Genomic signatures of pre-resistance in Mycobacterium tuberculosis.
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ABSTRACT:
SUBMITTER: Torres Ortiz A
PROVIDER: S-EPMC8674244 | biostudies-literature | 2021 Dec
REPOSITORIES: biostudies-literature
Publications
Genomic signatures of pre-resistance in Mycobacterium tuberculosis.
Torres Ortiz Arturo A Coronel Jorge J Vidal Julia Rios JR Bonilla Cesar C Moore David A J DAJ Gilman Robert H RH Balloux Francois F Kon Onn Min OM Didelot Xavier X Grandjean Louis L
Nature communications 20211215 1
Recent advances in bacterial whole-genome sequencing have resulted in a comprehensive catalog of antibiotic resistance genomic signatures in Mycobacterium tuberculosis. With a view to pre-empt the emergence of resistance, we hypothesized that pre-existing polymorphisms in susceptible genotypes (pre-resistance mutations) could increase the risk of becoming resistant in the future. We sequenced whole genomes from 3135 isolates sampled over a 17-year period. After reconstructing ancestral genomes o ...[more]
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Project description:Tuberculosis (TB) is the leading cause of death by an infectious disease, and global TB control efforts are increasingly threatened by drug resistance in Mycobacterium tuberculosis. Unlike most bacteria, where lateral gene transfer is an important mechanism of resistance acquisition, resistant M. tuberculosis arises solely by de novo chromosomal mutation. Using whole-genome sequencing data from two natural populations of M. tuberculosis, we characterized the population genetics of known drug resistance loci using measures of diversity, population differentiation, and convergent evolution. We found resistant subpopulations to be less diverse than susceptible subpopulations, consistent with ongoing transmission of resistant M. tuberculosis. A subset of resistance genes ("sloppy targets") were characterized by high diversity and multiple rare variants; we posit that a large genetic target for resistance and relaxation of purifying selection contribute to high diversity at these loci. For "tight targets" of selection, the path to resistance appeared narrower, evidenced by single favored mutations that arose numerous times in the phylogeny and segregated at markedly different frequencies in resistant and susceptible subpopulations. These results suggest that diverse genetic architectures underlie drug resistance in M. tuberculosis and that combined approaches are needed to identify causal mutations. Extrapolating from patterns observed for well-characterized genes, we identified novel candidate variants involved in resistance. The approach outlined here can be extended to identify resistance variants for new drugs, to investigate the genetic architecture of resistance, and when phenotypic data are available, to find candidate genetic loci underlying other positively selected traits in clonal bacteria. IMPORTANCEMycobacterium tuberculosis, the causative agent of tuberculosis (TB), is a significant burden on global health. Antibiotic treatment imposes strong selective pressure on M. tuberculosis populations. Identifying the mutations that cause drug resistance in M. tuberculosis is important for guiding TB treatment and halting the spread of drug resistance. Whole-genome sequencing (WGS) of M. tuberculosis isolates can be used to identify novel mutations mediating drug resistance and to predict resistance patterns faster than traditional methods of drug susceptibility testing. We have used WGS from natural populations of drug-resistant M. tuberculosis to characterize effects of selection for advantageous mutations on patterns of diversity at genes involved in drug resistance. The methods developed here can be used to identify novel advantageous mutations, including new resistance loci, in M. tuberculosis and other clonal pathogens.
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Project description:BackgroundMycobacterium tuberculosis complex (MTBC) species evolve slowly, so isolates from individuals linked in transmission often have identical or nearly identical genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared MTBC variation could help overcome this problem. Previous studies have reported MTBC diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear. Here, we aimed to quantify within-host MTBC variation and assess whether such information improves transmission inferences.MethodsWe conducted a retrospective genomic epidemiology study in which we reanalysed publicly available sequence data from household transmission studies published in PubMed from database inception until Jan 31, 2024, for which both genomic and epidemiological contact data were available, using household membership as a proxy for transmission linkage. We quantified minority variants (ie, positions with two or more alleles each supported by at least five-fold coverage and with a minor allele frequency of 1% or more) outside of PE and PPE genes, within individual samples and shared across samples. We used receiver operator characteristic (ROC) curves to compare the performance of a general linear model for household membership that included shared minority variants and one that included only fixed genetic differences.FindingsWe identified three MTBC household transmission studies with publicly available whole-genome sequencing data and epidemiological linkages: a household transmission study in Vitória, Brazil (Colangeli et al), a retrospective population-based study of paediatric tuberculosis in British Columbia, Canada (Guthrie et al), and a retrospective population-based study in Oxfordshire, England (Walker et al). We found moderate levels of minority variation present in MTBC sequence data from cultured isolates that varied significantly across studies: mean 168·6 minority variants (95% CI 151·4-185·9) for the Colangeli et al dataset, 5·8 (1·5-10·2) for Guthrie et al (p<0·0001, Wilcoxon rank sum test, vs Colangeli et al), and 7·1 (2·4-11·9) for Walker et al (p<0·0001, Wilcoxon rank sum test, vs Colangeli et al). Isolates from household pairs shared more minority variants than did randomly selected pairs of isolates: mean 97·7 shared minority variants (79·1-116·3) versus 9·8 (8·6-11·0) in Colangeli et al, 0·8 (0·1-1·5) versus 0·2 (0·1-0·2) in Guthrie et al, and 0·7 (0·1-1·3) versus 0·2 (0·2-0·2) in Walker et al (all p<0·0001, Wilcoxon rank sum test). Shared within-host variation was significantly associated with household membership (odds ratio 1·51 [95% CI 1·30-1·71], p<0·0001), for one standard deviation increase in shared minority variants. Models that included shared within-host variation versus models without within-host variation improved the accuracy of predicting household membership in all three studies: area under the ROC curve 0·95 versus 0·92 for the Colangeli et al study, 0·99 versus 0·95 for the Guthrie et al study, and 0·93 versus 0·91 for the Walker et al study.InterpretationWithin-host MTBC variation persists through culture of sputum and could enhance the resolution of transmission inferences. The substantial differences in minority variation recovered across studies highlight the need to optimise approaches to recover and incorporate within-host variation into automated phylogenetic and transmission inference.FundingNational Institutes of Health.
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