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BackgroundBedaquiline (BDQ) is a novel agent approved for use in combination treatment of multi-drug resistant tuberculosis (MDR-TB). We sought to determine BDQ epidemiological cut-off values (ECVs), define and assess interpretive criteria against putative resistance associated variants (RAVs), microbiological outcomes and cross resistance with clofazimine (CFZ).MethodsA retrospective cohort study was conducted. Minimal inhibitory concentrations (MIC) to BDQ were determined using 7H9 broth microdilution (BMD) and MGIT960. RAVs were genetically characterised using whole genome sequencing. BDQ ECVs were determined using ECOFFinder and compared with 6-month culture conversion status and CFZ MICs.FindingsA total of 391 isolates were analysed. Susceptible and intermediate categories were determined to have MICs of ≤ 0.125 μg/ml and 0.25 μg/ml using BMD and ≤ 1 μg/ml and 2 μg/ml using MGIT960 respectively. Microbiological failures occurred among BDQ exposed patients with a non-susceptible BDQ MIC, an Rv0678 mutation and ≤ 2 active drug classes. The Rv0678 RAVs were not the dominant mechanism of CFZ resistance and cross resistance was limited to isolates with an Rv0678 mutation.InterpretationCriteria for BDQ susceptibility are defined and will facilitate improved early detection of resistance. Cross- resistance between BDQ and CFZ is an emerging concern but in this study was primarily among those with an Rv0678 mutation.

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Drug-resistant tuberculosis persists as a major public health concern. Alongside efficacious treatments, validated and standardized drug susceptibility testing (DST) is required to improve patient care. This multicountry, multilaboratory external quality assessment (EQA) study aimed to validate the sensitivity, specificity, and reproducibility of provisional bedaquiline MIC breakpoints and World Health Organization interim critical concentrations (CCs) for categorizing clinical Mycobacterium tuberculosis isolates as susceptible/resistant to the drug. Three methods were used: Middlebrook 7H11 agar proportion (AP) assay, broth microdilution (BMD) assay, and mycobacterial growth indicator tube (MGIT) assay. Each of the five laboratories tested the 40-isolate (20 unique isolates, duplicated) EQA panel at three time points. The study validated the sensitivity and specificity of a bedaquiline MIC susceptibility breakpoint of 0.12 μg/ml for the BMD method and WHO interim CCs of 1 μg/ml for MGIT and 0.25 μg/ml for the 7H11 AP methods. Categorical agreements between observed and expected results and sensitivities/specificities for correctly identifying an isolate as susceptible/resistant were highest at the 0.25, 0.12, and 1 μg/ml bedaquiline concentrations for the AP method, BMD (frozen or dry plates), and MGIT960, respectively. At these concentrations, the very major error rates for erroneously categorizing an isolate as susceptible when it was resistant were the lowest and within CLSI guidelines. The most highly reproducible bedaquiline DST methods were MGIT960 and BMD using dry plates. These findings validate the use of standardized DST methodologies and interpretative criteria to facilitate routine phenotypic bedaquiline DST and to monitor the emergence of bedaquiline resistance.

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN/dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap’s simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.