Removing the bottleneck in whole genome sequencing of Mycobacterium tuberculosis for rapid drug resistance analysis: a call to action
Author(s) -
Ruth McNerney,
Taane G. Clark,
Susana Campino,
Camilla Rodrigues,
David L. Dolinger,
Liezel Smith,
Andrea Maurizio Cabibbe,
Keertan Dheda,
Marco Schito
Publication year - 2016
Publication title -
international journal of infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 89
eISSN - 1878-3511
pISSN - 1201-9712
DOI - 10.1016/j.ijid.2016.11.422
Subject(s) - mycobacterium tuberculosis , whole genome sequencing , drug resistance , bottleneck , computational biology , tuberculosis , sputum , dna sequencing , genomic dna , genome , biology , dna , microbiology and biotechnology , medicine , genetics , computer science , gene , pathology , embedded system
Whole genome sequencing (WGS) can provide a comprehensive analysis of Mycobacterium tuberculosis mutations that cause resistance to anti-tuberculosis drugs. With the deployment of bench-top sequencers and rapid analytical software, WGS is poised to become a useful tool to guide treatment. However, direct sequencing from clinical specimens to provide a full drug resistance profile remains a serious challenge. This article reviews current practices for extracting M. tuberculosis DNA and possible solutions for sampling sputum. Techniques under consideration include enzymatic digestion, physical disruption, chemical degradation, detergent solubilization, solvent extraction, ligand-coated magnetic beads, silica columns, and oligonucleotide pull-down baits. Selective amplification of genomic bacterial DNA in sputum prior to WGS may provide a solution, and differential lysis to reduce the levels of contaminating human DNA is also being explored. To remove this bottleneck and accelerate access to WGS for patients with suspected drug-resistant tuberculosis, it is suggested that a coordinated and collaborative approach be taken to more rapidly optimize, compare, and validate methodologies for sequencing from patient samples.
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