Whether human-associated environments drive adaptive genome evolution in gut commensal bacteria remains largely unknown. Here, we investigate how genomic adaptation in gut bacteria differs between industrialized and non-industrialized human populations. We generated a collection of isolate genomes spanning diverse host geographies, lifestyles, species, and strains. We first found that, compared with metagenome-assembled genomes (MAGs), paired isolate genomes recover more functional elements and signals of horizontal gene transfer (HGT). Leveraging isolate genomes from multiple species, we find that strains from industrialized hosts experience an expansion of proteome size and harbor greater pangenome fluidity, driven by recent HGT events. Gene- and variant-level analyses reveal convergent patterns of lifestyle-specific adaptation in functions that are critical for ecological adaptation, such as the stress response, cell-envelope remodeling, and central metabolism. Our results demonstrate that industrialization drives convergent genome evolution in gut bacteria, providing a framework for understanding the mechanisms of microbial adaptation to rapidly changing human environments.
Understanding how industrialization reshapes the human metaorganism requires integrating microbiome ecology with host physiology across globally diverse populations. Here, we generate multivariate data from the Global Microbiome Conservancy cohort, including gut microbiome, immunoglobulin A (IgA) sequencing, host genotyping, diet, lifestyle, and fecal biomarker profiles, to investigate host-microbiome interactions across gradients of industrialization and geography. We show that industrialization is associated with homogenized microbial compositions, reduced microbial diversity, and lower community stability, independent of host confounders. We further show that industrialization is linked to elevated markers of gut stress, increased IgA secretion, and altered patterns of IgA-bacteria interactions. Finally, we show that microbiome-based disease predictors trained on industrialized populations are uninformative in less industrialized cohorts, highlighting limited cross-population transferability. Together, our results reveal coordinated restructuring of the microbial ecosystem and host physiology and emphasize the need for inclusive, globally representative data to improve translational microbiome applications across diverse human populations.