Oxygen Availability and Metabolic Dynamics During Mycobacterium tuberculosis Latency

Elebeoba E. May, Cheryl L. Sershen

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Objective: In vitro models of Mycobacterium tuberculosis (Mtb) nonreplicating persistence (NRP) suggest the rate of oxygen (O2) depletion is a significant determinant in persistence. However, few studies have characterized the metabolic association between slow and rapid O2 depletion rates and successful versus failed persistence. Methods: We developed a theoretical model of Mtb metabolic adaptation that includes O2 driven genetic modulation of enzymes in the tricarboxylic acid cycle, energy, and redox recycling pathways. We conducted an in silico study of Mtb adaptation, and investigated the metabolic dynamics that enable persistence during slow versus rapid anaerobiosis. Results: Consistent with in vitro studies, during rapid anaerobiosis the most significant enzymatic changes occurred during the active growth period while the majority of the slow anaerobic system's adaptive response occurred during the first phase of aerobic shiftdown (NRP1). The characteristic response of the two conditions differed, with the slow anaerobic system exhibiting positive adaptation response, upregulating six enzymes during NRP1, while the rapid system exhibited a negative adaptation response, decreasing the levels of seven enzymes during active growth. Conclusion: Results of our study illustrate the intricate metabolic balance Mtb achieves during adaptation to anaerobic conditions, and how failure in redox recycling correlates to failure in persistence. Significance: We have provided the first theoretical description of the genetic and metabolic death profile for Mtb during anaerobic growth. Insight into Mtbs dynamic adaptation response provides a unique systems framework for the development of targeted therapies to reduce the likelihood of mycobacterial persistence and the related incidence of latent tuberculosis infection.

Original languageEnglish (US)
Article number7559795
Pages (from-to)2036-2046
Number of pages11
JournalIEEE Transactions on Biomedical Engineering
Volume63
Issue number10
DOIs
StatePublished - Oct 2016

Keywords

  • Computational systems biology
  • pathology

ASJC Scopus subject areas

  • Biomedical Engineering

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