Development and Comprehensive Evaluation of Culture-Independent,\nLong Amplicon-Based Targeted Next-Generation Sequencing Methods for\nPredicting Antimicrobial Resistance in Tuberculosis
The\ngreat variety of antimicrobial resistance (AMR) profiles among\ntuberculosis (TB) patients necessitates a comprehensive detection\nmethod. This study developed culture-independent, long amplicon-based\ntargeted next-generation sequencing (tNGS) methods for predicting\nAMR across 16 drugs within the <i>Mycobacterium tuberculosis</i> complex (MTBC). Multiplex PCR amplification was employed to enrich\n20 gene regions, with sequencing performed on either the Oxford Nanopore\nTechnologies (ONT) or Illumina platforms. Customized bioinformatics\npipelines provide a streamlined process from raw data to clinician-friendly\nreports. The ONT tNGS method has been optimized, and its performance\nhas been thoroughly evaluated, utilizing Q20+ chemistry in combination\nwith the R10.4.1 flow cell. It requires only 15 high-quality reads\nper target gene to accurately identify all variants, with the turnaround\ntime taking 4 h and 50 min. Studies confirmed that this method effectively\nidentifies <i>Mycobacterium</i> species and was highly resistant\nto interference from other clinical pathogens. To ensure optimal coverage,\nit is recommended to input at least 500 copies of the genome and sequence\n500MB of high-quality FASTQ data. Diagnostic performance evaluations\ndemonstrate that this method achieves 98.35% concordance with phenotypic\ndrug susceptibility testing (pDST) and is consistent with the results\nobtained from Xpert MTB/RIF assays. The design of long amplicons not\nonly ensures comprehensive coverage of target regions but also simplifies\nprimer design, facilitating compatibility with various sequencing\nplatforms. Compared with previous studies, the optimized ONT tNGS\nmethod in this study significantly improves turnaround time, detection\naccuracy, and the comprehensive coverage of mutations associated with\nAMR.
Publication Details
- Journal
- Figshare
- Published
- 2024-12-21
- DOI
- https://doi.org/10.1021/acs.analchem.4c04166.s001
- Primary Topic
- Tuberculosis Research and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00