- Email: [email protected]
Aging in the wild: Insights from free-living and non-model organisms
Experimental Gerontology 71 (2015) 1–3
Contents lists available at ScienceDirect
Experimental Gerontology journal homepage: www.elsevier.com/locate/expgero
Editorial
Aging in the wild: Insights from free-living and non-model organisms
Come forth into the light of things, let nature be your teacher. William Wordsworth. Aging is most commonly defined as a decrease in physiological function that leads to an age-related decrease in fitness. The manifestations of aging are apparent at all phenotypic levels, from declining performance at the level of the whole animal, all the way down to ageassociated damage to, and dysfunction in, individual cells, organelles and molecules. Unfortunately, most of us are only too well versed on the effects of aging. Similarly, we are all acutely aware that the world's population comprises an ever higher proportion of elderly individuals, with age being the primary risk factor for a number of pathologies that significantly affect late-life health and well-being. As a result, understanding why we age, and how we age, is a major research challenge in science. Much of what we know about the biological processes underlying aging has been obtained from studies of ‘model’ organisms, such as Caenorhabditis elegans, Drosophila melanogaster and laboratory mice; animals that are easily maintained under standard laboratory conditions, relatively short-lived, genetically homogenous and have genomes amenable to manipulation. Using model organisms in biogerontology has undeniably generated critical insights into the aging process. We now know that many aging phenotypes and aging-relevant genetic pathways are conserved across wide evolutionary distances, and that both aging and late-life health can be extended through a number of dietary, genetic and pharmacological interventions (Vijg and Campisi, 2008; Gems and Partridge, 2013; Selman, 2014). However, and as detailed elsewhere (e.g. Monaghan et al., 2009; Austad, 2010b; Selman et al., 2012), limiting aging research to model organisms may cause us to miss important factors that help explain how and why we age. A second, complimentary, approach to understanding how and why we age is through studying aging in free-living animals and non-model organisms (Austad, 2010a,2010b; Nussey et al., 2013; Roach and Carey, 2014). This approach is gaining significant momentum and there is now a large body of empirical evidence that clearly demonstrates that animals in the wild experience aging (Bronikowski and Promislow, 2005; Nussey et al., 2013; Roach and Carey, 2014). While a large proportion of free-living individuals within a population is likely to succumb to the various challenges of living in the wild long before they exhibit clear manifestations of aging, many studies have now shown that reproductive performance, aspects of physiological and cellular function, and survival probability all decrease with advancing age free-living animals (for detailed reviews see Nussey et al., 2013; Roach and Carey, 2014; but see also Jones et al., 2014). Similarly, studies using comparative approaches and non-classical model organisms have already, and will continue, to provide important insights into the aging process
http://dx.doi.org/10.1016/j.exger.2015.09.015 0531-5565/© 2015 Elsevier Inc. All rights reserved.
(Austad, 1993; Kapahi et al., 1999; Selman et al., 2002, 2008; Nussey et al., 2006, 2009, 2012; Edrey et al., 2011; Fletcher et al., 2013; Kraus et al., 2013; Lucas-Sanchez et al., 2014). Inter-specific rates of aging and lifespan differ significantly in nature, often by orders of magnitude, and profound variation even exists between closely related organisms and intra-specifically. For example, the longevity of different dog breeds varies by a factor of two (Kraus et al., 2013); bats, birds and naked mole rats (Heterocephalus glaber) live much longer than expected for their body mass (Austad, 2010a,2010b; Edrey et al., 2011), and different honey bee (Apis mellifera) castes show profound variation in aging rates (Münch et al., 2008). In the following Special Issue we present 15 articles consisting of perspectives, reviews and original research papers from a leading group of scientists interested in aging from the perspectives of ecology, ecophysiology, evolutionary biology, modelling and biogerontology. These articles can be broadly grouped into four topics; 1) Non-model organisms in aging research, 2) Aging in free-living animals, 3) Novel modelling and statistical approaches to understand aging, 4) Innovative methodologies applicable to understanding aging in non-model and free-living animals. 1. Non-model organisms in aging research In this section we present three papers that highlight the potential value of using non-model organisms to understand aging. Archer and Hunt (2015) provide compelling reasons as to how crickets (family Gryllidae) can be used to generate novel insights into how sexual selection and sexual conflict influence aging rate and longevity, both from evolutionary and mechanistic perspectives. Gilmore and Greer (2015) put forward a compelling case for the importance of the dog as a model for human aging and age-associated pathology. As mentioned above, it is well-established inter-breed differences in the rate of aging and longevity exist between different dog breeds (Kraus et al., 2013). This substantial variation has stimulated significant research interest in understanding the aging process in man's best friend. It has been suggested that companion animals, such as dogs, may provide a critical stepping-stone in translating what we know about aging in model organisms to aging in humans, while also simultaneously helping to identify interventions that improve the healthspan of our pets (Kaeberlein, in press). Finally, Briga and Verhulst (2015) take an unconventional look at model organisms by reviewing a number of experiments where the fitness and lifespan of various long-lived laboratory mutants were compared to wild type animals during competition experiments or when exposed to environmental conditions that were more challenging than standard laboratory conditions. In both circumstances, they report that long-lived mutants generally fare worse relative to wild type
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controls, and discuss potential reasons and implications of this for aging research. 2. Aging in free-living animals Inter-specific and intra-specific analyses are two general approaches used to study aging in free-ranging animals. Three articles in this special issue focus on the inter-specific approach. First, Sanchez et al. (2015) discuss the utility of using comparative approaches across species to understand aging, particularly by using species that show extremely long lifespans, which they call ‘extremophiles’. In particular they discuss the likelihood that various metabolic, endocrine and oxidative processes are conserved across ‘extremophiles’, and how this may help understand mechanisms of aging. Second, in an original research paper, Dantzer and Fletcher (2015) test the prediction originally explored by Vleck et al. (2003) and Haussmann et al. (2003) that telomere shortening rates are slower in long-lived species than in short-lived species. By collating all studies that have been conducted on free-ranging animals up until now, their findings support this prediction and also suggest that species with fast life-histories also have higher rates of telomere attrition. Third, in a research article, Gaillard et al. (2015) tested whether the intensity of tooth wear experienced by different species of large herbivores in the wild was related to the longevity and rate of aging in captive animals of these species. The rate of tooth wear is a strong predictor of aging intra-specifically within large herbivores (e.g. Garrott et al., 2002) because worn teeth limit the ability of animals to obtain resources. However, the relationship between tooth wear and aging has never been tested inter-specifically. In their study, Gaillard et al. find that the rate of tooth wear was not related to longevity, but that tooth wear was generally faster in the species experiencing faster rates of aging. Two articles in this Special Issue then go on to focus on intra-specific research. First, Hayward et al. (2015) present a research article testing whether or not phenotypic traits reflecting components and predictors of fitness age in synchrony in Soay sheep (Ovis aries). Although most traits showed senescent declines, others did not, and some of these divergent patterns were sex-specific. Overall, the lack of consistency between these findings and existing theory opens the door for theory to be revised and further developed. Hammers et al. (2015) then provides a review article outlining the detailed aging research that has been conducted on a marked population of Seychelles warblers (Acrocephalus sechellensis). In addition to demonstrating senescent declines in key physiological traits, research on this population has also been able to document how the environment, social interactions, and life-history trade-offs influence senescence. The authors conclude by urging researchers to take a more experimental and integrative approach to studying aging that incorporates multiple physiological mechanisms and environmental variables. 3. Novel modelling and statistical approaches to understand aging Theoretical models are an additional way in which we can gain insights into aging. Watson et al. (2015) use a theoretical model to help understand the role that environmental stressors may play in the evolution of actuarial senescence in a hypothetical population of birds in response to simultaneous physiological stressors. Their modelling approach suggests that if environmental stressors act synergistically, rather than additively, then this may rapidly increase agingdependant mortality due to physiological dysregulation, leading to a population collapse. In another contribution, Kowald and Kirkwood (2015) review the evidence for the presence of aging in wild animal populations, and then go on to estimate the costs of aging in wild animals using life history data collected from recent field studies. Finally, they discuss the implications of senescence in wild populations for the existing evolutionary theories of aging, showing that the presence of senescent individuals within a population is compatible with both the
antagonistic pleiotropy and the disposable soma theories, but not the mutation accumulation theory. In a final paper in this theme, Boonekamp et al. (2015) give an in-depth overview of redundancy models and then re-examine a published dataset (Mair et al., 2003) using these models to provide additional insights into the influence of dietary restriction and temperature manipulation on aging in Drosophila. 4. Innovative methodologies applicable to understanding aging in non-model and free- living organisms Investigating the mechanistic processes underlying aging in nonmodel and free-living organisms has historically been hampered by difficulties in collecting samples from difficult to catch, rare and/or protected species, the inability to appropriately process and store biological materials, unsequenced genomes and the lack of exposure of field ecologists to relatively straightforward laboratory techniques (Selman et al., 2012). It is evident that this is now changing, in part, due to the ‘omics’ revolution, but also due to greater crosstalk between field-based and lab-based scientists. Three papers in this Special Issue are from researchers who use laboratory-based methodologies to investigate aging in non-model organisms. Münch et al. (2015) use a combination of western blotting and in situ hybridisation to identify the localisation of vitellogenin (Vg), an egg-yolk protein, within the brain of honey bees. Vg, which is known to influence both bee social behaviour and aging rate, was shown to localise to glial cells. The authors discuss how their findings may help understand the differences in aging rate between different honey bee castes. A number of studies in both model and non-model organisms (Salmon et al., 2005, 2008; Harper et al., 2007, 2011) have reported a positive correlation between cellular stress resistance and longevity. Alper et al. (2015) review the literature in this area and discuss the potential strengths, and caveats, to using this approach as a means to identify conserved mechanisms of aging both within and between species. In particular, this approach may be highly applicable to studies of aging in endangered species, or those that are part of a long-term longitudinal study. What is clear is that tissue punches or biopsies could provide sufficient material to culture primary cells and then investigate a number of candidate mechanisms, including cellular stress resistance. Along similar lines, Stier et al. (2015), highlight that red blood cells can provide important insight into a diversity of agerelated physiological changes (e.g. oxidative stress, glucose homeostasis, mitochondrial functioning, and telomere dynamics). They then go on to provide an overview of all studies that have examined these physiological components in non-model organisms. They also argue that examining red blood cells is a powerful way to examine aging because red blood cells can be obtained repeatedly from individuals in longitudinal studies, which removes potential biases caused by selective disappearance in cross-sectional studies. Finally, employing a cutting-edge RNAseq approach, Schwartz et al. (2015) investigated mitochondrial genotypes and transcription in slow-aging and fast-aging garter snake (Thamnophis elegans) ecotypes. By reconstructing the garter snake mitochondrial sequence they investigated differences in mitochondrial gene expression between the ecotypes and in response to heat stress. Their approach found that expression of protein coding genes was higher in the fast-aging ecotype, and that divergence in mitochondrial haplotypes observed between these ecotypes fits with previous findings relating to mitochondrial function. Thisresearch demonstrates the clear potential for using high throughput next generation sequencing approaches to understanding aging-related processes in animals lacking sequenced genomes. Similarly, other ‘omic’ technologies such as metabolomics and lipidomics can offer exciting new insights into aging in non-model and free-living organisms (e.g. Aksenov et al., 2014; Roznere et al., 2014; Gomez et al., 2015). Over the last few decades there have been major advances in our understanding of the aging process, with much of this knowledge generated within model organisms. However, as discussed in this Special Issue
Editorial
there is much that can be learned from non-model organisms and field studies that can help augment what we already know, and help discover much of what we do not, both from the perspective of how and why we age. We hope that this Special Issue will help stimulate new ideas and greater cross-talk between field- and lab-based empiricists and theoreticians; scientists who have historically tended not to interact. What is clear is that given the complexity of the aging process, multidisciplinary approaches, at the very least, are likely to identify new pieces of the puzzle. Conflict of interest The authors have no conflicts of interest. Acknowledgements We are grateful to Prof. Christiaan Leeuwenburgh, Deputy Editor at Experimental Gerontology for recommending us, and to Prof. Tom Johnson, Editor-in-Chief, for enabling us to edit this Special Issue. We are extremely appreciative to all the contributors for their excellent and timely contributions, and we would like to thank all the reviewers who helped facilitate the bringing together of this body of work. Finally, we recognize the help, support and patience by the editorial staff at Experimental Gerontology. References Aksenov, A.A., Yeates, L., Pasamontes, A., Siebe, C., Zrodnikov, Y., Simmons, J., McCartney, M.M., Deplanque, J.P., Wells, R.S., Davis, C.E., 2014. Metabolite content profiling of bottlenose dolphin exhaled breath. Anal. Chem. 86, 10616–10624. Alper, S., Bronikowski, A.M., Harper, J.M., 2015. Comparative cellular biogerontology: where do we stand? Exp. Gerontol. 71, 109–117. Archer, C.R., Hunt, J., 2015. Understanding the link between sexual selection, sexual conflict and aging using crickets as a model. Exp. Gerontol. 71, 4–13. Austad, S.N., 1993. Retarded senescence in an insular population of Virginia opossums (Didelphis virginiana). J. Zool. 229, 695–708. Austad, S.N., 2010a. Cats, “rats,” and bats: the comparative biology of aging in the 21st century. Integr. Comp. Biol. 50, 783–792. Austad, S.N., 2010b. Methuselah’s Zoo: how nature provides us with clues for extending human health span. J. Comp. Pathol. 142 (Suppl. 1), S10–S21. Boonekamp, M., Briga, M., Verhulst, S., 2015. The heuristic value of redundancy models in ageing. Exp. Gerontol. 71, 95–102. Briga, M., Verhulst, S., 2015. What can long-lived mutants tell is about mechanisms causing ageing and lifespan variation in natural environments? Exp. Gerontol. 71, 21–26. Bronikowski, A.M., Promislow, D.E., 2005. Testing evolutionary theories of aging in wild populations. Trends Ecol. Evol. 20, 271–273. Dantzer, B., Fletcher, Q.E., 2015. Telomeres shorten more slowly in slow-aging wild animals than in fast-aging ones. Exp. Gerontol. 71, 38–47. Edrey, Y.H., Hanes, M., Pinto, M., Mele, J., Buffenstein, R., 2011. Successful aging and sustained good health in the naked mole rat: a long-lived mammalian model for biogerontology and biomedical research. ILAR J. 52, 41–53. Fletcher, Q.E., Selman, C., Boutin, S., McAdam, A.G., Woods, S.B., Seo, A.Y., Leeuwenburgh, C., Speakman, J.R., Humphries, M.M., 2013. Oxidative damage increases with reproductive energy expenditure and is reduced by food-supplementation. Evolution 67, 1527–1536. Gaillard, J.M., Berger, V., Tidiere, M., Duncan, P., Lemaitre, J.F., 2015. Does tooth wear influence ageing? A comparative study across large herbivores. Exp. Gerontol. 71, 48–55. Garrott, R.A., Eberhardt, L.L., Otton, J.K., White, P.J., Chaffee, M.A., 2002. A geochemical trophic cascade in Yellowstone's geothermal environments. Ecosystems 5, 659–666. Gems, D., Partridge, L., 2013. Genetics of longevity in model organisms: debates and paradigm shifts. Annu. Rev. Physiol. 75, 621–644. Gilmore, K.M., Greer, K.A., 2015. Why is the dog an ideal model for aging research? Exp. Gerontol. 71, 14–20. Gomez, A., Petrzelkova, K., Yeoman, C.J., Vlckova, K., Mrazek, J., Koppova, I., Carbonero, F., Ulanov, A., Modry, D., Todd, A., Torralba, M., Nelson, K.E., Gaskins, H.R., Wilson, B., Stumpf, R.M., White, B.A., Leigh, S.R., 2015. Gut microbiome composition and metabolomic profiles of wild western lowland gorillas (Gorilla gorilla gorilla) reflect host ecology. Mol. Ecol. 24, 2551–2565. Hammers, M., Kingma, S.A., Bebbington, K., van de Crommenacker, J., Spurgin, L.G., Richardson, D.S., Burke, T., Dugdale, H.L., Komdeur, J., 2015. Senescence in the wild: insights from a long-term study on Seychelles warblers. Exp. Gerontol. 71, 69–79. Harper, J.M., Salmon, A.B., Leiser, S.F., Galecki, A.T., Miller, R.A., 2007. Skin-derived fibroblasts from long-lived species are resistant to some, but not all, lethal stresses and to the mitochondrial inhibitor rotenone. Aging Cell 6, 1–13. Harper, J.M., Wang, M., Galecki, A.T., Ro, J., Williams, J.B., Miller, R.A., 2011. Fibroblasts from longlived bird species are resistant to multiple forms of stress. J. Exp. Biol. 214, 1902–1910. Haussmann, M.F., Winkler, D.W., O'Reilly, K.M., Huntington, C.E., Nisbet, I.C., Vleck, C.M., 2003. Telomeres shorten more slowly in long-lived birds and mammals than in short-lived ones. Proc. Biol. Sci. 270, 1387–1392.
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Hayward, A.D., Moorad, J., Regan, C.E., Berenos, C., Pilkington, J.G., Pemberton, J.M., Nussey, D.H., 2015. Asynchrony of senescence among phenotypic traits in a wild mammal population. Exp. Gerontol. 71, 56–68. Jones, O.R., Scheuerlein, A., Salguero-Gomez, R., Camarda, C.G., Schaible, R., Casper, B.B., Dahlgren, J.P., Ehrlen, J., Garcia, M.B., Menges, E.S., Quintana-Ascencio, P.F., Caswell, H., Baudisch, A., Vaupel, J.W., 2014. Diversity of ageing across the tree of life. Nature 505, 169–173. Kaeberlein, M., 2015. The biology of aging: citizen scientists and their pets as a bridge between research on model organisms and human subjects. Vet. Pathol. (in press). Kapahi, P., Boulton, M.E., Kirkwood, T.B., 1999. Positive correlation between mammalian life span and cellular resistance to stress. Free Radic. Biol. Med. 26, 495–500. Kowald, A., Kirkwood, T.B., 2015. Evolutionary significance of ageing in the wild. Exp. Gerontol. 71, 89–94. Kraus, C., Pavard, S., Promislow, D.E., 2013. The size-life span trade-off decomposed: why large dogs die young. Am. Nat. 181, 492–505. Lucas-Sanchez, A., Almaida-Pagan, P.F., Mendiola, P., de Costa, J., 2014. Nothobranchius as a model for aging studies. A review. Aging Dis. 5, 281–291. Mair, W., Goymer, P., Pletcher, S.D., Partridge, L., 2003. Demography of dietary restriction and death in Drosophila. Science 301, 1731–1733. Monaghan, P., Metcalfe, N.B., Torres, R., 2009. Oxidative stress as a mediator of life history tradeoffs: mechanisms, measurements and interpretation. Ecol. Lett. 12, 75–92. Münch, D., Amdam, G.V., Wolschin, F., 2008. Ageing in a eusocial insect: molecular and physiological characteristics of life span plasticity in the honey bee. Funct. Ecol. 22, 407–421. Münch, D., Ihle, K.E., Salmela, H., Amdam, G.V., 2015. Vitellogenin in the honey bee brain: atypical localization of a reproductive protein that promotes longevity. Exp. Gerontol. 71, 103–108. Nussey, D.H., Kruuk, L.E., Donald, A., Fowlie, M., Clutton-Brock, T.H., 2006. The rate of senescence in maternal performance increases with early-life fecundity in red deer. Ecol. Lett. 9, 1342–1350. Nussey, D.H., Pemberton, J.M., Pilkington, J.G., Blount, J.D., 2009. Life history correlates of oxidative damage in a free-living mammal population. Funct. Ecol. 23, 809–817. Nussey, D.H., Watt, K., Pilkington, J.G., Zamoyska, R., McNeilly, T.N., 2012. Age-related variation in immunity in a wild mammal population. Aging Cell 11, 178–180. Nussey, D.H., Froy, H., Lemaitre, J.F., Gaillard, J.M., Austad, S.N., 2013. Senescence in natural populations of animals: widespread evidence and its implications for bio-gerontology. Ageing Res. Rev. 12, 214–225. Roach, D.A., Carey, J.R., 2014. Population biology of aging in the wild. Annu. Rev. Ecol. Evol. Syst. 45 (45), 421–443. Roznere, I., Watters, G.T., Wolfe, B.A., Daly, M., 2014. Nontargeted metabolomics reveals biochemical pathways altered in response to captivity and food limitation in the freshwater mussel Amblema plicata. Comp. Biochem. Physiol. Part D Genomics Proteomics 12, 53–60. Salmon, A.B., Murakami, S., Bartke, A., Kopchick, J., Yasumura, K., Miller, R.A., 2005. Fibroblast cell lines from young adult mice of long-lived mutant strains are resistant to multiple forms of stress. Am. J. Physiol. Endocrinol. Metab. 289, E23–E29. Salmon, A.B., Sadighi Akha, A.A., Buffenstein, R., Miller, R.A., 2008. Fibroblasts from naked molerats are resistant to multiple forms of cell injury, but sensitive to peroxide, ultraviolet light, and endoplasmic reticulum stress. J. Gerontol. A Biol. Sci. Med. Sci. 63, 232–241. Sanchez, J.R., Milton, S.L., Corbit, K.C., Buffenstein, R., 2015. Multifactorial processes to slowing the biological clock: insights from a comparative approach. Exp. Gerontol. 71, 27–37. Schwartz, T.S., Arendsee, Z.N., Bronikowski, A.M., 2015. Mitochondrial stress response and haplotype divergence between slow- and fast-aging garter snakes. Exp. Gerontol. 71, 135–146. Selman, C., 2014. Dietary restriction and the pursuit of effective mimetics. Proc. Nutr. Soc. 1–11. Selman, C., Grune, T., Stolzing, A., Jakstadt, M., McLaren, J.S., Speakman, J.R., 2002. The consequences of acute cold exposure on protein oxidation and proteasome activity in shorttailed field voles, Microtus agrestis. Free Radic. Biol. Med. 33, 259–265. Selman, C., McLaren, J.S., Collins, A.R., Duthie, G.G., Speakman, J.R., 2008. The impact of experimentally elevated energy expenditure on oxidative stress and lifespan in the short-tailed field vole Microtus agrestis. Proc. Biol. Sci. 275, 1907–1916. Selman, C., Blount, J.D., Nussey, D.H., Speakman, J.R., 2012. Oxidative damage, ageing, and lifehistory evolution: where now? Trends Ecol. Evol. 27, 570–577. Stier, A., Reichert, S., Criscuolo, F., Bize, P., 2015. Red blood cells open promising avenues for longitudinal studies of ageing in laboratory, non-model and wild animals. Exp. Gerontol. 71, 118–134. Vijg, J., Campisi, J., 2008. Puzzles, promises and a cure for ageing. Nature 454, 1065–1071. Vleck, C.M., Haussmann, M.F., Vleck, D., 2003. The natural history of telomeres: tools for aging animals and exploring the aging process. Exp. Gerontol. 38, 791–795. Watson, H., Cohen, A.A., Isaksson, C., 2015. A theoretical model of the evolution of actuarial senescence under environmental stress. Exp. Gerontol. 71, 80–88.
Quinn E. Fletcher Department of Biology, University of Winnipeg, Winnipeg, MB R3B 2E9, Canada Corresponding author. E-mail address: q.fl[email protected]. Colin Selman Glasgow Ageing Research Network (GARNER), Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK E-mail address: [email protected].
Contents lists available at ScienceDirect
Experimental Gerontology journal homepage: www.elsevier.com/locate/expgero
Editorial
Aging in the wild: Insights from free-living and non-model organisms
Come forth into the light of things, let nature be your teacher. William Wordsworth. Aging is most commonly defined as a decrease in physiological function that leads to an age-related decrease in fitness. The manifestations of aging are apparent at all phenotypic levels, from declining performance at the level of the whole animal, all the way down to ageassociated damage to, and dysfunction in, individual cells, organelles and molecules. Unfortunately, most of us are only too well versed on the effects of aging. Similarly, we are all acutely aware that the world's population comprises an ever higher proportion of elderly individuals, with age being the primary risk factor for a number of pathologies that significantly affect late-life health and well-being. As a result, understanding why we age, and how we age, is a major research challenge in science. Much of what we know about the biological processes underlying aging has been obtained from studies of ‘model’ organisms, such as Caenorhabditis elegans, Drosophila melanogaster and laboratory mice; animals that are easily maintained under standard laboratory conditions, relatively short-lived, genetically homogenous and have genomes amenable to manipulation. Using model organisms in biogerontology has undeniably generated critical insights into the aging process. We now know that many aging phenotypes and aging-relevant genetic pathways are conserved across wide evolutionary distances, and that both aging and late-life health can be extended through a number of dietary, genetic and pharmacological interventions (Vijg and Campisi, 2008; Gems and Partridge, 2013; Selman, 2014). However, and as detailed elsewhere (e.g. Monaghan et al., 2009; Austad, 2010b; Selman et al., 2012), limiting aging research to model organisms may cause us to miss important factors that help explain how and why we age. A second, complimentary, approach to understanding how and why we age is through studying aging in free-living animals and non-model organisms (Austad, 2010a,2010b; Nussey et al., 2013; Roach and Carey, 2014). This approach is gaining significant momentum and there is now a large body of empirical evidence that clearly demonstrates that animals in the wild experience aging (Bronikowski and Promislow, 2005; Nussey et al., 2013; Roach and Carey, 2014). While a large proportion of free-living individuals within a population is likely to succumb to the various challenges of living in the wild long before they exhibit clear manifestations of aging, many studies have now shown that reproductive performance, aspects of physiological and cellular function, and survival probability all decrease with advancing age free-living animals (for detailed reviews see Nussey et al., 2013; Roach and Carey, 2014; but see also Jones et al., 2014). Similarly, studies using comparative approaches and non-classical model organisms have already, and will continue, to provide important insights into the aging process
http://dx.doi.org/10.1016/j.exger.2015.09.015 0531-5565/© 2015 Elsevier Inc. All rights reserved.
(Austad, 1993; Kapahi et al., 1999; Selman et al., 2002, 2008; Nussey et al., 2006, 2009, 2012; Edrey et al., 2011; Fletcher et al., 2013; Kraus et al., 2013; Lucas-Sanchez et al., 2014). Inter-specific rates of aging and lifespan differ significantly in nature, often by orders of magnitude, and profound variation even exists between closely related organisms and intra-specifically. For example, the longevity of different dog breeds varies by a factor of two (Kraus et al., 2013); bats, birds and naked mole rats (Heterocephalus glaber) live much longer than expected for their body mass (Austad, 2010a,2010b; Edrey et al., 2011), and different honey bee (Apis mellifera) castes show profound variation in aging rates (Münch et al., 2008). In the following Special Issue we present 15 articles consisting of perspectives, reviews and original research papers from a leading group of scientists interested in aging from the perspectives of ecology, ecophysiology, evolutionary biology, modelling and biogerontology. These articles can be broadly grouped into four topics; 1) Non-model organisms in aging research, 2) Aging in free-living animals, 3) Novel modelling and statistical approaches to understand aging, 4) Innovative methodologies applicable to understanding aging in non-model and free-living animals. 1. Non-model organisms in aging research In this section we present three papers that highlight the potential value of using non-model organisms to understand aging. Archer and Hunt (2015) provide compelling reasons as to how crickets (family Gryllidae) can be used to generate novel insights into how sexual selection and sexual conflict influence aging rate and longevity, both from evolutionary and mechanistic perspectives. Gilmore and Greer (2015) put forward a compelling case for the importance of the dog as a model for human aging and age-associated pathology. As mentioned above, it is well-established inter-breed differences in the rate of aging and longevity exist between different dog breeds (Kraus et al., 2013). This substantial variation has stimulated significant research interest in understanding the aging process in man's best friend. It has been suggested that companion animals, such as dogs, may provide a critical stepping-stone in translating what we know about aging in model organisms to aging in humans, while also simultaneously helping to identify interventions that improve the healthspan of our pets (Kaeberlein, in press). Finally, Briga and Verhulst (2015) take an unconventional look at model organisms by reviewing a number of experiments where the fitness and lifespan of various long-lived laboratory mutants were compared to wild type animals during competition experiments or when exposed to environmental conditions that were more challenging than standard laboratory conditions. In both circumstances, they report that long-lived mutants generally fare worse relative to wild type
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controls, and discuss potential reasons and implications of this for aging research. 2. Aging in free-living animals Inter-specific and intra-specific analyses are two general approaches used to study aging in free-ranging animals. Three articles in this special issue focus on the inter-specific approach. First, Sanchez et al. (2015) discuss the utility of using comparative approaches across species to understand aging, particularly by using species that show extremely long lifespans, which they call ‘extremophiles’. In particular they discuss the likelihood that various metabolic, endocrine and oxidative processes are conserved across ‘extremophiles’, and how this may help understand mechanisms of aging. Second, in an original research paper, Dantzer and Fletcher (2015) test the prediction originally explored by Vleck et al. (2003) and Haussmann et al. (2003) that telomere shortening rates are slower in long-lived species than in short-lived species. By collating all studies that have been conducted on free-ranging animals up until now, their findings support this prediction and also suggest that species with fast life-histories also have higher rates of telomere attrition. Third, in a research article, Gaillard et al. (2015) tested whether the intensity of tooth wear experienced by different species of large herbivores in the wild was related to the longevity and rate of aging in captive animals of these species. The rate of tooth wear is a strong predictor of aging intra-specifically within large herbivores (e.g. Garrott et al., 2002) because worn teeth limit the ability of animals to obtain resources. However, the relationship between tooth wear and aging has never been tested inter-specifically. In their study, Gaillard et al. find that the rate of tooth wear was not related to longevity, but that tooth wear was generally faster in the species experiencing faster rates of aging. Two articles in this Special Issue then go on to focus on intra-specific research. First, Hayward et al. (2015) present a research article testing whether or not phenotypic traits reflecting components and predictors of fitness age in synchrony in Soay sheep (Ovis aries). Although most traits showed senescent declines, others did not, and some of these divergent patterns were sex-specific. Overall, the lack of consistency between these findings and existing theory opens the door for theory to be revised and further developed. Hammers et al. (2015) then provides a review article outlining the detailed aging research that has been conducted on a marked population of Seychelles warblers (Acrocephalus sechellensis). In addition to demonstrating senescent declines in key physiological traits, research on this population has also been able to document how the environment, social interactions, and life-history trade-offs influence senescence. The authors conclude by urging researchers to take a more experimental and integrative approach to studying aging that incorporates multiple physiological mechanisms and environmental variables. 3. Novel modelling and statistical approaches to understand aging Theoretical models are an additional way in which we can gain insights into aging. Watson et al. (2015) use a theoretical model to help understand the role that environmental stressors may play in the evolution of actuarial senescence in a hypothetical population of birds in response to simultaneous physiological stressors. Their modelling approach suggests that if environmental stressors act synergistically, rather than additively, then this may rapidly increase agingdependant mortality due to physiological dysregulation, leading to a population collapse. In another contribution, Kowald and Kirkwood (2015) review the evidence for the presence of aging in wild animal populations, and then go on to estimate the costs of aging in wild animals using life history data collected from recent field studies. Finally, they discuss the implications of senescence in wild populations for the existing evolutionary theories of aging, showing that the presence of senescent individuals within a population is compatible with both the
antagonistic pleiotropy and the disposable soma theories, but not the mutation accumulation theory. In a final paper in this theme, Boonekamp et al. (2015) give an in-depth overview of redundancy models and then re-examine a published dataset (Mair et al., 2003) using these models to provide additional insights into the influence of dietary restriction and temperature manipulation on aging in Drosophila. 4. Innovative methodologies applicable to understanding aging in non-model and free- living organisms Investigating the mechanistic processes underlying aging in nonmodel and free-living organisms has historically been hampered by difficulties in collecting samples from difficult to catch, rare and/or protected species, the inability to appropriately process and store biological materials, unsequenced genomes and the lack of exposure of field ecologists to relatively straightforward laboratory techniques (Selman et al., 2012). It is evident that this is now changing, in part, due to the ‘omics’ revolution, but also due to greater crosstalk between field-based and lab-based scientists. Three papers in this Special Issue are from researchers who use laboratory-based methodologies to investigate aging in non-model organisms. Münch et al. (2015) use a combination of western blotting and in situ hybridisation to identify the localisation of vitellogenin (Vg), an egg-yolk protein, within the brain of honey bees. Vg, which is known to influence both bee social behaviour and aging rate, was shown to localise to glial cells. The authors discuss how their findings may help understand the differences in aging rate between different honey bee castes. A number of studies in both model and non-model organisms (Salmon et al., 2005, 2008; Harper et al., 2007, 2011) have reported a positive correlation between cellular stress resistance and longevity. Alper et al. (2015) review the literature in this area and discuss the potential strengths, and caveats, to using this approach as a means to identify conserved mechanisms of aging both within and between species. In particular, this approach may be highly applicable to studies of aging in endangered species, or those that are part of a long-term longitudinal study. What is clear is that tissue punches or biopsies could provide sufficient material to culture primary cells and then investigate a number of candidate mechanisms, including cellular stress resistance. Along similar lines, Stier et al. (2015), highlight that red blood cells can provide important insight into a diversity of agerelated physiological changes (e.g. oxidative stress, glucose homeostasis, mitochondrial functioning, and telomere dynamics). They then go on to provide an overview of all studies that have examined these physiological components in non-model organisms. They also argue that examining red blood cells is a powerful way to examine aging because red blood cells can be obtained repeatedly from individuals in longitudinal studies, which removes potential biases caused by selective disappearance in cross-sectional studies. Finally, employing a cutting-edge RNAseq approach, Schwartz et al. (2015) investigated mitochondrial genotypes and transcription in slow-aging and fast-aging garter snake (Thamnophis elegans) ecotypes. By reconstructing the garter snake mitochondrial sequence they investigated differences in mitochondrial gene expression between the ecotypes and in response to heat stress. Their approach found that expression of protein coding genes was higher in the fast-aging ecotype, and that divergence in mitochondrial haplotypes observed between these ecotypes fits with previous findings relating to mitochondrial function. Thisresearch demonstrates the clear potential for using high throughput next generation sequencing approaches to understanding aging-related processes in animals lacking sequenced genomes. Similarly, other ‘omic’ technologies such as metabolomics and lipidomics can offer exciting new insights into aging in non-model and free-living organisms (e.g. Aksenov et al., 2014; Roznere et al., 2014; Gomez et al., 2015). Over the last few decades there have been major advances in our understanding of the aging process, with much of this knowledge generated within model organisms. However, as discussed in this Special Issue
Editorial
there is much that can be learned from non-model organisms and field studies that can help augment what we already know, and help discover much of what we do not, both from the perspective of how and why we age. We hope that this Special Issue will help stimulate new ideas and greater cross-talk between field- and lab-based empiricists and theoreticians; scientists who have historically tended not to interact. What is clear is that given the complexity of the aging process, multidisciplinary approaches, at the very least, are likely to identify new pieces of the puzzle. Conflict of interest The authors have no conflicts of interest. Acknowledgements We are grateful to Prof. Christiaan Leeuwenburgh, Deputy Editor at Experimental Gerontology for recommending us, and to Prof. Tom Johnson, Editor-in-Chief, for enabling us to edit this Special Issue. 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Quinn E. Fletcher Department of Biology, University of Winnipeg, Winnipeg, MB R3B 2E9, Canada Corresponding author. E-mail address: q.fl[email protected]. Colin Selman Glasgow Ageing Research Network (GARNER), Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK E-mail address: [email protected].