Literature DB >> 34116244

Development and Validation of Signature Sequence-Based PCR for Improved Molecular Diagnosis of Tuberculosis.

Neha Quadir1, Syed A Rahman2, Javeed Ahmad3, Ayan K Das4, Naresh Arora5, Javaid A Sheikh6, Neeraj K Gupta7, Prem Kapur8, Mridu Dudeja4, Seyed E Hasnain9, Nasreen Z Ehtesham10.   

Abstract

Reliable, fast, and affordable diagnosis for tuberculosis (TB) remains a challenge to reduce disease incidence in resource-poor countries. Tests based on nucleotide sequences that are signature to Mycobacterium tuberculosis have the potential to make a positive impact on case detection rates, which can eventually help control TB. Using extensive comparative bioinformatics approach, we mined the genome for M. tuberculosis-specific genes and identified four genes so-called signature sequence (SS). With <25% homology with other known genes/proteins of mycobacterial/nonmycobacterial origin in various databases, these SS genes are ideal targets for species-specific identification. Sputum from suspected patients was liquefied using novel complete liquefying reagent, and DNA was isolated. Samples from patients (n = 417), reporting to TB clinics at two different hospitals, which met our inclusion criteria, were collected for this study. A small number (n = 143) was used for initial standardization, and the remaining patient samples (n = 274) were evaluated by SS and compared with smear microscopy, GeneXpert, culture, and clinical outcome. An overwhelming sensitivity of 97.0%, significantly higher than GeneXpert (95.0%), was seen. SS could pick all smear-negative, but culture-positive samples, along with other culture-negative samples; some of the latter were declared clinically positive. Our results yielded superior sensitivity and specificity through conventional PCR.
Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2021        PMID: 34116244     DOI: 10.1016/j.jmoldx.2021.05.014

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  1 in total

1.  Learning from COVID-19 to tackle TB pandemic: From despair to hope.

Authors:  Javaid Ahmad Sheikh; Asrar Ahmad Malik; Neha Quadir; Nasreen Zafar Ehtesham; Seyed Ehtesham Hasnain
Journal:  Lancet Reg Health Southeast Asia       Date:  2022-05-12
  1 in total

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