Multiple first- and second-line drugs are available for the treatment of tuberculosis (TB) caused by the bacterium Mycobacterium tuberculosis (M.tb). However, complex and lengthy treatment regimens result in poor adherence, leading to the emergence of drug-resistant infections (DR-TB). M.tb is intrinsically resistant to β-lactams hence this low-cost and easy-to-administer drug class is not commonly used for treatment, but recent evidence showing that some M.tb from DR-TB infections have developed β-lactam susceptibility has renewed interest in treatment strategies that incorporate β-lactams.

With the aim of identifying drug target combinations, we overlaid 111 β-lactam-associated genes identified through literature searches and with Watson for Drug Discovery onto protein-protein interaction and gene regulatory networks of M.tb, to characterise the association between network regions involved in susceptibility to β-lactams and resistance to 8 first- and second-line drugs.

We found that genes associated with β-lactam susceptibility formed a cluster that was highly connected to genes involved in resistance to first- and second-line drugs and their compensatory mechanisms, suggesting a high degree of crosstalk. To identify key genes in the information flow between these two network regions, we performed random walks and selected pairs of genes belonging to both classes with the largest pairwise influence. The knockdown of these genes was found to consistently lead to growth inhibition in an in silico metabolomic and regulatory model of M.tb, suggesting that combining β-lactams with first- and second-line drugs that target these genes is a possible treatment option.

In this study we used network analysis and regulatory models to identify possible drug targets for novel combination therapy for TB that include the low-cost β-lactam class of drugs. Our approach could also be extended to other drug classes and pathogens.