Salmonella Serotyping Using Whole Genome Sequencing
Salmonella Serotyping Using Whole Genome Sequencing
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DOI：
10.3389/fmicb.2018.02993
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发表时间：
2018-12-13
影响因子：
5.2
通讯作者：
Morin, Paul M.
中科院分区：
文献类型：
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作者：
Ibrahim, George M.;Morin, Paul M.
直到最近，传统血清学和考夫曼白色方案（KWS）一直是沙门氏菌血清分型的金标准。全基因组测序（WGS）现在已经成为这一领域的替代方案。血清型信息仍然是食品安全和公共卫生活动的基石，以减少沙门氏菌病的负担。与此同时，WGS的最新进展提高了进行高级病原体表征的能力，同时改善了追溯调查，以确定爆发期间食源性疾病的来源。基于WGS的血清型预测可以使用计算机数据分析工具进行。已经开发了三种这样的工具：沙门氏菌计算机分型资源（SISTR），（B）。SeqSero，和（c）.计算机模拟7-基因MLST ST（多位点序列分型亚型），其使用SISTR平台生成。世界各地的公共卫生官员正在努力验证这些工具，以取代传统的监测方法，为支持公共卫生调查提供更强大的分子流行病学方法。在这项研究中，我们报告了对1999年至2017年收集的1，041株沙门氏菌分离株的实验室库存的回顾性分析。这些分离株具有公共卫生意义，因为它们都来自食物、饲料或环境拭子。使用计算机模拟SeqSero工具进行血清型预测，通过传统血清学和WGS对它们进行血清分型。两者预测899个分离株（占1，041个沙门氏菌分离株的86.4%）中相同的沙门氏菌血清型。SeqSero分配不同于传统的血清学检测80株（7.7%），62株（5.9%），没有血清型预测确定。这项回顾性研究是使用WGS和SeqSero作为数据分析工具来预测沙门氏菌血清型的一个很好的例子，与传统的KWS血清分型相比，它可以提供许多优势，包括沙门氏菌分离株特征的分子和遗传细节。总之，很明显，使用WGS和计算机工具进行沙门氏菌血清分型可能有一天会取代传统的血清分型。
Until recently, traditional serology and the Kauffmann White Scheme (KWS) have been the gold standard for Salmonella serotyping. Whole Genome Sequencing (WGS) has now emerged as an alternative in this field. Serotype information remains a cornerstone in food safety and public health activities to reduce the burden of salmonellosis. At the same time, recent advances in WGS have improved the ability to perform advanced pathogen characterization while improving trace back investigations to determine the source of foodborne illness during outbreaks. Serovar prediction based on WGS can be performed using in silico data analysis tools. Three such tools have been developed: (a). Salmonella in silico Typing Resource (SISTR), (b). SeqSero, and (c). in silico 7-gene MLST ST (Multilocus Sequence Typing Sub-Typing) which was generated using the SISTR platform. Public health officials around the world are diligently working to validate these tools for replacing traditional surveillance methods to provide a more powerful approach for molecular epidemiology in support of public health investigations. In this study, we report a retrospective analysis of our laboratory inventory of 1,041 Salmonella isolates collected between 1999 and 2017. These isolates are of public health significance since they all came from either food, feed or environmental swabs. They were all serotyped by both traditional serology and WGS using an in silico SeqSero tool for serovar prediction. Both predicted identical Salmonella serotypes in 899 isolates (86.4% of the 1,041 Salmonella isolates). SeqSero assignments differed from traditional serological testing in 80 isolates (7.7%) and no serotype prediction was ascertained from 62 isolates (5.9%). This retrospective study is an excellent example of using WGS and SeqSero as a data analysis tool to predict Salmonella serotypes that can provide numerous advantages including molecular and genetic details regarding the characteristics of the Salmonella isolates compared to traditional KWS serotyping. In conclusion, it is evident that using WGS and in silico tools for Salmonella serotyping might someday replace traditional serotyping.