Natural diets promote retention of the native gut microbiota in captive rodents

Article metrics

Abstract

Wild animals entering captivity experience radical lifestyle changes resulting in microbiome alterations. However, little is known about the factors that drive microbial community shifts in captivity, and what actions could mitigate microbial changes. Using white-throated woodrats (Neotoma albigula), we tested whether offering natural diets in captivity facilitates retention of native microbial communities of captive animals. Wild-caught woodrats were brought to laboratory conditions. Woodrats received either a natural diet of Opuntia cactus or an artificial diet of commercial chow over three weeks. Microbial inventories from woodrat feces at the time of capture and in captivity were generated using Illumina 16S rRNA sequencing. We found that providing woodrats with wild-natural diets significantly mitigated alterations in their microbiota, promoting a 90% retention of native microbial communities across the experiment. In contrast, the artificial diet significantly impacted microbial structure to the extent that 38% of the natural microflora was lost. Core bacteria including Bifidobacterium and Allobaculum were lost, and abundances of microbes related to oxalate degradation decreased in individuals fed artificial but not natural diets. These results highlight the importance of supplementing captive diets with natural foods to maintain native microbiomes of animals kept in artificial conditions for scientific or conservation purposes.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. 1.

    McKenzie VJ, Song SJ, Delsufc F, Prest TL, Oliverio AM, Korpita TM, et al. The effects of captivity on the mammalian gut microbiome. Integr Comp Biol. 2017;57:690–704.

  2. 2.

    Kohl KD, Skopec MM, Dearing MD. Captivity results in disparate loss of gut microbial diversity in closely related hosts. Conserv Physiol. 2014;2:cou009.

  3. 3.

    Trevelline BK, Fontaine SS, Hartup BK, Kohl KD. Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc R Soc Lond B Biol Sci. 2019;286:20182448.

  4. 4.

    Kueneman JG, Woodhams DC, Harris R, Archer HM, Knight R, McKenzie VJ. Probiotic treatment restores protection against lethal fungal infection lost during amphibian captivity. Proc R Soc Lond B Biol Sci. 2016;283:20161553.

  5. 5.

    Wienemann T, Schmitt-Wagner D, Meuser K, Segelbacher G, Schink B, Brune A, et al. The bacterial microbiota in the ceca of capercaillie (Tetrao urogallus) differs between wild and captive. Syst Appl Microbiol. 2011;34:542–51.

  6. 6.

    Clayton JB, Vangay P, Huang H, Ward T, Hillmann BM, Al-Ghalith GA, et al. Captivity humanizes the primate microbiome. Proc Natl Acad Sci USA. 2016;113:10376–81.

  7. 7.

    Metcalf JL, Song SJ, Morton JT, Weiss S, Seguin-Orlando A, Joly F, et al. Evaluating the impact of domestication and captivity on the horse gut microbiome. Sci Rep. 2017;7:15497.

  8. 8.

    Schmidt E, Mykytczuk N, Schulte-Hostedde AI. Effects of the captive and wild environment on diversity of the gut microbiome of deer mice (Peromyscus maniculatus). ISME J. 2019. https://doi.org/10.1038/s41396-019-0345-8.

  9. 9.

    Courtney Jones SK, Munn AJ, Byrne PG. Effect of captivity on morphology: negligible changes in external morphology mask significant changes in internal morphology. R Soc Open Sci. 2018;5:172470.

  10. 10.

    Martin LB, Kidd L, Liebl AL, Coon CAC. Captivity induces hyper-inflammation in the house sparrows (Passer domesticus). J Exp Biol. 2011;214:2579–85.

  11. 11.

    Karl JP, Hatch AM, Arcidiacono SM, Pearce SC, Pantoja-Feliciano IG, Doherty LA, et al. Effects of psychological, environmental and physiological stressors on the gut microbiota. Front Microbiol. 2018;9:2013.

  12. 12.

    Noguera JC, Aira M, Perez-Lozada M, Dominguez J, Velando A. Glucocorticoids modulate gastrointestinal microbiome in a wild bird. R Soc Open Sci. 2018;5:171743.

  13. 13.

    Wasimuddin, Menke S, Melzheimer J, Thalwitzer S, Heinrich S, Watcher B, et al. Gut microbes of free-ranging and captive Namibian cheetahs: diversity, putative functions and occurrence of potential pathogens. Mol Ecol. 2017;27:5515–27.

  14. 14.

    Muegge BD, Kuczynski J, Knights D, Clemente JC, González A, Fontana L, et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science. 2011;332:970–4.

  15. 15.

    Smits SA, Leach J, Sonnenburg ED, Gonzalez CG, Litchman JS, Reid G, et al. Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania. Science. 2017;357:802–6.

  16. 16.

    Carmody RN, Gerber GK, Luevano JM Jr, Gatti DM, Somes L, Svenson KL, et al. Diet dominates host genotype in shaping the murine gut microbiota. Cell Host Microbe. 2015;17:72–84.

  17. 17.

    Sonnenburg ED, Smits SA, Tikhonov M, Higginbottom SK, Wingreen NS, Sonnenburg JL. Diet-induced extinctions in the gut microbiota compound over generations. Nature. 2016;529:212–5.

  18. 18.

    Kohl KD, Miller AW, Dearing MD. Evolutionary irony: evidence that ‘defensive’ plant spines act as proximate cue to attract a mammalian herbivore. Oikos. 2015;124:835–41.

  19. 19.

    Orr TJ, Newsome SD, Wolf BO. Cacti supply limited nutrients to a desert rodent community. Oecologia. 2015;178:1045–62.

  20. 20.

    Kohl KD, Luong K, Dearing MD. Validating the use of trap-collected feces for studying the gut microbiota of a small mammal (Neotoma lepida). J Mammal. 2015;96:90–3.

  21. 21.

    Knights D, Kuczynski J, Charlson ES, Zaneveld J, Mozer MC, Collman RG, et al. Bayesian community-wide culture-independent microbial source tracking. Nat Methods. 2011;8:761–3.

  22. 22.

    Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108:4516–22.

  23. 23.

    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high throughput community sequencing data. Nat Methods. 2010;7:335–6.

  24. 24.

    Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–4.

  25. 25.

    Skaug H, Fournier D, Nielsen A, Magnusson A, Bolker B. glmmADMB: Generalized linear mixed models using ‘AD Model Builder’. Version 0.8.3.4. 2018. http://glmmadmb.r-forge.r-project.org.

  26. 26.

    R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2017. https://www.R-project.org/

  27. 27.

    Hothorn T, Bretz F, Westfall P, Heiberger RM, Schuetzenmeister A, Scheibe S. Package ‘multcomp’: simultaneous inference in general parametric models. Version 1.4–10. 2019. https://CRAN.R-project.org/package=multcomp.

  28. 28.

    Lozupone C, Lladser ME, Knights D, Stormbaugh J, Knight R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 2011;5:169–72.

  29. 29.

    Oksanen J, Blanchet FG. Friendly M, Kindt R, Legendre P, McGlinn D, et al. Package “vegan”: Community ecology package. Version 2.5–4. 2019. https://CRAN.R-project.org/package=vegan.

  30. 30.

    Bittinger K. Package ‘qiimer’: Work with QIIME output files in R. Version 0.9.4. 2016. https://CRAN.R-project.org/package=qiimer.

  31. 31.

    Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol. 2013;31:814–21.

  32. 32.

    Lindgreen S, Adair KL, Gardner PP. An evaluation of the accuracy and speed of metagenome analysis tools. Sci Rep. 2016;6:19233.

  33. 33.

    Kohl KD, Oakeson KF, Orr TJ, Miller AW, Forbey JS, Phillips CD, et al. Metagenomic sequencing provides insights into microbial detoxification in the guts of small mammalian herbivores (Neotoma spp.). FEMS Microbiol Ecol. 2018;94:fiy184.

  34. 34.

    Allan N, Pesapane R, Foley J, Clifford D. Successful care and propagation of the endangered amargosa vole (Microtus californicus scirpensis) in captivity. Zoo Biol. 2018;37:59–63.

  35. 35.

    Luo Y, Zhang L, Li H, Smidt H, Wright ADG, Zhang K, et al. Different types of dietary fibers trigger specific alterations in composition and predicted functions of colonic bacterial communities in BALB/c mice. Front Microbiol. 2017;8:966.

  36. 36.

    Sheflin AM, Melby CL, Carbonero F, Weir TL. Linking dietary patterns with gut microbial composition and function. Gut Microbes. 2017;8:113–29.

  37. 37.

    Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes. 2012;3:289–306.

  38. 38.

    Biddle A, Stewart L, Blanchard J, Leschine. Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in diverse gut communities. Diversity. 2013;5:627–40.

  39. 39.

    Coyte KZ, Schluter J, Foster KR. The ecology of the microbiome: networks, competition, and stability. Science. 2015;350:663–6.

  40. 40.

    Allison SD, Martiny JBH. Resistance, resilience, and redundancy in microbial communities. Proc Natl Acad Sci USA. 2008;105:11512–9.

  41. 41.

    Faith JJ, Guruge JL, Charbonneau M, Subramanian S, Seedorf H, Goodman AL, et al. The long-term stability of the human gut microbiota. Science. 2013;341:1237439.

  42. 42.

    Shade A, Peter H, Allison SD, Baho DL, Berga M, Bürgmann H, et al. Fundamentals of microbial community resistance and resilience. Front Microbiol. 2012;3:417.

  43. 43.

    Macêdo RH, Mares MA. Neotoma albigula. Mamm Species. 1988;310:1–7.

  44. 44.

    Ormerod KL, Wood DLA, Lachner N, Gellatly SL, Daly JN, Parsons JD, et al. Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. Microbiome. 2016;4:36.

  45. 45.

    Monje PV, Baran EJ. Characterization of calcium oxalates generated as biominerals in cacti. Plant Physiol. 2002;128:707–13.

  46. 46.

    Miller AW, Oakeson KF, Dale C, Dearing MD. Effect of dietary oxalate on the gut microbiota of the mammalian herbivore Neotoma albigula. Appl Environ Microbiol. 2016;82:2669–75.

  47. 47.

    Miller AW, Dale C, Dearing MD. Microbiota diversification and crash induced by dietary oxalate in the mammalian herbivore Neotoma albigula. mSphere. 2017;2:e00428–17.

  48. 48.

    Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457:480–4.

  49. 49.

    Shade A, Handelsman J. Beyond the Venn diagram: the hunt for a core microbiome. Environ Microbiol. 2012;14:4–12.

  50. 50.

    Everard A, Lazarevic V, Gaïa N, Johansson M, Ståhlman M, Backhed F, et al. Microbiome of prebiotic-treated mice reveals novel targets involved in host response during obesity. ISME J. 2014;8:2116–30.

  51. 51.

    Walter J. Ecological role of Lactobacilli in the gastrointestinal tract: implications for fundamental and biomedical research. Appl Environ Microbiol. 2008;74:4985–96.

  52. 52.

    O’Callaghan A, van Sinderen D. Bifidobacteria and their roles as members of the human gut microbiota. Front Microbiol. 2016;7:925.

  53. 53.

    DeGruttola AK, Low D, Mizoguchi A, Mizoguchi E. Current understanding of dysbiosis in human and animal models. Inflamm Bowel Dis. 2016;22:1137–50.

  54. 54.

    Greene LK, McKenney EA, O’Connell TM, Drea CM. The critical role of dietary foliage in maintaining the gut microbiome and metabolome of folivorous sifakas. Sci Rep. 2018;8:14482.

  55. 55.

    Kohl KD, Dearing MD. Wild-caught rodents retain a majority of their natural gut microbiota upon entrance into captivity. Environ Microbiol Rep. 2014;6:191–5.

Download references

Acknowledgements

We thank Michele Skopec, Kika Kitanovic, Tess Stapleton, KayLene Yamada, Sara Weinstein, and Shin Enomoto for their help and comments during the project development. This project was funded by NSF DEB-1342615 to MDD. We also thank the Bonderman Field Station at Rio Mesa, UT for housing during the field work. RMM thanks CONACYT-Mexico for a postdoctoral fellowship.

Author information

Correspondence to M. Denise Dearing.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

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

Supplementary information

Figure S1. Nitrogen and carbon isotopic signatures of diets and hair of 12 white-throated woodrats (Neotoma albigula)

Figure S2. Mean ± SE measurements of microbial alpha diversity from feces of woodrats fed natural (dark grey) and artificial (light grey) diets

Figure S3. Predicted functions of microbial metagenomes assigned to the KEGG Level 2 Metabolism category from woodrats fed wild, natural, and artificial diets

Table S1. Cleaned up OTU table

Table S2. Results of the GLMM likelihood ratio test comparing a full against a null model for each alpha-diversity metric

Table S3. SIMPER analysis showing the contribution of microbial families to the dissimilarity between wild samples and samples from individuals fed the artificial diet at 3-days in captivity

Table S4. SIMPER analysis showing the contribution of microbial families to the dissimilarity between wild samples and samples from individuals fed the artificial diet at 21-days in captivity

Table S5. Relative abundances (%) of microbial families from feces of woodrats fed the natural diet and from the surface of cactus pads

Table S6. Relative abundances (%) of microbial families from feces of woodrats fed the artificial diet and from rabbit chow pellets

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark