A Rapid Drug Resistance Genotyping Workflow for Mycobacterium tuberculosis, Using Targeted Isothermal Amplification and Nanopore Sequencing.
A Rapid Drug Resistance Genotyping Workflow for Mycobacterium tuberculosis, Using Targeted Isothermal Amplification and Nanopore Sequencing.
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DOI：
10.1128/spectrum.00610-21
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发表时间：
2021-12-22
影响因子：
3.7
通讯作者：
McKendry RA
中科院分区：
文献类型：
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作者：
Gliddon HD;Frampton D;Munsamy V;Heaney J;Pataillot-Meakin T;Nastouli E;Pym AS;Steyn AJC;Pillay D;McKendry RA
结核病（TB）的表型药物敏感性测试（DST）需要数周才能得出结果。尽管分子检测可以快速检测耐药相关突变（DRM），但它们无法扩展到覆盖全基因组和许多可以预测耐药性的DRM。全基因组测序（WGS）方法是可扩展的，但如果直接在痰液中进行，通常需要靶富集步骤，如核酸扩增。我们开发了一种靶向等温扩增-纳米孔测序工作流程，用于快速预测TB分离株的耐药性。我们使用重组酶聚合酶扩增（RPA）对结核分枝杆菌基因组内的三个区域进行靶向等温扩增（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（DR）TB患者的分枝杆菌基因组DNA提取物，并将我们的结果与Illumina和表型DST的WGS结果进行比较，以评估对利福平和异烟肼耐药性预测的准确性。RPA扩增显示出与高保真PCR相当的保真度（100%一致性）。纳米孔测序产生的DRM预测与WGS的预测相同，测序运行时间更快，只需几分钟而不是几天。我们的工作流程预测利福平耐药的灵敏度和特异性分别为96.3%（95%置信区间[CI]，81.0 - 99.9%）和100.0%（95% CI，15.8 - 100.0%）。预测异烟肼耐药的敏感性和特异性分别为100.0%（95%CI，86.3 ~ 100.0%）和100.0%（95%CI，39.8 ~ 100.0%）。每个样品的工作流程耗材成本低于100英镑。我们的快速和低成本的耐药基因分型工作流程提供了准确的利福平和异烟肼耐药预测，使其适用于资源有限的环境。目前诊断耐药结核病的方法非常耗时，导致患者接受治疗和传播的延误。它们还需要高水平的实验室基础设施，而这些设施往往只能在中央设施中提供，从而导致诊断的进一步延误，并给在资源有限的环境中部署造成更多障碍。本文描述了一种新的工作流程，可以在更短的时间内诊断耐药结核病，使用更少的设备，并且比现有方法价格更低。TB DNA的量首先增加，而不需要庞大和昂贵的热循环设备。然后使用一种名为MinION的便携式测序仪读取DNA，该测序仪可以显示DNA中是否存在指示结核菌株是否具有耐药性的指示性变化。我们的工作流程可以在未来应对结核病耐药性这一公共卫生挑战的斗争中发挥重要作用。
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. IMPORTANCE 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.