ArticlePloS one2016
Deep Whole-Genome Sequencing to Detect Mixed Infection of Mycobacterium tuberculosis.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods for Detecting Mycobacterial Mixed Strain Infections-A Systematic Review.Frontiers in genetics · 2020Pooled it
- Genome-targeted enrichment and sequencing of human-infecting Cryptosporidium spp.Nature communications · 2026Article
- A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission.Genome medicine · 2025Article
- Phylogenomic reconstruction ofbioRxiv : the preprint server for biology · 2024Article
- Whole-genome sequencing reveals transmission pattern and drug resistance ofFrontiers in cellular and infection microbiology · 2024Article
- Molecular investigations of Mycobacterium tuberculosis genotypes among baseline and follow-up strains circulating in four regions of Eswatini.BMC infectious diseases · 2023Article
- Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis.Microbiology spectrum · 2023Article
- Tuberculosis treatment failure associated with evolution of antibiotic resilience.Science (New York, N.Y.) · 2022Article
- Tracking the transition to agriculture in Southern Europe through ancient DNA analysis of dental calculus.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Whole-Genome Sequencing Analysis to Identify Infection with Multiple Species of Nontuberculous Mycobacteria.Pathogens (Basel, Switzerland) · 2021Article
- Challenges forGenes · 2021Review
- Article
- Analysis of Factors Influencing Multidrug-Resistant Tuberculosis and Validation of Whole-Genome Sequencing in Children with Drug-Resistant Tuberculosis.Infection and drug resistance · 2021Article
- Discordant line probe genotypic testing vs culture-based drug susceptibility phenotypic testing in TB endemic KwaZulu-Natal: Impact on bedside clinical decision making.Journal of clinical tuberculosis and other mycobacterial diseases · 2020Article
- Detection of mixed-strain infections by FACS and ultra-low input genome sequencing.Gut microbes · 2020Article
- Article
- QuantTB - a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data.BMC genomics · 2020Article
- Article
- Computational Methods for Strain-Level Microbial Detection in Colony and Metagenome Sequencing Data.Frontiers in microbiology · 2020Review
- Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues.Nature reviews. Microbiology · 2019Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mixed infection by multiple Mycobacterium tuberculosis (MTB) strains is associated with poor treatment outcome of tuberculosis (TB). Traditional genotyping methods have been used to detect mixed infections of MTB, however, their sensitivity and resolution are limited. Deep whole-genome sequencing (WGS) has been proved highly sensitive and discriminative for studying population heterogeneity of MTB. Here, we developed a phylogenetic-based method to detect MTB mixed infections using WGS data. We collected published WGS data of 782 global MTB strains from public database. We called homogeneous and heterogeneous single nucleotide variations (SNVs) of individual strains by mapping short reads to the ancestral MTB reference genome. We constructed a phylogenomic database based on 68,639 homogeneous SNVs of 652 MTB strains. Mixed infections were determined if multiple evolutionary paths were identified by mapping the SNVs of individual samples to the phylogenomic database. By simulation, our method could specifically detect mixed infections when the sequencing depth of minor strains was as low as 1× coverage, and when the genomic distance of two mixed strains was as small as 16 SNVs. By applying our methods to all 782 samples, we detected 47 mixed infections and 45 of them were caused by locally endemic strains. The results indicate that our method is highly sensitive and discriminative for identifying mixed infections from deep WGS data of MTB isolates.
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