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The Mycobacterium tuberculosis regulatory network and hypoxia

Author

Listed:
  • James E. Galagan

    (Boston University
    Boston University
    Bioinformatics Program, Boston University
    The Eli and Edythe L. Broad Institute of Harvard and MIT)

  • Kyle Minch

    (Seattle Biomedical Research Institute)

  • Matthew Peterson

    (Boston University)

  • Anna Lyubetskaya

    (Bioinformatics Program, Boston University)

  • Elham Azizi

    (Bioinformatics Program, Boston University)

  • Linsday Sweet

    (Immunology and Allergy, Brigham and Women’s Hospital and Harvard Medical School)

  • Antonio Gomes

    (Bioinformatics Program, Boston University)

  • Tige Rustad

    (Seattle Biomedical Research Institute)

  • Gregory Dolganov

    (Stanford Medical School)

  • Irina Glotova

    (Bioinformatics Program, Boston University)

  • Thomas Abeel

    (The Eli and Edythe L. Broad Institute of Harvard and MIT
    Ghent University, 9052 Gent, Belgium)

  • Chris Mahwinney

    (Boston University)

  • Adam D. Kennedy

    (Metabolon Inc.)

  • René Allard

    (Caprion Proteomics, Inc., Montreal, Quebec H4S 2C8, Canada)

  • William Brabant

    (Seattle Biomedical Research Institute)

  • Andrew Krueger

    (Boston University)

  • Suma Jaini

    (Boston University)

  • Brent Honda

    (Boston University)

  • Wen-Han Yu

    (Boston University)

  • Mark J. Hickey

    (Seattle Biomedical Research Institute)

  • Jeremy Zucker

    (The Eli and Edythe L. Broad Institute of Harvard and MIT)

  • Christopher Garay

    (Boston University)

  • Brian Weiner

    (The Eli and Edythe L. Broad Institute of Harvard and MIT)

  • Peter Sisk

    (The Eli and Edythe L. Broad Institute of Harvard and MIT)

  • Christian Stolte

    (The Eli and Edythe L. Broad Institute of Harvard and MIT)

  • Jessica K. Winkler

    (Seattle Biomedical Research Institute)

  • Yves Van de Peer

    (Ghent University, 9052 Gent, Belgium)

  • Paul Iazzetti

    (Boston University)

  • Diogo Camacho

    (Boston University)

  • Jonathan Dreyfuss

    (Boston University)

  • Yang Liu

    (Stanford Medical School)

  • Anca Dorhoi

    (Max Planck Institute for Infection Biology, 10117 Berlin, Germany)

  • Hans-Joachim Mollenkopf

    (Microarray Core Facility, Max Planck Institute for Infection Biology, 10117 Berlin, Germany)

  • Paul Drogaris

    (Caprion Proteomics, Inc., Montreal, Quebec H4S 2C8, Canada)

  • Julie Lamontagne

    (Caprion Proteomics, Inc., Montreal, Quebec H4S 2C8, Canada)

  • Yiyong Zhou

    (Caprion Proteomics, Inc., Montreal, Quebec H4S 2C8, Canada)

  • Julie Piquenot

    (Caprion Proteomics, Inc., Montreal, Quebec H4S 2C8, Canada)

  • Sang Tae Park

    (Boston University)

  • Sahadevan Raman

    (Boston University)

  • Stefan H. E. Kaufmann

    (Max Planck Institute for Infection Biology, 10117 Berlin, Germany)

  • Robert P. Mohney

    (Metabolon Inc.)

  • Daniel Chelsky

    (Caprion Proteomics, Inc., Montreal, Quebec H4S 2C8, Canada)

  • D. Branch Moody

    (Immunology and Allergy, Brigham and Women’s Hospital and Harvard Medical School)

  • David R. Sherman

    (Seattle Biomedical Research Institute
    Interdisciplinary Program of Pathobiology, University of Washington)

  • Gary K. Schoolnik

    (Stanford Medical School
    Stanford Medical School)

Abstract

We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.

Suggested Citation

  • James E. Galagan & Kyle Minch & Matthew Peterson & Anna Lyubetskaya & Elham Azizi & Linsday Sweet & Antonio Gomes & Tige Rustad & Gregory Dolganov & Irina Glotova & Thomas Abeel & Chris Mahwinney & Ad, 2013. "The Mycobacterium tuberculosis regulatory network and hypoxia," Nature, Nature, vol. 499(7457), pages 178-183, July.
    • Handle: RePEc:nat:nature:v:499:y:2013:i:7457:d:10.1038_nature12337
    DOI: 10.1038/nature12337
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    Cited by:

    1. Cheng Bei & Junhao Zhu & Peter H. Culviner & Mingyu Gan & Eric J. Rubin & Sarah M. Fortune & Qian Gao & Qingyun Liu, 2024. "Genetically encoded transcriptional plasticity underlies stress adaptation in Mycobacterium tuberculosis," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

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