Evidence map›Paper›PMID 26154264›Full record

ArticlePloS one2015

Genomics and Machine Learning for Taxonomy Consensus: The Mycobacterium tuberculosis Complex Paradigm.

Jérôme Azé, Christophe Sola, Jian Zhang, Florian Lafosse-Marin, Memona Yasmin, Rubina Siddiqui, Kristin Kremer, Dick van Soolingen, Guislaine Refrégier

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Genotypic diversity ofIranian journal of microbiology · 2025
    Article
  2. Review
  3. Article
  4. Genetic diversities ofAccess microbiology · 2024
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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 · 2019
    Article
  13. Article
  14. Article
  15. Genetic characterization ofInfection and drug resistance · 2018
    Article
  16. Article
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jérôme AzéLIRMM UM CNRS, UMR 5506, 860 rue de St Priest, 34095 Montpellier cedex 5, France.
Christophe SolaInstitute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Sud, rue Gregor Mendel, Bât 400, 91405 Orsay cedex, France.
Jian ZhangInstitute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Sud, rue Gregor Mendel, Bât 400, 91405 Orsay cedex, France.
Florian Lafosse-MarinInstitute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Sud, rue Gregor Mendel, Bât 400, 91405 Orsay cedex, France.
Memona YasminPakistan Institute for Engineering and Applied Sciences (PIEAS), Lehtrar Road, Nilore, Islamabad, Pakistan; Health Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), P.O. Box # 577, Jhang Road, Faisalabad, Pakistan.
Rubina SiddiquiHealth Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), P.O. Box # 577, Jhang Road, Faisalabad, Pakistan.
Kristin KremerNational Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands.
Dick van SoolingenNational Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands; Department of Pulmonary Diseases and Department of Microbiology, Radbout University Nijmegen Medical Centre, University Lung Centre Dekkerswald, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
Guislaine RefrégierInstitute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Sud, rue Gregor Mendel, Bât 400, 91405 Orsay cedex, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

GenomicsMachine LearningAlgorithmsBacterial Typing TechniquesCluster AnalysisComputational BiologyDatabases, GeneticDNA, BacterialGenotypeInternetMolecular EpidemiologyMycobacterium tuberculosisPolymerase Chain ReactionPolymorphism, Restriction Fragment LengthPolymorphism, Single NucleotidePrevalenceDNA, Bacterial

Identifiers

PMID26154264
PMCPMC4496040

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.