Dietary Protein Sources Shape Gut Microbiome: Insights from Meta-analysis and Machine Learning

BackgroundDietary proteins shape gut microbial ecology, yet the taxonomic and functional consequences of plant- versus animal-based proteins remain poorly defined. Although digestibility and fermentation profiles differ by protein type, a systematic evaluation of how these differences influence microbial diversity, community structure, and metabolic capacity is lacking. This meta-analysis integrates taxonomic, machine learning, and functional inference approaches to identify microbial and metabolic signatures associated with dietary protein source in murine models. MethodsFollowing PRISMA guidelines, we analyzed 16S rRNA sequencing data from 10 murine studies (n = 187) comparing plant- and animal-protein diets. Alpha diversity was assessed using Shannon, Inverse Simpson, and Chao1 indices, and beta diversity with Aitchison distances. Differentially abundant taxa were identified using LEfSe and class-weighted Random Forest models. Functional potential was inferred with PICRUSt2, and taxon-pathway relationships were explored using correlation and network analyses. ResultsPlant-protein diets increased gut microbial diversity across all alpha diversity metrics and were associated with higher representation of saccharolytic and nitrogen-recycling genera such as Bacteroides, Muribaculaceae, and Allobaculum. Animal-protein diets favored proteolytic taxa, including Clostridium sensu stricto 1 and Colidextribacter. Microbial community structure differed significantly between diets (ANOSIM R = 0.663, p < 0.001). Random Forest models achieved >88% accuracy (AUC = 0.995) in predicting dietary groups, and LEfSe identified consistent discriminating taxa. Functional profiling showed that plant-based diets enriched pathways linked to short-chain fatty acid and aromatic amino acid metabolism, whereas animal-based diets favored sulfur- and branched-chain amino acid-associated pathways. Network analysis identified Muribaculaceae as a plant-associated hub and Lactobacillus as an animal-associated hub. ConclusionDietary protein source significantly influences gut microbiota composition and functional potential in mice. Plant- and animal-based proteins generate distinct metabolic signatures with implications for nitrogen cycling, sulfur metabolism, and microbial ecology. Future controlled dietary studies that harmonize protein source with other macronutrient variables are needed to isolate protein-specific effects. Statement of SignificanceThis study presents the first standardized meta-analysis of murine protein-intervention microbiome datasets, integrating taxonomic, machine learning, and predicted functional profiling to identify robust microbial and metabolic signatures that differentiate plant- from animal-based protein diets. By harmonizing evidence across diverse studies, it clarifies foundational ecological responses to protein source and provides mechanistic hypotheses that can inform future controlled nutrition and microbiome research