Basic Info

Serotype prediction based on their surface antigens, such as O, H, and K antigens.

More Details

The serotype represents the genetic markers displayed by proteins in blood plasma. Due to the genetic polymorphism of some serum proteins, phenotypic differences arise among individuals. Therefore, serotyping has become an important classification method, especially for many foodborne microorganisms such as Salmonella and Listeria monocytogenes. This method is also widely used in epidemiological investigations. By determining the serotype of bacteria, we can provide a solid basis for antimicrobial therapy. Specifically, through in-depth analysis of the characteristics of bacterial somatic cells, such as the O antigen, cell surface proteins, H antigen, and K antigen, we can accurately classify bacteria based on their serotypes.

What's New

The current classification, based on biochemical tests and O-antigen typing, splits the genus Shigella into four serogroups (originally considered to be species) – Shigella dysenteriae (serogroup A), S. flexneri (serogroup B), S. boydii (serogroup C) and S. sonnei (serogroup D) – comprising 60 serotypes. However, modern population genetics methods based on bacterial DNA sequences have shown that Shigella can be grouped into eight phylogenetically distinct clusters within the species Escherichia coli.

To date, using several genetic structures markers – including the rfb gene cluster, POAC genes, seven housekeeping (HK) genes (adk, fumC, gyrB, icd, mdh, recA and purA), the fliC gene and clustered regularly interspaced short palindromic repeats (CRISPR) spacers – can predict Shigella serotypes directly from WGS assemblies. 

Additional Information

Related links:

https://github.com/CFSAN-Biostatistics/shigatyper

Literature

Yassine I, Lefèvre S, Hansen EE, et al. Population structure analysis and laboratory monitoring of Shigella by core-genome multilocus sequence typing. Nat Commun. 2022;13(1):551. Published 2022 Jan 27. doi:10.1038/s41467-022-28121-1

Wu Y, Lau HK, Lee T, Lau DK, Payne J. In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification. Appl Environ Microbiol. 2019;85(7):e00165-19. Published 2019 Mar 22. doi:10.1128/AEM.00165-19

Wei Xiaoyu, You Li, Tian Kecheng, et al. Detection and analysis of virulence-related genes in *Shigella* strains isolated in Guizhou Province from 2007 to 2013 [J]. Modern Preventive Medicine, 2015, 42(21): 3935-3938