National Institute of Allergy and Infectious Diseases 1P01AI181935-01A1

Microbiology of Treatment Shortening in Tuberculosis

This award supports research to characterize drug-tolerant subpopulations of Mycobacterium tuberculosis at the single-cell level using advanced measurement and machine learning methods to inform strategies for shortening tuberculosis treatment.

Description

Tuberculosis treatment is lengthy because some bacterial subpopulations are more tolerant of drug treatment than others. Strategies to shorten treatment must consider how to target drug-tolerant subpopulations directly; to do so, we must first systematically and biologically characterize how different Mycobacterium tuberculosis (Mtb) subpopulations respond to treatment. This core leverages new measurement and analysis methods to overcome technological obstacles in measuring and characterizing drug response at the single-cell level for Mtb. We will work with program projects to generate single-cell profiles of Mtb response to drug treatment and gene knockdown. We will measure both cell morphological and transcriptomic responses, each providing different information types and highlighting different aspects of cellular responses. We will integrate these data modalities using cross-training in machine learning models. This data integration reveals multimodal signatures that differentiate cellular states to define and characterize Mtb subpopulations that respond differently to treatment. Evaluation of single-cell responses using the treatment and genetic knockdowns of focus in each of the four program projects will enable us to develop a broader dataset for integrative learning. We anticipate that the activities of the core will provide a practical platform to measure and interrogate subpopulation responses to treatment and genetic perturbations.

View original record