利用纳米孔元基因组测序评估禽流感病毒的商用 RNA 提取方案

Viruses Pub Date : 2024-09-07 DOI:10.3390/v16091429
Maria Chaves, Amro Hashish, Onyekachukwu Osemeke, Yuko Sato, David L. Suarez, Mohamed El-Gazzar
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引用次数: 0

摘要

禽流感病毒(AIV)是家禽业的重大威胁,需要快速准确的诊断。目前的 AIV 诊断过程依赖于通过实时反转录聚合酶链反应(rRT-PCR)进行病毒鉴定。随后,通过基因组测序进一步确定病毒特征。这两步诊断过程需要数天到数周的时间,但使用新型测序技术可以加快这一过程。我们的目标是优化和验证核酸提取,以此作为第一步,将牛津纳米孔技术(ONT)确立为从临床样本中鉴定和描述 AIV 的快速诊断工具。本研究使用已知 AIV 阳性的临床样本,比较了四种市售的 RNA 提取方案。提取的 RNA 采用总 RNA 浓度、rRT-PCR 测定的病毒拷贝数和 260/280 吸光度比值测定的纯度进行评估。NGS 测试后,评估了总读数和流感特异性读数的数量以及生成序列的质量分数。结果表明,在所有测量参数上,没有一种方案优于其他方案;但是,基于磁性颗粒的方法在 CT 值、纯度、总产量和 AIV 读数方面最为一致,而且不易出错。这项研究强调了不同的 RNA 提取方案如何影响 ONT 测序性能。
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Evaluation of Commercial RNA Extraction Protocols for Avian Influenza Virus Using Nanopore Metagenomic Sequencing
Avian influenza virus (AIV) is a significant threat to the poultry industry, necessitating rapid and accurate diagnosis. The current AIV diagnostic process relies on virus identification via real-time reverse transcription–polymerase chain reaction (rRT-PCR). Subsequently, the virus is further characterized using genome sequencing. This two-step diagnostic process takes days to weeks, but it can be expedited by using novel sequencing technologies. We aim to optimize and validate nucleic acid extraction as the first step to establishing Oxford Nanopore Technologies (ONT) as a rapid diagnostic tool for identifying and characterizing AIV from clinical samples. This study compared four commercially available RNA extraction protocols using AIV-known-positive clinical samples. The extracted RNA was evaluated using total RNA concentration, viral copies as measured by rRT-PCR, and purity as measured by a 260/280 absorbance ratio. After NGS testing, the number of total and influenza-specific reads and quality scores of the generated sequences were assessed. The results showed that no protocol outperformed the others on all parameters measured; however, the magnetic particle-based method was the most consistent regarding CT value, purity, total yield, and AIV reads, and it was less error-prone. This study highlights how different RNA extraction protocols influence ONT sequencing performance.
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