Work

Arrayed CRISPRi and quantitative imaging describe the morphotypic landscape of essential mycobacterial genes

Year: 2020

Type: article

Abstract: ABSTRACT Mycobacterium tuberculosis possesses a large number of genes of unknown or merely predicted function, undermining fundamental understanding of pathogenicity and drug susceptibility. To address this challenge, we developed a high-throughput functional genomics approach combining inducible CRISPR-interference and image-based analyses of morphological features and sub-cellular molecular localizations in the related non-pathogen, M. smegmatis . Applying automated imaging and analysis to an arrayed library of 272 essential gene knockdown mutants, we derive robust, quantitative descriptions of bacillary morphologies consequent on gene silencing. Leveraging statistical-learning, we demonstrate that functionally related genes cluster by morphotypic similarity and that this information can be used to infer gene function. Exploiting this observation, we reveal a previously unknown restriction-modification system, and identify filamentation as a defining mycobacterial response to histidine starvation. Our results support the application of large-scale image-based analyses for mycobacterial functional genomics, simultaneously establishing the utility of this approach for drug mechanism-of-action studies.

Source: eLife

DOI: 10.7554/elife.60083

Authors: Timothy J. de Wet, Kristin R. Winkler, Musa M. Mhlanga, Valerie Mizrahi, Digby F. Warner

Institutions: South African Medical Research Council, University of Cape Town, Institute of Infectious Disease and Molecular Medicine, Wellcome Centre for Infectious Diseases Research in Africa

Language: English

Topic: Tuberculosis Research and Epidemiology

Subfield: Infectious Diseases

Field: Medicine

Domain: Health Sciences

Open Access status: gold

Estimated APC paid: $2,500