Using a Label Free Quantitative Proteomics Approach to Identify Changes in Protein Abundance in Multidrug-Resistant Mycobacterium tuberculosis

Abstract

Reports in recent years indicate that the increasing emergence of resistance to drugs be using to TB treatment. The resistance to them severely affects to options for effective treatment. The emergence of multidrug-resistant tuberculosis has increased interest in understanding the mechanism of drug resistance in M. tuberculosis and the development of new therapeutics, diagnostics and vaccines. In this study, a label-free quantitative proteomics approach has been used to analyze proteome of multidrug-resistant and susceptible clinical isolates of M. tuberculosis and identify differences in protein abundance between the two groups. With this approach, we were able to identify a total of 1,583 proteins. The majority of identified proteins have predicted roles in lipid metabolism, intermediary metabolism, cell wall and cell processes. Comparative analysis revealed that 68 proteins identified by at least two peptides showed significant differences of at least twofolds in relative abundance between two groups. In all protein differences, the increase of some considering proteins such as NADH dehydrogenase, probable aldehyde dehydrogenase, cyclopropane mycolic acid synthase 3, probable arabinosyltransferase A, putative lipoprotein, uncharacterized oxidoreductase and six membrane proteins in resistant isolates might be involved in the drug resistance and to be potential diagnostic protein targets. The decrease in abundance of proteins related to secretion system and immunogenicity (ESAT-6-like proteins, ESX-1 secretion system associated proteins, O-antigen export system and MPT63) in the multidrug-resistant strains can be a defensive mechanism undertaken by the resistant cell.

Keywords: Label-free quantitation; Liquid chromatography mass spectrometry; Multidrug-resistance; Mycobacterium tuberculosis; Tuberculosis (TB).

Fig. 1

Functional assignment of proteins in M. tuberculosis identified by LC–MS/MS. Proteins were assigned to functional categories based on the TubercuList database. The pie charts (a) and (b) represent the distribution of all identified M. tuberculosis proteins and predicted membrane proteins respectively according to functional categories in percentage. Numbers in parenthesis indicate the number of proteins among total and membrane proteins respectively in each category

Fig. 2

Characteristics of proteins with different abundances (higher and lower abundant proteins) in susceptible and resistant M. tuberculosis isolates. These physiochemical properties of identified proteins were determined based on databases as mentioned in the text