Understanding how animals age may help us to prevent age-related or chronic diseases, such as type 2 diabetes and cancer. The tiny nematode worm known as C. elegans is widely used as a model to study aging and has enabled researchers to identify factors that can slow down the aging process. Like other animals, these worms contain female and male sex cells that originate from cells called germline stem cells. The normal lifespan of C. elegans is less than three weeks, but when the germline stem cells are removed, the worms can live for much longer.

Reproduction requires a lot of energy, which is typically ‘stored’ in molecules of fat. Animals utilize their fat reserves and release this energy by breaking the fat molecules down into smaller molecules as part of their ‘metabolism’. Worms that have had their germline stem cells removed have altered fat metabolism, and it is thought that this may contribute to their increased lifespan. These worms have increased levels of a protein called SKN-1, which alters fat metabolism and helps to protect cells from toxic molecules and other stresses.

SKN-1 works by regulating the activity (or ‘expression’) of many genes in cells, but it is not clear how this increases the lifespan of the worms. Steinbaugh et al. studied mutant worms that were lacking SKN-1. Unlike normal worms, when the germline stem cells were removed from the mutants, their lifespan did not increase. Further experiments analyzed the genes that are switched on by SKN-1, and identified many that are involved in fat metabolism, in degrading other proteins, and in detoxifying harmful molecules. The experiments also found that SKN-1 reduces the overall amount of fat stored in the body.

Next, Steinbaugh et al. investigated how SKN-1 stops fat from being stored. During reproduction, cells in the gut produce yolk—which is rich in fats—that will be provided to germ cells to nourish the developing embryo. Worms lacking germline stem cells are not able to reproduce, but they continue to make yolk. Steinbaugh et al. found that the build up of the yolk activates SKN-1, which in turn inhibits the further accumulation of fats.

Steinbaugh et al.'s findings show that SKN-1 can be activated by fat molecules and plays a direct role in controlling the amount of fat stored in the body of the worms. A future challenge will be to identify the specific fat molecules that activate SKN-1, which could provide a model for understanding how specific fats in human diets could have wide-ranging health benefits.

The nematode Caenorhabditis elegans has been invaluable for identifying mechanisms that slow aging and may prevent chronic disease (Kenyon, 2010). An intriguing finding that was first made in this organism is that when germline stem cells (GSCs) are ablated, mechanisms are activated in somatic tissues that protect against stress and increase lifespan (Hsin and Kenyon, 1999; Kenyon, 2010; Antebi, 2013; Hansen et al., 2013). GSC loss also increases lifespan in Drosophila melanogaster (Flatt et al., 2008), and castration has been associated with longevity in men (Min et al., 2012), suggesting that this relationship might be conserved. These beneficial effects of GSC removal may have evolved to maximize reproductive fitness under adversity (Partridge et al., 2005; Kenyon, 2010). This relationship provides paradigms for how tissue non-autonomous signals influence aging (Kenyon, 2010), and how a stem cell population communicates with the ‘niche’ that sustains it (Jones and Wagers, 2008).

In C. elegans, the effects of GSC absence have been studied by laser ablation of GSC precursors, which results in a complete loss of GSCs, or by analysis of genetic mutants in which GSC proliferation is inhibited so that the GSC number is very low, and mature germ cells are not formed (Hsin and Kenyon, 1999; Arantes-Oliveira et al., 2002; Kenyon, 2010). For simplicity, we will refer to each of these types of animals as GSC(−) animals. The lifespan extension seen in GSC(−) animals (GSC(−) longevity) requires the action of several conserved transcription factors in the intestine, the counterpart of the mammalian liver, digestive system, and adipose tissue (Kenyon, 2010; Antebi, 2013; Hansen et al., 2013). DAF-16/FOXO is needed for longevity from GSC ablation or reduced insulin/IGF-1 signaling (IIS) but is regulated differently by each pathway (Lin et al., 2001; Libina et al., 2003; Kenyon, 2010). GSC(−) longevity also requires HLH-30/TFEB, PHA-4/FOXA, and the nuclear receptors DAF-12/FXR, NHR-80/HNF4, and NHR-49/PPARα (Hsin and Kenyon, 1999; Goudeau et al., 2011; Lapierre et al., 2011; O'Rourke and Ruvkun, 2013; Ratnappan et al., 2014). Under most conditions, GSC(−) longevity also depends upon a hormonal signal from the somatic gonad that activates DAF-12 (Kenyon, 2010; Antebi, 2013). Aside from the identification of mechanisms required for DAF-16 function, we understand little about how GSCs influence these transcription factors (Kenyon, 2010; Antebi, 2013).

One hallmark of GSC(−) animals is enhancement of both proteostasis and stress resistance. During aging, GSC(−) animals maintain more robust responses to thermal and proteotoxic stress (Ben-Zvi et al., 2009). They also exhibit a striking daf-16-dependent increase in activity of the proteasome (Vilchez et al., 2012), a multisubunit complex which degrades proteins that the ubiquitylation system has tagged for decay (Glickman and Ciechanover, 2002; Goldberg, 2003). In addition, GSC removal enhances immunity (Alper et al., 2010) and boosts oxidative stress resistance through an undetermined DAF-16-independent mechanism (Libina et al., 2003).

Another notable characteristic of GSC(−) animals is that many aspects of lipid metabolism are altered. Expression of particular fatty acid (FA) oxidation, FA desaturation, and triglyceride lipase genes is increased, as is total lipase activity (Wang et al., 2008; Goudeau et al., 2011; Lapierre et al., 2011; McCormick et al., 2012; Ratnappan et al., 2014). Given that lipid catabolism is elevated, it seems paradoxical that GSC(−) animals also exhibit dramatically increased fat accumulation (O'Rourke et al., 2009). Interestingly, GSC(−) longevity seems to depend upon particular lipid metabolism processes. Production of the unsaturated free FA (FFA) oleic acid (OA) is required (Goudeau et al., 2011), as are the triglyceride lipases LIPL-4/LIPA and FARD-1/FAR2 (Wang et al., 2008; McCormick et al., 2012). It is of intense interest to determine whether the fat accumulation seen with GSC ablation might derive from production and storage of particular beneficial fats, or a salutary overall balance of lipid metabolism that is consistent with longevity (Ackerman and Gems, 2012; Hansen et al., 2013).

The C. elegans transcription factor SKN-1 controls a broad detoxification response to oxidative and xenobiotic stress and is orthologous to the mammalian Nrf1/2/3 (NF-E2-related factor) proteins (An and Blackwell, 2003; Oliveira et al., 2009; Park et al., 2009). SKN-1/Nrf proteins have been implicated in longevity from C. elegans to rodents (An and Blackwell, 2003; Bishop and Guarente, 2007; Leiser and Miller, 2010; Sykiotis and Bohmann, 2010; Steinbaugh et al., 2012; Ewald et al., 2015). Recent findings raise the question of whether these transcription regulators might also have important functions in lipid homeostasis. SKN-1/Nrf proteins influence expression of lipid metabolism genes (Oliveira et al., 2009; Paek et al., 2012; Hayes and Dinkova-Kostova, 2014; Tsujita et al., 2014), and SKN-1 has been linked to fat mobilization under particular starvation or dietary conditions (Paek et al., 2012; Pang et al., 2014). Mice that lack Nrf1 in the liver develop non-alcoholic fatty liver disease (NAFLD) that progresses to non-alcoholic steatohepatitis (NASH), and Nrf2^−/− mice develop NASH on a high-fat diet (Xu et al., 2005; Okada et al., 2013; Tsujita et al., 2014). However, reduced Nrf protein function is thought to predispose to NASH by impairing hepatic stress resistance (Xu et al., 2005; Lee et al., 2013). An understanding of NAFLD is a high priority, because its incidence is increasing as a sequella of metabolic syndrome (Cohen et al., 2011).

Here, we examined the role of SKN-1 in the effects of GSC absence on lifespan, stress resistance, and lipid metabolism. Genetic inhibition of GSCs activates SKN-1, thereby increasing lifespan and stress resistance. Expression profiling revealed that GSC(−) animals upregulate stress defense, extracellular matrix, and lipid metabolism genes, in many cases dependent upon skn-1. SKN-1 is also required for GSC inhibition to increase proteasome activity. SKN-1 is needed for GSC(−) longevity but reduces lipid storage, arguing against the idea that GSC(−) animals simply accumulate beneficial fat. Instead, these high-fat levels appear to derive from unconsumed yolk that was produced for reproduction. Unexpectedly, in GSC(−) animals, SKN-1 appears to be activated by specific FA signals, defining a new mechanism of SKN-1/Nrf protein regulation and GSC-to-soma communication. This homeostatic function of SKN-1 in lipid metabolism suggests that Nrf proteins have a similar role in preventing NASH.

The question of how events in one tissue can influence aging in others is of fundamental importance. The effects of GSC loss in C. elegans provide a paradigm for investigating this problem, as well as interactions between a stem cell population and its environment. Here, we determined that GSC inhibition leads to a broad transcriptional reprogramming in somatic tissues that involves activation of SKN-1, and that SKN-1 is required for many beneficial effects of GSC absence, including lifespan extension. Previous work showed that SKN-1 is required for lifespan to be extended by reduced insulin/IGF-1, mTORC1, or mTORC2 signaling, by dietary restriction and by low-level mitochondrial reactive oxygen species (ROS) production (Bishop and Guarente, 2007; Tullet et al., 2008; Robida-Stubbs et al., 2012; Zarse et al., 2012; Schmeisser et al., 2013; Mizunuma et al., 2014; Moroz et al., 2014; Ewald et al., 2015). Our new data further support the idea that SKN-1/Nrf proteins are broadly important for longevity assurance.

One major role of SKN-1 in GSC(−) animals is to increase proteasome activity (Figure 4C,D, and Figure 4—figure supplement 1). In WT animals, SKN-1 activates most proteasome subunit genes when the proteasome is inhibited (Li et al., 2011). This compensatory function is conserved in its mammalian ortholog Nrf1, which is cleaved and activated when proteasome activity is low (Radhakrishnan et al., 2010; Steffen et al., 2010; Radhakrishnan et al., 2014; Sha and Goldberg, 2014). By contrast, in GSC(−) animals, proteasome activity is elevated (Figure 4C,D) (Vilchez et al., 2012), suggesting that additional mechanisms influence SKN-1/Nrf regulation of proteasome genes. In GSC(−) animals, most if not all proteasome subunit genes are dependent upon SKN-1 for their expression (Figure 4A), and SKN-1 and DAF-16 together activate the proteasome subunit gene rpn-6.1 (Figure 4E,F), the levels of which are rate limiting for proteasome activity (Vilchez et al., 2012). Overexpression of either rpn-6.1 or the 20S proteasome subunit pbs-5 increases C. elegans lifespan, and in the latter case, lifespan extension was shown to be skn-1-dependent (Vilchez et al., 2012; Chondrogianni et al., 2015), suggesting that enhancement of proteasome activity may be an important mechanism through which SKN-1/Nrf promotes longevity.

The evidence that GSC(−) longevity is associated with fat accumulation, and altered lipid metabolism has raised the intriguing possibility that GSC absence induces production of lipids that promote health and longevity (see ‘Introduction’). Our results are consistent with aspects of this model but suggest an important modification. GSC(−) animals accumulate dramatically high levels of yolk lipoproteins by the first day of adulthood (Figure 6A,B), providing a likely reason that they accumulate so much lipid. Moreover, SKN-1 acts to reduce fat accumulation but is critical for the benefits of GSC loss (Figure 5B,C, and Figure 5—figure supplement 1A,B), suggesting that GSC(−) animals do not simply overproduce healthful lipids. Finally, excess yolk accumulation induced by another method (rme-2 RNAi) leads to increased SKN-1 nuclear accumulation and target gene activation, and skn-1-dependent stress resistance (Figure 6D–G). Taken together, our data suggest that GSC(−) animals accumulate excess fat because they cannot stop production of fat that would otherwise support reproduction (Figure 7). Importantly, however, in responding to and metabolizing this fat they produce specific lipids that activate SKN-1 and other regulators, which in turn increase lifespan and may promote a more healthy balance of lipids (Figure 7).

Several lines of evidence support this model. GSC inhibition induces SKN-1 and NHR-49 to upregulate largely distinct sets of FA oxidation genes (Figure 5A) (Ratnappan et al., 2014). This effect of SKN-1 could account for its inhibitory role in fat accumulation (Figure 5B,C). A need to metabolize excess fat could also explain the importance of lipophagy in GSC(−) longevity (Lapierre et al., 2011; Hansen et al., 2013). With respect to signaling lipids, GSC(−) longevity requires the triglyceride lipase LIPL-4 (Wang et al., 2008), which generates unsaturated FFAs that promote longevity (O'Rourke et al., 2013; Folick et al., 2015). While LIPL-4-dependent FAs act through NHR-49 and NHR-80 (Lapierre et al., 2011; Folick et al., 2015), and possibly not SKN-1 (Figure 6J), in GSC(−) animals, SKN-1 activation involves the LIPL-1/3 lipases (Figure 6J), which also promote longevity (O'Rourke and Ruvkun, 2013). This elevated SKN-1 activity also depends upon lipid transfer proteins, as well as OA (Figure 6H–J and Figure 6—figure supplement 1C). OA is required for GSC(−) longevity (Goudeau et al., 2011) and is a precursor to unsaturated FAs that have signaling functions (O'Rourke et al., 2013; Folick et al., 2015). Finally, SKN-1 upregulates lipl-3 and lbp-8 in WT and GSC(−) animals (Figure 5A and Figure 5—figure supplement 3; Supplementary file 1a,c), suggesting that it may function both downstream and upstream of lipid signals. The idea that SKN-1 can be activated by lipids that arise from prevention of reproduction and yolk consumption should be considered in evaluation of genetic or pharmacological interventions that increase SKN-1 activity.

SKN-1 is activated by lipids and regulates lipid metabolism gene expression not only in the high-fat GSC(−) model but also in WT animals under normal feeding conditions (Figures 5, 6; Supplementary file 1b–d). Moreover, SKN-1 profoundly reduced fat storage by the beginning of adult life in healthy, reproductively active animals that have not begun to age. Taken together, our findings suggest that SKN-1 plays an integral and direct role in maintaining lipid homeostasis. Our results predict that insufficient mammalian Nrf function does not lead to NAFLD/NASH simply by increasing chronic hepatic stress (Xu et al., 2005; Lee et al., 2013), and that a protective function of Nrf proteins in fat metabolism is likely to be involved. Nrf proteins therefore may provide an important line of defense against metabolic disease. Development of NAFLD is a growing obesity-related public health issue (Cohen et al., 2011). Our data suggest that analysis of Nrf proteins could be a promising underexplored direction for investigating causes and prevention of NAFLD, and that SKN-1 and C. elegans provide a genetically tractable model that will be valuable in this effort.

Our evidence that GSCs activate SKN-1 through lipid-based signaling suggests a new mechanism through which GSCs influence the soma. The response to GSC loss therefore involves metabolic signals that reflect the altered nutritional balance within the organism. Similar interactions could be important in other stem cell contexts. For example, in the mammalian bone marrow microenvironment, adipose tissue profoundly influences the function of hematopoietic and mesenchymal stem cells (Adler et al., 2014; Muruganandan and Sinal, 2014). In addition to the mechanisms we have described here, GSC(−) longevity involves endocrine signals from the somatic gonad and depends upon absence of GSCs per se, not simply reproductive cessation (Kenyon, 2010; Antebi, 2013). It will now be of interest to determine how these mechanisms, as well as other transcription factors that are required for GSC(−) longevity (see ‘Introduction’), interface with SKN-1 and its regulation.

Signaling lipids from endogenous, dietary, or microbiota sources constitute an area of considerable excitement, because these signals can induce beneficial effects such as anti-inflammatory protection, enhanced insulin sensitivity, protection against metabolic disease, and increased lifespan in C. elegans (Wang et al., 2008; Kniazeva and Han, 2013; Lim et al., 2013; O'Rourke and Ruvkun, 2013; Folick et al., 2015; Han and Brunet, 2015). Signals derived from OA are of particular interest in this regard, because of its dietary availability in olive oil. Mechanisms through which lipid signals are known to act on transcription networks include binding to nuclear receptors, and OA-induced protein kinase A activation that ultimately leads to FA oxidation (Fu et al., 2003; Lim et al., 2013; Folick et al., 2015). By revealing SKN-1 as a new regulator of metabolism and stress defenses that is activated in response to lipids, our data suggest the exciting possibility that this might also be the case for mammalian Nrf proteins. They also suggest that a ‘lipohormesis’ pathway in which signaling lipids confer health benefits by activating SKN-1/Nrf may not only be a characteristic of GSC-ablated animals but also might be more broadly applicable for enhancing health- and possibly lifespan.

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Author details

1. Michael J Steinbaugh

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   MJS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-2403-2221

2. Sri Devi Narasimhan

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   SDN, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

3. Stacey Robida-Stubbs

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   SR-S, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

4. Lorenza E Moronetti Mazzeo

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   LEMM, Acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

5. Jonathan M Dreyfuss

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Biomedical Engineering, Boston University, Boston, United States

   Contribution

   JMD, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

6. John M Hourihan

   Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Present address

   Research Division, Joslin Diabetes Center, Boston, United States

   Contribution

   JMH, Acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

7. Prashant Raghavan

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   PR, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

8. Theresa N Operaña

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   TNO, Acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

9. Reza Esmaillie

   1. Research Division, Joslin Diabetes Center, Boston, United States
   2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

   Contribution

   RE, Acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

10. T Keith Blackwell

    1. Research Division, Joslin Diabetes Center, Boston, United States
    2. Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston, United States

    Contribution

    TKB, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    For correspondence

    keith.blackwell@joslin.harvard.edu

    Competing interests

    The authors declare that no competing interests exist.

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