Evidence map›Paper›PMID 27903602›Full record

ArticleJournal of clinical microbiology2017

Whole-Genome Sequencing of Mycobacterium tuberculosis Provides Insight into the Evolution and Genetic Composition of Drug-Resistant Tuberculosis in Belarus.

Kurt R Wollenberg, Christopher A Desjardins, Aksana Zalutskaya, Vervara Slodovnikova, Andrew J Oler, Mariam Quiñones, Thomas Abeel, Sinead B Chapman, Michael Tartakovsky, Andrei Gabrielian and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of clinical microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
4.7field-weighted citation impact, top 5% of its field
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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 61 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Protein Architecture and Composition in Mycobacterium tuberculosis.Advances in experimental medicine and biology · 2026
    Review
  7. Article
  8. Article
  9. Review
  10. Large-scale Pan Genomic Analysis ofEvolutionary bioinformatics online · 2024
    Article
  11. Genomic Characterization of Drug-ResistantAntibiotics (Basel, Switzerland) · 2023
    Article
  12. Article
  13. Infection and drug resistance · 2023
    Article
  14. Combining Radiological and Genomic TB Portals Data for Drug Resistance Analysis.IEEE access : practical innovations, open solutions · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Low-Level Rifampin Resistance andJournal of clinical microbiology · 2021
    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

16 authors at 6 institutions in 3 countries.

Kurt R WollenbergOffice of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA.
Christopher A DesjardinsThe Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA.
Aksana ZalutskayaRepublican Scientific and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus.
Vervara SlodovnikovaRepublican Scientific and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus.
Andrew J OlerOffice of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA.
Mariam QuiñonesOffice of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA.
Thomas AbeelThe Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA.
Sinead B ChapmanThe Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA.
Michael TartakovskyOffice of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA.
Andrei GabrielianOffice of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA.
Sven HoffnerDepartment of Microbiology, The Public Health Agency of Sweden, Solna, Sweden.
Aliaksandr SkrahinBelarusian State Medical University, Minsk, Belarus.
Bruce W BirrenThe Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA.
Alexander RosenthalOffice of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA.
Alena SkrahinaRepublican Scientific and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus alena.skrahina@gmail.com aearl@broadinstitute.org.
Ashlee M EarlThe Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA alena.skrahina@gmail.com aearl@broadinstitute.org.
Broad Institute · USNational Institutes of Health · USRepublican Scientific and Practical Centre of Pulmonology and Tuberculosis · BYNational Institute of Allergy and Infectious Diseases · USBelarusian State Medical University · BYPublic Health Agency of Sweden · SE

Funding

Viral Genomics: evolution, spread, and host interactionsU19AI110818 · NIAID · BROAD INSTITUTE, INC. · PI NEAFSEY, DANIEL E · 2014 to 2024
$66.5M
NIAID NIH HHS HHSN272200900018CNIAID NIH HHS U19 AI110818
6 · The paper itself

Abstract

The emergence and spread of drug-resistant Mycobacterium tuberculosis (DR-TB) are critical global health issues. Eastern Europe has some of the highest incidences of DR-TB, particularly multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB. To better understand the genetic composition and evolution of MDR- and XDR-TB in the region, we sequenced and analyzed the genomes of 138 M. tuberculosis isolates from 97 patients sampled between 2010 and 2013 in Minsk, Belarus. MDR and XDR-TB isolates were significantly more likely to belong to the Beijing lineage than to the Euro-American lineage, and known resistance-conferring loci accounted for the majority of phenotypic resistance to first- and second-line drugs in MDR and XDR-TB. Using a phylogenomic approach, we estimated that the majority of MDR-TB was due to the recent transmission of already-resistant M. tuberculosis strains rather than repeated de novo evolution of resistance within patients, while XDR-TB was acquired through both routes. Longitudinal sampling of M. tuberculosis from 34 patients with treatment failure showed that most strains persisted genetically unchanged during treatment or acquired resistance to fluoroquinolones. HIV+ patients were significantly more likely to have multiple infections over time than HIV- patients, highlighting a specific need for careful infection control in these patients. These data provide a better understanding of the genomic composition, transmission, and evolution of MDR- and XDR-TB in Belarus and will enable improved diagnostics, treatment protocols, and prognostic decision-making.

Indexed as

Evolution, MolecularGenome, BacterialSequence Analysis, DNAAntitubercular AgentsDisease Transmission, InfectiousGenotypeHumansLongitudinal StudiesMolecular EpidemiologyMycobacterium tuberculosisRepublic of BelarusTuberculosis, Multidrug-ResistantAntitubercular AgentsBelarusextensively drug resistantmultidrug resistantMycobacterium tuberculosis

Identifiers

PMID27903602
PMCPMC5277515
OpenAlexW2558697996

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.