Insights into the Gut Microbial Diversity of Wild Siberian Musk Deer (Moschus moschiferus) in Republic of Korea

Abstract

The gut microbiota plays a crucial role in the health and well-being of wildlife. However, its composition and diversity remain unexplored, particularly in threatened species such as the Siberian musk deer (SMD). This study aimed to elucidate the gut microbiota composition within different wild SMD communities for assessing their health status. We conducted the first comprehensive fecal microbiome analysis of wild SMD inhabiting three distinct locations in Gangwon Province, Republic of Korea (Korea). Fecal samples were collected non-invasively and 16S rRNA gene sequencing was performed for gut microbiota characterization. Consistent with previous research, Firmicutes and Bacteroidetes were the dominant phyla in the gut microbiota of wild SMD. Planctomycetota was a prevalent phylum in wild SMD gut microbiota, warranting further investigation of its ecological significance. While significant differences were observed in the gut microbiota richness among the three groups, no significant disparities were detected in the beta diversity. Additionally, certain genera exhibited distinct relative abundances among the groups, suggesting potential associations with geographic factors, gut disorders, and dietary habits. Our findings provide valuable insights into the gut microbiome of wild SMD and offer a foundation for future microbiome-based conservation efforts for this vulnerable species.

Keywords: 16S rRNA; Moschus moschiferus; Siberian musk deer; fecal microbiome; non-invasive; wildlife conservation.

Figure 1

Sampling sites and captured images of wild Siberian musk deer (SMD). (A) The three distinct locations in Gangwon province for collecting wild SMD fecal samples. (B) Camera trapping confirmed the defecation of each individual wild SMD.

Figure 2

Rarefaction curves of observed species for the 20 SMD samples, with each curve color-coded according to the sampling locations. The X-axis represents the number of valid sequences per sample and the Y-axis denotes the observed species (operational taxonomic units, OTUs). As the sequencing depth increases, the observed species also increases and stabilizes with the expansion of extracted sequences, signifying an optimal point where the quantity of sequencing data is sufficient.

Figure 3

OTU Venn diagrams and bacterial taxa (phylum-level) pie charts.

Figure 4

Bacterial compositions of SMD among three groups at the phylum (A) and genus (B) levels. The bar charts depict the average relative abundance of all phyla and the most prevalent genera identified in Groups A, B, and C.

Figure 5

Bar diagrams depicting α-diversity indices of the gut microbiota among Groups A, B, and C. (A) The ACE and Chao1 indices were used to assess the number of OTUs within each community. (B) The Shannon and Simpson indices were used to estimate microbial diversity within each group. * represents p < 0.05.

Figure 6

Principal coordinate analysis (PCoA) plot of β-diversity based on Bray–Curtis index. Statistical significance was determined using PERMANOVA. Samples from the same group are depicted in the same color, with the horizontal and vertical axes representing relative distances.

Figure 7

Bar diagrams displaying the relative abundances (mean % ± standard deviation) of (A) five major bacterial phyla and (B) nine major bacterial genera among Groups A, B, and C. * p < 0.05.

Figure 8

Cluster heatmap analysis based on the bacterial composition of the top 20 genera. Horizontal clustering represents the similarity of genera richness in the samples from Group A, B, and C. The color gradient from red to blue indicates relative abundance from high to low.

Figure 9

Linear discriminant analysis (LDA) histogram identifying significantly different taxa among Groups A, B, and C. The length of the bar column represents the LDA score (LDA > 2).

Figure 10

Histogram illustrating the differential abundance of taxa at the genus level among the three groups (A, B, and C).