Mycobacterial DNA extraction for whole-genome sequencing from early positive liquid (MGIT) cultures

We developed a low-cost and reliable method of DNA extraction from as little as 1 ml of early positive mycobacterial growth indicator tube (MGIT) cultures that is suitable for whole-genome sequencing to identify mycobacterial species and predict antibiotic resistance in clinical samples. The DNA ext...

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Vydáno v:Journal of clinical microbiology Ročník 53; číslo 4; s. 1137
Hlavní autoři: Votintseva, Antonina A, Pankhurst, Louise J, Anson, Luke W, Morgan, Marcus R, Gascoyne-Binzi, Deborah, Walker, Timothy M, Quan, T Phuong, Wyllie, David H, Del Ojo Elias, Carlos, Wilcox, Mark, Walker, A Sarah, Peto, Tim E A, Crook, Derrick W
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 01.04.2015
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ISSN:1098-660X, 1098-660X
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Shrnutí:We developed a low-cost and reliable method of DNA extraction from as little as 1 ml of early positive mycobacterial growth indicator tube (MGIT) cultures that is suitable for whole-genome sequencing to identify mycobacterial species and predict antibiotic resistance in clinical samples. The DNA extraction method is based on ethanol precipitation supplemented by pretreatment steps with a MolYsis kit or saline wash for the removal of human DNA and a final DNA cleanup step with solid-phase reversible immobilization beads. The protocol yielded ≥0.2 ng/μl of DNA for 90% (MolYsis kit) and 83% (saline wash) of positive MGIT cultures. A total of 144 (94%) of the 154 samples sequenced on the MiSeq platform (Illumina) achieved the target of 1 million reads, with <5% of reads derived from human or nasopharyngeal flora for 88% and 91% of samples, respectively. A total of 59 (98%) of 60 samples that were identified by the national mycobacterial reference laboratory (NMRL) as Mycobacterium tuberculosis were successfully mapped to the H37Rv reference, with >90% coverage achieved. The DNA extraction protocol, therefore, will facilitate fast and accurate identification of mycobacterial species and resistance using a range of bioinformatics tools.
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ISSN:1098-660X
1098-660X
DOI:10.1128/JCM.03073-14