A quantitative approach to measure and predict microbiome response to antibiotics.
Vincent TuYue RenCeylan TanesSagori MukhopadhyayScott G DanielHongzhe LiKyle BittingerPublished in: mSphere (2024)
Antibiotics are potent influencers of the human microbiome and can be a source for enduring dysbiosis and antibiotic resistance in healthcare. Existing microbiome data analysis methods can quantify perturbations of bacterial communities but cannot evaluate whether the differences are aligned with the expected activity of a specific antibiotic. Here, we present a novel method to quantify and predict antibiotic-specific microbiome changes, implemented in a ready-to-use software package. This has the potential to be a critical tool to broaden our understanding of the relationship between the microbiome and antibiotics.