Ferrari Guglielmo, Romano Great, Pitrolo Antonino Maria Guglielmo, Baldanti Fausto, Piralla Antonio
Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy.
J Med Virol. 2025 Aug;97(8):e70571. doi: 10.1002/jmv.70571.
The most prevalent cause of severe respiratory infections in children is the human respiratory syncytial virus (RSV). The advent of next-generation sequencing (NGS) has made it possible to incorporate this technology into pathogen monitoring and surveillance. Whole-genome sequencing (WGS) of RSV has now become a relatively widely used method for tracking viral evolution. Here we report an improved high-throughput RSV-WGS assay performed directly on clinical samples that is suitable for short-read sequencing platforms. A total of 100 RSV-positive samples collected between November 2022 and March 2024 fulfilled the inclusion cycle quantification criteria and were randomly included in the validation process. The WGS protocol was designed to amplify three distinct amplicons to cover the entire RSV genome. The protocol described here can be successfully replicated in several instances (approximately 95%) in samples with a relatively low viral load, typically corresponding to cycle of quantification values of 27-32. The amplicon-based protocol produced meaningful sequencing results in terms of median depth of coverage (more than 12000×) and median of mapped reads (> 1 × 10 reads). The sequences that had passed the filters showed a coverage of at least 98% across the entire genome, with cycle quantification values of 32. Based on the obtained data resulting in an easy-to-perform protocol helpful for the molecular epidemiology surveillance of RSV.
儿童严重呼吸道感染最常见的病因是人类呼吸道合胞病毒（RSV）。下一代测序（NGS）技术的出现使将该技术应用于病原体监测和监视成为可能。RSV的全基因组测序（WGS）现已成为追踪病毒进化的一种相对广泛使用的方法。在此，我们报告一种改进的高通量RSV-WGS检测方法，该方法直接在临床样本上进行，适用于短读长测序平台。2022年11月至2024年3月期间收集的100份RSV阳性样本满足纳入循环定量标准，并被随机纳入验证过程。WGS方案设计用于扩增三个不同的扩增子以覆盖整个RSV基因组。本文所述方案在病毒载量相对较低的样本（通常对应于27-32的定量循环值）中可以在多个实例中（约95%）成功重复。基于扩增子的方案在覆盖深度中位数（超过12000×）和映射读数中位数（>1×10读数）方面产生了有意义的测序结果。通过筛选的序列在整个基因组中的覆盖率至少为98%，定量循环值为32。基于获得的数据产生了一种易于执行的方案，有助于RSV的分子流行病学监测。
