Discovering the Microbial Enzymes Driving Drug Toxicity with Activity-Based Protein Profiling

TLDR

Interindividual differences in gut microbiota composition influence drug responses, as seen with irinotecan‑induced GI toxicity caused by bacterial β‑glucuronidases that reactivate the drug, yet proteomics has not yet identified the specific enzymes responsible. This study aims to identify the bacterial GUS enzymes that generate the toxic metabolite SN‑38 from human fecal samples using an activity‑based protein profiling platform. An ABPP‑enabled proteomics pipeline was applied to fecal samples to quantify GUS enzymes, which were then combined with ex vivo kinetic data to pinpoint the enzymes driving SN‑38 reactivation and to explain differential inhibition among samples. The resulting pipeline provides a novel technical and bioinformatics approach to discover microbial enzymes from complex fecal material, offering potential precision biomarkers and drug targets for personalized medicine.

Abstract

It is increasingly clear that interindividual variability in human gut microbial composition contributes to differential drug responses. For example, gastrointestinal (GI) toxicity is not observed in all patients treated with the anticancer drug irinotecan, and it has been suggested that this variability is a result of differences in the types and levels of gut bacterial β-glucuronidases (GUSs). GUS enzymes promote drug toxicity by hydrolyzing the inactive drug–glucuronide conjugate back to the active drug, which damages the GI epithelium. Proteomics-based identification of the exact GUS enzymes responsible for drug reactivation from the complexity of the human microbiota has not been accomplished, however. Here, we discover the specific bacterial GUS enzymes that generate SN-38, the active and toxic metabolite of irinotecan, from human fecal samples using a unique activity-based protein profiling (ABPP) platform. We identify and quantify gut bacterial GUS enzymes from human feces with an ABPP-enabled proteomics pipeline and then integrate this information with ex vivo kinetics to pinpoint the specific GUS enzymes responsible for SN-38 reactivation. Furthermore, the same approach also reveals the molecular basis for differential gut bacterial GUS inhibition observed between human fecal samples. Taken together, this work provides an unprecedented technical and bioinformatics pipeline to discover the microbial enzymes responsible for specific reactions from the complexity of human feces. Identifying such microbial enzymes may lead to precision biomarkers and novel drug targets to advance the promise of personalized medicine.