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Absolute Proteome Composition and Dynamics during Dormancy and Resuscitation of Mycobacterium tuberculosis.

Abstract
Mycobacterium tuberculosis remains a health concern due to its ability to enter a non-replicative dormant state linked to drug resistance. Understanding transitions into and out of dormancy will inform therapeutic strategies. We implemented a universally applicable, label-free approach to estimate absolute cellular protein concentrations on a proteome-wide scale based on SWATH mass spectrometry. We applied this approach to examine proteomic reorganization of M. tuberculosis during exponential growth, hypoxia-induced dormancy, and resuscitation. The resulting data set covering >2,000 proteins reveals how protein biomass is distributed among cellular functions during these states. The stress-induced DosR regulon contributes 20% to cellular protein content during dormancy, whereas ribosomal proteins remain largely unchanged at 5%-7%. Absolute protein concentrations furthermore allow protein alterations to be translated into changes in maximal enzymatic reaction velocities, enhancing understanding of metabolic adaptations. Thus, global absolute protein measurements provide a quantitative description of microbial states, which can support the development of therapeutic interventions.
AuthorsOlga T Schubert, Christina Ludwig, Maria Kogadeeva, Michael Zimmermann, George Rosenberger, Martin Gengenbacher, Ludovic C Gillet, Ben C Collins, Hannes L Röst, Stefan H E Kaufmann, Uwe Sauer, Ruedi Aebersold
JournalCell host & microbe (Cell Host Microbe) Vol. 18 Issue 1 Pg. 96-108 (Jul 08 2015) ISSN: 1934-6069 [Electronic] United States
PMID26094805 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
CopyrightCopyright © 2015 Elsevier Inc. All rights reserved.
Chemical References
  • Bacterial Proteins
  • Proteome
Topics
  • Bacterial Physiological Phenomena
  • Bacterial Proteins (analysis)
  • Mass Spectrometry (methods)
  • Mycobacterium tuberculosis (chemistry, physiology)
  • Proteome (analysis)
  • Proteomics (methods)

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