Systematic, multiparametric analysis of Mycobacterium tuberculosis intracellular infection offers insight into coordinated virulence

Amy K. Barczak, Roi Avraham, Shantanu Singh, Samantha S. Luo, Wei Ran Zhang, Mark Anthony Bray, Amelia E. Hinman, Matthew Thompson, Raymond M. Nietupski, Aaron Golas, Paul Montgomery, Michael Fitzgerald, Roger S. Smith, Dylan W. White, Anna D. Tischler, Anne E. Carpenter, Deborah T. Hung

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


A key to the pathogenic success of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the capacity to survive within host macrophages. Although several factors required for this survival have been identified, a comprehensive knowledge of such factors and how they work together to manipulate the host environment to benefit bacterial survival are not well understood. To systematically identify Mtb factors required for intracellular growth, we screened an arrayed, non-redundant Mtb transposon mutant library by high-content imaging to characterize the mutant-macrophage interaction. Based on a combination of imaging features, we identified mutants impaired for intracellular survival. We then characterized the phenotype of infection with each mutant by profiling the induced macrophage cytokine response. Taking a systems-level approach to understanding the biology of identified mutants, we performed a multiparametric analysis combining pathogen and host phenotypes to predict functional relationships between mutants based on clustering. Strikingly, mutants defective in two well-known virulence factors, the ESX-1 protein secretion system and the virulence lipid phthiocerol dimycocerosate (PDIM), clustered together. Building upon the shared phenotype of loss of the macrophage type I interferon (IFN) response to infection, we found that PDIM production and export are required for coordinated secretion of ESX-1-substrates, for phagosomal permeabilization, and for downstream induction of the type I IFN response. Multiparametric clustering also identified two novel genes that are required for PDIM production and induction of the type I IFN response. Thus, multiparametric analysis combining host and pathogen infection phenotypes can be used to identify novel functional relationships between genes that play a role in infection.

Original languageEnglish (US)
Article numbere1006363
JournalPLoS pathogens
Issue number5
StatePublished - May 2017

Bibliographical note

Funding Information:
This work was supported by NIAID K08-AI080944 (AKB), a Massachusetts General Hospital Claflin Distinguished Scholar Award (AKB), a Massachusetts General Hospital Pingree Transformative Scholar Award (AKB), a Ragon Institute TB Seed Grant (DTH), the Broad Institute Tuberculosis donor group and the Pershing Square Foundation (DTH), and the Harvard CFAR BSL3 Core, an NIH funded program (P30 AI060354). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors would like to thank Dr. Emilie Layre and Dr. Branch Moody for training and advice on the design, execution, and interpretation of comparative lipidomics experiments, Dr. Tan-Yun Cheng for assistance interpreting CID-MS data, Dr. Eric Rubin for helpful discussions, Dr. Scarlet Shell for protocol advice, Dr. Jennifer Philips for the EsxGH antibody, and Dr. Edith Houben for the plasmid necessary for production of PPE41 antibodies.

Publisher Copyright:
© 2017 Barczak et al.

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