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

Matthew Ezewudo, Amanda Borens, Álvaro Chiner-Oms, Paolo Miotto, Leonid Chindelevitch, Angela M. Starks, Debra Hanna, Richard Liwski, Matteo Zignol, Christopher Gilpin, Stefan Niemann, Thomas Andreas Kohl, Robin M. Warren, Derrick Crook, Sebastien Gagneux, Sven Hoffner, Camilla Rodrigues, Iñaki Comas, David M. Engelthaler, David AllandLeen Rigouts, Christoph Lange, Keertan Dheda, Rumina Hasan, Ruth McNerney, Daniela M. Cirillo, Marco Schito, Timothy C. Rodwell, James Posey

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

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.

Original languageEnglish (US)
Article number15382
JournalScientific reports
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2018

All Science Journal Classification (ASJC) codes

  • General

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