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Multi-drug resistant Mycobacterium tuberculosis requires a complex antibiotic treatment program and poses a major threat to tuberculosis (TB) treatment outcomes. Resistance is mostly conferred by chromosomal single nucleotide polymorphisms, many of which are well characterized and catalogued. However, not all mutations have been mapped and novel mutations can emerge. Methods able to quickly predict the effects of such mutations are needed to complement the existing catalogues, thereby permitting the prescription of effective treatment for patients and preventing the further spread of resistant strains. Relative binding free energy (RBFE) calculations can rapidly predict the effects of mutations, but this approach has not been tested on large, complex proteins. We use RBFE calculations to predict the effects of seven M. tuberculosis RNA polymerase mutations on rifampicin susceptibility and five M. tuberculosis DNA gyrase mutations on moxifloxacin susceptibility. These mutations encompass a range of amino acid substitutions with known effects and include large steric perturbations and charged moieties. We find that moderate numbers (n=3-15) of short RBFE calculations can predict resistance in cases where the mutation results in a large change in the binding free energy, but that the method lacks discrimination in cases with either a small change in energy or that involve charged amino acids, due to the associated large magnitude of error. We investigate how this error may be decreased by analyzing the sources of error and the distributions of repeated measurements from the different components of the RBFE calculations.

9 páginas, 4 figuras, 1 tabla., Background: Molecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosiscomplex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. Methods: A candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: 15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: This first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes. Funding: UNITAID, Wellcome, MRC, BMGF., Unitaid, Wellcome Trust, UK Medical Research Council, and Bill and Melinda Gates Foundation

The Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) presents here a compendium of 15,211 Mycobacterium tuberculosis global clinical isolates, all of which have undergone whole genome sequencing (WGS) and have had their minimum inhibitory concentrations to 13 antitubercular drugs measured in a single assay. It is the largest matched phenotypic and genotypic dataset for M. tuberculosis to date. Here, we provide a summary detailing the breadth of data collected, along with a description of how the isolates were collected and uniformly processed in CRyPTIC partner laboratories across 23 countries. The compendium contains 6,814 isolates resistant to at least one drug, including 2,129 samples that fully satisfy the clinical definitions of rifampicin resistant (RR), multi-drug resistant (MDR), pre-extensively drug resistant (pre-XDR) or extensively drug resistant (XDR). Accurate prediction of resistance status (sensitive/resistant) to eight antitubercular drugs by using a genetic mutation catalogue is presented along with the presence of suspected resistance-conferring mutations for isolates resistant to the newly introduced drugs bedaquiline, clofazimine, delamanid and linezolid. Finally, a case study of rifampicin mono-resistance demonstrates how this compendium could be used to advance our genetic understanding of rare resistance phenotypes. The compendium is fully open-source and it is hoped that the dataset will facilitate and inspire future research for years to come.