Persisters are a subpopulation of bacteria that resist killing by antibiotics, even though they are genetically similar to their drug-susceptible counterpart. Like in several other bacteria, persisters are also reported in the human pathogen Mycobacterium tuberculosis (Mtb). Stochastic formation of Mtb persisters with a high level of antimicrobial tolerance set the stage for subsequent multidrug-resistant mutations. Despite significant advancement in our understanding, much remains to be learnt about the biology of this drug-recalcitrant bacterial subpopulation. Most of the information pertaining to the metabolic evolution required for emergence of drug tolerance in tuberculosis (TB) pathogens has come from transcriptional, metabolomic, and mutagenesis studies. Since proteins are the key functional molecules regulating the majority of metabolic activities in the cell, investigation of the whole-cell protein expression profile will further provide valuable insights into the physiology of Mtb persisters. We performed a quantitative proteomic analysis of Mtb H37Rv cultured under an in vitro persistence model to identify the proteomic profile of the phenotypic drug-tolerant bacterial population. Our study reveals that proteins related to intermediary metabolism and respiration, cell-wall and cell processes, lipid metabolism, information pathways, and virulence, detoxification and adaptation functional categories are primarily modulated in the persister subpopulation. Further, we demonstrate that various surface-localized mycobacterial membrane protein large (MmpL) proteins, which exhibit a high level of expression in Mtb persisters, are crucial for the mycobacterial survival during persistent growth state. A drug-induced persister subpopulation of Mtb exhibit various differentially regulated proteins that might be critical in mitigating the antimicrobial effect of drugs and can be further explored to develop novel anti-TB agents. The peptide identifications and tandem mass spectra (MS/MS) have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD013621.
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