Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs.Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance.Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first-and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool. Measurements and Main Results:The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci.Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.

This systematic review highlights those mutations that have been shown to causally change phenotypic resistance in M. tuberculosis and brings attention to a notable lack of allelic exchange data for several of the genes known to be associated with drug resistance.

BackgroundMeningitis is the most severe manifestation of tuberculosis. It is largely unknown why some people develop pulmonary TB (PTB) and others TB meningitis (TBM); we examined if the genetic background of infecting M. tuberculosis strains may be relevant.MethodsWe whole-genome sequenced M. tuberculosis strains isolated from 322 HIV-negative tuberculosis patients from Indonesia and compared isolates from patients with TBM (n = 106) and PTB (n = 216). Using a phylogeny-adjusted genome-wide association method to count homoplasy events we examined phenotype-related changes at specific loci or genes in parallel branches of the phylogenetic tree. Enrichment scores for the TB phenotype were calculated on single nucleotide polymorphism (SNP), gene, and pathway level. Genetic associations were validated in an independent set of isolates.ResultsStrains belonged to the East-Asian lineage (36.0%), Euro-American lineage (61.5%), and Indo-Oceanic lineage (2.5%). We found no association between lineage and phenotype (Chi-square = 4.556; p = 0.207). Large genomic differences were observed between isolates; the minimum pairwise genetic distance varied from 17 to 689 SNPs. Using the phylogenetic tree, based on 28,544 common variable positions, we selected 54 TBM and 54 PTB isolates in terminal branch sets with distinct phenotypes. Genetic variation in Rv0218, and absence of Rv3343c, and nanK were significantly associated with disease phenotype in these terminal branch sets, and confirmed in the validation set of 214 unpaired isolates.ConclusionsUsing homoplasy counting we identified genetic variation in three separate genes to be associated with the TB phenotype, including one (Rv0218) which encodes a secreted protein that could play a role in host-pathogen interaction by altering pathogen recognition or acting as virulence effector.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4498-z) contains supplementary material, which is available to authorized users.