Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

Abstract

BackgroundCombating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance.MethodsTo investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods.ResultsThe analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites.ConclusionsUsing the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0575-9) contains supplementary material, which is available to authorized users.

The variability and reproducibility of whole genome sequencing technology for detecting resistance to anti-tuberculous drugs

“…This is critical in XDR-TB and resistance beyond XDR-TB where use of drugs like PAS may make the difference in providing a life-saving effective regimen of at least five drugs [29]. Large deletions and other structural variants may be detected by applying a combination of complementary approaches (pair-end, split-read and depth of coverage) followed by a validation process involving de novo assembly of bordering reads and re-alignment to the reference genome [10, 16, 24]. However, high genome-wide sequence coverage is necessary to perform such analyses.…”

“…For the bioinformatic analysis we used a previously reported pipeline [10, 15, 16]. Unless stated otherwise, software was run at default settings.…”

Primary Clofazimine and Bedaquiline Resistance among Isolates from Patients with Multidrug-Resistant Tuberculosis

“…Rv1979c is associated with isoniazid (INH) resistance (27). Mutations of Rv1979c were found in in vitro-selected clofazimine-resistant isolates without Rv0678 mutations (11).…”

The epidemiology, pathogenesis, transmission, diagnosis, and management of multidrug-resistant, extensively drug-resistant, and incurable tuberculosis

“…An example is the common first-line drug rifampicin, in which changes in the conformation of the drug binding site cause highlevel resistance, but mutations at sites outside of that region result in lower MICs. 262 Similarly, mutations in inhA typically confer low-level resistance to isoniazid, whereas katG mutations confer high-level resistance. 263 Mutation analysis also offers some advantages in differentiating susceptibilities to closely related drugs; cross-resistance in drug families is common, but not universal.…”