London Centre for Nanotechnology, Faculty of Mathematics and Physical Sciences, University College London, London, United Kingdom.
National Public Health Speciality Training Programme, South West, United Kingdom.
Microbiol Spectr. 2021 Dec 22;9(3):e0061021. doi: 10.1128/Spectrum.00610-21. Epub 2021 Nov 24.
Phenotypic drug susceptibility testing (DST) for tuberculosis (TB) requires weeks to yield results. Although molecular tests rapidly detect drug resistance-associated mutations (DRMs), they are not scalable to cover the full genome and the many DRMs that can predict resistance. Whole-genome sequencing (WGS) methods are scalable, but if conducted directly on sputum, typically require a target enrichment step, such as nucleic acid amplification. We developed a targeted isothermal amplification-nanopore sequencing workflow for rapid prediction of drug resistance of TB isolates. We used recombinase polymerase amplification (RPA) to perform targeted isothermal amplification (37°C for 90 min) of three regions within the Mycobacterium tuberculosis genome, followed by nanopore sequencing on the MinION. We tested 29 mycobacterial genomic DNA extracts from patients with drug-resistant (DR) TB and compared our results to those of WGS by Illumina and phenotypic DST to evaluate the accuracy of prediction of resistance to rifampin and isoniazid. Amplification by RPA showed fidelity equivalent to that of high-fidelity PCR (100% concordance). Nanopore sequencing generated DRM predictions identical to those of WGS, with considerably faster sequencing run times of minutes rather than days. The sensitivity and specificity of rifampin resistance prediction for our workflow were 96.3% (95% confidence interval [CI], 81.0 to 99.9%) and 100.0% (95% CI, 15.8 to 100.0%), respectively. For isoniazid resistance prediction, the sensitivity and specificity were 100.0% (95% CI, 86.3 to 100.0%) and 100.0% (95% CI, 39.8 to 100.0%), respectively. The workflow consumable costs per sample are less than £100. Our rapid and low-cost drug resistance genotyping workflow provides accurate prediction of rifampin and isoniazid resistance, making it appropriate for use in resource-limited settings. Current methods for diagnosing drug-resistant tuberculosis are time consuming, resulting in delays in patients receiving treatment and in transmission onwards. They also require a high level of laboratory infrastructure, which is often only available at centralized facilities, resulting in further delays to diagnosis and additional barriers to deployment in resource-limited settings. This article describes a new workflow that can diagnose drug-resistant TB in a shorter time, with less equipment, and for a lower price than current methods. The amount of TB DNA is first increased without the need for bulky and costly thermocycling equipment. The DNA is then read using a portable sequencer called a MinION, which indicates whether there are tell-tale changes in the DNA that indicate whether the TB strain is drug resistant. Our workflow could play an important role in the future in the fight against the public health challenge that is TB drug resistance.
表型药物敏感性测试(DST)需要数周才能得出结果。虽然分子测试可以快速检测耐药相关突变(DRMs),但它们不能扩展到涵盖全基因组和可以预测耐药的许多 DRMs。全基因组测序(WGS)方法具有可扩展性,但如果直接在痰液上进行,通常需要目标富集步骤,例如核酸扩增。我们开发了一种针对结核分枝杆菌分离物的快速预测药物耐药性的靶向等温扩增-纳米孔测序工作流程。我们使用重组酶聚合酶扩增(RPA)在结核分枝杆菌基因组的三个区域内进行靶向等温扩增(37°C 90 分钟),然后在 MinION 上进行纳米孔测序。我们测试了 29 个来自耐药性结核病(DR)患者的分枝杆菌基因组 DNA 提取物,并将我们的结果与 Illumina 的 WGS 结果和表型 DST 进行比较,以评估预测利福平和异烟肼耐药的准确性。RPA 扩增显示出与高保真度 PCR 相同的保真度(100%一致性)。纳米孔测序生成的 DRM 预测与 WGS 相同,测序运行时间快得多,只需几分钟,而不是几天。我们的工作流程对利福平耐药性预测的灵敏度和特异性分别为 96.3%(95%置信区间 [CI],81.0 至 99.9%)和 100.0%(95%CI,15.8 至 100.0%)。对于异烟肼耐药性预测,灵敏度和特异性分别为 100.0%(95%CI,86.3 至 100.0%)和 100.0%(95%CI,39.8 至 100.0%)。每个样本的工作流程耗材成本低于 100 英镑。我们的快速、低成本耐药基因分型工作流程可准确预测利福平与异烟肼耐药性,适合在资源有限的环境中使用。 当前诊断耐多药结核病的方法耗时较长,导致患者延迟接受治疗并继续传播。它们还需要高水平的实验室基础设施,而这些基础设施通常仅在集中设施中可用,这进一步延迟了诊断,并为在资源有限的环境中进一步部署增加了障碍。本文描述了一种新的工作流程,与当前方法相比,该流程可以在更短的时间内,使用更少的设备和更低的价格诊断耐多药结核病。首先,无需使用庞大且昂贵的热循环设备即可增加 TB DNA 的数量。然后,使用称为 MinION 的便携式测序仪读取 DNA,该测序仪可指示 DNA 是否存在表明 TB 菌株是否耐药的明显变化。我们的工作流程在未来对抗结核病这一公共卫生挑战方面可能发挥重要作用。