Literature DB >> 11795406

Molecular techniques in the diagnosis of Mycobacterium tuberculosis and the detection of drug resistance.

M Caws1, F A Drobniewski.   

Abstract

Early diagnosis of Mycobacterium tuberculosis disease is crucial in initiating treatment and interrupting the train of transmission. The increasing incidence of MDR TB worldwide has also placed emphasis on the need for early detection of drug resistance, particularly to isoniazid and rifampicin. Molecular diagnostic techniques and automated culture systems have reduced turnaround times in the modern mycobacteriology laboratory, and the continuing evaluation and development of such techniques is increasing the use of molecular technology in developed nations. Simple phenotypic methods for the detection of resistance to first-line drugs and genotypic kit-form assays for detection of rifampicin resistance have been developed that have become key tools in the containment of MDR TB.

Entities:  

Mesh:

Year:  2001        PMID: 11795406     DOI: 10.1111/j.1749-6632.2001.tb11371.x

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  11 in total

1.  Evaluation of a PCR-based universal heteroduplex generator assay as a tool for rapid detection of multidrug-resistant Mycobacterium tuberculosis in Peru.

Authors:  Holger Mayta; Robert H Gilman; Fanny Arenas; Teresa Valencia; Luz Caviedes; Sonia H Montenegro; Eduardo Ticona; Jaime Ortiz; Rosa Chumpitaz; Carlton A Evans; Diana L Williams
Journal:  J Clin Microbiol       Date:  2003-12       Impact factor: 5.948

2.  Rapid detection of isoniazid, rifampin, and ofloxacin resistance in Mycobacterium tuberculosis clinical isolates using high-resolution melting analysis.

Authors:  Xiaoyou Chen; Fanrong Kong; Qinning Wang; Chuanyou Li; Jianyuan Zhang; Gwendolyn L Gilbert
Journal:  J Clin Microbiol       Date:  2011-08-10       Impact factor: 5.948

3.  Utility of an in-house mycobacteriophage-based assay for rapid detection of rifampin resistance in Mycobacterium tuberculosis clinical isolates.

Authors:  N Galí; J Domínguez; S Blanco; C Prat; M D Quesada; L Matas; V Ausina
Journal:  J Clin Microbiol       Date:  2003-06       Impact factor: 5.948

4.  High-resolution melting curve analysis for rapid detection of rifampin resistance in Mycobacterium tuberculosis: a meta-analysis.

Authors:  Xiaomao Yin; Lei Zheng; Qinlan Liu; Li Lin; Xiumei Hu; Yanwei Hu; Qian Wang
Journal:  J Clin Microbiol       Date:  2013-07-24       Impact factor: 5.948

5.  Rapid direct detection of multiple rifampin and isoniazid resistance mutations in Mycobacterium tuberculosis in respiratory samples by real-time PCR.

Authors:  Mercedes Marín; Darío García de Viedma; María Jesús Ruíz-Serrano; Emilio Bouza
Journal:  Antimicrob Agents Chemother       Date:  2004-11       Impact factor: 5.191

6.  High-resolution melting curve analysis for rapid detection of rifampin and isoniazid resistance in Mycobacterium tuberculosis clinical isolates.

Authors:  Go Eun Choi; Sun Min Lee; Jongyoun Yi; Sang Hyun Hwang; Hyung Hoi Kim; Eun Yup Lee; Eun Hae Cho; Jee Hee Kim; Hwa-Jung Kim; Chulhun L Chang
Journal:  J Clin Microbiol       Date:  2010-09-15       Impact factor: 5.948

7.  A rifampin-hypersensitive mutant reveals differences between strains of Mycobacterium smegmatis and presence of a novel transposon, IS1623.

Authors:  David C Alexander; Joses R W Jones; Jun Liu
Journal:  Antimicrob Agents Chemother       Date:  2003-10       Impact factor: 5.191

8.  Investigation of the rpoB Mutations Causing Rifampin Resistance by Rapid Screening in Mycobacterium Tuberculosis in North-East of Iran.

Authors:  Amir Tajbakhsh; Faezeh Ghasemi; Seyedeh Zohre Mirbagheri; Mastoureh Momen Heravi; Mehdi Rezaee; Zahra Meshkat
Journal:  Iran J Pathol       Date:  2018-09-25

9.  Rapid molecular detection of rifampicin resistance facilitates early diagnosis and treatment of multi-drug resistant tuberculosis: case control study.

Authors:  Philly O'Riordan; Uli Schwab; Sarah Logan; Graham Cooke; Robert J Wilkinson; Robert N Davidson; Paul Bassett; Robert Wall; Geoffrey Pasvol; Katie L Flanagan
Journal:  PLoS One       Date:  2008-09-09       Impact factor: 3.240

10.  Machine learning reveals that Mycobacterium tuberculosis genotypes and anatomic disease site impacts drug resistance and disease transmission among patients with proven extra-pulmonary tuberculosis.

Authors:  Doctor B Sibandze; Beki T Magazi; Lesibana A Malinga; Nontuthuko E Maningi; Bong-Akee Shey; Jotam G Pasipanodya; Nontombi N Mbelle
Journal:  BMC Infect Dis       Date:  2020-07-31       Impact factor: 3.090

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