual, 2001; Sonoda et al., 2008; Pardee et al., 2011). Humans have 48 of these NHRs, while C. elegans have an astounding number of 271 NHRs, many of which are homologs to human NHRs but have yet to be characterized (Pardee et al., 2011; Reece-Hoyes et al., 2005). Perhaps some of these NHRs are involved in sensing certain compounds from the bacteria and activating a downstream physiological response. The use of multiple bacterial diets in all studies will help us elucidate the mechanisms underlying these complex diet-gene response pathways.

5. The future requires a defined diet

Although convenient, the use of a living organism, such as OP50, as a food source presents additional complications when trying to define diet-gene interactions. The metabolic status of the microbes and their pathogenicity (Kim, 2013) to the host are both key determinates of host–microbe interactions that impact health and lifespan. Previous attempts to synthesize a defined chemical diet for C. elegans have been unsuccessful for lifespan studies (Houthoofd et al., 2002a; Johnson et al., 1984; Lenaerts et al., 2008; Castelein et al., 2014). Formulation of bacteria-free culture systems has always impacted developmental timing, growth, metabolism and reproduction (Houthoofd et al., 2002a; Johnson et al., 1984; Castelein et al., 2014; Szewczyk et al., 2006). As each of these biological processes has profound impacts on lifespan, the utility of these abiotic growth systems for aging is confounded.

In order to decipher the effects of individual macro- or micronutrient on an animal's physiology, the development of a defined diet that is composed of known concentration of each nutritional component is needed. The development of defined diets has helped other fields in investigating the role of dietary components in aging. For example, a study done by Lee et al. in Drosophila melanogaster has found that a protein-to-carbohydrate ratio of 1:16 resulted in the flies living longer, while a ratio of 1:4 maximizes reproduction (Lee et al., 2008b). Similarly, another study done in mice demonstrated that different ratios of macronutrients have opposing effects on lifespan and reproduction (Solon-Biet et al., 2015a; Solon-Biet et al., 2015b; Solon-Biet et al., 2015c). Additional studies using a defined diet in flies revealed how different concentrations of glucose and methionine can affect lifespan (Troen et al., 2007). Moreover, recent development of an entirely holidic diet for D. melanogaster resolves the prior inconsistencies in experiments between laboratories due to the use of oligidic diet, and also allows the manipulation of individual dietary component in nutritional studies while maintaining similar lifespan and fecundity as before with a minimal effect on developmental rate (Piper et al., 2014) With a defined diet, the complicated diet-fitness response in an animal can be unraveled using methods such as a “Geometric Framework” that focuses on first understanding the target nutrient intake of the specific organism, changing intake ratios so as to observe how the organism adjusts, and finally, mapping this information to organism fitness (Simpson and Raubenheimer, 2007; Simpson and Raubenheimer, 2012).

Without a defined diet, the effects from any individual dietary component cannot be separated. This problem is not limited to C. elegans; an example of the disadvantage of not having a defined diet is highlighted in the conflicting findings between the two 20-year studies of dietary restriction (DR) in rhesus monkeys by National Institute on Aging (NIA) and Wisconsin National Primate Research Center (WNPRC). The study done by NIA had concluded that 30% DR did not extend the lifespan of these animals (Mattison et al., 2012), while the WNPRC study found that 30% DR significantly increases their lifespan (Colman et al., 2009). The problem with comparing the results of these two studies is that the dietary composition of the food they fed the animals is very different. The composition of the diet in the NIA study in many aspects is overall more nutritious than that of WNPRC. NIA study's diet contains 3.9% sucrose while the WNPRC's diet contains 28.5%. The sources of protein for the NIA study include wheat, corn, soybean, fish, and alfalfa meal, while the WNPRC sole protein source was lactalbumin. The NIA study's diet has fat derived from soy, wheat, corn, and fish, whereas the WNPRC study's diet contains fat from corn oil (Mattison et al., 2012; Colman et al., 2009). Therefore, in order to better understand how a specific amount of a nutrient in a diet can affect our physiology and even the rate we age, a chemically defined diet is needed for metabolism- and diet-centric studies.

For worms, defining a diet is difficult because its food source, E. coli and other soil bacteria, are living organisms, some of which are also pathogenic (Tan et al., 1999; Sifri et al., 2005). For instance, C. elegans live longer on UV-killed or non-proliferating version of the standard OP50 diet (Gems and Riddle, 2000; Garigan et al., 2002). Several groups have attempted to generate a bacteria-free chemically defined diet, but most are exceptionally complicated to make and as previously stated, impact several life history events and phenotypes (Lenaerts et al., 2008; Szewczyk et al., 2003). In addition, there is emerging evidence that the host-microbe relationship can be symbiotic, where certain metabolites produced by the bacteria – like nitric oxide – can be utilized by worms, and have significant impact on life- and healthspan (Gusarov et al., 2013). One study demonstrated that folate can negatively regulate the lifespan of C. elegans. This was due to a mutation in aroD gene of the bacterial food source, which resulted in decreased folate availability for the worms; when fed this diet, worms lived longer (Virk et al., 2012). However, whether the effect of decreased folate synthesis on extending lifespan is a result that acts directly on the worm or through the bacteria remains to be determined. As such, while a defined diet will remove the pathogenic effect of bacteria on C. elegans, further study is still needed to fully appreciate the totality of the relationship bacteria have with their worm hosts.

6. Conclusions and perspectives

Although much work has been done in identifying the metabolic signaling pathways in C. elegans and in characterizing the effects of different bacterial diets on its life history traits, the molecular mechanisms behind diet-induced genetic responses in an organism and the relationship between diet and lifespan remains a complicated problem to solve. Furthermore, modernization of society entails the mass production of highly processed foods that are often high in caloric content but low in nutritional value and the global trend of increasing incidences of obesity; this makes understanding the interplay between dietary composition and metabolic pathways more important than ever. Having a defined diet in laboratory studies will be helpful in dissecting the specific molecules that contribute to aging and healthspan, but there are many hurdles to overcome before this can be accomplished in C. elegans, since worms currently require a “live diet” to provide important metabolites (Lenaerts et al., 2008). Despite what still remains to be overcome, C. elegans continues to be a useful model organism for diet and aging studies for many reasons, including its genetic homology to humans, genetic tractability, as well as the ability to conduct large-scale experiments in a short amount of time. Complex modeling techniques, such as those found in the field of systems biology, may help uncover complicated genetic interactions between different pathways and differentiate a dietary response from a pathogenic response in C. elegans to its bacterial diet, as shown in recent work by Watson et al. (Watson et al., 2013). Work in C. elegans isolated from the wild may help contribute to identification of new diet-gene pairs masked by using the traditional wildtype "N2" strain that has been maintained on the standard OP50 diet for a long time. Continuing work in dietary effects on the overall health and aging of an organism will undoubtedly contribute to a future where diet can be more personalized, incorporating the genetic makeup of an individual to promote better aging.

References

  • Abada EA, et al. C. elegans behavior of preference choice on bacterial food. Mol. Cells. 2009;28(3):209–213. [PubMed]
  • Andersen EC, et al. Chromosome-scale selective sweeps shape Caenorhabditis elegans genomic diversity. Nat. Genet. 2012;44(3):285–290. [PMC free article] [PubMed]
  • Aranda A, Pascual A. Nuclear hormone receptors and gene expression. Physiol. Rev. 2001;81(3):1269–1304. [PubMed]
  • Arvanitis M, Glavis-Bloom J, Mylonakis E. C. elegans for anti-infective discovery. Curr. Opin. Pharmacol. 2013;13(5):769–774. [PubMed]
  • Asghar O, et al. Obesity, diabetes and atrial flbrillation; epidemiology, mechanisms and interventions. Curr. Cardiol. Rev. 2012;8(4):253–264. [PMC free article] [PubMed]
  • Ashrafi K, et al. Genome-wide RNAi analysis of Caenorhabditis elegans fat regulatory genes. Nature. 2003;421(6920):268–272. [PubMed]
  • Avery L, Shtonda BB. Food transport in the C. elegans pharynx. J. Exp. Biol. 2003;206(14):2441–2457. [PMC free article] [PubMed]
  • Bargmann CI, Horvitz HR. Control of larval development by chemosensory neurons in Caenorhabditis elegans. Science. 1991;251(4998):1243–1246. [PubMed]
  • Bargmann CI, Hartwieg E, Horvitz HR. Odorant-selective genes and neurons mediate olfaction in C. elegans. Cell. 1993;74(3):515–527. [PubMed]
  • Bishop N, Guarente L. Two neurons mediate diet-restriction-induced longevity in C. elegans. Nature. 2007;447(7144):545–549. [PubMed]
  • Braeckman BP, Houthoofd K, Vanfleteren JR. Assessing metabolic activity in aging Caenorhabditis elegans: concepts and controversies. Aging Cell. 2002;1(2):82–88. discussion 102-3. [PubMed]
  • Braeckman BP, Demetrius L, Vanfleteren JR. The dietary restriction effect in C. elegans and humans: is the worm a one-millimeter human? Biogerontology. 2006 [PubMed]
  • Brenner S. The genetics of Caenorhabditis elegans. Genetics. 1974;77(1):71–94. [PubMed]
  • Brignull HR, et al. Modeling polyglutamine pathogenesis in C. elegans. Methods Enzymol. 2006;412:256–282. [PubMed]
  • Brooks KK, Liang B, Watts JL. The influence of bacterial diet on fat storage in C. elegans. PLoS One. 2009;4(10):e7545. [PMC free article] [PubMed]
  • Burnell AM, et al. Alternate metabolism during the dauer stage of the nematode Caenorhabditis elegans. Exp. Gerontol. 2005;40(11):850–856. [PubMed]
  • Castelein N, et al. Mitochondrial efficiency is increased in axenically cultured Caenorhabditis elegans. Exp. Gerontol. 2014;56:26–36. [PubMed]
  • Chiang JT, et al. Evolution of pharyngeal behaviors and neuronal functions in free-living soil nematodes. J. Exp. Biol. 2006;209(10):1859–1873. [PubMed]
  • Colman RJ, et al. Caloric restriction delays disease onset and mortality in rhesus monkeys. Science. 2009;325(5937):201–204. [PMC free article] [PubMed]
  • Conus F, Rabasa-Lhoret R, Peronnet F. Characteristics of metabolically obese normal-weight (MONW) subjects. Appl. Physiol. Nutr. Metab. 2007;32(1):4–12. [PubMed]
  • Coolon JD, et al. Caenorhabditis elegans genomic response to soil bacteria predicts environment-specific genetic effects on life history traits. PLoS Genet. 2009;5(6):e1000503. [PMC free article] [PubMed]
  • Curran S, Ruvkun G. Lifespan regulation by evolutionarily conserved genes essential for viability. PLoS Genet. 2007;3(4):e56. [PubMed]
  • de Bono M, Bargmann CI. Natural variation in a neuropeptide Y receptor homolog modifies social behavior and food response in C. elegans. Cell. 1998;94(5):679–689. [PubMed]
  • Desalermos A, et al. Using C. elegans for antimicrobial drug discovery. Expert Opin. Drug Discovery. 2011;6(6):645–652. [PMC free article] [PubMed]
  • Dillin A, et al. Rates of behavior and aging specified by mitochondrial function during development. Science. 2002;298(5602):2398–2401. [PubMed]
  • Duveau F, Felix MA. Role of pleiotropy in the evolution of a cryptic developmental variation in Caenorhabditis elegans. PLoS Biol. 2012;10(1):e1001230. [PMC free article] [PubMed]
  • Felix MA, Duveau F. Population dynamics and habitat sharing of natural populations of Caenorhabditis elegans and C. briggsae. BMC Biol. 2012;10:59. [PMC free article] [PubMed]
  • Flegal KM, et al. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013;309(1):71–82. [PMC free article] [PubMed]
  • Fontana L, Partridge L, Longo VD. Extending healthy life span—from yeast to humans. Science. 2010;328(5976):321–326. [PMC free article] [PubMed]
  • Frezal L, Felix MA. C. elegans outside the Petri dish. Elife. 2015:4. [PMC free article] [PubMed]
  • Gallagher T, et al. The geometry of locomotive behavioral states in C. elegans. PLoS One. 2013a;8(3):e59865. [PMC free article] [PubMed]
  • Gallagher T, et al. ASI regulates satiety quiescence in C. elegans. J. Neurosci. 2013b;33(23):9716–9724. [PMC free article] [PubMed]
  • Garigan D, et al. Genetic analysis of tissue aging in Caenorhabditis elegans: a role for heat-shock factor and bacterial proliferation. Genetics. 2002;161(3):1101–1112. [PubMed]
  • Gems D, Riddle DL. Genetic, behavioral and environmental determinants of male longevity in Caenorhabditis elegans. Genetics. 2000;154(4):1597–1610. [PubMed]
  • Glater EE, Rockman MV, Bargmann CI. Multigenic natural variation underlies Caenorhabditis elegans olfactory preference for the bacterial pathogen Serratia marcescens. G3 (Bethesda) 2014;4(2):265–276. [PMC free article] [PubMed]
  • Gomez-Amaro RL, et al. Measuring food intake and nutrient absorption in Caenorhabditis elegans. Genetics. 2015;200(2):443–454. [PMC free article] [PubMed]
  • Gracida X, Eckmann CR. Fertility and germline stem cell maintenance under different diets requires nhr-114/HNF4 in C. elegans. Curr. Biol. 2013;23(7):607–613. [PubMed]
  • Greer EL, Brunet A. Different dietary restriction regimens extend lifespan by both independent and overlapping genetic pathways in C. elegans. Aging cell. 2009;8(2):113–127. [PMC free article] [PubMed]
  • Greer EL, et al. An AMPK-FOXO pathway mediates longevity induced by a novel method of dietary restriction in C. elegans. Curr. Biol. 2007;17(19):1646–1656. [PMC free article] [PubMed]
  • Greer EL, et al. Transgenerational epigenetic inheritance of longevity in Caenorhabditis elegans. Nature. 2011;479(7373):365–371. [PMC free article] [PubMed]
  • Greer EL, et al. A histone methylation network regulates transgenerational epigenetic memory in C. elegans. Cell. Rep. 2014;7(1):113–126. [PMC free article] [PubMed]
  • Gusarov I, et al. Bacterial nitric oxide extends the lifespan of C. elegans. Cell. 2013;152(4):818–830. [PubMed]
  • Hamilton B, et al. A systematic RNAi screen for longevity genes in C. elegans. Genes Dev. 2005;19(13):1544–1555. [PubMed]
  • Hansen M, et al. New genes tied to endocrine, metabolic, and dietary regulation of lifespan from a Caenorhabditis elegans genomic RNAi screen. PLoS Genet. 2005a;1(1):119–128. [PMC free article] [PubMed]
  • Hansen M, et al. New genes tied to endocrine, metabolic, and dietary regulation of lifespan from a Caenorhabditis elegans genomic RNAi screen. PLoS Genet. 2005b;1(1):e17. [PMC free article] [PubMed]
  • Hansen M, et al. Lifespan extension by conditions that inhibit translation in Caenorhabditis elegans. Aging Cell. 2007;6(1):95–110. [PubMed]
  • Hertweck M, Gobel C, Baumeister R. C. elegans SGK-1 is the critical component in the Akt/PKB kinase complex to control stress response and life span. Dev. Cell. 2004;6(4):577–588. [PubMed]
  • Hodgkin J, Doniach T. Natural variation and copulatory plug formation in Caenorhabditis elegans. Genetics. 1997;146(1):149–164. [PubMed]
  • Houthoofd K, et al. Axenic growth up-regulates mass-specific metabolic rate, stress resistance, and extends life span in Caenorhabditis elegans. Exp. Gerontol. 2002a;37(12):1371–1378. [PubMed]
  • Houthoofd K, et al. No reduction of metabolic rate in food restricted Caenorhabditis elegans. Exp. Gerontol. 2002b;37(12):1359–1369. [PubMed]
  • Houthoofd K, et al. Life extension via dietary restriction is independent of the Ins/ IGF-1 signalling pathway in Caenorhabditis elegans. Exp. Gerontol. 2003;38(9):947–954. [PubMed]
  • Houthoofd K, et al. DAF-2 pathway mutations and food restriction in aging Caenorhabditis elegans differentially affect metabolism. Neurobiol. Aging. 2005a;26(5):689–696. [PubMed]
  • Houthoofd K, et al. Metabolism, physiology and stress defense in three aging Ins/ IGF-1 mutants of the nematode Caenorhabditis elegans. Aging Cell. 2005b;4(2):87–95. [PubMed]
  • Houthoofd K, et al. Dietary restriction in the nematode Caenorhabditis elegans. Interdiscip. Top. Gerontol. 2007;35:98–114. [PubMed]
  • Iser WB, Gami MS, Wolkow CA. Insulin signaling in Caenorhabditis elegans regulates both endocrine-like and cell-autonomous outputs. Dev. Biol. 2007;303(2):434–447. [PMC free article] [PubMed]
  • Jia K, Chen D, Riddle DL. The TOR pathway interacts with the insulin signaling pathway to regulate C. elegans larval development, metabolism and life span. Development. 2004;131(16):3897–3906. [PubMed]
  • Johnson TE, et al. Arresting development arrests aging in the nematode Caenorhabditis elegans. Mech. Ageing Dev. 1984;28(1):23–40. [PubMed]
  • Kenyon C, et al. A C. elegans mutant that lives twice as long as wild type. Nature. 1993;366(6454):461–464. [PubMed]
  • Khanna AP, Curran SP. Emerging roles for MAF1 beyond the regulation of RNA polymerase III activity. J. Mol. Biol. 2015 .A. [PMC free article] [PubMed]
  • Khanna A, Johnson DL, Curran SP. Physiological roles for mafr-1 in reproduction and lipid homeostasis. Cell Rep. 2014;9(6):2180–2191. [PMC free article] [PubMed]
  • Kim DH. Bacteria and the aging and longevity of Caenorhabditis elegans. Annu. Rev. Genet. 2013;47:233–246. [PubMed]
  • Kimura KD, et al. daf-2, an insulin receptor-like gene that regulates longevity and diapause in Caenorhabditis elegans. Science. 1997;277(5328):942–946. [PubMed]
  • Kiontke KC, et al. A phylogeny and molecular barcodes for Caenorhabditis, with numerous new species from rotting fruits. BMC Evol. Biol. 2011;11:339. [PMC free article] [PubMed]
  • Klass M, Hirsh D. Non-ageing developmental variant of Caenorhabditis elegans. Nature. 1976;260(5551):523–525. [PubMed]
  • Lakowski B, Hekimi S. The genetics of caloric restriction in Caenorhabditis elegans. Proc. Natl. Acad. Sci. U. S. A. 1998;95(22):13091–13096. [PubMed]
  • Lee C, Longo VD. Fasting vs dietary restriction in cellular protection and cancer treatment: from model organisms to patients. Oncogene. 2011;30(30):3305–3316. [PubMed]
  • Lee SS, et al. A systematic RNAi screen identifies a critical role for mitochondria in C. elegans longevity. Nat. Genet. 2003;33(1):40–48. [PubMed]
  • Lee I, et al. A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans. Nat. Genet. 2008a;40(2):181–188. [PubMed]
  • Lee KP, et al. Lifespan and reproduction in Drosophila: new insights from nutritional geometry. Proc. Natl. Acad. Sci. U. S. A. 2008b;105(7):2498–2503. [PubMed]
  • Lee SJ, Murphy CT, Kenyon C. Glucose shortens the life span of C. elegans by downregulating DAF-16/FOXO activity and aquaporin gene expression. Cell Metab. 2009;10(5):379–391. [PMC free article] [PubMed]
  • Lenaerts I, et al. Dietary restriction of Caenorhabditis elegans by axenic culture reflects nutritional requirement for constituents provided by metabolically active microbes. J. Gerontol. A Biol. Sci. Med. Sci. 2008;63(3):242–252. [PMC free article] [PubMed]
  • Liang V, et al. Altered proteostasis in aging and heat shock response in C. elegans revealed by analysis of the global and de novo synthesized proteome. Cell. Mol. Life Sci. 2014;71(17):3339–3361. [PMC free article] [PubMed]
  • Libina N, Berman J, Kenyon C. Tissue-specific activities of C. elegans DAF-16 in the regulation of lifespan. Cell. 2003;115(4):489–502. [PubMed]
  • Lin K, et al. daf-16: an HNF-3/forkhead family member that can function to double the life-span of Caenorhabditis elegans. Science. 1997;278(5341):1319–1322. [PubMed]
  • Lynn DA, Curran SP. The SKN-1 hunger games: may the odds be ever in your favor. Worm. 2015;4(3):e1078959. [PMC free article] [PubMed]
  • Lynn DA, et al. 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. 2015;112(50):15378–15383. [PubMed]
  • Ma Y, et al. Association between dietary carbohydrates and body weight. Am. J. Epidemiol. 2005;161(4):359–367. [PMC free article] [PubMed]
  • Macneil LT, Walhout AJ. Food, pathogen, signal: the multifaceted nature of a bacterial diet. Worm. 2013;2(4):e26454. [PMC free article] [PubMed]
  • MacNeil LT, et al. Diet-induced developmental acceleration independent of TOR and insulin in C. elegans. Cell. 2013;153(1):240–252. [PMC free article] [PubMed]
  • Maglich JM, et al. Comparison of complete nuclear receptor sets from the human, Caenorhabditis elegans and Drosophila genomes. Genome Biol. 2001;2(8) (p. RESEARCH0029) [PMC free article] [PubMed]
  • Maier W, et al. A neuromedin U receptor acts with the sensory system to modulate food type-dependent effects on C. elegans lifespan. PLoS Biol. 2010;8(5):e1000376. [PMC free article] [PubMed]
  • Mair W, Dillin A. Aging and survival: the genetics of life span extension by dietary restriction. Annu. Rev. Biochem. 2008;77:727–754. [PubMed]
  • Marsh EK, May RC. Caenorhabditis elegans, a model organism for investigating immunity. Appl. Environ. Microbiol. 2012;78(7):2075–2081. [PMC free article] [PubMed]
  • Matsuki M, Kunitomo H, Iino Y. Goalpha regulates olfactory adaptation by antagonizing Gqalpha-DAG signaling in Caenorhabditis elegans. Proc. Natl. Acad. Sci. U. S. A. 2006;103(4):1112–1117. [PubMed]
  • Mattison JA, et al. Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study. Nature. 2012;489(7415):318–321. [PMC free article] [PubMed]
  • Maures TJ, et al. The H3K27 demethylase UTX-1 regulates C. elegans lifespan in a germline-independent, insulin-dependent manner. Aging Cell. 2011;10(6):980–990. [PMC free article] [PubMed]
  • Miller WC, et al. Dietary fat, sugar, and fiber predict body fat content. J. Am. Diet. Assoc. 1994;94(6):612–615. [PubMed]
  • Montalvo-Katz S, et al. Association with soil bacteria enhances p38-dependent infection resistance in Caenorhabditis elegans. Infect. Immun. 2013;81(2):514–520. [PMC free article] [PubMed]
  • Morris JZ, Tissenbaum HA, Ruvkun G. A phosphatidylinositol-3-OH kinase family member regulating longevity and diapause in Caenorhabditis elegans. Nature. 1996;382(6591):536–539. [PubMed]
  • Odermatt A. The Western-style diet: a major risk factor for impaired kidney function and chronic kidney disease. Am. J. Physiol. Renal Physiol. 2011;301(5):F919–F931. [PubMed]
  • Ogden CL, et al. Prevalence of childhood and adult obesity in the United States, 2011–2012. JAMA. 2014;311(8):806–814. [PMC free article] [PubMed]
  • Ogg S, et al. The fork head transcription factor DAF-16 transduces insulin-like metabolic and longevity signals in C. elegans. Nature. 1997;389(6654):994–999. [PubMed]
  • Paek J, et al. Mitochondrial SKN-1/Nrf mediates a conserved starvation response. Cell Metab. 2012;16(4):526–537. [PMC free article] [PubMed]
  • Pang S, Curran SP. Longevity and the long arm of epigenetics: acquired parental marks influence lifespan across several generations. BioEssays. 2012;34(8):652–654. [PMC free article] [PubMed]
  • Pang S, Curran SP. Adaptive capacity to bacterial diet modulates aging in C. elegans. Cell Metab. 2014;19(2):221–231. [PMC free article] [PubMed]
  • Pang S, et al. SKN-1 and Nrf2 couples proline catabolism with lipid metabolism during nutrient deprivation. Nat. Commun. 2014;5:5048. [PMC free article] [PubMed]
  • Panowski S, et al. PHA-4/Foxa mediates diet-restriction-induced longevity of C. elegans. Nature. 2007;447(7144):550–555. [PubMed]
  • Paradis S, Ruvkun G. Caenorhabditis elegans Akt/PKB transduces insulin receptor-like signals from AGE-1 PI3 kinase to the DAF-16 transcription factor. Genes Dev. 1998;12(16):2488–2498. [PubMed]
  • Paradis S, et al. A PDK1 homolog is necessary and sufficient to transduce AGE-1 PI3 kinase signals that regulate diapause in Caenorhabditis elegans. Genes Dev. 1999;13(11):1438–1452. [PubMed]
  • Pardee K, Necakov AS, Krause H. Nuclear receptors: small molecule sensors that coordinate growth, metabolism and reproduction. Subcell. Biochem. 2011;52:123–153. [PubMed]
  • Pereira MA, et al. Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet. 2005;365(9453):36–42. [PubMed]
  • Piper MD, et al. A holidic medium for Drosophila melanogaster. Nat. Methods. 2014;11(1):100–105. [PMC free article] [PubMed]
  • Popkin BM. Global nutrition dynamics: the world is shifting rapidly toward a diet linked with noncommunicable diseases. Am. J. Clin. Nutr. 2006;84(2):289–298. [PubMed]
  • Studies C, et al. Body-mass index and cause-specific mortality in 900,000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373(9669):1083–1096. [PMC free article] [PubMed]
  • Hoyes JS, et al. A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks. Genome Biol. 2005;6(13):R110. [PMC free article] [PubMed]
  • Reis-Rodrigues P, et al. Proteomic analysis of age-dependent changes in protein solubility identifies genes that modulate lifespan. Aging cell. 2012;11(1):120–127. [PMC free article] [PubMed]
  • Ren P, et al. Control of C. elegans larval development by neuronal expression of a TGF-beta homolog. Science. 1996;274(5291):1389–1391. [PubMed]
  • Rose MR, Archer MA. Genetic analysis of mechanisms of aging. Curr. Opin. Genet. Dev. 1996;6(3):366–370. [PubMed]
  • Rosenheck R. Fast food consumption and increased caloric intake: a systematic review of a trajectory towards weight gain and obesity risk. Obes. Rev. 2008;9(6):535–547. [PubMed]
  • Sandholt CH, Hansen T, Pedersen O. Beyond the fourth wave of genome-wide obesity association studies. Nutr. Diabetes. 2012;2:e37. [PMC free article] [PubMed]
  • Schulz TJ, et al. Glucose restriction extends Caenorhabditis elegans life span by inducing mitochondrial respiration and increasing oxidative stress. Cell Metab. 2007;6(4):280–293. [PubMed]
  • Shtonda BB, Avery L. Dietary choice behavior in Caenorhabditis elegans. J. Exp. Biol. 2006;209(1):89–102. [PMC free article] [PubMed]
  • Sifri CD, Begun J, Ausubel FM. The worm has turned—microbial virulence modeled in Caenorhabditis elegans. Trends Microbiol. 2005;13(3):119–127. [PubMed]
  • Simpson SJ, Raubenheimer D. Caloric restriction and aging revisited: the need for a geometric analysis of the nutritional bases of aging. J. Gerontol. A Biol. Sci. Med. Sci. 2007;62(7):707–713. [PubMed]
  • Simpson SJ, Raubenheimer D. In: The Nature of Nutrition: A Unifying Framework from Animal Adaptation to Human Obesity. Simpson SJ, Raubenheimer D, editors. Princeton University Press; 2012.
  • Solon-Biet SM, et al. Dietary protein to carbohydrate ratio and caloric restriction: comparing metabolic outcomes in mice. Cell Rep. 2015a;11(10):1529–1534. [PMC free article] [PubMed]
  • Solon-Biet SM, et al. Macronutrients and caloric intake in health and longevity. J. Endocrinol. 2015b;226(1):R17–R28. [PMC free article] [PubMed]
  • Solon-Biet SM, et al. Macronutrient balance, reproductive function, and lifespan in aging mice. Proc. Natl. Acad. Sci. U. S. A. 2015c;112(11):3481–3486. [PubMed]
  • Sonoda J, Pei L, Evans RM. Nuclear receptors: decoding metabolic disease. FEBS Lett. 2008;582(1):2–9. [PMC free article] [PubMed]
  • Soukas AA, et al. Rictor/TORC2 regulates fat metabolism, feeding, growth, and life span in Caenorhabditis elegans. Genes Dev. 2009;23(4):496–511. [PubMed]
  • Sowa JN, et al. Olfaction modulates reproductive plasticity through neuroendocrine signaling in Caenorhabditis elegans. Curr. Biol. 2015;25(17):2284–2289. [PMC free article] [PubMed]
  • Sulston JE, Brenner S. The DNA of Caenorhabditis elegans. Genetics. 1974;77(1):95–104. [PubMed]
  • Szewczyk NJ, Kozak E, Conley CA. Chemically defined medium and Caenorhabditis elegans. BMC Biotechnol. 2003;3:19. [PMC free article] [PubMed]
  • Szewczyk NJ, et al. Delayed development and lifespan extension as features of metabolic lifestyle alteration in C. elegans under dietary restriction. J. Exp. Biol. 2006;209(20):4129–4139. [PubMed]
  • Tan MW, Mahajan-Miklos S, Ausubel FM. Killing of Caenorhabditis elegans by Pseudomonas aeruginosa used to model mammalian bacterial pathogenesis. Proc. Natl. Acad. Sci. U. S. A. 1999;96(2):715–720. [PubMed]
  • Timmons L, Fire A. Specific interference by ingested dsRNA. Nature. 1998;395(6705):854. [PubMed]
  • Timmons L, Court DL, Fire A. Ingestion of bacterially expressed dsRNAs can produce specific and potent genetic interference in Caenorhabditis elegans. Gene. 2001;263(1–2):103–112. [PubMed]
  • Troen AM, et al. Lifespan modification by glucose and methionine in Drosophila melanogaster fed a chemically defined diet. Age (Dordr.) 2007;29(1):29–39. [PMC free article] [PubMed]
  • Vellai T, et al. Genetics: influence of TOR kinase on lifespan in C. elegans. Nature. 2003;426(6967):620. [PubMed]
  • Virk B, et al. Excessive folate synthesis limits lifespan in the C. elegans: E. coli aging model. BMC Biol. 2012;10:67. [PMC free article] [PubMed]
  • Wang J, Barr MM. RNA interference in Caenorhabditis elegans. Methods Enzymol. 2005;392:36–55. [PubMed]
  • Wang MC, O'Rourke EJ, Ruvkun G. Fat metabolism links germline stem cells and longevity in C. elegans. Science. 2008;322(5903):957–960. [PMC free article] [PubMed]
  • Ward S. Chemotaxis by the nematode Caenorhabditis elegans: identification of attractants and analysis of the response by use of mutants. Proc. Natl. Acad. Sci. U. S. A. 1973;70(3):817–821. [PubMed]
  • Watson E, et al. Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response. Cell. 2013;153(1):253–266. [PMC free article] [PubMed]
  • Williams MJ, et al. What model organisms and interactomics can reveal about the genetics of human obesity. Cell. Mol. Life Sci. 2012;69(22):3819–3834. [PubMed]
  • Wolkow CA, et al. Regulation of C. elegans life-span by insulinlike signaling in the nervous system. Science. 2000;290(5489):147–150. [PubMed]
  • Xiao R, et al. RNAi interrogation of dietary modulation of development, metabolism, behavior, and aging in C. elegans. Cell Rep. 2015;11(7):1123–1133. [PMC free article] [PubMed]
  • Yang F, et al. An ARC/Mediator subunit required for SREBP control of cholesterol and lipid homeostasis. Nature. 2006;442(7103):700–704. [PubMed]
  • Zhang Y, Lu H, Bargmann CI. Pathogenic bacteria induce aversive olfactory learning in Caenorhabditis elegans. Nature. 2005;438(7065):179–184. [PubMed]
  • Zheng J, Greenway FL. Caenorhabditis elegans as a model for obesity research. Int. J. Obes. 2012;36(2):186–194. [PubMed]