Evidence map›Paper›PMID 39198827›Full record

ArticleAnnals of clinical microbiology and antimicrobials2024

Detection of multidrug-resistance in Mycobacterium tuberculosis by phenotype- and molecular-based assays.

Laima Vasiliauskaitė, Zofia Bakuła, Edita Vasiliauskienė, Daiva Bakonytė, Przemysław Decewicz, Mikołaj Dziurzyński, Małgorzata Proboszcz, Edita Valerija Davidavičienė, Birutė Nakčerienė, Rafał Krenke and 3 more

Abstract read
In one paragraph

Article in Annals of clinical microbiology and antimicrobials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

13 authors.

Laima VasiliauskaitėDepartment of Physiology, Biochemistry, Microbiology and Laboratory Medicine, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.
Zofia BakułaInstitute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
Edita VasiliauskienėDepartment of Physiology, Biochemistry, Microbiology and Laboratory Medicine, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.
Daiva BakonytėInstitute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
Przemysław DecewiczDepartment of Environmental Microbiology and Biotechnology, Institute of Microbiology, Faculty of Biology, University of Warsaw, Warsaw, Poland.
Mikołaj DziurzyńskiDepartment of Biology (DBIO), University of Florence, Florence, Italy.
Małgorzata ProboszczDepartment of Internal Medicine, Pulmonology, and Allergology, Warsaw Medical University, Warsaw, Poland.
Edita Valerija DavidavičienėDepartment of Programs and State Tuberculosis Information System, Vilnius University Hospital Santaros klinikos, Vilnius, Lithuania.
Birutė NakčerienėDepartment of Programs and State Tuberculosis Information System, Vilnius University Hospital Santaros klinikos, Vilnius, Lithuania.
Rafał KrenkeDepartment of Internal Medicine, Pulmonology, and Allergology, Warsaw Medical University, Warsaw, Poland.
Tomas KačergiusDepartment of Physiology, Biochemistry, Microbiology and Laboratory Medicine, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.
Petras StakėnasInstitute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
Tomasz JagielskiDepartment of Medical Microbiology, Institute of Microbiology, Faculty of Biology, University of Warsaw, Warsaw, Poland. t.jagielski@uw.edu.pl.

Funding

Lietuvos Mokslo Taryba S-LL-18-4Narodowe Centrum Nauki 2017/27/L/NZ6/03279
6 · The paper itself

Abstract

backgroundThe whole-genome sequencing (WGS) is becoming an increasingly effective tool for rapid and accurate detection of drug resistance in Mycobacterium tuberculosis complex (MTBC). This approach, however, has still been poorly evaluated on strains from Central and Eastern European countries. The purpose of this study was to assess the performance of WGS against conventional drug susceptibility testing (DST) for the detection of multi-drug resistant (MDR) phenotypes among MTBC clinical strains from Poland and Lithuania.

methodsThe study included 208 MTBC strains (130 MDR; 78 drug susceptible), recovered from as many tuberculosis patients in Lithuania and Poland between 2018 and 2021. Resistance to rifampicin (RIF) and isoniazid (INH) was assessed by Critical Concentration (CC) and Minimum Inhibitory Concentration (MIC) DST as well as molecular-based techniques, including line-probe assay (LPA) and WGS. The analysis of WGS results was performed using bioinformatic pipeline- and software-based tools.

resultsThe results obtained with the CC DST were more congruent with those by LPA compared to pipeline-based WGS. Software-based tools showed excellent concordance with pipeline-based analysis in prediction of RIF/INH resistance. The RIF-resistant strains demonstrated a relatively homogenous MIC distribution with the mode at the highest tested MIC value. The most frequent RIF-resistance conferring mutation was rpoB S450L. The mode MIC for INH was two-fold higher among double katG and inhA mutants than among single katG mutants. The overall rate of discordant results between all methods was calculated at 5.3%. Three strains had discordant results by both genotypic methods (LPA and pipeline-based WGS), one strain by LPA only, three strains by MIC DST, two strains by both MIC DST and pipeline-based WGS, and the remaining two strains showed discordant results with all three methods, compared to CC DST.

conclusionsConsidering MIC DST results, current CCs of the first-line anti-TB drugs might be inappropriately high and may need to be revised. Both molecular methods demonstrated 100% specificity, while pipeline-based WGS had slightly lower sensitivity for RIF and INH than LPA, compared to CC DST.

Indexed as

Antitubercular AgentsBacterial ProteinsDrug Resistance, Multiple, BacterialIsoniazidMicrobial Sensitivity TestsMycobacterium tuberculosisPhenotypeRifampinTuberculosis, Multidrug-ResistantWhole Genome SequencingCatalaseDNA-Directed RNA PolymerasesHumansLithuaniaMutationOxidoreductasesAntitubercular AgentsBacterial ProteinsCatalaseDNA-Directed RNA PolymerasesInhA protein, MycobacteriumIsoniazidkatG protein, Mycobacterium tuberculosisOxidoreductasesRifampinrpoB protein, Mycobacterium tuberculosisDrug susceptibility testingMDR-TBMinimum inhibitory concentrationWhole-genome sequencing

Identifiers

PMID39198827
PMCPMC11360294

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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.