Evidence map›Paper›PMID 33054726›Full record

ArticleBMC infectious diseases2020

Detection of Beijing strains of MDR M. tuberculosis and their association with drug resistance mutations in katG, rpoB, and embB genes.

Anamika Gupta, Pallavi Sinha, Vijay Nema, Pramod K Gupta, Pampi Chakraborty, Savita Kulkarni, Nalin Rastogi, Shampa Anupurba

Abstract read
In one paragraph

Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
–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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Patterns ofFrontiers in tuberculosis · 2025
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  10. Prevalence and Characterization ofPathogens (Basel, Switzerland) · 2023
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  14. Snapshot ofGenes · 2022
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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

8 authors.

Anamika GuptaDepartment of Microbiology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221 005, India.
Pallavi SinhaDepartment of Microbiology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221 005, India.
Vijay NemaDivision of Molecular Biology, National AIDS Research Institute, 73 G MIDC Bhosari, Pune, 411026, India.
Pramod K GuptaLaboratory Nuclear Medicine Section, Isotope Group, Bhabha Atomic Research Centre C/o T.M.H. Annexe, Parel, Mumbai, 400012, India.
Pampi ChakrabortyLaboratory Nuclear Medicine Section, Isotope Group, Bhabha Atomic Research Centre C/o T.M.H. Annexe, Parel, Mumbai, 400012, India.
Savita KulkarniLaboratory Nuclear Medicine Section, Isotope Group, Bhabha Atomic Research Centre C/o T.M.H. Annexe, Parel, Mumbai, 400012, India.
Nalin RastogiWHO Supranational TB Reference Laboratory, TB & Mycobacteria Unit, Institute Pasteur de Guadeloupe, Abymes, Guadeloupe, France.
Shampa AnupurbaDepartment of Microbiology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221 005, India. shampa_anupurba@yahoo.co.in.ORCID http://orcid.org/0000-0002-3530-1116

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMolecular epidemiological studies of Mycobacterium tuberculosis (MTB) are the core of current research to find out the association of the M. tuberculosis genotypes with its outbreak and transmission. The high prevalence of the Beijing genotype strain among multidrug resistance (MDR) TB has already been reported in various studies around India. The overall objective of this study was to detect the prevalence of Beijing genotype strains of MDR M. tuberculosis and their association with the clinical characteristics of TB patients.

methodsIn this study 381 M. tuberculosis clinical isolates were obtained from sputum samples from 2008 to 2014. The multiplex-PCR and Spoligotyping (n = 131) methods were used to investigate the prevalence of the Beijing genotype strain by targeting the Rv2820 gene and their association with drug resistance and clinical characteristics of TB patients. The drug susceptibility testing of first-line anti-TB drugs was performed by using the proportion method and MGIT960. A collection of isolates having Beijing and non-Beijing strains were also characterized to see if Beijing genotype strains had a higher rate of mutations at codons 516, 526 and 531 of the 81-bp region of the rpoB gene, codon 315 of the katG gene, and codon 306 of the embB gene.

resultsThe sensitivities and specificities of multiplex-PCR assay compared to that of standard Spoligotyping was detected to be 100%. Further, we observe that the multi drug-resistance was significantly associated with Beijing genotype strains (p = 0.03) and a strong correlation between Beijing genotype strains and specific resistance mutations at the katG315, rpoB531, and embB306 codons (p = < 0.0001, < 0.0001 & 0.0014 respectively) was also found.

conclusionsThis rapid, simple, and cost-effective multiplex PCR assay can effectively be used for monitoring the prevalence of Beijing genotype strains in low resource settings. Findings of this study may provide a scientific basis for the development of new diagnostic tools for detection and effective management of DR-TB in countries with a higher incidence rate of Beijing genotype strains.

Indexed as

AdolescentAdultAgedAged, 80 and overAntitubercular AgentsBacterial ProteinsCatalaseChildDNA-Directed RNA PolymerasesDrug Resistance, Multiple, BacterialFemaleGenotypeHumansIndiaMaleMicrobial Sensitivity TestsAntitubercular AgentsBacterial ProteinsCatalaseDNA-Directed RNA PolymerasesEmbB protein, Mycobacterium tuberculosiskatG protein, Mycobacterium tuberculosisPentosyltransferasesrpoB protein, Mycobacterium tuberculosisBeijing genotypeDrug resistant-TBRv2820SpoligotypingTransmissionTuberculosis

Identifiers

PMID33054726
PMCPMC7557036

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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.