Perturbation-specific transcriptional mapping for unbiased target elucidation of antibiotics.

Proceedings of the National Academy of Sciences of the United States of America
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Abstract

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the postgenomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called perturbation-specific transcriptional mapping (PerSpecTM), in which large-throughput expression profiling of wild-type or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three molecules with activity against by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small-molecule inhibition resemble those resulting from genetic depletion of essential targets by clustered regularly interspaced short palindromic repeats interference (CRISPRi) by PerSpecTM, demonstrating proof of concept that correlations between expression profiles of small-molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.

Year of Publication
2024
Journal
Proceedings of the National Academy of Sciences of the United States of America
Volume
121
Issue
45
Pages
e2409747121
Date Published
11/2024
ISSN
1091-6490
DOI
10.1073/pnas.2409747121
PubMed ID
39467118
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