Identifying evolutionarily conserved genes in the dietary restriction response using bioinformatics and subsequent testing in Caenorhabditis elegans
© Springer-Verlag Berlin Heidelberg 2013
Received: 14 October 2013
Accepted: 16 November 2013
Published: 6 December 2013
Dietary restriction (DR) increases life span, health span and resistance to stress in a wide range of organisms. Work from a large number of laboratories has revealed evolutionarily conserved mechanisms that mediate the DR response. Here, we analyzed the genome-wide gene expression profiles of Caenorhabditis elegans under DR versus ad libitum conditions. Using the Ortho2ExpressMatrix tool, we searched for C. elegans orthologs of mouse genes that have been shown to be differentially expressed under DR conditions in nearly 600 experiments. Based on our bioinformatic approaches, we obtained 189 DR-responsive genes, and 45 of these are highly conserved from worm to man. Subsequent testing of sixteen genes that are up-regulated under DR identified eight genes that abolish the DR-induced resistance to heat stress in C. elegans. Further analyses revealed that fkb-4, dod-22 and ikb-1 genes also abolish increased life span in response to DR. The identified genes that are necessary for the DR response are sensitive to certain stress signals such as metabolic perturbances (dod-22, fkb-4 and nhr-85), DNA damage (ikb-1), heat shock (hsp-12.6) and cancer-like overgrowth (prk-2 and tsp-15). We propose that most of the DR-responsive genes identified are components of the recently discovered cellular surveillance-activated detoxification and defenses pathway, which is, among others, important for the survival of organisms in times of food deprivation.
In the past decades, nutritional science has increasingly shifted from an expert niche to the central focus of molecular genetics, biochemistry, bioinformatics and medical research as important interconnections between the diet and widespread diseases such as cancer, stroke, neurodegenerative diseases and cardiovascular diseases became apparent (Hirabayashi et al. 2013; Hariri and Thibault 2010; Kahn et al. 2006; Van Gaal et al. 2006). Even more importantly, dietary restriction (DR) increases life span, health span and resistance to environmental stress in a wide range of organisms (Mair and Dillin 2008). DR is defined as a significant reduction in energy and macronutrient intake in the absence of malnutrition (Weindruch et al. 1988). A large number of laboratories are involved in unraveling the molecular mechanisms that mediate the DR response. The TOR/AMPK, insulin, sirtuin and autophagy pathways are important for this response (Kenyon 2010). Notably, many components of these pathways were first identified in model organisms such as Caenorhabditis elegans and have subsequently been confirmed as important in higher organisms, including humans (Kenyon 2010; Kenyon et al. 1993; Tissenbaum and Guarente 2001; Mair and Dillin 2008).
Over the past 30 years, the increasing application of high-throughput technologies (HTP) within the field of molecular genetic research has shifted the focus from studying the activity of single genes, proteins and pathways to the level of whole genomes, transcriptomes and metabolomes, thus introducing the “-omics” era of life science (Szewczyk et al. 2006; Smith and Petrenko 1997; Li et al. 2004; Pungaliya et al. 2009). As a consequence, huge amounts of data derived from various HTP approaches studying a large number of species, tissues and diseases are being assembled. Nevertheless, adequately dissecting those data to generate relevant scientific information still appears to be very challenging. In the present study, we introduce a comprehensive meta-analysis of microarray data acquired in the model organisms C. elegans and the mouse, under DR versus ad libitum (AL) conditions. The major aim of the study was the identification of evolutionarily conserved genes in the DR response. Therefore, we combined bioinformatic approaches with functional assays in C. elegans.
Materials and methods
Data sets and databases
Five microarray data sets were generated in our laboratory [(Palgunow et al. 2012); Klapper et al. unpublished]. Two microarray data sets were obtained from the Gene Expression Omnibus (Barrett et al. 2009) and Array Express (Parkinson et al. 2009) databases. Common databases and tools such as Wormbase, InterPro, NCBI GenBank, KEGG pathways, Pfam, Gene Ontology, DAVID, a tissue-specific expression prediction tool (Chikina et al. 2009) and the Ortho2Express Matrix program (Meinel et al. 2011) were used.
Nematode strains and dietary restriction protocol
The following C. elegans strains were used:
Wild-type N2, cpr-2(ok2833), hsp-12.6(ok1077), odr-10(ky225), ftn-1(ok3625), fkb-4(ok240), ikb-1(nr2027), C05D11.7b aka dpy-5(e907) I, sEx16156, nhr-85(ok2051), prk-2(ok3069), tsp-15(sv15), dod-22(ok1918), F35E12.8(ok2220), dod-17(ok2387), dod-24(ok2629), C33A11.1(ok3681) and sup-12(ok1843). Mutant strains were obtained from the Caenorhabditis Genetics Center (Minneapolis, MN, USA). The DR protocol was recently established in our group (Palgunow et al. 2012). Briefly, standard NGM medium without bactopeptone was used to induce DR on 90-mm-diameter agar plates. E. coli OP50 bacteria were grown at 37 °C in DYT medium until they reached an optical density (600 nm) of 1.5. Subsequently, the bacterial suspension was concentrated or diluted in M9 buffer, resulting in a series of bacterial suspensions ranging from OD600 nm 0.3 to 6.0. In total, 250 μl of each suspension was seeded per plate. For the ad libitum condition, the plates used were standard NGM plates that were seeded with 250 μl E. coli with an OD600 nm of 1.5. Plates were incubated at 37 °C overnight.
Heat stress assays
The experimental plates were 35-mm-diameter NGM plates seeded with OP50. Late L4-stage worms were picked from synchronized NGM plates and transferred (15–25 worms per plate) to experimental plates. After completion of development to adults at 20 °C (16 h), plates were incubated at 35 °C. After 6 h of heat exposure, survival was scored hourly by assessing touch-provoked movement until all worms had died. At least four plates were used for each condition; all experiments were carried out at least twice at two different times. The SPSS version 19 (IBM) statistical analysis package was used for all thermotolerance statistics. P values were calculated using the log-rank (Mantel–Cox) method.
Life span assays
A total of 100 hermaphrodite N2 worms were picked from synchronized plates, transferred to 35-mm-diameter NGM plates seeded with OP50 and then allowed to lay eggs for 60 min. Thirty eggs were picked from each plate and transferred to fresh plates seeded with OP50 bacteria. Worms were transferred every 2 days until they stopped reproducing. Subsequently, they were transferred every 7 days until death. Animals were scored as dead if they failed to respond to a tip on the head and tail with a platinum wire. Worms with internal hatching, exploding worms or worms that left the plate were excluded.
Identification of evolutionarily conserved genes that are differentially expressed in response to dietary restriction
Twenty evolutionarily conserved gene (a) up- and (b) down-regulated in response to dietary restriction
Amino acid methylation
Ferritin heavy chain homologs
Regulated by DAF-2
Lipid metabolic process
Cysteine protease related
Heat shock protein
Amyloid beta protein binding
Secreted surface protein
Folate transporter family
Sugar efflux transporter
Heat shock protein
Nhr-49 ard starv sensing
Wnt inhibitory factor 1
H(+) Myoinositol transporters
Acyl coenzyme A oxidase
Lysosomal serine-type peptidase
Intrinsic/integral to membrane
Lysosomal protective protein
Purple acid phosphatase
Allocation of identified genes into functional clusters and networks
The DAVID tools were used to allocate the identified genes into functional gene clusters. The 25 down-regulated genes assemble into five clusters (Table S6). Cluster 1 (pcp-3, pcp-2, K10B2.2, asp-2, T18H9.2, Y40D12A.2 and Y16B4A.2) contains genes involved in proteolysis and lysosomal activity. Cluster 2 (C49C3.9, F40F4.6, T25C12.3, T25C12.5, clec-41, C48B4.9, ZK899.2, hpo-34, F57F4.4, col-101, C29F3.7b and F40F4.6) encompasses genes involved in the positive regulation of growth. Of note, the genes in these clusters are down-regulated under DR. This result agrees with previous studies showing decreased growth under DR (Tain et al. 2008). Cluster 3 (col-80, col-8, col-184, col-143 and col-19) exclusively contains genes that encode collagen isoforms. The genes in cluster 4 (ugt-22, ugt-26 and ugt-41) encode UDP-glucuronosyl/UDP-glucosyl transferases. When we analyzed the function and functional domains of these genes, we found that an extraordinarily high number (27) of down-regulated genes are members of the CUB-like domain protein family (Table S5, S10). Furthermore, we found groups of genes that are involved in lipid homeostasis (20), amino acid metabolism (11), synthesis of small signaling molecules (8) and innate immunity (5) (Fig. 1b, Table S7).
Next, we analyzed the identified genes with respect to functional interconnections. We noticed a general high interconnectivity between genes that are involved in amino acid metabolism (F57F5.1), fatty acid desaturation (C48B4.1) or growth regulation (F40F4.6) (Table S7); for instance, the gene that encodes the muscle positioning protein MUP-4 displayed a high degree of interconnectivity with other DR-regulated genes. Seven out of ten interacting genes are part of our gene list (Table S2-S4). An additional 14 genes are part of the MUP-4 network, indicating that mup-4 functions as a hub gene in the regulation of DR-related processes (Figure S3A). The lysosomal protective gene Y40D12A.2 interconnects with several genes (i.e., kin-2, ftn-1) that have not been described in the context of lysosome function (Figure S3B).
Heat stress resistance and life span of selected C. elegans mutants grown under ad libitum and dietary restriction conditions
In this study, we identified 189 genes that are differentially expressed in response to DR. Based on sequence homology, approximately 25 % of these genes are evolutionarily conserved, but their functions are not known. Among this group, 32 genes were also identified using a functional ortholog approach (Meinel et al. 2011), suggesting that the functions of these genes are similar between species. Thus, the 32 identified genes are prime candidates for playing a crucial role in the DR response. Based on this strategy, sixteen genes that are up-regulated in response to DR were tested in C. elegans. We found that eight of these genes are indeed necessary for resistance to heat stress, which is an established DR response (Lithgow et al. 1994). Moreover, three of the genes were identified as necessary for life span extension under DR conditions. Recently, two remarkable analyses have been published in which high-throughput technologies, data mining and sequence comparisons between species were also used to predict the function of uncharacterized genes. By assuming that most biological processes are regulated by protein complexes, Tacutu and colleagues uncovered new genes involved in the regulation of life span by systematically analyzing interacting proteins that are encoded by known longevity genes found in C. elegans and humans (Tacutu et al. 2013). Depuydt and colleagues searched for overlapping sets of C. elegans proteins that are differentially expressed in response to DR and in the daf-2 mutant (Depuydt et al. 2013). Similar to the results from our study, both publications revealed novel genes of the DR response by combining bioinformatic approaches with functional assays. Thus, data mining of “-omics” data sets is a useful approach for the detection of as-of-yet unknown key players in fundamental biological processes within and across species. In the future, the increasing availability of mutant strains enabled by the million mutation project (Thompson et al. 2013) will facilitate the systematic analysis of a large number of putative functional orthologs in the C. elegans model organism. It is also important to mention that the effects of DR on health parameters and gene expression are abolished after 6 months of refeeding in mice (Giller et al. 2013). This has to be taken into account in future studies.
Although cpr-2, odr-10, sup-12 and ftn-1 are consistently and highly up-regulated in response to DR, DR-induced resistance to heat stress was not abolished in the corresponding mutant strains. It is possible that these genes are necessary for other DR responses, such as reduced brood size (Mair and Dillin 2008) or reduced body size (Palgunow et al. 2012). In line with this, the levels of the predicted DAF-16-interacting protein DAF-22 displayed no changes in response to DR. DR-mediated heat stress tolerance was not affected in daf-22 mutants, and increased longevity in response to DR was completely abolished in this mutant. Alternatively, the functions of cpr-2, odr-10, sup-12 and ftn-1 might be redundant with paralogous genes. For instance, the cytoskeleton protein encoded by the sup-12 gene has 18 paralogs, and the G-protein-coupled receptor encoded by the odr-10 gene has 25 direct paralogs. Thus, functional redundancy of identified DR-responsive genes might explain why functional tests of these genes are not always consistent.
In our analysis of DR-responsive genes, the number of down-regulated genes is higher than the number of up-regulated genes (114 versus 75, respectively). One prominent group of down-regulated genes encodes proteins containing a CUP-like domain and a signal peptide, indicating that these proteins are secreted. Similar genes are present in mammals, but their functions are unknown (O’Rourke et al. 2006). The CUB-like domain consists of approximately 130 amino acids and contains two conserved cysteine residues (InterPro). The CUB-like domain is related to the CUB domain, which consists of approximately 110 amino acids and contains four conserved cysteine residues that likely form two disulfide bridges (Bork and Beckmann 1993). In C. elegans, proteins containing the CUP-like domain act in the pathogen and immune response and are predominantly expressed in the intestine and neurons (http://worm-tissue.princeton.edu). They are up-regulated in response to the pathogens P. aeruginosa and Y. pestis (Bolz et al. 2010; Cornejo Castro et al. 2010; O’Rourke et al. 2006; Shapira et al. 2006; Troemel et al. 2006). RNAi against genes (dod-24, C17H12.8 and F08G5.6) that encode CUP-like domain-containing proteins resulted in an enhanced susceptibility to pathogens, indicating functions in the immune response. The induction of CUP-like domain-encoded genes by pathogens depends on p38 MAPK (Alper et al. 2007), the intestine-specific GATA transcription factor elt-2 (Shapira et al. 2006) and the phospholipase egl-8 (Kawli et al. 2010). Genes containing the CUB-like domain are also induced by exposure to other stress factors such as X-rays (O’Rourke et al. 2006). So far, the function of CUP-like domain-containing proteins in the DR response is not known. The best-known members of this family are described as “downstream of daf-16” (dod) (Lee et al. 2008; Sakaguchi et al. 2004). Thus, DR-induced down-regulation of genes that encode CUP-like domain-containing proteins might be mediated by the FOXO-like transcription factor DAF-16. Nevertheless, the physiological function of these genes in the DR response remains obscure.
We found eight genes (C05D11.7, nhr-85, prk-2, tsp-15, hsp-12.6, ikb-1, dod-22 and fkb-4) that are up-regulated in response to DR and are necessary for the DR-induced resistance to heat stress. Moreover, increased life span in response to DR is abolished in dod-22, ikb-1 and fkb-4 mutants. Except for hsp-12.6 (Uno et al. 2013), all genes have not been annotated in the context of DR. Interestingly, seven out of eight genes seem to be responsive to certain stress signals such as metabolic stress (dod-22, fkb-4 and nhr-85), DNA damage (ikb-1), heat shock (hsp-12.6) or cancer-like overgrowth (prk-2 and tsp-15). Very recently, the Ruvkun lab discovered the cellular surveillance-activated detoxification and defenses (cSADDs) pathway, which has a central cytoprotective role in the regulation of longevity (Melo and Ruvkun 2012; Shore and Ruvkun 2013; Shore et al. 2012). Here, we propose that most of the identified DR-responsive genes are components of this cSADDs pathway, which is, among others, important for the survival of organisms during food deprivation.
We thank Astrid Reinke for high-throughput plating and Fabian Neumann for strain processing. This work was supported by a grant from the German Ministry of Education and Science (FD). We also thank the Caenorhabditis Genetics Center (CGC, Minneapolis, USA). Some strains were provided by the CGC, which is funded by the NIH Office of Research Infrastructure Programs (P40 OD01040).
- Alper S, McBride SJ, Lackford B, Freedman JH, Schwartz DA (2007) Specificity and complexity of the Caenorhabditis elegans innate immune response. Mol Cell Biol 27(15):5544–5553. doi:10.1128/MCB.02070-06 PubMed CentralPubMedView ArticleGoogle Scholar
- Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Muertter RN, Edgar R (2009) NCBI GEO: archive for high-throughput functional genomic data. Nucleic Acids Res 37 (Database issue):D885–890. doi:10.1093/nar/gkn764
- Bolz DD, Tenor JL, Aballay A (2010) A conserved PMK-1/p38 MAPK is required in Caenorhabditis elegans tissue-specific immune response to Yersinia pestis infection. J Biol Chem 285(14):10832–10840. doi:10.1074/jbc.M109.091629 PubMed CentralPubMedView ArticleGoogle Scholar
- Bork P, Beckmann G (1993) The CUB domain. A widespread module in developmentally regulated proteins. J Mol Biol 231(2):539–545. doi:10.1006/jmbi.1993.1305 PubMedView ArticleGoogle Scholar
- Chikina MD, Huttenhower C, Murphy CT, Troyanskaya OG (2009) Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans. PLoS Comput Biol 5(6):e1000417. doi:10.1371/journal.pcbi.1000417 PubMed CentralPubMedView ArticleGoogle Scholar
- Cornejo Castro EM, Waak J, Weber SS, Fiesel FC, Oberhettinger P, Schutz M, Autenrieth IB, Springer W, Kahle PJ (2010) Parkinson’s disease-associated DJ-1 modulates innate immunity signaling in Caenorhabditis elegans. J Neural Transm 117(5):599–604. doi:10.1007/s00702-010-0397-4 PubMedView ArticleGoogle Scholar
- Depuydt G, Xie F, Petyuk VA, Shanmugam N, Smolders A, Dhondt I, Brewer HM, Camp DG, Smith RD, Braeckman BP (2013) Reduced insulin/IGF-1 signaling and dietary restriction inhibit translation but preserve muscle mass in Caenorhabditis elegans. Mol Cell Proteomics. doi:10.1074/mcp.M113.027383 PubMed CentralPubMedGoogle Scholar
- Gerisch B, Weitzel C, Kober-Eisermann C, Rottiers V, Antebi A (2001) A hormonal signaling pathway influencing C. elegans metabolism, reproductive development, and life span. Dev Cell 1(6):841–851PubMedView ArticleGoogle Scholar
- Giller K, Huebbe P, Hennig S, Dose J, Pallauf K, Doering F, Rimbach G (2013) Beneficial effects of a 6-month dietary restriction are time-dependently abolished within 2 weeks or 6 months of refeeding-genome-wide transcriptome analysis in mouse liver. Free Radical Biol Med 61C:170–178. doi:10.1016/j.freeradbiomed.2013.03.023 View ArticleGoogle Scholar
- Hariri N, Thibault L (2010) High-fat diet-induced obesity in animal models. Nutr Res Rev 23(2):270–299. doi:10.1017/S0954422410000168 PubMedView ArticleGoogle Scholar
- Hirabayashi S, Baranski TJ, Cagan RL (2013) Transformed drosophila cells evade diet-mediated insulin resistance through wingless signaling. Cell 154(3):664–675. doi:10.1016/j.cell.2013.06.030 PubMed CentralPubMedView ArticleGoogle Scholar
- Honjoh S, Yamamoto T, Uno M, Nishida E (2009) Signalling through RHEB-1 mediates intermittent fasting-induced longevity in C. elegans. Nature 457(7230):726–730. doi:10.1038/nature07583 PubMedView ArticleGoogle Scholar
- Kahn SE, Hull RL, Utzschneider KM (2006) Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 444(7121):840–846. doi:10.1038/nature05482 PubMedView ArticleGoogle Scholar
- Kawli T, Wu C, Tan MW (2010) Systemic and cell intrinsic roles of Gqalpha signaling in the regulation of innate immunity, oxidative stress, and longevity in Caenorhabditis elegans. Proc Natl Acad Sci USA 107(31):13788–13793. doi:10.1073/pnas.0914715107 PubMed CentralPubMedView ArticleGoogle Scholar
- Kenyon CJ (2010) The genetics of ageing. Nature 464(7288):504–512. doi:10.1038/nature08980 PubMedView ArticleGoogle Scholar
- Kenyon C, Chang J, Gensch E, Rudner A, Tabtiang R (1993) A C. elegans mutant that lives twice as long as wild type. Nature 366(6454):461–464. doi:10.1038/366461a0 PubMedView ArticleGoogle Scholar
- Lee JM, Takahashi M, Mon H, Mitsunobu H, Koga K, Kawaguchi Y, Nakajima Y, Kusakabe T (2008) Construction of gene expression systems in insect cell lines using promoters from the silkworm Bombyx mori. J Biotechnol 133(1):9–17. doi:10.1016/j.jbiotec.2007.08.033 PubMedView ArticleGoogle Scholar
- Li S, Armstrong CM, Bertin N, Ge H, Milstein S, Boxem M, Vidalain PO, Han JD, Chesneau A, Hao T, Goldberg DS, Li N, Martinez M, Rual JF, Lamesch P, Xu L, Tewari M, Wong SL, Zhang LV, Berriz GF, Jacotot L, Vaglio P, Reboul J, Hirozane-Kishikawa T, Li Q, Gabel HW, Elewa A, Baumgartner B, Rose DJ, Yu H, Bosak S, Sequerra R, Fraser A, Mango SE, Saxton WM, Strome S, Van Den Heuvel S, Piano F, Vandenhaute J, Sardet C, Gerstein M, Doucette-Stamm L, Gunsalus KC, Harper JW, Cusick ME, Roth FP, DE Hill, Vidal M (2004) A map of the interactome network of the metazoan C. elegans. Science 303(5657):540–543. doi:10.1126/science.1091403 PubMed CentralPubMedView ArticleGoogle Scholar
- Lithgow GJ, White TM, Hinerfeld DA, Johnson TE (1994) Thermotolerance of a long-lived mutant of Caenorhabditis elegans. J Gerontol 49(6):B270–B276PubMedView ArticleGoogle Scholar
- Mair W, Dillin A (2008) Aging and survival: the genetics of life span extension by dietary restriction. Ann Rev Biochem 77:727–754. doi:10.1146/annurev.biochem.77.061206.171059 PubMedView ArticleGoogle Scholar
- Meinel T, Schweiger MR, Ludewig AH, Chenna R, Krobitsch S, Herwig R (2011) Ortho2ExpressMatrix–a web server that interprets cross-species gene expression data by gene family information. BMC Genomics 12:483. doi:10.1186/1471-2164-12-483 PubMed CentralPubMedView ArticleGoogle Scholar
- Melo JA, Ruvkun G (2012) Inactivation of conserved C. elegans genes engages pathogen- and xenobiotic-associated defenses. Cell 149(2):452–466. doi:10.1016/j.cell.2012.02.050 PubMed CentralPubMedView ArticleGoogle Scholar
- O’Rourke D, Baban D, Demidova M, Mott R, Hodgkin J (2006) Genomic clusters, putative pathogen recognition molecules, and antimicrobial genes are induced by infection of C. elegans with M. nematophilum. Genome Res 16(8):1005–1016. doi:10.1101/gr.50823006 PubMed CentralPubMedView ArticleGoogle Scholar
- Palgunow D, Klapper M, Doring F (2012) Dietary restriction during development enlarges intestinal and hypodermal lipid droplets in Caenorhabditis elegans. PLoS One 7(11):e46198. doi:10.1371/journal.pone.0046198 PubMed CentralPubMedView ArticleGoogle Scholar
- Parkinson H, Kapushesky M, Kolesnikov N, Rustici G, Shojatalab M, Abeygunawardena N, Berube H, Dylag M, Emam I, Farne A, Holloway E, Lukk M, Malone J, Mani R, Pilicheva E, Rayner TF, Rezwan F, Sharma A, Williams E, Bradley XZ, Adamusiak T, Brandizi M, Burdett T, Coulson R, Krestyaninova M, Kurnosov P, Maguire E, Neogi SG, Rocca-Serra P, Sansone SA, Sklyar N, Zhao M, Sarkans U, Brazma A (2009) ArrayExpress update–from an archive of functional genomics experiments to the atlas of gene expression. Nucleic Acids Res 37 (Database issue):D868–872. doi:10.1093/nar/gkn889
- Pungaliya C, Srinivasan J, Fox BW, Malik RU, Ludewig AH, Sternberg PW, Schroeder FC (2009) A shortcut to identifying small molecule signals that regulate behavior and development in Caenorhabditis elegans. Proc Natl Acad Sci USA 106(19):7708–7713. doi:10.1073/pnas.0811918106 PubMed CentralPubMedView ArticleGoogle Scholar
- Sakaguchi A, Matsumoto K, Hisamoto N (2004) Roles of MAP kinase cascades in Caenorhabditis elegans. J Biochem 136(1):7–11. doi:10.1093/jb/mvh097 PubMedView ArticleGoogle Scholar
- Shapira M, Hamlin BJ, Rong J, Chen K, Ronen M, Tan MW (2006) A conserved role for a GATA transcription factor in regulating epithelial innate immune responses. Proc Natl Acad Sci USA 103(38):14086–14091. doi:10.1073/pnas.0603424103 PubMed CentralPubMedView ArticleGoogle Scholar
- Shore DE, Ruvkun G (2013) A cytoprotective perspective on longevity regulation. Trends Cell Biol 23(9):409–420. doi:10.1016/j.tcb.2013.04.007 PubMed CentralPubMedView ArticleGoogle Scholar
- Shore DE, Carr CE, Ruvkun G (2012) Induction of cytoprotective pathways is central to the extension of lifespan conferred by multiple longevity pathways. PLoS Genet 8(7):e1002792. doi:10.1371/journal.pgen.1002792 PubMed CentralPubMedView ArticleGoogle Scholar
- Smith GP, Petrenko VA (1997) Phage display. Chem Rev 97(2):391–410PubMedView ArticleGoogle Scholar
- Swindell WR (2008) Genes regulated by caloric restriction have unique roles within transcriptional networks. Mech Ageing Dev 129(10):580–592. doi:10.1016/j.mad.2008.06.001 PubMed CentralPubMedView ArticleGoogle Scholar
- Szewczyk NJ, Udranszky IA, Kozak E, Sunga J, Kim SK, Jacobson LA, Conley CA (2006) Delayed development and lifespan extension as features of metabolic lifestyle alteration in C. elegans under dietary restriction. J Exp Biol 209(Pt 20):4129–4139. doi:10.1242/jeb.02492 PubMedView ArticleGoogle Scholar
- Tacutu R, Craig T, Budovsky A, Wuttke D, Lehmann G, Taranukha D, Costa J, Fraifeld VE, de Magalhaes JP (2013) Human ageing genomic resources: integrated databases and tools for the biology and genetics of ageing. Nucleic Acids Res 41 (Database issue):D1027–1033. doi:10.1093/nar/gks1155
- Tain LS, Lozano E, Saez AG, Leroi AM (2008) Dietary regulation of hypodermal polyploidization in C. elegans. BMC Dev Biol 8:28. doi:10.1186/1471-213X-8-28 PubMed CentralPubMedView ArticleGoogle Scholar
- Thompson O, Edgley M, Strasbourger P, Flibotte S, Ewing B, Adair R, Au V, Chaudhry I, Fernando L, Hutter H, Kieffer A, Lau J, Lee N, Miller A, Raymant G, Shen B, Shendure J, Taylor J, Turner EH, Hillier LW, Moerman DG, Waterston RH (2013) The million mutation project: a new approach to genetics in Caenorhabditis elegans. Genome Res 23(10):1749–1762. doi:10.1101/gr.157651.113 PubMed CentralPubMedView ArticleGoogle Scholar
- Tissenbaum HA, Guarente L (2001) Increased dosage of a sir-2 gene extends lifespan in Caenorhabditis elegans. Nature 410(6825):227–230. doi:10.1038/35065638 PubMedView ArticleGoogle Scholar
- Troemel ER, Chu SW, Reinke V, Lee SS, Ausubel FM, Kim DH (2006) p38 MAPK regulates expression of immune response genes and contributes to longevity in C. elegans. PLoS Genet 2(11):e183. doi:10.1371/journal.pgen.0020183 PubMed CentralPubMedView ArticleGoogle Scholar
- Uno T, Sakamoto K, Isoyama Y, Hiragaki S, Uno Y, Kanamaru K, Yamagata H, Takagi M, Mizoguchi A, Takeda M (2013) Relationship between the expression of Rab family GTPases and neuropeptide hormones in the brain of Bombyx mori. Histochem Cell Biol 139(2):299–308. doi:10.1007/s00418-012-1021-5 PubMedView ArticleGoogle Scholar
- Van Gaal LF, Mertens IL, De Block CE (2006) Mechanisms linking obesity with cardiovascular disease. Nature 444(7121):875–880. doi:10.1038/nature05487 PubMedView ArticleGoogle Scholar
- Weindruch R, Naylor PH, Goldstein AL, Walford RL (1988) Influences of aging and dietary restriction on serum thymosin alpha 1 levels in mice. J Gerontol 43(2):B40–B42PubMedView ArticleGoogle Scholar