The effects of food provisioning on the gut microbiota community and antibiotic resistance genes of Yunnan snub-nosed monkey

Abstract

Yunnan snub-nosed monkeys (Rhinopithecus bieti) are the highest elevation lived non-human primate, and their survival has been threatened for decades. To promote their population growth, a reserve provides a typical monkey population with supplemental food. However, the influences of this food provisioning on their gut microbiota and antibiotic resistance genes (ARGs) were unknown. Therefore, we investigated the gut microbiota and ARGs of the food-provisioned monkey population compared with another wild foraging population. We found that food provisioning significantly increased the gut microbiota diversity and changed the community composition, particularly increased both the Firmicutes abundance and Firmicutes/Bacteroidetes ratio. Meanwhile, the food provisioning decreased the complex and stable gut microbiota network. KEGG functions were also influenced by food provisioning, with wild foraging monkeys showing higher functions of metabolism and genetic information processing, especially the carbohydrate metabolism, while food-provisioned monkeys exhibited increased environmental information processing, cellular processes, and organismal systems, including valine, leucine, and isoleucine degradation. In addition, food provisioning increased the abundance of ARGs in the gut microbiota, with most increasing the abundance of bacA gene and changing the correlations between specific ARGs and bacterial phyla in each population. Our study highlights that even food provisioning could promote wildlife nutrient intake, and it is necessary to pay attention to the increased ARGs and potential effects on gut microbiota stability and functions for this human conservation measure.

Keywords: Yunnan snub-nosed monkey; antibiotic resistance genes; food provisioning; gut microbiota; microbial network.

Figure 1

(A) Relative abundance of bacterial phyla in wild foraging (WF) and food-provisioned (FP) fecal samples. (B) The biomarker taxa listed in descending order of importance to the model accuracy, the up arrow means abundance increasing in FP fecal samples, vice versa. (C) Manhattan plots showing enriched or depleted ASVs in WF or FP fecal samples. Threshold = −log_e (p − value) > 3. (D) PCoA of gut microbial communities and ellipses with different colors indicate 95% confidence intervals for each treatment. Boxplot above the PCoA ordination is the comparison of beta diversity of gut microbial communities based on Bray–curtis distance. ***p < 0.001; **p < 0.001; and *p < 0.05.

Figure 2

Importance of individual variables of gut enzyme activities and nutrients across models for all predominant ASV taxa. Asterisk means the significant t-test of the importance between WF and FP. ***p < 0.001; **p < 0.001; and *p < 0.05.

Figure 3

(A) Correlation network of gut microbes in WF and FP populations. The node size indicates the relative abundance of the ASV. (B) Robustness analysis for gut microbial communities between WF and FP populations by removing the same proportion of nodes.

Figure 4

Plots of KEGG pathways comparisons between the WF (green) and FP (orange) populations at levels (A) 1, (B) 2, and (C) 3 analyzed by LEfSe analysis. LDA > 3.0, p < 0.05.

Figure 5

(A) Relative abundance of classification of antibiotic resistance genes (ARGs) according to antibiotic resistance type. (B) Relative abundance of predominant ARGs comparing to the total abundance of FP population. (C) Volcano plot revealed the abundance of differentially ARGs between FP and WF populations.

Figure 6

Correlation networks between antibiotic resistance genes (ARGs) and gut bacterial phyla.