Institut Pasteur, Université Paris Cité, Unité des Bactéries pathogènes entériques, Centre National de Référence des Escherichia coli, Shigella et Salmonella, Paris, F-75015, France.
Laboratoire Microbiologie Santé et Environnement (LMSE), Doctoral School of Sciences and Technology, Faculty of Public Health, Lebanese University, Tripoli, Lebanon.
Microb Genom. 2023 Mar;9(3). doi: 10.1099/mgen.0.000961.
is one of the commonest causes of diarrhoea worldwide and a major public health problem. serotyping is based on a standardized scheme that splits strains into four serogroups and 60 serotypes on the basis of biochemical tests and O-antigen structures. This conventional serotyping method is laborious, time-consuming, impossible to automate, and requires a high level of expertise. Whole-genome sequencing (WGS) is becoming more affordable and is now used for routine surveillance, opening up possibilities for the development of much-needed accurate rapid typing methods. Here, we describe ShigaPass, a new tool for predicting serotypes from WGS assemblies on the basis of gene cluster DNA sequences, phage and plasmid-encoded O-antigen modification genes, seven housekeeping genes (EnteroBase's MLST scheme), alleles and clustered regularly interspaced short palindromic repeats (CRISPR) spacers. Using 4879 genomes, including 4716 reference strains and clinical isolates of characterized with a panel of biochemical tests and serotyped by slide agglutination, we show here that ShigaPass outperforms all existing tools, particularly for the identification of and serotypes, with a correct serotype assignment rate of 98.5 % and a sensitivity rate (i.e. ability to make any prediction) of 100 %.
是全球范围内最常见的腹泻病因之一,也是一个主要的公共卫生问题。血清型分型基于一个标准化方案,根据生化试验和 O 抗原结构将 菌株分为四个血清群和 60 个血清型。这种传统的血清分型方法既繁琐又耗时,无法实现自动化,并且需要高度专业的知识。全基因组测序(WGS)的成本越来越低,现已用于常规监测,为开发急需的准确快速分型方法提供了可能性。在这里,我们描述了 ShigaPass,这是一种新的工具,用于根据 基因簇 DNA 序列、噬菌体和质粒编码的 O 抗原修饰基因、七个管家基因(EnteroBase 的 MLST 方案)、等位基因和簇状规则间隔短回文重复序列(CRISPR)间隔物,从 WGS 组装中预测 血清型。使用包括 4716 个参考菌株和 4879 个临床分离株的基因组,这些菌株经过一系列生化试验进行了特征描述,并通过玻片凝集进行了血清型分型,我们在此表明,ShigaPass 优于所有现有的 工具,特别是对于 和 血清型的鉴定,正确的血清型分配率为 98.5%,敏感性(即进行任何预测的能力)为 100%。