Evidence map›Paper›PMID 40287399›Full record

ReviewFEMS microbiology reviews2025

Molecular typing of Mycobacterium tuberculosis: a review of current methods, databases, softwares, and analytical tools.

David Couvin, Anne-Sophie Allaguy, Ayoub Ez-Zari, Tomasz Jagielski, Nalin Rastogi

Abstract readReview
In one paragraph

Review in FEMS microbiology reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
  6. Article
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  9. Article
  10. Beyond H37Rv:Frontiers in microbiology · 2025
    Review
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

5 authors.

David CouvinWHO Supranational TB Reference Laboratory-TB and Mycobacteria Unit, Institut Pasteur de la Guadeloupe, F-97139, Les Abymes, Guadeloupe, France.ORCID 0000-0002-7897-9023
Anne-Sophie AllaguyLaboratoire de Mathématiques Informatique et Applications (LAMIA), Université des Antilles, F-97154, Pointe-à-Pitre, Guadeloupe, France.
Ayoub Ez-ZariLaboratory of Biology and Health (UAE/U06FS), Department of Biology, Faculty of Science, Abdelmalek Essaâdi University, BP 2121, 93002 Tetouan, Morocco.
Tomasz JagielskiDepartment of Medical Microbiology, Institute of Microbiology, Faculty of Biology, University of Warsaw, I. Miecznikowa 1, 02-096 Warsaw, Poland.ORCID 0000-0001-9553-5742
Nalin RastogiWHO Supranational TB Reference Laboratory-TB and Mycobacteria Unit, Institut Pasteur de la Guadeloupe, F-97139, Les Abymes, Guadeloupe, France.ORCID 0000-0002-7199-7747

Funding

National Science Centre, Poland 2017/27/L/NZ6/03279
6 · The paper itself

Abstract

Studies on the epidemiology and clinical relevance of Mycobacterium tuberculosis complex (MTBC) have immensely benefited from molecular typing methods, associated software applications, and bioinformatics tools. Over the last two decades, the Pasteur Institute of Guadeloupe has developed a range of bioinformatic resources, including databases and software, to advance understanding of TB epidemiology. Traditional methods, such as IS6110-RFLP, MIRU-VNTR typing, and spoligotyping, have been instrumental but are increasingly supplanted by more precise and high-throughput techniques. These typing methods offer relatively good discrimination and reproducibility, making them popular choices for epidemiological studies. However, the advent of whole-genome sequencing (WGS) has revolutionized Mycobacterium tuberculosis complex (MTBC) typing, providing unparalleled resolution and data analysis depth. WGS enables the identification of single nucleotide polymorphisms and other genetic variations, facilitating robust phylogenetic reconstructions, and detailed outbreak investigations. This review summarizes current molecular typing methods, as well as databases and software tools used for MTBC data analysis. A comprehensive comparison of available tools and databases is provided to guide future research on the epidemiology of TB and pathogen-associated variables (drug resistance or virulence) and public health initiatives.

Indexed as

Molecular TypingMycobacterium tuberculosisTuberculosisComputational BiologyHumansSoftwaredatabasedrug resistanceepidemiologyfamilygenomicsgenotypinglineageMycobacterium tuberculosissoftwaretuberculosis

Identifiers

PMID40287399
PMCPMC12065434

What OpenQuestion 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 OpenQuestion graph.