ArticlePloS one2015
Genomics and Machine Learning for Taxonomy Consensus: The Mycobacterium tuberculosis Complex Paradigm.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Genotypic diversity ofIranian journal of microbiology · 2025Article
- Artificial Intelligence in Bacterial Infections Control: A Scoping Review.Antibiotics (Basel, Switzerland) · 2025Review
- Performance of the T-SPOT.TB test in patients with indeterminate QuantiFERON-TB Gold Plus results: proposal for an algorithm for the diagnosis of Latent Tuberculosis Infection.Le infezioni in medicina · 2024Article
- Genetic diversities ofAccess microbiology · 2024Article
- The shortcut of mycobacterial interspersed repetitive unit-variable number tandem repeat typing forFrontiers in microbiology · 2022Article
- CRISPRbuilder-TB: "CRISPR-builder for tuberculosis". Exhaustive reconstruction of the CRISPR locus in mycobacterium tuberculosis complex using SRA.PLoS computational biology · 2021Article
- Molecular epidemiology of Mycobacterium tuberculosis in Brazil before the whole genome sequencing era: a literature review.Memorias do Instituto Oswaldo Cruz · 2021Review
- Novel methods included in SpolLineages tool for fast and precise prediction of Mycobacterium tuberculosis complex spoligotype families.Database : the journal of biological databases and curation · 2020Article
- A guide to machine learning for bacterial host attribution using genome sequence data.Microbial genomics · 2019Article
- Enhancing the differentiation of specific genotypes in Mycobacterium tuberculosis population.Scientific reports · 2019Article
- Diversity of Mycobacterium tuberculosis in the Middle Fly District of Western Province, Papua New Guinea: microbead-based spoligotyping using DNA from Ziehl-Neelsen-stained microscopy preparations.Scientific reports · 2019Article
- Towards better prediction of Mycobacterium tuberculosis lineages from MIRU-VNTR data.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2019Article
- Simplified Model to Survey Tuberculosis Transmission in Countries Without Systematic Molecular Epidemiology Programs.Emerging infectious diseases · 2019Article
- Universal genotyping reveals province-level differences in the molecular epidemiology of tuberculosis.PloS one · 2019Article
- Genetic characterization ofInfection and drug resistance · 2018Article
- Systematic evaluation of supervised classifiers for fecal microbiota-based prediction of colorectal cancer.Oncotarget · 2017Article
- Optimizing and accelerating the assignation of lineages in Mycobacterium tuberculosis using novel alternative single-tube assays.PloS one · 2017Article
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9 authors.
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Abstract
Infra-species taxonomy is a prerequisite to compare features such as virulence in different pathogen lineages. Mycobacterium tuberculosis complex taxonomy has rapidly evolved in the last 20 years through intensive clinical isolation, advances in sequencing and in the description of fast-evolving loci (CRISPR and MIRU-VNTR). On-line tools to describe new isolates have been set up based on known diversity either on CRISPRs (also known as spoligotypes) or on MIRU-VNTR profiles. The underlying taxonomies are largely concordant but use different names and offer different depths. The objectives of this study were 1) to explicit the consensus that exists between the alternative taxonomies, and 2) to provide an on-line tool to ease classification of new isolates. Genotyping (24-VNTR, 43-spacers spoligotypes, IS6110-RFLP) was undertaken for 3,454 clinical isolates from the Netherlands (2004-2008). The resulting database was enlarged with African isolates to include most human tuberculosis diversity. Assignations were obtained using TB-Lineage, MIRU-VNTRPlus, SITVITWEB and an algorithm from Borile et al. By identifying the recurrent concordances between the alternative taxonomies, we proposed a consensus including 22 sublineages. Original and consensus assignations of the all isolates from the database were subsequently implemented into an ensemble learning approach based on Machine Learning tool Weka to derive a classification scheme. All assignations were reproduced with very good sensibilities and specificities. When applied to independent datasets, it was able to suggest new sublineages such as pseudo-Beijing. This Lineage Prediction tool, efficient on 15-MIRU, 24-VNTR and spoligotype data is available on the web interface "TBminer." Another section of this website helps summarizing key molecular epidemiological data, easing tuberculosis surveillance. Altogether, we successfully used Machine Learning on a large dataset to set up and make available the first consensual taxonomy for human Mycobacterium tuberculosis complex. Additional developments using SNPs will help stabilizing it.
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