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


ABSTRACT: Mycobacterium tuberculosis possesses a large number of genes of unknown or 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 chromosomal localizations in the related non-pathogen, M. smegmatis. Applying automated imaging and analysis to 263 essential gene knockdown mutants in an arrayed library, 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 inform investigations of gene function. Exploiting this observation, we infer the existence of a mycobacterial 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.

SUBMITTER: de Wet TJ 

PROVIDER: S-EPMC7647400 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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

de Wet Timothy J TJ   Winkler Kristy R KR   Mhlanga Musa M   Mizrahi Valerie V   Warner Digby F DF  

eLife 20201106


<i>Mycobacterium tuberculosis</i> possesses a large number of genes of unknown or 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 chromosomal localizations in the related non-pathogen, <i>M. smegmatis</i>. Applying automated imaging and analysis to 263  ...[more]

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2020-12-21 | GSE159327 | GEO