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Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences

Authors :
Bloomsbury Research Foundation
Fundação para a Ciência e a Tecnologia (Portugal)
King Abdullah University of Science and Technology
Medical Research Council (UK)
Wellcome Trust
Coll, Francesc [0000-0002-7882-2325]
Coll, Francesc
McNerney, Ruth
Preston, Mark D.
Guerra-Assunção, José Afonso
Warry, Andrew
Hill-Cawthorne, Grant
Mallard, Kim
Nair, Mridul
Miranda, Anabela
Alves, Adriana
Perdigão, João
Viveiros, Miguel
Portugal, Isabel
Hasan, Zahra
Hasan, Rumina
Glynn, Judith R.
Martin, Nigel
Pain, Arnab
Clark, Taane G.
Bloomsbury Research Foundation
Fundação para a Ciência e a Tecnologia (Portugal)
King Abdullah University of Science and Technology
Medical Research Council (UK)
Wellcome Trust
Coll, Francesc [0000-0002-7882-2325]
Coll, Francesc
McNerney, Ruth
Preston, Mark D.
Guerra-Assunção, José Afonso
Warry, Andrew
Hill-Cawthorne, Grant
Mallard, Kim
Nair, Mridul
Miranda, Anabela
Alves, Adriana
Perdigão, João
Viveiros, Miguel
Portugal, Isabel
Hasan, Zahra
Hasan, Rumina
Glynn, Judith R.
Martin, Nigel
Pain, Arnab
Clark, Taane G.
Publication Year :
2015

Abstract

Mycobacterium tuberculosis drug resistance (DR) challenges effective tuberculosis disease control. Current molecular tests examine limited numbers of mutations, and although whole genome sequencing approaches could fully characterise DR, data complexity has restricted their clinical application. A library (1,325 mutations) predictive of DR for 15 anti-tuberculosis drugs was compiled and validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online 'TB-Profiler' tool was developed to report DR and strain-type profiles directly from raw sequences. Using our DR mutation library, in silico diagnostic accuracy was superior to some commercial diagnostics and alternative databases. The library will facilitate sequence-based drug-susceptibility testing.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1431961131
Document Type :
Electronic Resource