Mars Global Food Safety Center, Beijing, 101407, China.
Center for Food Safety, University of Georgia, Griffin, GA, 30223, USA.
Food Microbiol. 2020 Aug;89:103452. doi: 10.1016/j.fm.2020.103452. Epub 2020 Feb 5.
The use of whole genome sequencing (WGS) data generated by short-read sequencing technologies such as the Illumina sequencing platforms has been shown to provide reliable results for Salmonella serotype prediction. Emerging long-read sequencing platforms developed by Oxford Nanopore Technologies (ONT) provide an alternative WGS method to meet the needs of industry for rapid and accurate Salmonella confirmation and serotype classification. Advantages of the ONT sequencing platforms include portability, real-time base-calling and long-read sequencing. To explore whether WGS data generated by an ONT sequencing platform could accurately predict Salmonella serotypes, 38 Salmonella strains representing 34 serotypes were sequenced using R9.4 flow cells on an ONT sequencer for up to 2 h. The downstream bioinformatics analysis was performed using pipelines with different assemblers including Canu, Wdbtg2 combined with Racon, or Miniasm combined with Racon. In silico serotype prediction programs were carried out using both SeqSero2 (raw reads and genome assemblies) and SISTR (genome assemblies). The WGS data of the same strains were also obtained from Illumina Hiseq (200 x depth of coverage per genome) as a benchmark of accurate serotype prediction. Predictions using WGS data generated after 30 min, 45 min, 1 h, and 2 h of ONT sequencing time all matched the prediction results from Illumina WGS data. This study demonstrated the comparable accuracy of WGS-based serotype prediction between ONT and Illumina sequencing platforms. This study also sets a start point for future validation of ONT WGS as a rapid Salmonella confirmation and serotype classification tool for the food industry.
全基因组测序（WGS）数据的使用，通过短读测序技术，如 Illumina 测序平台，已被证明为沙门氏菌血清型预测提供可靠的结果。新兴的长读测序平台由牛津纳米孔技术（ONT）开发，提供了一种替代 WGS 方法，以满足行业对快速和准确的沙门氏菌确认和血清型分类的需求。ONT 测序平台的优势包括便携性、实时碱基调用和长读测序。为了探索 ONT 测序平台生成的 WGS 数据是否可以准确预测沙门氏菌血清型，对 38 株代表 34 种血清型的沙门氏菌菌株进行了测序，使用 ONT 测序仪上的 R9.4 流动池测序长达 2 小时。下游生物信息学分析使用不同的组装程序，包括 Canu、Wdbtg2 与 Racon 结合或 Miniasm 与 Racon 结合的程序进行。使用 SeqSero2（原始读数和基因组组装）和 SISTR（基因组组装）进行了基于计算的血清型预测程序。同样的菌株的 WGS 数据也从 Illumina Hiseq 获得（每个基因组 200x 的覆盖深度）作为准确血清型预测的基准。使用 ONT 测序 30 分钟、45 分钟、1 小时和 2 小时后生成的 WGS 数据进行预测，均与 Illumina WGS 数据的预测结果相匹配。这项研究证明了 ONT 和 Illumina 测序平台在基于 WGS 的血清型预测方面具有相当的准确性。这项研究还为未来验证 ONT WGS 作为食品工业中快速沙门氏菌确认和血清型分类工具奠定了基础。
