Transcriptional regulatory networks of the human gut symbiont Bacteroides thetaiotaomicron are uncovered using machine learning.

Bacteroides thetaiotaomicron VPI-5482 is a prominent human gut symbiont of increasing importance to human health and therapeutic applications. Despite its significance, the transcriptional regulatory network (TRN) governing its survival and resilience in vivo remains poorly understood. Here, we present BtModulome, a comprehensive transcriptional regulatory framework derived from independent component analysis of 461 RNA-seq datasets spanning diverse niche-specific conditions and genetic backgrounds. This analysis revealed the BtModulome consisting of 110 independently modulated gene sets (iModulons), explaining 72.9% of the variance in the RNA-seq dataset. We validated strong associations with 39 known regulators and identified 311 novel regulator-regulon relationships, accounting for 22.4% expansion of the known TRN of B. thetaiotaomicron. In addition, we functionally characterized 11 ECF-σs, including SigW-1, which orchestrates arylsulfatase expression critical for host colonization, and SigH-1, which mediates (p)ppGpp-dependent stringent response. Integration of iModulon activities with multi-omics datasets provided mechanistic insights into stress responses and carbon utilization both in vitro and in vivo. This comprehensive TRN framework establishes a foundation for understanding adaptive mechanisms in gut commensals and demonstrates the utility of module-centric analysis for biological discovery in non-model organisms.