Wadsworth Centergrid.465543.5, New York State Department of Health, Albany, New York, USA.
Department of Biomedical Sciences, University at Albany, SUNY, Albany, New York, USA.
J Clin Microbiol. 2021 Nov 18;59(12):e0064921. doi: 10.1128/JCM.00649-21. Epub 2021 Sep 22.
Fast and effective methods are needed for sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome to track genetic mutations and to identify new and emerging variants during the ongoing pandemic. The objectives were to assess the performance of the SARS-CoV-2 AmpliSeq research panel and S5 plug-in analysis tools for whole-genome sequencing analysis of SARS-CoV-2 and to compare the results with those obtained with the MiSeq-based ARTIC analysis pipeline, using metrics such as depth, coverage, and concordance of single-nucleotide variant (SNV) calls. A total of 191 clinical specimens and a single cultured isolate were extracted and sequenced with AmpliSeq technology and analysis tools. Of the 191 clinical specimens, 83 (with threshold cycle [] values of 15.58 to 32.54) were also sequenced using an Illumina MiSeq-based method with the ARTIC analysis pipeline, for direct comparison. A total of 176 of the 191 clinical specimens sequenced on the S5XL system and prepared using the SARS-CoV-2 research panel had nearly complete coverage (>98%) of the viral genome, with an average depth of 5,031×. Similar coverage levels (>98%) were observed for 81/83 primary specimens that were sequenced with both methods tested. The sample with the lowest viral load ( value of 32.54) achieved 89% coverage using the MiSeq method and failed to sequence with the AmpliSeq method. Consensus sequences produced by each method were identical for 81/82 samples in areas of equal coverage, with a single difference present in one sample. The AmpliSeq approach is as effective as the Illumina-based method using ARTIC v3 amplification for sequencing SARS-CoV-2 directly from patient specimens across a range of viral loads ( values of 15.56 to 32.54 [median, 22.18]). The AmpliSeq workflow is very easily automated with the Ion Chef and S5 instruments and requires less training and experience with next-generation sequencing sample preparation than the Illumina workflow.
需要快速有效的方法来对严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 基因组进行测序,以追踪遗传突变,并在当前大流行期间识别新出现的变体。目的是评估 SARS-CoV-2 AmpliSeq 研究面板和 S5 插件分析工具在 SARS-CoV-2 全基因组测序分析中的性能,并使用深度、覆盖度和单核苷酸变异 (SNV) 调用的一致性等指标,将结果与使用基于 MiSeq 的 ARTIC 分析管道获得的结果进行比较。总共提取和测序了 191 份临床标本和一份单一培养分离物,使用 AmpliSeq 技术和分析工具。在 191 份临床标本中,有 83 份(阈值循环 [] 值为 15.58 至 32.54)也使用基于 Illumina MiSeq 的方法和 ARTIC 分析管道进行测序,用于直接比较。在 S5XL 系统上测序的 191 份临床标本中的 176 份,使用 SARS-CoV-2 研究面板进行制备,具有几乎完整的病毒基因组覆盖度(>98%),平均深度为 5031×。用两种方法测试的 81/83 份原始标本也观察到类似的覆盖水平(>98%)。用 MiSeq 方法获得最低病毒载量(值为 32.54)的样本实现了 89%的覆盖率,而 AmpliSeq 方法未能测序。在覆盖度相等的区域,每种方法产生的一致序列在 81/82 个样本中都是相同的,在一个样本中存在一个差异。在各种病毒载量(值为 15.56 至 32.54 [中位数,22.18])下,直接从患者标本中测序 SARS-CoV-2 时,AmpliSeq 方法与基于 Illumina 的方法使用 ARTIC v3 扩增一样有效。AmpliSeq 工作流程与 Ion Chef 和 S5 仪器非常容易自动化,并且与基于 Illumina 的工作流程相比,需要更少的下一代测序样本制备培训和经验。