Mapping Drug-Microbe Interactions and Evolution in the Human Gut Microbiome

Trillions of microbes line the gastrointestinal tract to form the gut microbiome, a symbiotic organ whose supportive functions include energy production, immune homeostasis, and defense against pathogens. Disturbances to gut microbial composition, in turn, drive the pathogenesis of various metabolic, inflammatory, and carcinogenic diseases. Much effort has been dedicated to elucidating environmental triggers of gut dysbiosis, not the least of which is the consumption of medications. Antibiotics eradicate keystone commensals and enhance pathogenic behaviors of persisting pathobionts, whose resistance mechanisms can have off-target effects on human physiology and treatment response. Recent evidence indicates that the spectrum of antimicrobial compounds that disturb the gut microbiome extends far beyond traditional antibiotics, and includes commonly prescribed cardiovascular, neuropsychiatric, metabolic, and cancer medications. Although the capacity of non-antibiotic pharmaceuticals to induce gut dysbiosis is well appreciated, their impact on gut microbial function has not been studied systematically. Bacterial multi-omic profiling offers a cost-effective, high-throughput approach to understanding bacterial genetic responses to chemical perturbations, and how these functional changes might reciprocally impact relevant human phenotypes. Our laboratory, which houses a personal strain biobank of over 30,000 gut bacterial isolates spanning over 400 taxa, has established scalable pipelines for bacterial genomic and transcriptomic profiling that are readily applicable to diverse non-model gut microbes. We applied these methodologies to healthy fecal samples and bacterial isolates to elucidate strain-level responses to common pharmaceuticals with known gut microbiome associations. We first performed a gut microbiota transcriptomic screen of 19 representative fecal isolates against 20 top-prescribed orally delivered medications. Computational analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed induction of pathways associated with metabolism and multidrug resistance, including upregulation of efflux machinery by lipid-lowering drugs, antidepressants and cardiovascular medications. We discovered many bacterial responses with clinical significance, which we computationally validated using clinical metagenomic datasets. Most importantly, we showed that statin-mediated overexpression of the AcrAB-TolC efflux pump generates collateral toxicity in dietary retinol and secondary bile acids, resulting in depletion of pump-containing Bacteroidales species from patient microbiomes. We next performed the first comprehensive screen for antimicrobial activity in cancer drugs by exposing three healthy fecal samples to a panel of 41 first-line cancer therapeutics. Using 16S-genomic profiling, we identified several members of the targeted kinase inhibitor (TKI) class that induced gut dysbiosis, including first-line hepatocellular carcinoma (HCC) treatment sorafenib. We profiled natural bacterial isolates exposed to different TKI HCC treatments, and again observed transcriptional induction of conserved multidrug efflux pumps. Adaptive evolution assays identified Resistance-Nodulation-Division (RND) efflux pumps as effectors of TKI resistance. Remarkably, we demonstrated that acquired TKI resistance in evolved Bacteroidales lineages generated strain-specific cross-resistances and collateral sensitivities to several unrelated antibiotics. Collectively, our work demonstrates the importance of profiling xenobiotic impacts on the gut microbial resistome, as bacterial adaptations to pharmaceutical toxicities can feed back onto microbiome communities and the human host to affect health outcomes