Seasonal shift in gut microbiome diversity in wild Sichuan takin (Budorcas tibetanus) and environmental adaptation

Analysis of fungal diversity in the gut feces of wild takin (Budorcas taxicolor)

Introduction

The composition of the intestinal microbiome correlates significantly with an animal's health status. Hence, this indicator is highly important and sensitive for protecting endangered animals. However, data regarding the fungal diversity of the wild Budorcas taxicolor (takin) gut remain scarce. Therefore, this study analyzes the fungal diversity, community structure, and pathogen composition in the feces of wild B. taxicolor.

Methods

To ensure comprehensive data analyses, we collected 82 fecal samples from five geographical sites. Amplicon sequencing of the internal transcribed spacer (ITS) rRNA was used to assess fecal core microbiota and potential pathogens to determine whether the microflora composition is related to geographical location or diet. We further validated the ITS rRNA sequencing results via amplicon metagenomic sequencing and culturing of fecal fungi.

Results and discussion

The fungal diversity in the feces of wild Budorcas taxicolor primarily comprised three phyla (99.69%): Ascomycota (82.19%), Fungi_unclassified (10.37%), and Basidiomycota (7.13%). At the genus level, the predominant fungi included Thelebolus (30.93%), Functional_unclassified (15.35%), and Ascomycota_unclassified (10.37%). Within these genera, certain strains exhibit pathogenic properties, such as Thelebolus, Cryptococcus, Trichosporon, Candida, Zopfiella, and Podospora. Collectively, this study offers valuable information for evaluating the health status of B. taxicolor and formulating protective strategies.

Analysis of the microbial diversity in takin (Budorcas taxicolor) feces

Introduction

The intestinal tract of animals is a complex and dynamic microecosystem that is inextricably linked to the health of the host organism. Takin (Budorcas taxicolor) is a threatened species, and its gut microbiome is poorly understood. Therefore, this study aimed to analyze the microbial community structure and potential pathogens of takin.

Methods

Takin fecal samples were collected from five sites in a nature reserve to ensure the uniformity of sample collection, determine the effects of different geographical locations on gut microbes, and analyze the differences in microbial communities between sites. Subsequently, high-throughput 16S rDNA gene sequencing was performed to analyze the microbial diversity and potential pathogens in the gut; the findings were verified by isolating and culturing bacteria and metagenomic sequencing.

Results and discussion

The takin gut microflora consisted mainly of four phyla: Firmicutes (69.72%), Bacteroidota (13.55%), Proteobacteria (9.02%), and Verrucomicrobiota (3.77%), representing 96.07% of all microorganisms. The main genera were UCG-005 (20.25%), UCG-010_unclassified (12.35%), Firmicus_unclassified (4.03%), and Rumino coccsea_unclassified (3.49%), while the main species were assigned to Bacteria_unclassified. Potential pathogens were also detected, which could be used as a reference for the protection of takin. Pseudomonas presented the highest abundance at Shuichiping and may represent the main pathogen responsible for the death of takin at the site. This study provides an important reference for investigating the composition of the bacterial community in the intestine of takin.

CDEMI: characterizing differences in microbial composition and function in microbiome data

Microbial communities influence host phenotypes through microbiota-derived metabolites and interactions between exogenous active substances (EASs) and the microbiota. Owing to the high dynamics of microbial community composition and difficulty in microbial functional analysis, the identification of mechanistic links between individual microbes and host phenotypes is complex. Thus, it is important to characterize variations in microbial composition across various conditions (for example, topographical locations, times, physiological and pathological conditions, and populations of different ethnicities) in microbiome studies. However, no web server is currently available to facilitate such characterization. Moreover, accurately annotating the functions of microbes and investigating the possible factors that shape microbial function are critical for discovering links between microbes and host phenotypes. Herein, an online tool, CDEMI, is introduced to discover microbial composition variations across different conditions, and five types of microbe libraries are provided to comprehensively characterize the functionality of microbes from different perspectives. These collective microbe libraries include (1) microbial functional pathways, (2) disease associations with microbes, (3) EASs associations with microbes, (4) bioactive microbial metabolites, and (5) human body habitats. In summary, CDEMI is unique in that it can reveal microbial patterns in distributions/compositions across different conditions and facilitate biological interpretations based on diverse microbe libraries. CDEMI is accessible at http://rdblab.cn/cdemi/.