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Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase

Ezewudo, Matthew and Borens, Amanda and Chiner-Oms, Álvaro and Miotto, Paolo and Chindelevitch, Leonid and Starks, Angela M. and Hanna, Debra and Liwski, Richard and Zignol, Matteo and Gilpin, Christopher and Niemann, Stefan and Kohl, Thomas Andreas and Warren, Robin M. and Crook, Derrick and Gagneux, Sebastien and Hoffner, Sven and Rodrigues, Camilla and Comas, Iñaki and Engelthaler, David M. and Alland, David and Rigouts, Leen and Lange, Christoph and Dheda, Keertan and Hasan, Rumina and McNerney, Ruth and Cirillo, Daniela M. and Schito, Marco and Rodwell, Timothy C. and Posey, James. (2018) Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase. Scientific Reports, 8 (1). p. 15382.

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Official URL: https://edoc.unibas.ch/66263/

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Abstract

Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) ( https://github.com/CPTR-ReSeqTB/UVP ) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Medical Parasitology and Infection Biology (MPI) > Tuberculosis Research (Gagneux)
UniBasel Contributors:Gagneux, Sebastien
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Springer Nature
ISSN:0169-5487
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
Identification Number:
Last Modified:24 Oct 2018 14:22
Deposited On:24 Oct 2018 14:22

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