Literature DB >> 31645373

Genotyping of Mycobacterium tuberculosis Rifampin Resistance-Associated Mutations by Use of Data from Xpert MTB/RIF Ultra Enables Large-Scale Tuberculosis Molecular Epidemiology Studies.

Brian Weinrick1.   

Abstract

Molecular epidemiology studies of tuberculosis have been empowered in recent years by the availability of whole-genome sequencing, which has allowed a new focus on the adaptive significance of drug resistance mutations. Genome sequencing technology remains expensive, however, limiting the potential for larger studies. Conversely, during this same time the GeneXpert molecular diagnostic method has been deployed globally and now serves as a cornerstone of tuberculosis diagnosis and drug sensitivity testing. In this issue, Y. Cao, H. Parmar, A. M. Simmons, D. Kale, et al. (J Clin Microbiol 57:e00907-19, 2019, https://doi.org/10.1128/JCM.00907-19) report the development of an algorithm that can use high-resolution melting temperature data generated in the course of analysis using the next-generation Xpert MTB/RIF Ultra assay to accurately genotype rifampin resistance-associated mutations. When paired with a system to aggregate data from diagnostic laboratories, this technique has the potential to enable studies on the global scale of the epidemiology of tuberculosis drug resistance.
Copyright © 2019 American Society for Microbiology.

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Year:  2019        PMID: 31645373      PMCID: PMC6935915          DOI: 10.1128/JCM.01504-19

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  12 in total

1.  Treatment of tuberculosis with streptomycin; a summary of observations on one hundred cases.

Authors:  H C HINSHAW; W H FELDMAN; K H PFUETZE
Journal:  J Am Med Assoc       Date:  1946-11-30

2.  Automatic Identification of Individual rpoB Gene Mutations Responsible for Rifampin Resistance in Mycobacterium tuberculosis by Use of Melting Temperature Signatures Generated by the Xpert MTB/RIF Ultra Assay.

Authors:  Yuan Cao; Heta Parmar; Ann Marie Simmons; Devika Kale; Kristy Tong; Deanna Lieu; David Persing; Robert Kwiatkowski; David Alland; Soumitesh Chakravorty
Journal:  J Clin Microbiol       Date:  2019-12-23       Impact factor: 5.948

3.  Connectivity of diagnostic technologies: improving surveillance and accelerating tuberculosis elimination.

Authors:  E Andre; C Isaacs; D Affolabi; R Alagna; D Brockmann; B C de Jong; E Cambau; G Churchyard; T Cohen; M Delmee; J-C Delvenne; M Farhat; A Habib; P Holme; S Keshavjee; A Khan; P Lightfoot; D Moore; Y Moreno; Y Mundade; M Pai; S Patel; A U Nyaruhirira; L E C Rocha; J Takle; A Trébucq; J Creswell; C Boehme
Journal:  Int J Tuberc Lung Dis       Date:  2016-08       Impact factor: 2.373

4.  Rapid detection of Mycobacterium tuberculosis and rifampin resistance by use of on-demand, near-patient technology.

Authors:  Danica Helb; Martin Jones; Elizabeth Story; Catharina Boehme; Ellen Wallace; Ken Ho; JoAnn Kop; Michelle R Owens; Richard Rodgers; Padmapriya Banada; Hassan Safi; Robert Blakemore; N T Ngoc Lan; Edward C Jones-López; Michael Levi; Michele Burday; Irene Ayakaka; Roy D Mugerwa; Bill McMillan; Emily Winn-Deen; Lee Christel; Peter Dailey; Mark D Perkins; David H Persing; David Alland
Journal:  J Clin Microbiol       Date:  2009-10-28       Impact factor: 5.948

5.  Fluorometric assay for testing rifampin susceptibility of Mycobacterium tuberculosis complex.

Authors:  K G P Hoek; N C Gey van Pittius; H Moolman-Smook; K Carelse-Tofa; A Jordaan; G D van der Spuy; E Streicher; T C Victor; P D van Helden; R M Warren
Journal:  J Clin Microbiol       Date:  2008-02-27       Impact factor: 5.948

6.  Large-scale whole genome sequencing of M. tuberculosis provides insights into transmission in a high prevalence area.

Authors:  J A Guerra-Assunção; A C Crampin; R M G J Houben; T Mzembe; K Mallard; F Coll; P Khan; L Banda; A Chiwaya; R P A Pereira; R McNerney; P E M Fine; J Parkhill; T G Clark; J R Glynn
Journal:  Elife       Date:  2015-03-03       Impact factor: 8.140

7.  Xpert Ultra Can Unambiguously Identify Specific Rifampin Resistance-Conferring Mutations.

Authors:  Emmanuel André; Bouke C de Jong; Kamela C S Ng; Armand van Deun; Conor J Meehan; Gabriela Torrea; Michèle Driesen; Siemon Gabriëls; Leen Rigouts
Journal:  J Clin Microbiol       Date:  2018-08-27       Impact factor: 5.948

8.  Evolution and transmission of drug-resistant tuberculosis in a Russian population.

Authors:  Nicola Casali; Vladyslav Nikolayevskyy; Yanina Balabanova; Simon R Harris; Olga Ignatyeva; Irina Kontsevaya; Jukka Corander; Josephine Bryant; Julian Parkhill; Sergey Nejentsev; Rolf D Horstmann; Timothy Brown; Francis Drobniewski
Journal:  Nat Genet       Date:  2014-01-26       Impact factor: 38.330

9.  The New Xpert MTB/RIF Ultra: Improving Detection of Mycobacterium tuberculosis and Resistance to Rifampin in an Assay Suitable for Point-of-Care Testing.

Authors:  Soumitesh Chakravorty; Ann Marie Simmons; Mazhgan Rowneki; Heta Parmar; Yuan Cao; Jamie Ryan; Padmapriya P Banada; Srinidhi Deshpande; Shubhada Shenai; Alexander Gall; Jennifer Glass; Barry Krieswirth; Samuel G Schumacher; Pamela Nabeta; Nestani Tukvadze; Camilla Rodrigues; Alena Skrahina; Elisa Tagliani; Daniela M Cirillo; Amy Davidow; Claudia M Denkinger; David Persing; Robert Kwiatkowski; Martin Jones; David Alland
Journal:  mBio       Date:  2017-08-29       Impact factor: 7.867

10.  Potential Application of Digitally Linked Tuberculosis Diagnostics for Real-Time Surveillance of Drug-Resistant Tuberculosis Transmission: Validation and Analysis of Test Results.

Authors:  Kamela Charmaine Ng; Conor Joseph Meehan; Gabriela Torrea; Léonie Goeminne; Maren Diels; Leen Rigouts; Bouke Catherine de Jong; Emmanuel André
Journal:  JMIR Med Inform       Date:  2018-02-27
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