Mechanisms behind antibiotic recalcitrance

This project aims to understand antibiotic recalcitrance, a bacterial survival mechanism including both persistence and tolerance and, which contributes to emergence of antibiotic resistance.

We will use cutting-edge methods including Deep Phenotyping (BacterAI) robotics and bacterial bulk and single cell transcriptomics to (i) identify environmental stresses and molecular mechanisms that drive formation of antibiotic recalcitrant bacterial population, (ii) identify compositions of in vivo infection environments triggering antibiotic recalcitrance, (iii) reveal bacterial physiology at their in vivo infection sites, and identify the recalcitrant subpopulations that emerge upon antibiotic exposure in in vivo mimicking stress conditions and in difficult-to-treat human biofim infections.

The strains to be analyzed include clinically problematic Gram-negative and Gram-positive bacteria.This is a collaborative effort involving four PIs with complementary expertise in infection biology, single cell technology, and machine learning driven automated systems. The project offers a unique approach to tackle the global threat of antibiotic resistance.

Our unique collection of bacterial stress response data, state-of-the-art techniques for Deep Phenotyping robotics, and competence in bacterial scRNA-seq put us in a unique position to retrieve new information about bacterial physiology and mechanisms behind antibiotic recalcitrance in host clinical contexts.