Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase - PubMed (original) (raw)

. 2018 Oct 18;8(1):15382.

doi: 10.1038/s41598-018-33731-1.

Amanda Borens 1, Álvaro Chiner-Oms 2, Paolo Miotto 3, Leonid Chindelevitch 4, Angela M Starks 5, Debra Hanna 1, Richard Liwski 1, Matteo Zignol 6, Christopher Gilpin 6, Stefan Niemann 7, Thomas Andreas Kohl 8, Robin M Warren 9, Derrick Crook 10, Sebastien Gagneux 11, Sven Hoffner 12, Camilla Rodrigues 13, Iñaki Comas 14, David M Engelthaler 15, David Alland 16, Leen Rigouts 17, Christoph Lange 18, Keertan Dheda 19, Rumina Hasan 20, Ruth McNerney 21, Daniela M Cirillo 3, Marco Schito 1, Timothy C Rodwell 22 23, James Posey 24

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

Matthew Ezewudo et al. Sci Rep. 2018.

Erratum in

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.

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Conflict of interest statement

M. Schito, R. Liwski, A. Borens and M. Ezewudo reports grants from Bill & Melinda Gates Foundation, during the conduct of the study. Dr. D. Hanna reports grants from Bill & Melinda Gates Foundation, outside the submitted work. C. Lange reports personal fees from Chiesi, personal fees from Gilead, personal fees from Becton Dickinson, personal fees from Janssen, personal fees from Astra Zeneca, personal fees from Thermo Fisher Scientific, outside the submitted work. I. Comas reports personal fees from FIND Foundation for Innovative Diagnostics, within the scope of relevance to submitted work. D. Alland reports grants from Cepheid, other from Rutgers University Patent Pool, during the conduct of the study; In addition, D. Alland has a patent for primers and probes to detect drug resistance mutations issued. L. Rigouts reports other from FIND, during the conduct of the study. K. Dheda reports grants from FIND, grants and personal fees from ALERE, grants and personal fees from Oxford Immunotec, grants and personal fees from Cellestis (now Qiagen), grants from eNose Company, grants from Statens Serum Institut, grants and personal fees from bioMeriux, grants and personal fees from Cepheid, grants from Antrum Biotec, grants from Hain Lifescience, outside the submitted work; In addition, Dr. Dheda has a patent Characterization of novel TB-specific urinary biomarkers pending, a patent A smart mask for monitoring cough-related infectious diseases pending, and a patent device for diagnosing extrapulmonary tuberculosis (EPTB) issued. S. Niemann reports grants from German Center for Infection Research, during the conduct of the study and worked as consultant for FIND. T.C. Rodwell reports funding from NIH (NIAID) and FIND during the conduct of the study. Á. Chiner-Oms, P. Miotto, A.M. Starks, J. Posey, D. Crook, R.M. Warren, R. Hasan, M. Zignol, C. Gilpin, L. Chindelevitch, R. McNerney, D. Engelthaler, C. Rodrigues, S. Gagneux, D.M. Cirillo, S. Hoffner and T. A. Kohl have nothing to disclose.

Figures

Figure 1

Figure 1

Distribution of isolates on ReSeqTB platform among the seven major lineages of the Mycobacterium tuberculosis complex (MTBC). This schematic shows the proportional representation of the major MTBC lineages in our dataset. The Euro American lineage has the most representation, but every other major lineage including Lineage 7 and animal strains are represented in the dataset.

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