Integrative Multi-Omics Analysis of Cecal Microbiome in BXD Mice Reveals Diet, Age, and Genotype Effects on Host Phenotypes (microbiomejournal.biomedcentral.com)

• High-fat diet reduced microbial alpha-diversity by 30-50% across all ages and genotypes.
• Machine learning (RF) using 614 species predicted age with AUC 0.84 and body weight with AUC 0.84 (within diet).
• Integrating top 5 microbial features with top 5 liver proteins improved age prediction to AUC 0.95.
• Duncaniella dubosii decreased with age; Streptococcus danieliae increased.
• Cecal Ido1 negatively correlated with Lachnospiraceae (SCFA producers), implicating tryptophan metabolism in diet-microbiome interactions.

"This study sequenced cecal metagenomes, metatranscriptomes, and host transcriptomes from 232 BXD mice across two diets, four ages, and 43 genotypes. Diet and genetics most strongly influenced microbiome composition, with high-fat diet reducing diversity by 30-50%. Machine learning models predicted body weight (AUC=0.84) and chronological age (AUC=0.84) from microbial profiles. Integrating liver proteomics with top microbial features improved age prediction to AUC=0.95. Network analyses linked cecal Ido1 expression with SCFA-producing Lachnospiraceae, suggesting a diet-modulated tryptophan metabolism pathway. The study demonstrates the predictive power of microbiome profiling for aging and obesity biomarkers even across genetic and dietary variation."