Abstract
BACKGROUND: The emergence of Mycobacterium tuberculosis with complex drug resistance profiles necessitates a rapid and comprehensive drug susceptibility test for guidance of patient treatment. We developed two targeted-sequencing workflows based on Illumina MiSeq and Nanopore MinION for the prediction of drug resistance in M. tuberculosis toward 12 antibiotics. METHODS: A total of 163 M. tuberculosis isolates collected from Hong Kong and Ethiopia were subjected to a multiplex PCR for simultaneous amplification of 19 drug resistance-associated genetic regions. The amplicons were then barcoded and sequenced in parallel on MiSeq and MinION in respective batch sizes of 24 and 12 samples. A web-based bioinformatics pipeline, BacterioChek-TB, was developed to translate the raw datasets into clinician-friendly reports. RESULTS: Both platforms successfully sequenced all samples with mean read depths of 1,127× and 1,649×, respectively. The variant calling by MiSeq and MinION could achieve 100% agreement if variants with an allele frequency of <40% reported by MinION were excluded. Both workflows achieved a mean clinical sensitivity of 94.8% and clinical specificity of 98.0% when compared with phenotypic drug susceptibility test (pDST). Turnaround times for the MiSeq and MinION workflows were 38 and 15 h, facilitating the delivery of treatment guidance at least 17-18 days earlier than pDST, respectively. The higher cost per sample on the MinION platform ($71.56) versus the MiSeq platform ($67.83) was attributed to differences in batching capabilities. CONCLUSION: Our study demonstrates the interchangeability of MiSeq and MinION platforms for generation of accurate and actionable results for the treatment of tuberculosis.
| Original language | English |
|---|---|
| Pages (from-to) | 809-820 |
| Number of pages | 12 |
| Journal | Clinical Chemistry |
| Volume | 66 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 1 2020 |
| Externally published | Yes |
ASJC Scopus subject areas
- General Medicine
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