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Transcriptional regulator-induced phenotype screen reveals drug potentiators in Mycobacterium tuberculosis

Nature Microbiology volume 6, pages 44–50 (2021)Cite this article

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Abstract

Transposon-based strategies provide a powerful and unbiased way to study the bacterial stress response1,2,3,4,5,6,7,8, but these approaches cannot fully capture the complexities of network-based behaviour. Here, we present a network-based genetic screening approach: the transcriptional regulator-induced phenotype (TRIP) screen, which we used to identify previously uncharacterized network adaptations of Mycobacterium tuberculosis to the first-line anti-tuberculosis drug isoniazid (INH). We found regulators that alter INH susceptibility when induced, several of which could not be identified by standard gene disruption approaches. We then focused on a specific regulator, mce3R, which potentiated INH activity when induced. We compared mce3R-regulated genes with baseline INH transcriptional responses and implicated the gene ctpD (Rv1469) as a putative INH effector. Evaluating a ctpD disruption mutant demonstrated a previously unknown role for this gene in INH susceptibility. Integrating TRIP screening with network information can uncover sophisticated molecular response programs.

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Fig. 1: Schematic of the TRIP screen.
Fig. 2: Regulon-mediated growth responses.
Fig. 3: mce3R regulon reveals effector of INH susceptibility.

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Data availability

The data reported in this paper are available in Supplementary Tables 1–5. The raw TRIP fastq sequence data files are deposited in the Sequence Read Archive database under accession PRJNA483505. The RNA-seq data are deposited in the Gene Expression Omnibus database under accession GSE151991. The TFI strains are available from BEI Resources (https://www.beiresources.org/Home.aspx).

Code availability

The code required to process the TRIP and RNA-seq sequenced reads are available at https://github.com/robertdouglasmorrison/DuffyNGS, https://github.com/robertdouglasmorrison/DuffyTools and https://github.com/DavidRShermanLab/TRIPscreen.

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Acknowledgements

We gratefully acknowledge J. Rock for kindly providing us with the pJR965 plasmid encoding a tetracyline-inducible dCas9 and kanamycin-selectable marker. We also thank J. Winkler, J. Lohmiller and R. Liao for technical assistance and S. Shen for helpful discussions. This work was supported by the National Institutes of Health (grant nos. U19 AI106761; U19 AI111276; U19 AI135976 and 5T32AI007509).

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Authors and Affiliations

  1. Department of Microbiology, University of Washington, Seattle, WA, USA

    Shuyi Ma, Robert Morrison, Jessica Farrow-Johnson & David R. Sherman

  2. Interdisciplinary Program of Pathobiology, Department of Global Health, University of Washington, Seattle, WA, USA

    Shuyi Ma, Samuel J. Hobbs, Jessica Farrow-Johnson, Andrew Frando, Neil Fleck, Christoph Grundner, Tige R. Rustad & David R. Sherman

  3. Division of Infectious Diseases, Department of Medicine, Weill Cornell Medical College, New York, NY, USA

    Vijay Soni & Kyu Y. Rhee

  4. Department of Microbiology and Immunology, Weill Cornell Medical College, New York, NY, USA

    Vijay Soni & Kyu Y. Rhee

  5. Center for Global Infectious Disease Research, Seattle Children’s Research Institute, Seattle, WA, USA

    Andrew Frando, Neil Fleck & Christoph Grundner

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Contributions

S.M., T.R.R. and D.R.S. conceived of the study, led the design, generated data, analysed the results and drafted the manuscript. R.M. developed the software to convert raw sequencing data into abundance values for each TFI strain. S.J.H. generated data and assembled the pooled TFI library cultures. J.F.-J. assisted with sample preparation for sequencing. V.S. and K.Y.R. generated, analysed and interpreted the metabolite profiling data. A.F., N.F. and C.G. generated the CRISPRi strain.

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Correspondence to David R. Sherman.

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Extended data

Extended Data Fig. 1 Comparing TFI pool growth between experimental conditions.

Number of doublings for TFI strain pool over duration of TRIP experiments in the untreated vs. INH treated conditions, estimated from the change of OD600 over the course of the experiment. Data show mean ± SD of four biological replicates from a representative experiment (three independent experiments were performed in total).

Extended Data Fig. 2 Chemical induction triggers mce3R expression change.

Expression fold change of mce3R relative to the housekeeping gene sigA, assessed by qPCR. Data show mean ± SD of 4 biological replicates from a representative experiment (two were performed in total). Conditions compared are in absence (white bars) and presence (black bars) of anhydrous-tetracycline (ATc) inducer, and presence and absence of INH exposure. Results show at least 8-fold activation of mce3R expression upon induction with ATc in both absence and presence of INH (p = 0.00035, two-sided t-test for -ATc untreated vs. +ATc untreated; p = 0.0036, two-sided t-test for -ATc + INH vs. +ATc + INH).

Extended Data Fig. 3 mce3Rind metabolic viability after 7 days INH.

Viability upon TFI induction (blue) is compared to uninduced (white), as measured by luminescence (see Methods). Data presented as mean Error bars show ± SD from four biological replicates. ** indicates significant differences between induction states (p = 8.3 x 10-6 comparing uninduced vs. TFI induced at 1.6 μM; p = 5.7 x 10-6 comparing uninduced vs. TFI induced at 1.8 μM; p = 1.3 x 10-3 comparing uninduced vs. TFI induced at 2.1 μM; p = 4.3 x 10-4 comparing uninduced vs. TFI induced at 2.4 μM; p = 7.6 x 10-3 comparing uninduced vs. TFI induced at 2.8 μM; p = 6.9 x 10-3 comparing uninduced vs. TFI induced at 3.2 μM; p = 4.6 x 10-4 comparing uninduced vs. TFI induced at 3.6 μM). Each p-value was calculated based on a two-sided t-test.

Extended Data Fig. 4 Overlap of genes regulated by mce3R that also modulate expression in baseline response to INH exposure.

a, Network diagram depicts the genes differentially expressed upon induction of mce3R expression (left), and upon exposure to INH (right). Three genes alter expression under both these conditions. b, Table summarizes the expression fold-changes of the genes perturbed both by mce3R induction and INH exposure.

Extended Data Fig. 5 Association between ctpD expression and INH sensitivity.

a, CFU/mL at 0 days and 7 days of H37Rv (black bar) and a ctpD CRISPRi-knockdown strain without (yellow) and with (red) chemical induction of CRISPRi activity. Both strains were exposed to 3.6 µM INH or no drug. There was no significant difference between the growth of strains without drug, and the average untreated CFU/mL is plotted in the gray bar. Data show mean ± SD of three biological replicates from two independent experiments (for H37Rv conditions) or one experiment (pJR965-ctpD conditions). There is a significant difference between the CRISPRi knockdown and wildtype strains (p = 0.00027 for Day 7 H37Rv + INH vs. Day 7 pJR965-ctpD – ATc + INH, Wilcoxon ranksum test with continuity correction; p = 0.00027 for Day 7 H37Rv + INH vs. Day 7 pJR965-ctpD + ATc + INH, Wilcoxon ranksum test with continuity correction; p = 0.0012 for Day 7 pJR965-ctpD – ATc + INH vs. Day 7 pJR965-ctpD + ATc + INH, Wilcoxon ranksum test with continuity correction). b, qPCR quantification of ctpD expression levels relative to the wildtype H37Rv in the CRISPRi knockdown strain with and without chemical induction of activity. The CRISPRi strain exhibited marked repression even in the absence of chemical induction. Data shown are from two biological replicates for the CRISPRi knockdown strain, uninduced and four biological replicates for the CRISPRi knockdown strain with induction. The experiment was performed once.

Extended Data Fig. 6 Comparing the effect of in vitro INH on mce3R and ctpD perturbation strains.

We measured the effect of mce3R induction in the CDC1551 strain background (blue) and in the ctpD::Himar1 strain background (orange) on Mtb survival in INH (3.6 μM), added on Day 0, as quantified by CFU/mL. Solid blue and orange lines indicate TFI induction and dashed blue and orange lines indicate TFI uninduced. As additional controls, we also compared survival of the CDC1551 wildtype strain (gray), as well as the ctpD::Himar1 strain (red). The data suggest that mce3R induction conveys significant additional fitness defect relative to ctpD::Himar1 strain at day 14 (p = 0.00058, two-sided t-test comparing ctpD::Himar1:: mce3Rind TFI induced vs. ctpD::Himar1; p = 0.0024, two-sided t-test comparing mce3Rind (CDC1551) TFI induced vs. CDC1551). There appears to be a modest (though not statistically significant) difference in the extent of INH-mediated killing at 7 days between the ctpD::Himar strain (red) and the ctpD::Himar1 strain with mce3R induction (orange solid) (p = 0.09, two-sided t-test). Data show mean ± SD of three biological replicates from one experiment.

Extended Data Fig. 7 Association between mce3R, ctpD expression and abundance of INH and INH-NAD adduct during drug exposure.

Relative abundance of INH and INH-NAD adduct in Mtb lysate (panels a, b, d, e, or supernatant (panels c, f) of strains exposed to 7.2μM INH for 24 hours. Panels a, b, and c show effect of ctpD transposon disruption and complementation with episomally ATc-inducible ctpD expression. Panels d, e, and f show the effect of mce3R induction with or without ctpD transposon disruption. ctpD disruption conveyed increased intracellular INH and INH-NAD levels and concomitant decreased levels of INH in the supernatant. Induction of mce3R also increases intracellular INH and INH-NAD levels, but does not convey additional accumulation increase in the ctpD transposon strain background. Bars plot mean ± SD for 3 biological replicates.

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Table 1: Detailed results of TRIP screens in the presence and absence of 3.6 µM INH. Tab 1 reports the mean log2[abundance fold change] for each TFI strain relative to no induction. Tab 2 reports the log2[RPM] values for each sample analysed for the study. Supplementary Table 2: Detailed regulon and accompanying Gene Ontology term enrichment information of transcription factors that convey altered fitness under different conditions. The Gene Ontology annotations are from ref. 52. Tab 1 provides information for transcription factors conveying the growth phenotype under log-phase growth conditions. Tab 2 provides information for transcription factors conveying the conditional resistance to INH (group A). Tab 3 provides information for transcription factors conveying the hypersusceptibility to INH but no growth defect in the absence of drug (group B). Tab 4 provides information for transcription factors conveying hypersusceptibility to INH and a growth defect in the absence of drug (group C). Tab 5 provides information for all transcription factors conveying hypersusceptibility to INH (groups B and C combined). The regulon information is based on data generated from refs. 13,14. The essentiality information is based on data generated from refs. 7,19. Supplementary Table 3: Overlap of TFI regulons with the INH growth phenotype and genes with the INH fitness phenotype in a Tn-seq assay measured by ref. 19. Supplementary Table 4: Correlation between ctpD regulation and INH response phenotype. Shown is a summary of the regulatory impact and TRIP abundance fold change upon INH exposure for the transcription factors that regulate ctpD. Note that Rv1990c and Rv0022c do not have TRIP values associated because the raw sequence data had poor detection of these TFI strains under all conditions. Expression fold-change values were assembled from ref. 14. Supplementary Table 5: Correlation between Rv0119 regulation and INH response phenotype. Shown is a summary of the regulatory impact and TRIP abundance fold change upon INH exposure for the transcription factors that regulate Rv0119, the other gene induced during basal INH exposure in H37Rv and repressed by mce3R.

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Ma, S., Morrison, R., Hobbs, S.J. et al. Transcriptional regulator-induced phenotype screen reveals drug potentiators in Mycobacterium tuberculosis. Nat Microbiol 6, 44–50 (2021). https://doi.org/10.1038/s41564-020-00810-x

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