PropertyValue
?: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.
is ?:annotates of
?:creator
?:doi
?:doi
  • 10.7554/elife.60083
?:externalLink
?:license
  • cc-by
?:pdf_json_files
  • document_parses/pdf_json/54e148ea7decb01bb034c3c611ccbefb588c96f4.json
?:pmc_json_files
  • document_parses/pmc_json/PMC7647400.xml.json
?:pmcid
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • PMC
?:title
  • Arrayed CRISPRi and quantitative imaging describe the morphotypic landscape of essential mycobacterial genes
?:type
?:year
  • 2020-11-06

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