Journal
JOURNAL OF CLINICAL MICROBIOLOGY
Volume 58, Issue 10, Pages -Publisher
AMER SOC MICROBIOLOGY
DOI: 10.1128/JCM.00632-20
Keywords
direct test; drug-resistant tuberculosis; next-generation sequencing; portable sequencer; rapid drug susceptibility testing
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Funding
- Foundation for Innovative New Diagnostics (FIND)
- Ospedale San Raffaele
- Unitaid funds [2019-32-FIND MDR]
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Targeted next-generation sequencing (tNGS) has emerged as a comprehensive alternative to existing methods for drug susceptibility testing (DST) of Mycobacterium tuberculosis from patient sputum samples for clinical diagnosis of drug-resistant tuberculosis (DR-TB). However, the complexity of sequencing platforms has limited their uptake in low-resource settings. The goal of this study was to evaluate the use of the tNGS-based DST solution Genoscreen Deeplex Myc-TB, for use on the compact, low-cost Oxford Nanopore Technologies MinION sequencer. One hundred four DNA samples extracted from smear-positive sputum sediments, previously sequenced using the Deeplex assay on an Illumina MiniSeq, were resequenced on MinION after applying a custom library preparation. MinION read quality, mapping statistics, and variant calling were computed using an in-house pipeline and compared to the reference MiniSeq data. The average percentage of MinION reads mapped to an H37RV reference genome was 90.8%, versus 99.5% on MiniSeq. The mean depths of coverage were 4,151 x and 4,177 x on MinION and MiniSeq, respectively, with heterogeneous distribution across targeted genes. Composite reference coverage breadth was >99% for both platforms. We observed full concordance between technologies in reporting the clinically relevant drug-resistant markers, including full gene deletions. In conclusion, we demonstrated that the workflow and sequencing data obtained from Deeplex on MinION are comparable to those for the MiniSeq, despite the higher raw error rates on MinION, with the added advantage of MinION's portability, versatility, and low capital costs. Targeted NGS on MinION is a promising DST solution for rapidly providing clinically relevant data to manage complex DR-TB cases.
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