The paper develops a CRISPRi system for studying essential genes in Pseudomonas aeruginosa, revealing gene function and small molecule interactions through phenotypic analysis.

mBio · Feb 11, 2026Peer-reviewedMicrobiology

Massively parallel combination screen reveals small molecule sensitization of antibiotic-resistant Gram-negative ESKAPE pathogens

Megan W. Tse, Meilin Zhu, Benjamin Peters, Efrat Hamami, Julie Chen, Kathleen P. Davis, Samuel Nitz, Juliane Weller, Thulasi Warrier, Diana K. Hunt, Yoelkys Morales, Tomohiko Kawate, Jeffrey L. Gaulin, Jon H. Come, Juan Hernandez-Bird, , Paul C. Blainey

This study uses high-throughput screening to identify small molecules that enhance antibiotic efficacy against multidrug-resistant Gram-negative bacteria.

Proceedings of the National Academy of Sciences · Mar 24, 2025Peer-reviewedMicrobiology

Multiplexed screen identifies a Pseudomonas aeruginosa-specific small molecule targeting the outer membrane protein OprH and its interaction with LPS

Bradley E. Poulsen, Thulasi Warrier, Sulyman Barkho, Josephine Bagnall, Keith P. Romano, T. L. White, Xiao Yu, Tomohiko Kawate, Phuong H. Nguyen, Kyra Raines, Kristina M. Ferrara, Aaron J. Golas, Michael G. FitzGerald, Andras Boeszoermenyi, Virendar K. Kaushik, , Deborah Tan Hung

The paper identifies a Pseudomonas aeruginosa-specific small molecule, BRD1401, that targets OprH and disrupts its interaction with LPS, increasing membrane fluidity.

Cell chemical biology · Dec 27, 2024Peer-reviewedMicrobiology

Perturbation-Specific Transcriptional Mapping for unbiased target elucidation of antibiotics.

Keith P. Romano, Josephine Bagnall, Thulasi Warrier, Jaryd Sullivan, Kristina M. Ferrara, Marek Orzechowski, Phuong Nguyen, Kyra Raines, Jonathan Livny, Noam Shoresh F, Deborah Tan Hung

This paper introduces PerSpecTM, a method to predict antibiotic mechanisms of action by comparing transcriptional responses of new molecules to known perturbations, demonstrating its effectiveness with three new anti-Pseudomonas aeruginosa compounds.

Proceedings of the National Academy of Sciences · Oct 28, 2024Peer-reviewedGenomics

Essential and virulence-related protein interactions of pathogens revealed through deep learning

Ian R. Humphreys, Jing Zhang, Minkyung Baek, Yaxi Wang, Aditya Krishnakumar, Jimin Pei, Ivan V. Anishchenko, Catherine A. Tower, Blake A. Jackson, Thulasi Warrier, Deborah Tan Hung, Snow Brook Peterson, Joseph D. Mougous, Qian Cong, David A. Baker

This study uses deep learning to predict protein-protein interactions in bacterial pathogens, identifying new complexes involving essential genes and virulence factors, with half of tested predictions validated.

Nature Microbiology · Sep 18, 2024Peer-reviewedBiochemistry