ArticleBMC genomics2018
Identifying mixed Mycobacterium tuberculosis infections from whole genome sequence data.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.
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Who cites it
58 citing papers in PubMed, 2 syntheses or guidelines pooled it, 88 citations in OpenAlex.
- Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark.The Lancet. Microbe · 2021Pooled it
- Methods for Detecting Mycobacterial Mixed Strain Infections-A Systematic Review.Frontiers in genetics · 2020Pooled it
- Dormancy regulon reduction was pivotal to the evolution of Mycobacterium tuberculosis.Nature communications · 2026Article
- Heteroresistance inFrontiers in cellular and infection microbiology · 2026Review
- Article
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- Whole genome sequencing for tuberculosis disease species identification, lineage determination, and drug resistance detection in Kashgar prefecture, China.BMC infectious diseases · 2025Article
- Dissecting rifampicin heteroresistance inJournal of medical microbiology · 2025Article
- Quantifying prevalence and risk factors of HIV multiple infection in Uganda from population-based deep-sequence data.PLoS pathogens · 2025Article
- Demixer: a probabilistic generative model to delineate different strains of a microbial species in a mixed infection sample.Bioinformatics (Oxford, England) · 2025Article
- TBtypeR: Sensitive detection and sublineage classification of Mycobacterium tuberculosis complex mixed-strain infections.Communications biology · 2025Article
- A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission.Genome medicine · 2025Article
- Distribution and transmission of M. tuberculosis in a high-HIV prevalence city in Malawi: A genomic and spatial analysis.PLOS global public health · 2025Article
- Within-host population dynamics of extensively drug-resistantEvolution, medicine, and public health · 2025Article
- A pragmatic pipeline for drug resistance and lineage identification in Mycobacterium tuberculosis using whole genome sequencing.PLOS global public health · 2025Article
- Pulmonary Tuberculosis with Polyclonal Infection - Diagnostic Challenges and the Importance of Sequencing to the Improvement of Case Management - Case Report.Infection and drug resistance · 2025Article
- TGV: suite of tools to visualize transmission graphs.NAR genomics and bioinformatics · 2024Article
- SNP-slice resolves mixed infections: simultaneously unveiling strain haplotypes and linking them to hosts.Bioinformatics (Oxford, England) · 2024Article
- Genetic Characterization and Population Structure of Drug-ResistantAntibiotics (Basel, Switzerland) · 2024Article
- The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova.Nature communications · 2024Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 3 countries.
Funding
Abstract
backgroundMixed, polyclonal Mycobacterium tuberculosis infection occurs in natural populations. Developing an effective method for detecting such cases is important in measuring the success of treatment and reconstruction of transmission between patients. Using whole genome sequence (WGS) data, we assess two methods for detecting mixed infection: (i) a combination of the number of heterozygous sites and the proportion of heterozygous sites to total SNPs, and (ii) Bayesian model-based clustering of allele frequencies from sequencing reads at heterozygous sites.
resultsIn silico and in vitro artificially mixed and known pure M. tuberculosis samples were analysed to determine the specificity and sensitivity of each method. We found that both approaches were effective in distinguishing between pure strains and mixed infection where there was relatively high (> 10%) proportion of a minor strain in the mixture. A large dataset of clinical isolates (n = 1963) from the Karonga Prevention Study in Northern Malawi was tested to examine correlations with patient characteristics and outcomes with mixed infection. The frequency of mixed infection in the population was found to be around 10%, with an association with year of diagnosis, but no association with age, sex, HIV status or previous tuberculosis.
conclusionsMixed Mycobacterium tuberculosis infection was identified in silico using whole genome sequence data. The methods presented here can be applied to population-wide analyses of tuberculosis to estimate the frequency of mixed infection, and to identify individual cases of mixed infections. These cases are important when considering the evolution and transmission of the disease, and in patient treatment.
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Registered trials
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