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Comparative Analysis of Gut Microbiome Community Structures in Different Populations of Asian Elephants in China and Their Correlation with Diet

BACKGROUND

The interaction and co-evolution between the gut microbiome and the host play important roles in the host's physiology, nutrition, and health. Diet is considered an important driver of differences in the gut microbiota; however, research on the relationship between the gut microbiota and diet in Asian elephants remains limited.

METHODS

In this study, we explored the gut microbiota structure and its relationship with diet in different populations of Asian elephants through metagenomic sequencing, combined with previously published dietary data.

RESULTS

This study found that the dominant gut microbiota of Asian elephants includes the phyla Bacillota (29.85% in BP, 22.79% in RC, 21.89% in SM, 31.67% in ML, and 33.00% in NGH), Bacteroidota (25.25% in BP, 31.44% in RC, 16.44% in SM, 25.73% in ML, and 23.74% in NGH), and Spirochaetota (3.49% in BP, 6.18% in RC, 1.71% in SM, 2.69% in ML, and 3.52% in NGH), with significant differences in the gut microbiota among different populations. Correlation analysis between the gut microbiota and diet revealed that dietary diversity did not directly affect the alpha diversity of the gut microbiota. However, specific food types might play a key role in shaping the gut microbiota structure by regulating the abundance of certain microbiota.

CONCLUSIONS

This study reveals significant differences in the gut microbiota structure among different populations of Asian elephants and explores the impact of diet on the structure. The results provide foundational data for a deeper understanding of the gut microbiota structure of Asian elephants and offer important references for the scientific conservation and precise management strategies of this species.

The Impact of Antibiotic Therapy on Intestinal Microbiota: Dysbiosis, Antibiotic Resistance, and Restoration Strategies

The human gut microbiota-an intricate and dynamic ecosystem-plays a pivotal role in metabolic regulation, immune modulation, and the maintenance of intestinal barrier integrity. Although antibiotic therapy is indispensable for managing bacterial infections, it profoundly disrupts gut microbial communities. Such dysbiosis is typified by diminished diversity and shifts in community structure, especially among beneficial bacterial genera (e.g., Bifidobacterium and Eubacterium), and fosters antibiotic-resistant strains and the horizontal transfer of resistance genes. These alterations compromise colonization resistance, increase intestinal permeability, and amplify susceptibility to opportunistic pathogens like Clostridioides difficile. Beyond gastrointestinal disorders, emerging evidence associates dysbiosis with systemic conditions, including chronic inflammation, metabolic syndrome, and neurodegenerative diseases, underscoring the relevance of the microbiota-gut-brain axis. The recovery of pre-existing gut communities post-antibiotic therapy is highly variable, influenced by drug spectrum, dosage, and treatment duration. Innovative interventions-such as fecal microbiota transplantation (FMT), probiotics, synbiotics, and precision microbiome therapeutics-have shown promise in counteracting dysbiosis and mitigating its adverse effects. These therapies align closely with antibiotic stewardship programs aimed at minimizing unnecessary antibiotic use to preserve microbial diversity and curtail the spread of multidrug-resistant organisms. This review emphasizes the pressing need for microbiota-centered strategies to optimize antibiotic administration, promote long-term health resilience, and alleviate the disease burden associated with antibiotic-induced dysbiosis.

EasyMetagenome: A user-friendly and flexible pipeline for shotgun metagenomic analysis in microbiome research

Shotgun metagenomics has become a pivotal technology in microbiome research, enabling in-depth analysis of microbial communities at both the high-resolution taxonomic and functional levels. This approach provides valuable insights of microbial diversity, interactions, and their roles in health and disease. However, the complexity of data processing and the need for reproducibility pose significant challenges to researchers. To address these challenges, we developed EasyMetagenome, a user-friendly pipeline that supports multiple analysis methods, including quality control and host removal, read-based, assembly-based, and binning, along with advanced genome analysis. The pipeline also features customizable settings, comprehensive data visualizations, and detailed parameter explanations, ensuring its adaptability across a wide range of data scenarios. Looking forward, we aim to refine the pipeline by addressing host contamination issues, optimizing workflows for third-generation sequencing data, and integrating emerging technologies like deep learning and network analysis, to further enhance microbiome insights and data accuracy. EasyMetageonome is freely available at https://github.com/YongxinLiu/EasyMetagenome.