| Literature DB >> 33936022 |
Binghua Sun1,2, Yingna Xia1,2, Paul A Garber3,4, Katherine R Amato5, Andres Gomez6, Xiaojuan Xu1,7, Wenbo Li1,2, Mingjing Huang1,2, Dongpo Xia2,8, Xi Wang1,2, Jinhua Li1,2,7.
Abstract
Although recent studies have revealed that gut fungi may play an important functional role in animal biology and health, little is known concerning the effects of anthropogenic pressures on the gut mycobiome. Here, we examined differences of the gut mycobiome in wild and captive populations of Tibetan macaques (Macaca thibetana) targeting the fungal internal transcribed spacer (ITS) and using next generation sequencing. Our findings demonstrate that the diversity, composition, and functional guild of the Tibetan macaque gut mycobiome differ across populations living in different habitats. We found that Tibetan macaques translocated from the wild into a captive setting for a period of 1 year, were characterized by a reduction in fungal diversity and an increase in the abundance of potential gut fungal pathogens compared to wild individuals. Furthermore, we found that the relative abundance of two main fungal guilds of plant pathogens and ectomycorrhizal fungi was significantly lower in captive individuals compared to those living in the wild. Our results highlight that, in addition to bacteria, gut fungi vary significantly among individuals living in captive and wild settings. However, given limited data on the functional role that fungi play in the host's gut, as well as the degree to which a host's mycobiome is seeded from fungi in the soil or ingested during the consumption of plant and animal foods, controlled studies are needed to better understand the role of the local environment in seeding the mycobiome.Entities:
Keywords: captivity; diversity; gut mycobiome; tibetan macaque; wild
Year: 2021 PMID: 33936022 PMCID: PMC8085381 DOI: 10.3389/fmicb.2021.665853
Source DB: PubMed Journal: Front Microbiol ISSN: 1664-302X Impact factor: 5.640
Figure 1The distributions of phylum, families, and genera. (A) Relative abundance of fecal fungal taxa at the phylum level. Stacked bar graphs illustrate the abundances of phyla, and the x-axis represents the sample groups. (B) The distributions of core families and genera (average relative abundance >0.01, present in more than 90% of all fecal samples).
Figure 2Differences in fecal fungal diversity across three study groups. (A) Comparison of amplicon sequence variant (ASV) richness. (B) Comparison of Shannon diversity index. A Kruskal-Wallis ANOVA test was used to evaluate the variation across treatment groups. Post hoc tests (Dunn’s test) for pairwise comparison tests (values of p were adjusted by Bonferroni). (C,D) Differentiation of fecal mycobiota structure (C) based on unweighted UniFrac distance and (D) based on weighted UniFrac distance. Principal coordinates analysis (PCoA) was used to show patterns across three study groups. Adonis tests were performed on unweighted and weighted UniFrac, respectively. Significance was set at the 0.05 level.
Figure 3Variation of fecal fungal taxonomy across three study groups. (A) Comparison of the dominant phyla Ascomycota. (B) Comparison of the dominant phyla Basidiomycota. A Kruskal-Wallis ANOVA test was used to evaluate the variation across treatment groups. Post hoc tests (Dunn’s test) for pairwise comparison tests (values of p were adjusted by Bonferroni). (C) Indicators of known fungal taxa in one of the three groups (at the genus, family, order, class, and phylum levels, the mean relative abundance of known taxa accounting for ≥1% of all the fecal sample), identified by linear discriminant analysis effect size (LEfSe) analysis (LDA > 3, p < 0.05).
Figure 4Variation of fecal fungal functional trophic modes across three study groups. (A) Relative abundance of functional trophic modes. Stacked bar graphs illustrate the abundances, x-axis represents the sample types. (B–D) Comparison of the functional guilds of animal pathogens, plant pathogens, and ectomycorrhizal fungi, respectively. A Kruskal-Wallis ANOVA test was used to evaluate the variation across treatment groups. Post hoc tests (Dunn’s test) for pairwise comparison tests (values of p were adjusted by Bonferroni). Significance was set at the 0.05 level.