Covariation of diet and gut microbiome in African megafauna

Edited by John Terborgh, University of Florida, Cedar Key, FL, and approved October 10, 2019 (received for review April 2, 2019)
November 4, 2019
116 (47) 23588-23593

Significance

Diet and gut microbiome composition are important for health and nutrition in mammals, but how they covary in response to environmental change remains poorly understood—both because diet composition is rarely quantified precisely, and because studies of diet−microbiome linkages in captive animals may not accurately reflect the dynamics of natural communities. By analyzing diet−microbiome linkages in an assemblage of large mammalian herbivores in Kenya, we found that seasonal changes in diet and microbiome composition were strongly correlated within some populations, whereas other populations exhibited little temporal turnover in either diet or microbiome. Identifying mechanisms that generate species-specific variation in the sensitivity of the diet−microbiome nexus to environmental changes could help to explain differential population performance and food-web structure within ecological communities.

Abstract

A major challenge in biology is to understand how phylogeny, diet, and environment shape the mammalian gut microbiome. Yet most studies of nonhuman microbiomes have relied on relatively coarse dietary categorizations and have focused either on individual wild populations or on captive animals that are sheltered from environmental pressures, which may obscure the effects of dietary and environmental variation on microbiome composition in diverse natural communities. We analyzed plant and bacterial DNA in fecal samples from an assemblage of 33 sympatric large-herbivore species (27 native, 6 domesticated) in a semiarid East African savanna, which enabled high-resolution assessment of seasonal variation in both diet and microbiome composition. Phylogenetic relatedness strongly predicted microbiome composition (r = 0.91) and was weakly but significantly correlated with diet composition (r = 0.20). Dietary diversity did not significantly predict microbiome diversity across species or within any species except kudu; however, diet composition was significantly correlated with microbiome composition both across and within most species. We found a spectrum of seasonal sensitivity at the diet−microbiome nexus: Seasonal changes in diet composition explained 25% of seasonal variation in microbiome composition across species. Species’ positions on (and deviations from) this spectrum were not obviously driven by phylogeny, body size, digestive strategy, or diet composition; however, domesticated species tended to exhibit greater diet−microbiome turnover than wildlife. Our results reveal marked differences in the influence of environment on the degree of diet−microbiome covariation in free-ranging African megafauna, and this variation is not well explained by canonical predictors of nutritional ecology.

Continue Reading

Data Availability

Data deposition: Illumina data and unrarefied sequence count tables are available at Dryad (https://doi.org/10.5061/dryad.c119gm5); mitochondrial DNA sequences are available at GenBank (accession nos. MN262920–MN262991 and MN262700–MN262919).

Acknowledgments

We thank the Government of Kenya, National Museums of Kenya, Mpala Research Centre, and Ol Jogi Conservancy for permission to conduct this research; Sam Kurukura and Ali Hassan for field assistance; Patricia Chen and Tina Hansen for sample preparation; Lawrence David and 2 anonymous reviewers for comments; and funders including The Institute at Brown for Environment and Society, The Nature Conservancy’s NatureNet Fellowship, The Princeton Environmental Institute, The Fund for New Ideas in the Natural Sciences from the Office of the Dean of Research at Princeton University, The Cameron Schrier Foundation, and NSF Grants DEB-1355122, DEB-1457697, and IOS-1656527 and Graduate Research Fellowship Program.

Supporting Information

Appendix (PDF)
Dataset_S01 (XLSX)
Dataset_S02 (XLSX)
Dataset_S03 (XLSX)
Dataset_S04 (XLSX)

References

1
K. L. Arnolds, C. A. Lozupone, Striking a balance with help from our little friends—How the gut microbiota contributes to immune homeostasis. Yale J. Biol. Med. 89, 389–395 (2016).
2
C. Duvallet, S. M. Gibbons, T. Gurry, R. A. Irizarry, E. J. Alm, Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Nat. Commun. 8, 1784 (2017).
3
M. D. Dearing, K. D. Kohl, Beyond fermentation: Other important services provided to endothermic herbivores by their gut microbiota. Integr. Comp. Biol. 57, 723–731 (2017).
4
E. A. McKenney, K. Koelle, R. R. Dunn, A. D. Yoder, The ecosystem services of animal microbiomes. Mol. Ecol. 27, 2164–2172 (2018).
5
R. E. Ley et al., Evolution of mammals and their gut microbes. Science 320, 1647–1651 (2008).
6
A. W. Brooks, K. D. Kohl, R. M. Brucker, E. J. van Opstal, S. R. Bordenstein, Phylosymbiosis: Relationships and functional effects of microbial communities across host evolutionary history. PLoS Biol. 14, e2000225 (2016).
7
K. D. Kohl, M. D. Dearing, The woodrat gut microbiota as an experimental system for understanding microbial metabolism of dietary toxins. Front. Microbiol. 7, 1165 (2016).
8
L. A. David et al., Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).
9
V. J. McKenzie et al., The effects of captivity on the mammalian gut microbiome. Integr. Comp. Biol., 57, 690–704 (2017).
10
B. D. Muegge et al., Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332, 970–974 (2011).
11
A. T. Reese, R. R. Dunn, Drivers of microbiome diversity: A review of general rules, feces, and ignorance. MBio 9, e01294-18 (2018).
12
M. Groussin et al., Unraveling the processes shaping mammalian gut microbiomes over evolutionary time. Nat. Commun. 8, 14319 (2017).
13
K. R. Amato et al., Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes. ISME J. 13, 576–587 (2019).
14
A. Gomez et al., Temporal variation selects for diet-microbe co-metabolic traits in the gut of Gorilla spp. ISME J. 10, 514–526 (2016).
15
J. Tung et al., Social networks predict gut microbiome composition in wild baboons. eLife 4, e05224 (2015).
16
R. M. Pringle et al., Predator-induced collapse of niche structure and species coexistence. Nature 570, 58–64 (2019).
17
N. G. Hairston, F. E. Smith, L. B. Slobodkin, Community structure, population control, and competition. Am. Nat. 94, 421–425 (1960).
18
R. T. Paine, Food web complexity and species diversity. Am. Nat. 100, 65–75 (1966).
19
J. L. Metcalf et al., Evaluating the impact of domestication and captivity on the horse gut microbiome. Sci. Rep. 7, 15497 (2017).
20
G. T. Bergmann, J. M. Craine, M. S. I. Robeson 2nd, N. Fierer, Seasonal shifts in diet and gut microbiota of the American Bison (Bison bison). PLoS One 10, e0142409 (2015).
21
D. Codron, J. S. Brink, L. Rossouw, M. Clauss, The evolution of ecological specialization in southern African ungulates: Competition- or physical environmental turnover. Oikos 117, 344–353 (2008).
22
J. S. Brashares, T. Garland, P. Arcese, Phylogenetic analysis of coadaptation in behavior, diet, and body size in the African antelope. Behav. Ecol. 11, 452–463 (2000).
23
D. I. Bolnick et al., The ecology of individuals: Incidence and implications of individual specialization. Am. Nat. 161, 1–28 (2003).
24
P. Taberlet et al., Power and limitations of the chloroplast trnL (UAA) intron for plant DNA barcoding. Nucleic Acids Res. 35, e14 (2007).
25
J. G. Caporaso et al., QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).
26
T. Z. DeSantis et al., Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).
27
B. A. Gill et al., Plant DNA-barcode library and community phylogeny for a semi-arid East African savanna. Mol. Ecol. Resour. 19, 838–846 (2019).
28
P. J. Jarman, The social organization of antelope in relation to their ecology. Behaviour 48, 215–266 (1974).
29
B. T. Moyers, P. L. Morrell, J. K. McKay, Genetic costs of domestication and improvement. J. Hered. 109, 103–116 (2018).
30
A. H. Moeller, T. A. Suzuki, M. Phifer-Rixey, M. W. Nachman, Transmission modes of the mammalian gut microbiota. Science 362, 453–457 (2018).
31
J. R. Goheen et al., Conservation lessons from large-mammal manipulations in East African savannas: The KLEE, UHURU, and GLADE experiments. Ann. N. Y. Acad. Sci. 1429, 31–49 (2018).
32
G. E. Belovsky, Optimal foraging and community structure: The allometry of herbivore food selection and competition. Evol. Ecol. 11, 641–672 (1997).
33
E. O. Price, Behavioral aspects of animal domestication. Q. Rev. Biol. 59, 1–32 (1984).
34
M. Gustafsson, P. Jensen, F. H. de Jonge, T. Schuurman, Domestication effects on foraging strategies in pigs (Sus scrofa). Appl. Anim. Behav. Sci. 62, 305–317 (1999).
35
J. G. Kie, Optimal foraging and risk of predation: Effects on behavior and social structure in ungulates. J. Mammal. 80, 1114–1129 (1999).
36
A. D. Letten, P.-J. Ke, T. Fukami, Linking modern coexistence theory and contemporary niche theory. Ecol. Monogr. 87, 161–177 (2016).
37
K. S. McCann, The diversity-stability debate. Nature 405, 228–233 (2000).
38
T. R. Kartzinel et al., DNA metabarcoding illuminates dietary niche partitioning by African large herbivores. Proc. Natl. Acad. Sci. U.S.A. 112, 8019–8024 (2015).
39
B. E. Deagle et al., Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? Mol. Ecol. 28, 391–406 (2019).
40
E. Willerslev et al., Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506, 47–51 (2014).
41
J. M. Craine, E. G. Towne, M. Miller, N. Fierer, Climatic warming and the future of bison as grazers. Sci. Rep. 5, 16738 (2015).
42
S. A. Fritz, O. R. P. Bininda-Emonds, A. Purvis, Geographical variation in predictors of mammalian extinction risk: Big is bad, but only in the tropics. Ecol. Lett. 12, 538–549 (2009).

Information & Authors

Information

Published in

The cover image for PNAS Vol.116; No.47
Proceedings of the National Academy of Sciences
Vol. 116 | No. 47
November 19, 2019
PubMed: 31685619

Classifications

Data Availability

Data deposition: Illumina data and unrarefied sequence count tables are available at Dryad (https://doi.org/10.5061/dryad.c119gm5); mitochondrial DNA sequences are available at GenBank (accession nos. MN262920–MN262991 and MN262700–MN262919).

Submission history

Published online: November 4, 2019
Published in issue: November 19, 2019

Keywords

  1. 16S rRNA
  2. DNA metabarcoding
  3. megaherbivores
  4. phylosymbiosis

Acknowledgments

We thank the Government of Kenya, National Museums of Kenya, Mpala Research Centre, and Ol Jogi Conservancy for permission to conduct this research; Sam Kurukura and Ali Hassan for field assistance; Patricia Chen and Tina Hansen for sample preparation; Lawrence David and 2 anonymous reviewers for comments; and funders including The Institute at Brown for Environment and Society, The Nature Conservancy’s NatureNet Fellowship, The Princeton Environmental Institute, The Fund for New Ideas in the Natural Sciences from the Office of the Dean of Research at Princeton University, The Cameron Schrier Foundation, and NSF Grants DEB-1355122, DEB-1457697, and IOS-1656527 and Graduate Research Fellowship Program.

Notes

This article is a PNAS Direct Submission.

Authors

Affiliations

Department of Ecology & Evolutionary Biology, Brown University, Providence, RI 02912;
Julianna C. Hsing
Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544;
Paul M. Musili
Botany Department, National Museums of Kenya, Nairobi, Kenya 00100
Bianca R. P. Brown
Department of Ecology & Evolutionary Biology, Brown University, Providence, RI 02912;
Robert M. Pringle
Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544;

Notes

1
To whom correspondence may be addressed. Email: [email protected].
Author contributions: T.R.K. and R.M.P. designed research; T.R.K., J.C.H., P.M.M., B.R.P.B., and R.M.P. performed research; T.R.K. and R.M.P. contributed new reagents/analytic tools; T.R.K. and B.R.P.B. analyzed data; and T.R.K. and R.M.P. wrote the paper.

Competing Interests

The authors declare no competing interest.

Metrics & Citations

Metrics

Note: The article usage is presented with a three- to four-day delay and will update daily once available. Due to ths delay, usage data will not appear immediately following publication. Citation information is sourced from Crossref Cited-by service.


Altmetrics

Citations

Export the article citation data by selecting a format from the list below and clicking Export.

Cited by

    Loading...

    View Options

    View options

    PDF format

    Download this article as a PDF file

    DOWNLOAD PDF

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Personal login Institutional Login

    Recommend to a librarian

    Recommend PNAS to a Librarian

    Purchase options

    Purchase this article to access the full text.

    Single Article Purchase

    Covariation of diet and gut microbiome in African megafauna
    Proceedings of the National Academy of Sciences
    • Vol. 116
    • No. 47
    • pp. 23365-23862

    Figures

    Tables

    Media

    Share

    Share

    Share article link

    Share on social media