» Articles » PMID: 36951906

ShigaPass: an Tool Predicting Serotypes from Whole-genome Sequencing Assemblies

Abstract

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 %.

Citing Articles

Mecillinam activity against multidrug-resistant and .

Stefanovic A, Gowland L, Ritchie G, Lee C, Chorlton S, Matic N Microbiol Spectr. 2025; 13(3):e0100624.

PMID: 39918320 PMC: 11878017. DOI: 10.1128/spectrum.01006-24.


Genome and antibiotic resistance characteristics of clinical isolates in Fujian Province, Southeast China, 2005-2019.

Huang M, Zhang X, Luo C, Xu H, Qiu Y, Yang J Microb Genom. 2024; 10(11).

PMID: 39565081 PMC: 11893363. DOI: 10.1099/mgen.0.001325.


Genomic analysis of isolates from Lebanon reveals marked genetic diversity and antimicrobial resistance.

Yassine I, Rafei R, Pardos de la Gandara M, Osman M, Fabre L, Dabboussi F Microb Genom. 2023; 9(12).

PMID: 38100171 PMC: 10763507. DOI: 10.1099/mgen.0.001157.

References
1.
Pettengill E, Pettengill J, Binet R . Phylogenetic Analyses of Shigella and Enteroinvasive Escherichia coli for the Identification of Molecular Epidemiological Markers: Whole-Genome Comparative Analysis Does Not Support Distinct Genera Designation. Front Microbiol. 2016; 6:1573. PMC: 4718091. DOI: 10.3389/fmicb.2015.01573. View

2.
Pupo G, Lan R, REEVES P . Multiple independent origins of Shigella clones of Escherichia coli and convergent evolution of many of their characteristics. Proc Natl Acad Sci U S A. 2000; 97(19):10567-72. PMC: 27065. DOI: 10.1073/pnas.180094797. View

3.
Njamkepo E, Fawal N, Tran-Dien A, Hawkey J, Strockbine N, Jenkins C . Global phylogeography and evolutionary history of Shigella dysenteriae type 1. Nat Microbiol. 2016; 1:16027. DOI: 10.1038/nmicrobiol.2016.27. View

4.
Rohde J, Breitkreutz A, Chenal A, Sansonetti P, Parsot C . Type III secretion effectors of the IpaH family are E3 ubiquitin ligases. Cell Host Microbe. 2007; 1(1):77-83. DOI: 10.1016/j.chom.2007.02.002. View

5.
Casalino M, Latella M, Prosseda G, Colonna B . CadC is the preferential target of a convergent evolution driving enteroinvasive Escherichia coli toward a lysine decarboxylase-defective phenotype. Infect Immun. 2003; 71(10):5472-9. PMC: 201042. DOI: 10.1128/IAI.71.10.5472-5479.2003. View