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BACKGROUND: The antibiotic bedaquiline is a key component of new WHO regimens for drug-resistant tuberculosis; however, predicting bedaquiline resistance from bacterial genotypes remains challenging. We aimed to understand the genetic mechanisms of bedaquiline resistance by analysing Mycobacterium tuberculosis isolates from South Africa. METHODS: For this genomic analysis, we conducted whole-genome sequencing of Mycobacterium tuberculosis samples collected at two referral laboratories in Cape Town and Johannesburg, covering regions of South Africa with a high prevalence of tuberculosis. We used the tool ARIBA to measure the status of predefined genes that are associated with bedaquiline resistance. To produce a broad genetic landscape of M tuberculosis in South Africa, we extended our analysis to include all publicly available isolates from the European Nucleotide Archive, including isolates obtained by the CRyPTIC consortium, for which minimum inhibitory concentrations of bedaquiline were available. FINDINGS: Between Jan 10, 2019, and July, 22, 2020, we sequenced 505 M tuberculosis isolates from 461 patients. Of the 64 isolates with mutations within the mmpR5 regulatory gene, we found 53 (83%) had independent acquisition of 31 different mutations, with a particular enrichment of truncated MmpR5 in bedaquiline-resistant isolates resulting from either frameshift mutations or the introduction of an insertion element. Truncation occurred across three M tuberculosis lineages, and were present in 66% of bedaquiline-resistant isolates. Although the distributions overlapped, the median minimum inhibitory concentration of bedaquiline was 0·25 mg/L (IQR 0·12-0·25) in mmpR5-disrupted isolates, compared with 0·06 mg/L (0·03-0·06) in wild-type M tuberculosis. INTERPRETATION: Reduction in the susceptibility of M tuberculosis to bedaquiline has evolved repeatedly across the phylogeny. In our data, we see no evidence that this reduction has led to the spread of a successful strain in South Africa. Binary phenotyping based on the bedaquiline breakpoint might be inappropriate to monitor resistance to this drug. We recommend the use of minimum inhibitory concentrations in addition to MmpR5 truncation screening to identify moderate increases in resistance to bedaquiline. FUNDING: US Centers for Disease Control and Prevention.
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Outbreak strains of Mycobacterium tuberculosis are promising candidates as targets in the search for intrinsic determinants of transmissibility, as they are responsible for many cases with sustained transmission; however, the use of low-resolution typing methods and restricted geographical investigations represent flaws in assessing the success of long-lived outbreak strains. We can now address the nature of outbreak strains by combining large genomic data sets and phylodynamic approaches. We retrospectively sequenced the whole genome of representative samples assigned to an outbreak circulating in the Canary Islands (the GC strain) since 1993, which accounts for ~20% of local tuberculosis cases. We selected a panel of specific single nucleotide polymorphism (SNP) markers for an in-silico search for additional outbreak-related sequences within publicly available tuberculosis genomic data. Using this information, we inferred the origin, spread, and epidemiological parameters of the GC strain. Our approach allowed us to accurately trace the historical and more recent dispersion of the GC strain. We provide evidence of a highly successful nature within the Canarian archipelago but limited expansion abroad. Estimation of epidemiological parameters from genomic data disagree with a distinctive biology of the GC strain. With the increasing availability of genomic data allowing for the accurate inference of strain spread and critical epidemiological parameters, we can now revisit the link between Mycobacterium tuberculosis genotypes and transmission, as is routinely carried out for SARS-CoV-2 variants of concern. We demonstrate that social determinants rather than intrinsically higher bacterial transmissibility better explain the success of the GC strain. Importantly, our approach can be used to trace and characterize strains of interest worldwide. IMPORTANCE Infectious disease outbreaks represent a significant problem for public health. Tracing outbreak expansion and understanding the main factors behind emergence and persistence remain critical to effective disease control. Our study allows researchers and public health authorities to use Whole-Genome Sequencing-based methods to trace outbreaks, and shows how available epidemiological information helps to evaluate the factors underpinning outbreak persistence. Taking advantage of all the freely available information placed in public repositories, researchers can accurately establish the expansion of an outbreak beyond original boundaries, and determine the potential risk of a strain to inform health authorities which, in turn, can define target strategies to mitigate expansion and persistence. Finally, we show the need to evaluate strain transmissibility in different geographic contexts to unequivocally associate spread to local or pathogenic factors, an important lesson taken from genomic surveillance of SARS-CoV-2.
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Two billion people are infected with Mycobacterium tuberculosis, leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations. Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data. We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.