陈丹妮, 韩营营, 李杰, 李臻鹏, 闫梅英. 基于基因组序列的3种沙门菌分子血清分型方法比较研究[J]. 疾病监测, 2021, 36(5): 468-474. DOI: 10.3784/jbjc.202002050063
引用本文: 陈丹妮, 韩营营, 李杰, 李臻鹏, 闫梅英. 基于基因组序列的3种沙门菌分子血清分型方法比较研究[J]. 疾病监测, 2021, 36(5): 468-474. DOI: 10.3784/jbjc.202002050063
Chen Danni, Han Yingying, Li Jie, Li Zhenpeng, Yan Meiying. Comprehensive assessment of three molecular serotyping methods of Salmonella based on genomic sequence[J]. Disease Surveillance, 2021, 36(5): 468-474. DOI: 10.3784/jbjc.202002050063
Citation: Chen Danni, Han Yingying, Li Jie, Li Zhenpeng, Yan Meiying. Comprehensive assessment of three molecular serotyping methods of Salmonella based on genomic sequence[J]. Disease Surveillance, 2021, 36(5): 468-474. DOI: 10.3784/jbjc.202002050063

基于基因组序列的3种沙门菌分子血清分型方法比较研究

Comprehensive assessment of three molecular serotyping methods of Salmonella based on genomic sequence

  • 摘要:
      目的  比较3种沙门菌分子血清分型方法,获得一种准确度较高的方法用来替代传统的血清凝集技术用于沙门菌血清型判定。
      方法  对覆盖50个血清型的509株沙门菌提取核酸进行全基因组测序,根据全基因组序列分别利用多位点序列分型(MLST)、SalmonSeroPredicition以及SISTR(Salmonella in silico typing resource)3种方法在线预测获得每株菌的血清型,然后与传统血清凝集获得的血清型进行一致性比较分析,评估每种方法血清型预测的准确度。
      结果  SISTR、MLST以及SalmonSeroPredicition预测血清型的准确率分别为96.67%、93.52%、69.16%。 常见沙门菌血清型印第安纳沙门菌和鼠伤寒沙门菌血清型预测正确率最高,为100%,德尔卑沙门菌、肠炎沙门菌血清型预测正确率分别为99.17%、95.74%。 3种方法均预测错误的血清型有肠炎沙门菌、德尔卑沙门菌和沙门菌的萨拉姆亚种、亚利桑那亚种和双相亚利桑那亚种等;预测错误原因主要是基因序列丢失和鞭毛抗原基因未表达。
      结论  基于基因组序列的SISTR血清型预测方法具有较高的血清型预测准确度,在传统血清凝集难以开展或沙门菌鞭毛基因不表达的情况下,可以替代血清凝集试验进行沙门菌血清型判定。

     

    Abstract:
      Objective  To determine an alternative method for serotyping of Salmonella to replace the traditional serum agglutination test, we compared three molecular serotyping methods and selected a method with higher accuracy.
      Methods  A total of 509 isolates of Salmonella of 50 serotypes were used to extract DNA for whole-genome sequencing and predict the serotypes of the strains by online prediction using three methods: MLST, SalmonSeroPredicition and SISTR. Compared with the serotype identified by traditional serum agglutination, the consistency of the serotype prediction of three methods was analyzed to evaluate the accuracy of serotype prediction by each method.
      Results  The prediction accuracy rates of SISTR, MLST and SalmonSeroPredicition were 96.67%, 93.52%, 69.16%, respectively. The highest prediction accuracy rate of common Salmonella serotypes such as S. Indiana and S. Typhimurium was 100%, the accuracy rate was 99.17% for S. Derby and 95.74% for S. Enteritidis. The serotypes that all three methods predicted incorrectly were S. Enteritidis, S. Derby, Salmonella enterica subsp. salamae, subsp. arizonae and subsp. diarizonae etc. The main reasons for the error were the missing of sequence genes and the loss of the switching mechanism or the ability to express the flagellar gene.
      Conclusion  SISTR based on genomic sequence has high serotype prediction accuracy. In the case that traditional serum agglutination is unavailable or cannot be conducted in time, SISTR can replace serum agglutination test to determine the serotype of Salmonella.

     

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