Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Experimental manipulation of microbiota reduces host thermal tolerance and fitness under heat stress in a vertebrate ectotherm

Nature Ecology & Evolution volume 6, pages 405–417 (2022)Cite this article

Subjects

Abstract

Identifying factors that influence how ectothermic animals respond physiologically to changing temperatures is of high importance given current threats of global climate change. Host-associated microbial communities impact animal physiology and have been shown to influence host thermal tolerance in invertebrate systems. However, the role of commensal microbiota in the thermal tolerance of ectothermic vertebrates is unknown. Here we show that experimentally manipulating the tadpole microbiome through environmental water sterilization reduces the host’s acute thermal tolerance to both heat and cold, alters the thermal sensitivity of locomotor performance, and reduces animal survival under prolonged heat stress. We show that these tadpoles have reduced activities of mitochondrial enzymes and altered metabolic rates compared with tadpoles colonized with unmanipulated microbiota, which could underlie differences in thermal phenotypes. These results demonstrate a strong link between the microbiota of an ectothermic vertebrate and the host’s thermal tolerance, performance and fitness. It may therefore be important to consider host-associated microbial communities when predicting species’ responses to climate change.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Effects of microbial colonization treatment and acclimation temperature on tadpole gut microbial communities, morphometrics and acute thermal tolerance.
Fig. 2: Survival of colonized and depleted tadpoles under heat stress conditions.
Fig. 3: Maximum swimming velocity of colonized and depleted tadpoles at six assay temperatures.
Fig. 4: Mitochondrial enzyme activities in tail muscle of colonized and depleted tadpoles at three assay temperatures.
Fig. 5: Relationship between mass-specific resting metabolic rate and body mass in colonized and depleted tadpoles at two temperatures.

Similar content being viewed by others

Data availability

The raw microbiome sequencing data are available from NCBI’s Sequence Read Archive under accession no. PRJNA732310. All other raw datasets are available from the Zenodo repository at https://doi.org/10.5281/zenodo.5703371.

Code availability

The R code used for the statistical analyses in this study is available from the Zenodo repository at https://doi.org/10.5281/zenodo.5703371.

References

  1. Paaijmans, K. P. et al. Temperature variation makes ectotherms more sensitive to climate change. Glob. Change Biol. 19, 2373–2380 (2013).

    Article  Google Scholar 

  2. Clusella-Trullas, S., Blackburn, T. M. & Chown, S. L. Climatic predictors of temperature performance curve parameters in ectotherms imply complex responses to climate change. Am. Nat. 177, 738–751 (2011).

    Article  PubMed  Google Scholar 

  3. Pounds, J. A. et al. Widespread amphibian extinctions from epidemic disease driven by global warming. Nature 439, 161–167 (2006).

    Article  CAS  PubMed  Google Scholar 

  4. Sinervo, B. et al. Erosion of lizard diversity by climate change and altered thermal niches. Science 328, 894–899 (2010).

    Article  CAS  PubMed  Google Scholar 

  5. Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Change 5, 215–224 (2015).

    Article  Google Scholar 

  6. Angilletta, M. J. Jr Thermal Adaptation: A Theoretical and Empirical Synthesis (Oxford Univ. Press, 2009).

  7. Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).

    Article  PubMed  Google Scholar 

  8. Jørgensen, L. B., Malte, H. & Overgaard, J. How to assess Drosophila heat tolerance: unifying static and dynamic tolerance assays to predict heat distribution limits. Funct. Ecol. 33, 629–642 (2019).

    Article  Google Scholar 

  9. Pörtner, H.-O., Bock, C. & Mark, F. C. Oxygen- and capacity-limited thermal tolerance: bridging ecology and physiology. J. Exp. Biol. 220, 2685–2696 (2017).

    Article  PubMed  Google Scholar 

  10. Gangloff, E. J. & Telemeco, R. S. High temperature, oxygen, and performance: insights from reptiles and amphibians. Integr. Comp. Biol. 58, 9–24 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Perry, G. M., Danzmann, R. G., Ferguson, M. M. & Gibson, J. P. Quantitative trait loci for upper thermal tolerance in outbred strains of rainbow trout (Oncorhynchus mykiss). Heredity 86, 333–341 (2001).

    Article  CAS  PubMed  Google Scholar 

  12. Healy, T. M. & Schulte, P. M. Factors affecting plasticity in whole-organism thermal tolerance in common killifish (Fundulus heteroclitus). J. Comp. Physiol. B 182, 49–62 (2012).

    Article  PubMed  Google Scholar 

  13. Hu, X. P. & Appel, A. G. Seasonal variation of critical thermal limits and temperature tolerance in Formosan and eastern subterranean termites (Isoptera: Rhinotermitidae). Environ. Entomol. 33, 197–205 (2004).

    Article  CAS  Google Scholar 

  14. Nyamukondiwa, C. & Terblanche, J. S. Thermal tolerance in adult Mediterranean and Natal fruit flies (Ceratitis capitata and Ceratitis rosa): effects of age, gender and feeding status. J. Therm. Biol. 34, 406–414 (2009).

    Article  Google Scholar 

  15. Greenspan, S. E. et al. Infection increases vulnerability to climate change via effects on host thermal tolerance. Sci. Rep. 7, 9349 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Padfield, D., Castledine, M. & Buckling, A. Temperature-dependent changes to host–parasite interactions alter the thermal performance of a bacterial host. ISME J. 14, 389–398 (2020).

    Article  PubMed  Google Scholar 

  17. Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Goodrich, J. K. et al. Human genetics shape the gut microbiome. Cell 159, 789–799 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Alberdi, A., Aizpurua, O., Bohmann, K., Zepeda-Mendoza, M. L. & Gilbert, M. T. P. Do vertebrate gut metagenomes confer rapid ecological adaptation? Trends Ecol. Evol. 31, 689–699 (2016).

    Article  PubMed  Google Scholar 

  20. Kohl, K. D. & Carey, H. V. A place for host–microbe symbiosis in the comparative physiologist’s toolbox. J. Exp. Biol. 219, 3496–3504 (2016).

    Article  PubMed  Google Scholar 

  21. Fontaine, S. S. & Kohl, K. D. Optimal integration between host physiology and functions of the gut microbiome. Phil. Trans. R. Soc. B 375, 20190594 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Velagapudi, V. R. et al. The gut microbiota modulates host energy and lipid metabolism in mice. J. Lipid Res. 51, 1101–1112 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Donohoe, D. R. et al. The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab. 13, 517–526 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 14213 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Russell, J. A. & Moran, N. A. Costs and benefits of symbiont infection in aphids: variation among symbionts and across temperatures. Proc. R. Soc. B 273, 603–610 (2006).

    Article  PubMed  Google Scholar 

  26. Montllor, C. B., Maxmen, A. & Purcell, A. H. Facultative bacterial endosymbionts benefit pea aphids Acyrthosiphon pisum under heat stress. Ecol. Entomol. 27, 189–195 (2002).

    Article  Google Scholar 

  27. Herrera, M. et al. Unfamiliar partnerships limit cnidarian holobiont acclimation to warming. Glob. Change Biol. 26, 5539–5553 (2020).

    Article  Google Scholar 

  28. Jaramillo, A. & Castaneda, L. E. Gut microbiota of Drosophila subobscura contributes to its heat tolerance and is sensitive to transient thermal stress. Front. Microbiol. 12, 886 (2021).

    Article  Google Scholar 

  29. Moghadam, N. N. et al. Strong responses of Drosophila melanogaster microbiota to developmental temperature. Fly 12, 1–12 (2018).

    Article  PubMed  Google Scholar 

  30. Fontaine, S. S., Novarro, A. J. & Kohl, K. D. Environmental temperature alters the digestive performance and gut microbiota of a terrestrial amphibian. J. Exp. Biol. 221, 187559 (2018).

    Article  Google Scholar 

  31. Kohl, K. D. & Yahn, J. Effects of environmental temperature on the gut microbial communities of tadpoles. Environ. Microbiol. 18, 1561–1565 (2016).

    Article  PubMed  Google Scholar 

  32. Fontaine, S. S. & Kohl, K. D. The gut microbiota of invasive bullfrog tadpoles responds more rapidly to temperature than a non‐invasive congener. Mol. Ecol. 29, 2449–2462 (2020).

    Article  PubMed  Google Scholar 

  33. Bestion, E. et al. Climate warming reduces gut microbiota diversity in a vertebrate ectotherm. Nat. Ecol. Evol. 1, 0161 (2017).

    Article  Google Scholar 

  34. Zhu, L. et al. Environmental temperatures affect the gastrointestinal microbes of the Chinese giant salamander. Front. Microbiol. 12, 493 (2021).

    Google Scholar 

  35. Moeller, A. H. et al. The lizard gut microbiome changes with temperature and is associated with heat tolerance. Appl. Environ. Microbiol. 86, e01181-20 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kokou, F. et al. Host genetic selection for cold tolerance shapes microbiome composition and modulates its response to temperature. eLife 7, e36398 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Hanage, W. P. Microbiology: microbiome science needs a healthy dose of scepticism. Nature 512, 247–248 (2014).

    Article  CAS  PubMed  Google Scholar 

  38. Pascoe, E. L., Hauffe, H. C., Marchesi, J. R. & Perkins, S. E. Network analysis of gut microbiota literature: an overview of the research landscape in non-human animal studies. ISME J. 11, 2644–2651 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Mykles, D. L., Ghalambor, C. K., Stillman, J. H. & Tomanek, L. Grand challenges in comparative physiology: integration across disciplines and across levels of biological organization. Integr. Comp. Biol. 50, 6–16 (2010).

    Article  PubMed  Google Scholar 

  40. Kohl, K. D. A microbial perspective on the grand challenges in comparative animal physiology. mSystems 3, e00146-17 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Gray, K. T., Escobar, A. M., Schaeffer, P. J., Mineo, P. M. & Berner, N. J. Thermal acclimatization in overwintering tadpoles of the green frog, Lithobates clamitans (Latreille, 1801). J. Exp. Zool. A 325, 285–293 (2016).

    Article  Google Scholar 

  42. Brattstrom, B. H. & Lawrence, P. The rate of thermal acclimation in anuran amphibians. Physiol. Zool. 35, 148–156 (1962).

    Article  Google Scholar 

  43. Knutie, S. A., Wilkinson, C. L., Kohl, K. D. & Rohr, J. R. Early-life disruption of amphibian microbiota decreases later-life resistance to parasites. Nat. Commun. 8, 86 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Warne, R. W., Kirschman, L. & Zeglin, L. Manipulation of gut microbiota during critical developmental windows affects host physiological performance and disease susceptibility across ontogeny. J. Anim. Ecol. 88, 845–856 (2019).

    Article  PubMed  Google Scholar 

  45. Morgun, A. et al. Uncovering effects of antibiotics on the host and microbiota using transkingdom gene networks. Gut 64, 1732–1743 (2015).

    Article  CAS  PubMed  Google Scholar 

  46. Kohl, K. D., Cary, T. L., Karasov, W. H. & Dearing, M. D. Restructuring of the amphibian gut microbiota through metamorphosis. Environ. Microbiol. Rep. 5, 899–903 (2013).

    Article  PubMed  Google Scholar 

  47. Vences, M. et al. Gut bacterial communities across tadpole ecomorphs in two diverse tropical anuran faunas. Sci. Nat. 103, 25 (2016).

    Article  Google Scholar 

  48. Fontaine, S. S., Mineo, P. M. & Kohl, K. D. Changes in the gut microbial community of the eastern newt (Notophthalmus viridescens) across its three distinct life stages. FEMS Microbiol. Ecol. 97, fiab021 (2021).

    Article  CAS  PubMed  Google Scholar 

  49. Anderson, M. J. & Walsh, D. C. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: what null hypothesis are you testing? Ecol. Monogr. 83, 557–574 (2013).

    Article  Google Scholar 

  50. Sepulveda, J. & Moeller, A. H. The effects of temperature on animal gut microbiomes. Front. Microbiol. 11, 384 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Arango, R. A., Schoville, S. D., Currie, C. R. & Carlos-Shanley, C. Experimental warming reduces survival, cold tolerance, and gut prokaryotic diversity of the eastern subterranean termite, Reticulitermes flavipes (Kollar). Front. Microbiol. 12, 1116 (2021).

    Article  Google Scholar 

  52. Stothart, M. R. et al. Stress and the microbiome: linking glucocorticoids to bacterial community dynamics in wild red squirrels. Biol. Lett. 12, 20150875 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Zaneveld, J. R., McMinds, R. & Thurber, R. V. Stress and stability: applying the Anna Karenina principle to animal microbiomes. Nat. Microbiol. 2, 17121 (2017).

    Article  CAS  PubMed  Google Scholar 

  54. Orrock, J. L. & Watling, J. I. Local community size mediates ecological drift and competition in metacommunities. Proc. R. Soc. B 277, 2185–2191 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Deeg, C. M. et al. Chromulinavorax destructans, a pathogen of microzooplankton that provides a window into the enigmatic candidate phylum Dependentiae. PLoS Pathog. 15, e1007801 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Kaboré, O. D., Godreuil, S. & Drancourt, M. Planctomycetes as host-associated bacteria: a perspective that holds promise for their future isolations, by mimicking their native environmental niches in clinical microbiology laboratories. Front. Cell. Infect. Microbiol. 10, 729 (2020).

    Article  Google Scholar 

  57. Sheremet, A. et al. Ecological and genomic analyses of candidate phylum WPS‐2 bacteria in an unvegetated soil. Environ. Microbiol. 22, 3143–3157 (2020).

    Article  CAS  PubMed  Google Scholar 

  58. Correa, D. T. et al. Multilevel community assembly of the tadpole gut microbiome. Preprint at bioRxiv https://doi.org/10.1101/2020.07.05.188698 (2020).

  59. Contijoch, E. J. et al. Gut microbiota density influences host physiology and is shaped by host and microbial factors. eLife 8, e40553 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Warne, R. W., Kirschman, L. & Zeglin, L. Manipulation of gut microbiota reveals shifting community structure shaped by host developmental windows in amphibian larvae. Integr. Comp. Biol. 57, 786–794 (2017).

    Article  PubMed  Google Scholar 

  61. Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc. R. Soc. B 286, 20182448 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Lutterschmidt, W. I. & Hutchison, V. H. The critical thermal maximum: history and critique. Can. J. Zool. 75, 1561–1574 (1997).

    Article  Google Scholar 

  63. Gosner, K. L. A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16, 183–190 (1960).

    Google Scholar 

  64. Daloso, D. M. The ecological context of bilateral symmetry of organ and organisms. Nat. Sci. 6, 43340 (2014).

    Google Scholar 

  65. Goldstein, J. A., Hoff, K. v. S. & Hillyard, S. D. The effect of temperature on development and behaviour of relict leopard frog tadpoles. Conserv. Physiol. 5, cow075 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Harkey, G. A. & Semlitsch, R. D. Effects of temperature on growth, development, and color polymorphism in the ornate chorus frog Pseudacris ornata. Copeia 1998, 1001–1007 (1988).

    Article  Google Scholar 

  67. Marian, M. & Pandian, T. Effect of temperature on development, growth and bioenergetics of the bullfrog tadpole Rana tigrina. J. Therm. Biol. 10, 157–161 (1985).

    Article  Google Scholar 

  68. Alvarez, D. & Nicieza, A. Effects of temperature and food quality on anuran larval growth and metamorphosis. Funct. Ecol. 16, 640–648 (2002).

    Article  Google Scholar 

  69. Kohl, K. D., Brun, A., Bordenstein, S. R., Caviedes‐Vidal, E. & Karasov, W. H. Gut microbes limit growth in house sparrow nestlings (Passer domesticus) but not through limitations in digestive capacity. Integr. Zool. 13, 139–151 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Potti, J. et al. Bacteria divert resources from growth for Magellanic penguin chicks. Ecol. Lett. 5, 709–714 (2002).

    Article  Google Scholar 

  71. Coates, M. E., Fuller, R., Harrison, G., Lev, M. & Suffolk, S. A comparison of the growth of chicks in the Gustafsson germ-free apparatus and in a conventional environment, with and without dietary supplements of penicillin. Br. J. Nutr. 17, 141–150 (1963).

    Article  CAS  PubMed  Google Scholar 

  72. Gaskins, H., Collier, C. & Anderson, D. Antibiotics as growth promotants: mode of action. Anim. Biotechnol. 13, 29–42 (2002).

    Article  CAS  PubMed  Google Scholar 

  73. Gitsels, A., Sanders, N. & Vanrompay, D. Chlamydial infection from outside to inside. Front. Microbiol. 10, 2329 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Denver, R. J. Proximate mechanisms of phenotypic plasticity in amphibian metamorphosis. Am. Zool. 37, 172–184 (1997).

    Article  CAS  Google Scholar 

  75. Chevalier, C. et al. Gut microbiota orchestrates energy homeostasis during cold. Cell 163, 1360–1374 (2015).

    Article  CAS  PubMed  Google Scholar 

  76. Khakisahneh, S., Zhang, X.-Y., Nouri, Z. & Wang, D.-H. Gut microbiota and host thermoregulation in response to ambient temperature fluctuations. mSystems 5, e00514–e00520 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Xie, B. et al. Chlamydomonas reinhardtii thermal tolerance enhancement mediated by a mutualistic interaction with vitamin B12-producing bacteria. ISME J. 7, 1544–1555 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Gutiérrez‐Pesquera, L. M. et al. Testing the climate variability hypothesis in thermal tolerance limits of tropical and temperate tadpoles. J. Biogeogr. 43, 1166–1178 (2016).

    Article  Google Scholar 

  79. Litmer, A. R. & Murray, C. M. Critical thermal tolerance of invasion: comparative niche breadth of two invasive lizards. J. Therm. Biol. 86, 102432 (2019).

    Article  PubMed  Google Scholar 

  80. Semlitsch, R. D. Effects of body size, sibship, and tail injury on the susceptibility of tadpoles to dragonfly predation. Can. J. Zool. 68, 1027–1030 (1990).

    Article  Google Scholar 

  81. Cabrera-Guzmán, E., Crossland, M. R., Brown, G. P. & Shine, R. Larger body size at metamorphosis enhances survival, growth and performance of young cane toads (Rhinella marina). PLoS ONE 8, e70121 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Tejedo, M. Effects of body size and timing of reproduction on reproductive success in female natterjack toads (Bufo calamita). J. Zool. 228, 545–555 (1992).

    Article  Google Scholar 

  83. Warne, R. W., Crespi, E. J. & Brunner, J. L. Escape from the pond: stress and developmental responses to ranavirus infection in wood frog tadpoles. Funct. Ecol. 25, 139–146 (2011).

    Article  Google Scholar 

  84. Urban, M. C. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).

    Article  CAS  PubMed  Google Scholar 

  85. Pearce, T. A. & Paustian, M. E. Are temperate land snails susceptible to climate change through reduced altitudinal ranges? A Pennsylvania example. Am. Malacol. 31, 213–224 (2013).

    Article  Google Scholar 

  86. Wolfe, D. W. et al. Projected change in climate thresholds in the northeastern US: implications for crops, pests, livestock, and farmers. Mitig. Adapt. Strateg. Glob. Change 13, 555–575 (2008).

    Article  Google Scholar 

  87. Huey, R. B. & Kingsolver, J. G. Evolution of thermal sensitivity of ectotherm performance. Trends Ecol. Evol. 4, 131–135 (1989).

    Article  CAS  PubMed  Google Scholar 

  88. Bennett, A. F. Thermal dependence of locomotor capacity. Am. J. Physiol. 259, R253–R258 (1990).

    CAS  PubMed  Google Scholar 

  89. Seebacher, F. & Walter, I. Differences in locomotor performance between individuals: importance of parvalbumin, calcium handling and metabolism. J. Exp. Biol. 215, 663–670 (2012).

    Article  CAS  PubMed  Google Scholar 

  90. Husak, J. F., Fox, S. F., Lovern, M. B. & Bussche, R. A. V. D. Faster lizards sire more offspring: sexual selection on whole‐animal performance. Evolution 60, 2122–2130 (2006).

    Article  CAS  PubMed  Google Scholar 

  91. Mineo, P. M., Waldrup, C., Berner, N. J. & Schaeffer, P. J. Differential plasticity of membrane fatty acids in northern and southern populations of the eastern newt (Notophthalmus viridescens). J. Comp. Physiol. B 189, 249–260 (2019).

    Article  CAS  PubMed  Google Scholar 

  92. Chung, D. J., Sparagna, G. C., Chicco, A. J. & Schulte, P. M. Patterns of mitochondrial membrane remodeling parallel functional adaptations to thermal stress. J. Exp. Biol. 221, 174458 (2018).

    Article  Google Scholar 

  93. Gladwell, R., Bowler, K. & Duncan, C. Heat death in crayfish Austropotamobius pallipes: ion movements and their effects on excitable tissues during heat death. J. Therm. Biol. 1, 79–94 (1976).

    Article  CAS  Google Scholar 

  94. Wang, Z. et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472, 57–63 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Pörtner, H. Climate change and temperature-dependent biogeography: oxygen limitation of thermal tolerance in animals. Naturwissenschaften 88, 137–146 (2001).

    Article  PubMed  Google Scholar 

  96. Gräns, A. et al. Aerobic scope fails to explain the detrimental effects on growth resulting from warming and elevated CO2 in Atlantic halibut. J. Exp. Biol. 217, 711–717 (2014).

    Article  PubMed  Google Scholar 

  97. Jutfelt, F. et al. Oxygen- and capacity-limited thermal tolerance: blurring ecology and physiology. J. Exp. Biol. 221, 169615 (2018).

    Article  Google Scholar 

  98. St-Pierre, J., Charest, P.-M. & Guderley, H. Relative contribution of quantitative and qualitative changes in mitochondria to metabolic compensation during seasonal acclimatisation of rainbow trout Oncorhynchus mykiss. J. Exp. Biol. 201, 2961–2970 (1998).

    Article  CAS  Google Scholar 

  99. Grim, J., Miles, D. & Crockett, E. Temperature acclimation alters oxidative capacities and composition of membrane lipids without influencing activities of enzymatic antioxidants or susceptibility to lipid peroxidation in fish muscle. J. Exp. Biol. 213, 445–452 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. LeMoine, C. M., Genge, C. E. & Moyes, C. D. Role of the PGC-1 family in the metabolic adaptation of goldfish to diet and temperature. J. Exp. Biol. 211, 1448–1455 (2008).

    Article  CAS  PubMed  Google Scholar 

  101. McClelland, G. B., Craig, P. M., Dhekney, K. & Dipardo, S. Temperature‐ and exercise‐induced gene expression and metabolic enzyme changes in skeletal muscle of adult zebrafish (Danio rerio). J. Physiol. 577, 739–751 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Pichaud, N. et al. Cardiac mitochondrial plasticity and thermal sensitivity in a fish inhabiting an artificially heated ecosystem. Sci. Rep. 9, 17832 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  103. Seebacher, F., Guderley, H., Elsey, R. M. & Trosclair, P. L. Seasonal acclimatisation of muscle metabolic enzymes in a reptile (Alligator mississippiensis). J. Exp. Biol. 206, 1193–1200 (2003).

    Article  CAS  PubMed  Google Scholar 

  104. Berner, N. J. & Bessay, E. P. Correlation of seasonal acclimatization in metabolic enzyme activity with preferred body temperature in the eastern red spotted newt (Notophthalmus viridescens viridescens). Comp. Biochem. Physiol. A 144, 429–436 (2006).

    Article  Google Scholar 

  105. Vigelsø, A., Andersen, N. B. & Dela, F. The relationship between skeletal muscle mitochondrial citrate synthase activity and whole body oxygen uptake adaptations in response to exercise training. Int. J. Physiol. Pathophysiol. Pharmacol. 6, 84–101 (2014).

    PubMed  PubMed Central  Google Scholar 

  106. Li, Y., Park, J.-S., Deng, J.-H. & Bai, Y. Cytochrome c oxidase subunit IV is essential for assembly and respiratory function of the enzyme complex. J. Bioenerg. Biomembr. 38, 283–291 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Pryor, G. S. & Bjorndal, K. A. Symbiotic fermentation, digesta passage, and gastrointestinal morphology in bullfrog tadpoles (Rana catesbeiana). Physiol. Biochem. Zool. 78, 201–215 (2005).

    Article  PubMed  Google Scholar 

  108. Clark, A. & Mach, N. The crosstalk between the gut microbiota and mitochondria during exercise. Front. Physiol. 8, 319 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  109. Payne, N. L. et al. Temperature dependence of fish performance in the wild: links with species biogeography and physiological thermal tolerance. Funct. Ecol. 30, 903–912 (2016).

    Article  Google Scholar 

  110. Van Dijk, P., Tesch, C., Hardewig, I. & Portner, H. Physiological disturbances at critically high temperatures: a comparison between stenothermal Antarctic and eurythermal temperate eelpouts (Zoarcidae). J. Exp. Biol. 202, 3611–3621 (1999).

    Article  PubMed  Google Scholar 

  111. Schulte, P. M. The effects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment. J. Exp. Biol. 218, 1856–1866 (2015).

    Article  PubMed  Google Scholar 

  112. Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M. & Charnov, E. L. Effects of size and temperature on metabolic rate. Science 293, 2248–2251 (2001).

    Article  CAS  PubMed  Google Scholar 

  113. Hoppeler, H. & Weibel, E. R. Scaling functions to body size: theories and facts. J. Exp. Biol. 208, 1573–1574 (2005).

    Article  PubMed  Google Scholar 

  114. Hopkins, W. A., Rowe, C. L. & Congdon, J. D. Elevated trace element concentrations and standard metabolic rate in banded water snakes (Nerodia fasciata) exposed to coal combustion wastes. Environ. Toxicol. Chem. 18, 1258–1263 (1999).

    Article  CAS  Google Scholar 

  115. Sokolova, I. Bioenergetics in environmental adaptation and stress tolerance of aquatic ectotherms: linking physiology and ecology in a multi-stressor landscape. J. Exp. Biol. 224, 236802 (2021).

    Article  Google Scholar 

  116. Sokolova, I. M. & Lannig, G. Interactive effects of metal pollution and temperature on metabolism in aquatic ectotherms: implications of global climate change. Clim. Res. 37, 181–201 (2008).

    Article  Google Scholar 

  117. Peralta-Maraver, I. & Rezende, E. L. Heat tolerance in ectotherms scales predictably with body size. Nat. Clim. Change 11, 58–63 (2021).

    Article  Google Scholar 

  118. Bahrndorff, S., Alemu, T., Alemneh, T. & Lund Nielsen, J. The microbiome of animals: implications for conservation biology. Int. J. Genomics 2016, 5304028 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Hauffe, H. C. & Barelli, C. Conserve the germs: the gut microbiota and adaptive potential. Conserv. Genet. 20, 19–27 (2019).

    Article  Google Scholar 

  120. Jiménez, R. R. & Sommer, S. The amphibian microbiome: natural range of variation, pathogenic dysbiosis, and role in conservation. Biodivers. Conserv. 26, 763–786 (2017).

    Article  Google Scholar 

  121. Swaddle, J. P. Fluctuating asymmetry, animal behavior, and evolution. Adv. Study Behav. 32, 169–205 (2003).

    Article  Google Scholar 

  122. R Core Team R: A Language and Environment for Statistical Computing v.3.4.3 (R Foundation for Statistical Computing, 2019).

  123. Bates, D., Machler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. Preprint at https://arxiv.org/abs/1406.5823 (2014).

  124. Pinheiro, J. et al. nlme: Linear and Nonlinear Mixed Effects Models. R package version 3 (2017).

  125. Hulbert, A., Pamplona, R., Buffenstein, R. & Buttemer, W. Life and death: metabolic rate, membrane composition, and life span of animals. Physiol. Rev. 87, 1175–1213 (2007).

    Article  CAS  PubMed  Google Scholar 

  126. Oksanen, J. et al. vegan: Community Ecology Package. R package version 2 (2013).

  127. Mary-Huard, T., Daudin, J.-J., Baccini, M., Biggeri, A. & Bar-Hen, A. Biases induced by pooling samples in microarray experiments. Bioinformatics 23, i313–i318 (2007).

    Article  CAS  PubMed  Google Scholar 

  128. Singer, J. D. & Willett, J. B. It’s about time: using discrete-time survival analysis to study duration and the timing of events. J. Educ. Stat. 18, 155–195 (1993).

    Google Scholar 

  129. Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput. Biol. 17, e100442 (2021).

    Article  Google Scholar 

Download references

Acknowledgements

We thank M. Ohmer, K. Altman and E. Le Sage for field collection assistance; K. Kohler, M. Maurer, M. Maier, S. Reilly, A. Haid, C. Duckworth and J. Adams for animal husbandry and DNA extraction assistance; and N. Barts for technical assistance. We also thank the University of Pittsburgh’s Health Sciences Metabolomics and Lipidomics core facility (NIH S10OD023402 PI Wendell), the DNA Services Facility at the University of Illinois at Chicago, and the Microbial Analysis, Resources, and Services Facility at the University of Connecticut for sample processing. This work was supported by the University of Pittsburgh (start-up funds to K.D.K.), Elmhurst University (faculty research grant to P.M.M.) and the National Science Foundation (GRFP to S.S.F.).

Author information

Authors and Affiliations

  1. Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA

    Samantha S. Fontaine & Kevin D. Kohl

  2. Department of Biology, Elmhurst University, Elmhurst, IL, USA

    Patrick M. Mineo

Authors
  1. Samantha S. Fontaine
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Patrick M. Mineo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kevin D. Kohl
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.S.F., K.D.K. and P.M.M. designed the study. S.S.F. and P.M.M. collected the data. S.S.F. analysed the data, generated the figures and wrote the initial manuscript draft with editing from K.D.K. and P.M.M. K.D.K. supervised the research.

Corresponding author

Correspondence to Samantha S. Fontaine.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Ecology & Evolution thanks Camila Carlos-Shanley and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Experimental designs and sample sizes for experiments 1 and 2.

For both experiments, tadpoles were reared from pairs of adult frogs in the laboratory and divided into colonized (C) and depleted (D) water treatments at Gosner stage (GS) 25. For experiment 1, green frog tadpoles and pond water from Louisiana (LA, USA) were used and for experiment 2, green frog tadpoles and pond water from Pennsylvania (PA, USA) were used. Images created with BioRender.com.

Extended Data Fig. 2 Environmental microbial communities of pond water used for the colonized microbial treatment.

a, Principal Coordinate (PCo) analysis plot based on Bray-Curtis dissimilarity between microbial communities of water samples collected fresh from the pond or after storage in the laboratory at 4 °C. b, Principal Coordinate (PCo) analysis plot based on Bray-Curtis dissimilarity between tadpole gut microbial communities and microbial communities of pond water collected fresh from the pond or after storage in the laboratory. Due to overlap between water types on the plot, fresh pond water samples are outlined in black. For both PCoA plots, percentages represent the proportion of variation explained by each axis. c, mean relative abundances of bacterial phyla found in pond water samples fresh from the pond or after storage in the laboratory. The top ten most abundant phyla are shown individually, and the remainder are grouped together as “other”. Any bacteria that were unable to be assigned to a phylum are grouped together as “unassigned”. d, mean relative abundances of bacterial genera found in pond water samples fresh from the pond or after storage in the laboratory. The top ten most abundant genera from each group are shown individually, and the remainder are grouped together as “other”. Any bacteria that were unable to be assigned to a genus are grouped together as “unassigned”. For all figures, N = 2 for fresh pond samples and N = 7 for stored samples.

Extended Data Fig. 3 Mean relative abundances of bacterial phyla in gut microbial communities of tadpoles from experiment 1 across microbial colonization and acclimation temperature treatment groups.

The top ten most abundant phyla are shown individually, and the remainder are grouped together as “other”. Any bacteria that were unable to be assigned to a phylum are grouped together as “unassigned”. N = 27 animals per group.

Extended Data Fig. 4 Impacts of microbial colonization treatment and acclimation temperature on tadpole gut microbial communities in experiment 1.

a, Faith’s phylogenetic diversity of the gut bacterial community b, Shannon diversity of the gut bacterial community c, Pielou’s evenness within the gut bacterial community d, Number of bacterial cells in tadpole gut contents measured using flow cytometry and shown on a log scale e, Principal Coordinate (PCo) analysis plot based on Unweighted UniFrac distance between gut bacterial community samples f, Principal Coordinate analysis (PCo) plot based on Weighted UniFrac distance between gut bacterial community samples. For boxplots a-c, N = 25 for the 14 °C colonized and depleted groups, 26 for the 22 °C colonized and depleted groups, 26 for the 28 °C depleted group, and 27 for the 28 °C colonized group. For boxplot d, N = 3 for the 14 °C colonized group, 10 for the 14 °C depleted group, 10 for the 22 °C colonized group, 11 for the 22 °C depleted group, 10 for the 28 °C depleted group, and 9 for the 28 °C colonized group. For all boxplots, the center line represents the median, the length of the box extends through the IQR, and whiskers extend to 1.5x IQR. All points outside this range are plotted individually. For all principal coordinate analysis plots, percentages represent the proportion of variation explained by each axis. C = colonized tadpoles and D = depleted tadpoles. Colors represent tadpole acclimation temperature.

Extended Data Fig. 5 Plots used to determine gating parameters for flow cytometry from one representative sample.

a, A plot of fluorescein isothiocyanate (FITC) vs. cell counts was used to distinguish cells stained with SYBR Green dye from all other cells b, A plot of forward scatter (FSC) vs. side scatter (SSC) was used to distinguish populations of counting beads from all other events. To establish initial gates for counting beads, blank samples spiked only with beads were used. On both plots, red rectangles represent the gates and surround the events counted. Percentages indicate the proportion of events within the gate out of total events. R1 = stained bacterial cells and R2 = counting beads.

Extended Data Fig. 6 Tadpole morphometrics across microbial colonization and acclimation temperature treatment groups from experiment 1.

a, tadpole body length b, tadpole body width c, tadpole facial symmetry, calculated as the absolute value, subtracted from 1, of the difference between the distance from the center of each eye to the tip of the nose. The center line of each boxplot represents the median, the length of the box extends through the IQR, and whiskers extend to 1.5x IQR. All points outside this range are plotted individually. C = colonized tadpoles and D = depleted tadpoles. Colors represent tadpole acclimation temperature. N = 27 animals per group.

Extended Data Fig. 7 Impact of microbial colonization treatment on tadpole gut microbial communities in experiment 2.

a, Number of bacterial ASVs in the tadpole gut bacterial community, b, Faith’s phylogenetic diversity of the tadpole gut bacterial community, c, Pielou’s evenness of the tadpole gut bacterial community, and d, Principal Coordinate (PCo) analysis plot based on Bray-Curtis dissimilarity between gut bacterial community samples. Percentages represent the proportion of variation explained by each axis. The center line of each boxplot represents the median, the length of the box extends through the IQR, and whiskers extend to 1.5x IQR. All points outside this range are plotted individually. C = colonized tadpoles and D = depleted tadpoles. N = 13 colonized animals and 15 depleted animals.

Extended Data Fig. 8 The impact of microbial colonization treatment on tadpole morphometrics and heat tolerance in experiment 2.

a, tadpole body mass b, tadpole body length c, tadpole developmental stage based on the Gosner system d, tadpole critical thermal maximum (CTmax). The center line of each boxplot represents the median, the length of the box extends through the IQR, and whiskers extend to 1.5x IQR. All points outside this range are plotted individually. C = colonized tadpoles and D = depleted tadpoles. For boxplots a and b, N = 19 colonized animals and 21 depleted animals. For boxplot c, N = 19 colonized animals and 20 depleted animals. For boxplot d, N = 17 colonized animals and 18 depleted animals.

Extended Data Fig. 9 Impacts of microbial colonization treatment and assay temperature on tadpole mass-specific resting metabolic rate.

The center line of each boxplot represents the median, the length of the box extends through the IQR, and whiskers extend to 1.5x IQR. All points outside this range are plotted individually. C = colonized tadpoles and D = depleted tadpoles. On the y-axis VO2 refers to oxygen consumption. N = 10 colonized animals per temperature and 9 depleted animals per temperature.

Supplementary information

Supplementary Information

Supplementary Discussions 1–3, Tables 1–4, Methods and References.

Reporting Summary

Peer Review Information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fontaine, S.S., Mineo, P.M. & Kohl, K.D. Experimental manipulation of microbiota reduces host thermal tolerance and fitness under heat stress in a vertebrate ectotherm. Nat Ecol Evol 6, 405–417 (2022). https://doi.org/10.1038/s41559-022-01686-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41559-022-01686-2

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing