Dataset Information

Shifting national surveillance of Shigella infections toward geno-serotyping by the development of a tailored Luminex assay and NGS workflow.

ABSTRACT: The phylogenetically closely related Shigella species and enteroinvasive Escherichia coli (EIEC) are responsible for millions of episodes of bacterial dysenteriae worldwide. Given its distinct epidemiology and public health relevance, only Shigellae are subject to mandatory reporting and follow-up by public health authorities. However, many clinical laboratories struggle to differentiate non-EIEC, EIEC, and Shigella in their current workflows, leading to inaccuracies in surveillance and rising numbers of misidentified E. coli samples at the National Reference Centre (NRC). In this paper, we describe two novel tools to enhance Shigella surveillance. First, we developed a low-cost Luminex-based multiplex assay combining five genetic markers for species identification with 11 markers for serotype prediction for S. sonnei and S. flexneri isolates. Using a test panel of 254 clinical samples, this assay has a sensitivity of 100% in differentiation of EIEC/Shigella pathotype from non-EIEC strains, and 68.7% success rate in distinction of Shigella and EIEC. A novel, and particularly successful marker was a Shigella-specific deletion in the spermidine acetyltransferase gene speG, reflecting its metabolic decay. For Shigella serotype prediction, the multiplex assay scored a sensitivity and specificity of 96.6% and 98.4%, respectively. All discrepancies were analyzed with whole-genome sequencing and shown to be related to causative mutations (stop codons, indels, and promoter mutations) in glycosyltransferase genes. This observation spurred the development of an in silico workflow which extracts the Shigella serotype from Next-Generation Sequencing (NGS) data, taking into account gene functionality. Both tools will be implemented in the workflow of the NRC, and will play a major role in the shift from phenotypic to genotyping-based surveillance of shigellosis in Belgium.

SUBMITTER: Ventola E

PROVIDER: S-EPMC6692546 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Shifting national surveillance of Shigella infections toward geno-serotyping by the development of a tailored Luminex assay and NGS workflow.

Ventola Eleonora E Bogaerts Bert B De Keersmaecker Sigrid C J SCJ Vanneste Kevin K Roosens Nancy H C NHC Mattheus Wesley W Ceyssens Pieter-Jan PJ

MicrobiologyOpen 20190328 8

The phylogenetically closely related Shigella species and enteroinvasive Escherichia coli (EIEC) are responsible for millions of episodes of bacterial dysenteriae worldwide. Given its distinct epidemiology and public health relevance, only Shigellae are subject to mandatory reporting and follow-up by public health authorities. However, many clinical laboratories struggle to differentiate non-EIEC, EIEC, and Shigella in their current workflows, leading to inaccuracies in surveillance and rising n ...[more]

PMID: 30924299

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Project description:Bacteria of the genus Shigella, consisting of 4 species and >50 serotypes, cause shigellosis, a foodborne disease of significant morbidity, mortality, and economic loss worldwide. Classical Shigella identification based on selective media and serology is tedious, time-consuming, expensive, and not always accurate. A molecular diagnostic assay does not distinguish Shigella at the species level or from enteroinvasive Escherichia coli (EIEC). We inspected genomic sequences from 221 Shigella isolates and observed low concordance rates between conventional designation and molecular serotyping: 86.4% and 80.5% at the species and serotype levels, respectively. Serotype determinants for 6 additional serotypes were identified. Examination of differentiation gene markers commonly perceived as characteristic hallmarks in Shigella showed high variability among different serotypes. Using this information, we developed ShigaTyper, an automated workflow that utilizes limited computational resources to accurately and rapidly determine 59 Shigella serotypes using Illumina paired-end whole-genome sequencing (WGS) reads. Shigella serotype determinants and species-specific diagnostic markers were first identified through read alignment to an in-house curated reference sequence database. Relying on sequence hits that passed a threshold level of coverage and accuracy, serotype could be unambiguously predicted within 1 min for an average-size WGS sample of ∼500 MB. Validation with WGS data from 380 isolates showed an accuracy rate of 98.2%. This pipeline is the first step toward building a comprehensive WGS-based analysis pipeline of Shigella spp. in a field laboratory setting, where speed is essential and resources need to be more cost-effectively dedicated.IMPORTANCEShigella causes diarrheal disease with serious public health implications. However, conventional Shigella identification methods are laborious and time-consuming and can be erroneous due to the high similarity between Shigella and enteroinvasive Escherichia coli (EIEC) and cross-reactivity between serotyping antisera. Further, serotype interpretation is complicated for inexperienced users. To develop an easier method with higher accuracy based on whole-genome sequencing (WGS) for Shigella serotyping, we systematically examined genomic information of Shigella isolates from 53 serotypes to define rules for differentiation and serotyping. We created ShigaTyper, an automated pipeline that accurately and rapidly excludes non-Shigella isolates and identifies 59 Shigella serotypes using Illumina paired-end WGS reads. A serotype can be unambiguously predicted at a data processing speed of 538 MB/min with 98.2% accuracy from a regular laptop. Once it is installed, training in bioinformatics analysis and Shigella genetics is not required. This pipeline is particularly useful to general microbiologists in field laboratories.

Dataset Information

Shifting national surveillance of Shigella infections toward geno-serotyping by the development of a tailored Luminex assay and NGS workflow.

Publications

Shifting national surveillance of Shigella infections toward geno-serotyping by the development of a tailored Luminex assay and NGS workflow.

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