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

  1. Timothy J de Wet
  2. Kristy R Winkler
  3. Musa Mhlanga
  4. Valerie Mizrahi
  5. Digby F Warner

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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.

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  1. Version published to 10.7554/elife.60083 on eLife
  2. eLife

    ###Reviewer #3:

    In this manuscript the authors used high throughput light microscopy and image analysis to study the effects of essential gene knockdown via an arrayed CRISPRi library in M.smegmatis.

    There are many technical advances to this paper, and the experiments are well executed. The data and its analysis adds value to the mycobacterial field. I particularly appreciated the thoughtful Discussion, which honestly laid out the limitations for the author's work.

    However, in some areas, the lengthy manuscript came across as a bit unfocused. For example, in addition to describing the methods of their technique, the author's validate or give examples of what their data contain (identification of cryptic putative RM system, histidine auxotroph phenotypes, effects of disrupting mycolic acid biosynthesis). They then discuss the potential to use CRISPRi to conform compound MOA. This is a lot of information (10 figures with many subpanels), but none of these threads are really taken to completion. I appreciate the amount of work that doing that would take, so I'm not suggesting that as a revision. But, reshuffling or restructuring some of these sections, may help to guide the reader towards the utility of these data.

    Lastly, and I think importantly, after reading this manuscript, I was left with the lingering question: for any essential gene that I'm interested in, would these data help to make hypotheses about its function. And ... I'm not sure... The data as presented in Figure 6 do not help this case. While some functionally related genes cluster together, many do not, especially for genes that fall into cluster 2.

    With some textual changes to streamline the manuscript, I think the manuscript could be improved.

  3. eLife

    ###Reviewer #2:

    de Wet et al. screen a CRISPRi library of M. smeg. essential genes for morphological phenotypes. Using a sensitive analytical approach, they find that most essential knockdown strains have morphological phenotypes. They further show that functionally related genes cluster by morphology in multidimensional space. Finally, they associate morphological changes with antibiotics to probe antibiotic MOA. This manuscript will be of interest to researchers studying essential genes in Mycobacteria.

    General Comments:

    1. "Moreover,to verify the reproducibility of the imaging workflow, replicate imaging was performed on separate days for 134 strains." Does this mean that the authors don't have replicate data for 29 strains? If so, imaging of these strains must be repeated to verify reproducibility. Have the authors validated any phenotypes with a second guide RNA to rule out off target effects?

    2. MSMEG_3213 isn't an example of defining the function of an uncharacterized gene--instead it simply validates existing database predictions. Further, the data presented here do not demonstrate that MSMEG_3213 is the methylase of an R-M pair.

    3. The his gene depletion phenotypes are likely due to translation defects that result from uncharged tRNAs. This is consistent with tRNA synthetase/ribosomal protein knockdown phenotypes presented in this manuscript, as well as the observation that translation inhibition by knockdown or serine hydroxymate produced elongated cells in Bacillus subtilis (PMID: 27238023).

  4. eLife

    ###Reviewer #1:

    General assessment:

    This manuscript addresses the lag in identifying functions of genes annotated in bacterial genomes. It is an epic presentation of a line of investigation from inception through assay development and validation to identifying previously unknown functional associations. Beyond these initial novel insights, the developed phenoprinting approach and the resulting UMAP space provide a solid foundation for future conditional gene function and initial drug mechanism of action studies.

    Substantive concerns:

    None

  5. eLife

    ##Preprint Review

    This preprint was reviewed using eLife’s Preprint Review service, which provides public peer reviews of manuscripts posted on bioRxiv for the benefit of the authors, readers, potential readers, and others interested in our assessment of the work. This review applies only to version 1 of the manuscript.

    ###Summary:

    This manuscript combines a CRISPRi library in Mycobacterium smegmatis with high throughput light microscopy and image analysis to investigate the effects of essential gene knockdown on bacterial morphology. The reviewers all agree that there are many technical advances presented in this paper, the experiments are well executed, and the data and its analysis is significant for the field. However, there are some questions regarding the reproducibility of the data and the utility of these data as a predictive tool. The reviewers believe that these questions should be straightforward to address, as described more below.

  6. Version published to 10.1101/2020.03.20.000372v1 on bioRxiv