Genomics Development and Applications Branch, Division of Food Safety Genomics, Office of Applied Microbiology and Technology, Office of Laboratory Operations and Applied Science, Human Foods Program, Food & Drug Administration, College Park, MD 20740, USA.
Int J Mol Sci. 2024 Nov 5;25(22):11877. doi: 10.3390/ijms252211877.
Leafy greens are a significant source of produce-related Shiga toxin-producing (STEC) outbreaks in the United States, with agricultural water often implicated as a potential source. Current FDA outbreak detection protocols are time-consuming and rely on sequencing methods performed in costly equipment. This study evaluated the potential of Oxford Nanopore Technologies (ONT) with Q20+ chemistry as a cost-effective, rapid, and accurate method for identifying and clustering foodborne pathogens. The study focuses on assessing whether ONT Q20+ technology could facilitate near real-time pathogen identification, including SNP differences, serotypes, and antimicrobial resistance genes. This pilot study evaluated different combinations of two DNA extraction methods (Maxwell RSC Cultured Cell DNA kit and Monarch high molecular weight extraction kits) and two ONT library preparation protocols (ligation and the rapid barcoding sequencing kit) using five well-characterized strains representing diverse foodborne pathogens. High-quality, closed bacterial genomes were obtained from all combinations of extraction and sequencing kits. However, variations in assembly length and genome completeness were observed, indicating the need for further optimization. In silico analyses demonstrated that Q20+ nanopore sequencing chemistry accurately identified species, genotype, and virulence factors, with comparable results to Illumina sequencing. Phylogenomic clustering showed that ONT assemblies clustered with reference genomes, though some indels and SNP differences were observed, likely due to sequencing and analysis methodologies rather than inherent genetic variation. Additionally, the study evaluated the impact of a change in the sampling rates from 4 kHz (260 bases pair second) to 5 kHz (400 bases pair second), finding no significant difference in sequencing accuracy. This evaluation workflow offers a framework for evaluating novel technologies for use in surveillance and foodborne outbreak investigations. Overall, the evaluation demonstrated the potential of ONT Q20+ nanopore sequencing chemistry to assist in identifying the correct strain during outbreak investigations. However, further research, validation studies, and optimization efforts are needed to address the observed limitations and fully realize the technology's potential for improving public health outcomes and enabling more efficient responses to foodborne disease threats.
绿叶蔬菜是美国与农产品相关的产志贺毒素大肠杆菌（STEC）暴发的重要来源，农业用水通常被认为是一个潜在的来源。目前，FDA 的暴发检测方案耗时且依赖于在昂贵设备上进行的测序方法。本研究评估了牛津纳米孔技术（ONT）与 Q20+ 化学物质的潜力，该技术作为一种具有成本效益、快速且准确的方法，可用于识别和聚类食源性病原体。本研究侧重于评估 ONT Q20+ 技术是否能够促进食源性病原体的近乎实时识别，包括 SNP 差异、血清型和抗生素耐药基因。这项试点研究评估了两种 DNA 提取方法（Maxwell RSC 培养细胞 DNA 试剂盒和 Monarch 高分子量提取试剂盒）和两种 ONT 文库制备方案（连接和快速条形码测序试剂盒）的不同组合，使用五种具有代表性的代表不同食源性病原体的菌株。从所有提取和测序试剂盒的组合中均获得了高质量、闭合的细菌基因组。然而，观察到组装长度和基因组完整性存在差异，表明需要进一步优化。计算机分析表明，Q20+ 纳米孔测序化学物质能够准确识别物种、基因型和毒力因子，结果与 Illumina 测序相当。系统发育聚类表明，ONT 组装与参考基因组聚类，尽管观察到一些插入缺失和 SNP 差异，可能是由于测序和分析方法而不是固有遗传变异所致。此外，该研究还评估了采样率从 4 kHz（260 碱基对/秒）变为 5 kHz（400 碱基对/秒）的影响，发现测序准确性没有显著差异。该评估工作流程为评估用于监测和食源性病原体暴发调查的新技术提供了框架。总体而言，该评估表明 ONT Q20+ 纳米孔测序化学物质具有在暴发调查期间协助识别正确菌株的潜力。然而，需要进一步的研究、验证研究和优化工作，以解决观察到的限制，并充分发挥该技术在改善公共卫生结果和实现更高效应对食源性疾病威胁方面的潜力。
