Covariation of diet and gut microbiome in African megafauna

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.

Covariation of the gut microbiome with diet in Aves

“…S4). Although not all samples clustered according to food characteristics, our results support the conclusion that food source is a major factor determining differences in intestinal microbial composition [18]. The MaAsLin2 analysis further supported the conclusion that diet has a greater effect than phylogeny on the gut microbiome ( Supplementary Fig.…”

“…Groups that have diets containing plant-derived fiber (fruit, omni and foliage) had similar enzyme profiles and clustered together. Discussion community composition in the vertebrate gut [15,18]. When wild animals are used to study the influence of diet and phylogeny in the composition of the gut microbiome, other factors, such as habitat, weather, and season can bias the analysis and conclusions.…”

Multiple dimensions of dietary diversity in large mammalian herbivores

“…We did however find greater ses MPD in domesticated species than in wild ones. This could reflect characteristics selected by humans to facilitate livestock hardiness to spatiotemporal variability in food availability, and/or local husbandry practices whereby foraging routines are determined by herders to reduce competition and predation risk (Kartzinel et al, 2019a). We also observed positive TDD– ses MNTD relationships for some of the strictest browsers (kudu, camel, giraffe), but not others (dik‐dik, bushbuck).…”

“…Our field and laboratory protocols were similar to those described by Kartzinel et al (2015), and Kartzinel, Hsing, Musili, Brown, and Pringle (2019a); Appendix S1 contains a detailed account of the procedures used in sample collection, processing, sequencing, and quality control. Briefly, we extracted DNA from fresh (at most several‐hours old) faecal samples, which we preserved in the field using Zymo Soil/Fecal Mini Kits (Appendix S1).…”

“…In most cases, we either observed animals defecating or could identify species of origin based on dung size, shape, and consistency. To confirm uncertain identifications for a minority of samples, we used mammalian mitochondrial DNA markers to verify the herbivore species based on comparison to sequences available in GenBank (Kartzinel et al, 2015, 2019; Appendix S1).…”