Effects of population density stress on fecal microbiota and metabolites of Qinghai-Tibet Plateau root voles (Microtus oeconomus)—A field experiment

Overview

This study examined the effects of population density stress on fecal microbiota composition and metabolic profiles in root voles (Microtus oeconomus) using a field enclosure experimental design. Population density stress was confirmed through elevated fecal corticosterone metabolite levels in high-density voles. The research employed 16S rRNA gene sequencing for microbial community analysis and untargeted metabolomics to characterize metabolic alterations associated with density-dependent stress.

Methods and approach

Root voles were maintained in field enclosures under controlled high-density and control density conditions. Fecal samples were collected and analyzed using 16S rRNA sequencing to characterize bacterial communities at the phylum and genus levels. Functional prediction was conducted to identify pathway-level alterations. Untargeted metabolomics was performed to detect differential metabolites across positive and negative ion modes. Fecal corticosterone metabolite concentrations were quantified to confirm physiological stress responses. KEGG pathway analysis was applied to identify metabolic pathways affected by density stress. Correlation analysis examined relationships between specific bacterial taxa and metabolite classes.

Key Findings

High-density conditions induced a significant stress response characterized by elevated fecal corticosterone metabolite levels. Bacterial community composition showed marked alterations, with high-density voles displaying increased abundances of Bacteroidota, CAG-485, Duncaniella, and Paramuribaculum, while Firmicutes_A, Firmicutes_D, Desulfobacterota_I, Lactobacillus, Desulfovibrio_R, and Butyribacter were reduced. Functional prediction revealed upregulation of antibiotic biosynthesis, D-alanine metabolism, and pentose phosphate pathway genes, with concurrent downregulation of amino acid biosynthesis pathways. Metabolomics analysis identified 938 differential metabolites in positive ion mode and 920 in negative ion mode. Elevated metabolites in high-density voles included cholic acid, lithocholic acid, and succinic acid, while L-lysine, L-valine, and dehydroepiandrosterone were reduced. KEGG pathway analysis identified 142 affected metabolic pathways, predominantly involving amino acid metabolism, the tricarboxylic acid cycle, bile secretion, and protein digestion. Correlation analysis demonstrated negative associations between Lactobacillus abundance and elevated bile acids, and positive associations with downregulated amino acid-related metabolites.

Implications

Population density stress induces substantial restructuring of the fecal microbiota in root voles, with shifts toward a bacterial community composition characterized by reduced saccharolytic bacteria (Firmicutes) and increased proteolytic and stress-responsive genera. The coordinated alteration of microbial functional capacity and host metabolic profiles suggests density-dependent stress engages both microbial and host metabolic systems. The upregulation of antibiotic biosynthesis pathways and pentose phosphate metabolism may represent microbial stress responses or adaptive metabolic shifts under conditions of increased intraspecific competition and social stress within high-density populations. The suppression of Lactobacillus, a taxon often associated with metabolic stability and amino acid production, alongside reductions in essential amino acids such as lysine and valine, indicates potential constraints on protein metabolism and biosynthesis under density stress conditions. These metabolic alterations may have broader consequences for host immune function, neuroendocrine signaling, and fitness-related physiological processes. The observed changes in bile acid metabolism and secondary bile acid production warrant further investigation given their roles in microbial community structuring and energy metabolism.

Scope and limitations

This summary is based on the study abstract and available metadata. It does not include a full analysis of the complete paper, supplementary materials, or underlying datasets unless explicitly stated. Findings should be interpreted in the context of the original publication.