Molecular differentiation of Shigella spp. from enteroinvasive E. coli

Løbersli, Inger; Wester, Astrid Lousie; Kristiansen, Åse; Brandal, Lin Thorstensen

doi:10.1556/1886.2016.00004

Cited by 20 publications

(17 citation statements)

References 32 publications

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“…lacY (a lactose permease gene). Two previous studies 43,44 found that 100% of their Shigella stool sample isolates were ipaH positive/ lacY negative, whereas their EIEC isolates were more likely to be ipaH positive/ lacY positive.…”

Section: Discussionmentioning

confidence: 98%

Culture‐positive shigellosis cases are epidemiologically different to culture‐negative/PCR‐positive cases

Quinn

Najjar

Huhtinen

et al. 2019

Australian and New Zealand Journal of Public Health

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Objective: To review the epidemiological differences between culture‐positive and culture‐negative (but ipaH PCR‐positive) cases of shigellosis in Sydney Local Health District (SLHD), NSW, to inform whether changes to the national case definition for shigellosis are required. Methods: An audit of all cases of shigellosis (culture‐positive vs. culture‐negative/PCR‐positive) in SLHD from 1 January 2013 to 30 June 2015 was conducted and demographic, clinical and risk factors were analysed and compared between these groups. Results: Of the 148 shigellosis cases notified to SLHD, 122 cases (85 culture‐positive vs. 37 culture‐negative) were included for analysis. Culture‐positive cases were more likely than culture‐negative/PCR‐positive cases to have experienced at least three symptoms (OR 3.18, 95%CI 1.3–7.5), been hospitalised (OR 4.2, 95%CI 1.4–13.2), and have had men‐who‐have‐sex‐with‐men exposure identified as the source of their infection (OR 28.7, 95%CI 6.2–132.6). Conclusions: This study has identified that culture‐positive vs. culture‐negative/PCR‐positive shigellosis cases in NSW differ by clinical severity and risk factors for infection. Implications for public health: The study findings warrant further research to determine the true diagnostic prevalence of Shigella in the culture‐negative/PCR‐positive group in the Australian context, in order to inform further changes to the national case definition for shigellosis.

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Section: Discussionmentioning

confidence: 98%

Culture‐positive shigellosis cases are epidemiologically different to culture‐negative/PCR‐positive cases

Quinn

Najjar

Huhtinen

et al. 2019

Australian and New Zealand Journal of Public Health

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“…Likewise, Lobersli et al. [11] established a duplex real-time PCR ( ipa H and lac Y) to differentiate EIEC and Shigella spp., where lac Y is specific to E. coli. This PCR target differentiated Shigella spp.…”

Section: Currently Used Molecular Methods For Differentiation Of mentioning

confidence: 99%

Accurate differentiation of Escherichia coli and Shigella serogroups: challenges and strategies

Ragupathi

Sethuvel

Inbanathan

et al. 2018

New Microbes and New Infections

106

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Shigella spp. and Escherichia coli are closely related; both belong to the family Enterobacteriaceae. Phenotypically, Shigella spp. and E. coli share many common characteristics, yet they have separate entities in epidemiology and clinical disease, which poses a diagnostic challenge. We collated information for the best possible approach to differentiate clinically relevant E. coli from Shigella spp. We found that a molecular approach is required for confirmation. High discriminatory potential is seen with whole genome sequencing analysed for k-mers and single nucleotide polymorphism. Among these, identification using single nucleotide polymorphism is easy to perform and analyse, and it thus appears more promising. Among the nonmolecular methods, matrix-assisted desorption ionization–time of flight mass spectrometry may be applicable when data analysis is assisted with advanced analytic tools.

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“…(ii) lacY. EclacY was reported to be absent from Shigella organisms except S. sonnei and S. dysenteriae 1 while present in most EIEC isolates (64). A remnant from the 5= end of EclacY was detected in 21 of 22 S. sonnei (107 to 270 bp) and 8 of 8 S. dysenteriae 1 (361 to 475 bp) genomes, respectively.…”

Section: Resultsmentioning

confidence: 98%

In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

Yun

Lau

Lee

et al. 2019

Appl Environ Microbiol

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Bacteria of the genus Shigella, consisting of 4 species and Ͼ50 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 ϳ500 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. IMPORTANCE Shigella causes diarrheal disease with serious public health implications. However, conventional Shigella identification methods are laborious and timeconsuming 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.

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Molecular differentiation of Shigella spp. from enteroinvasive E. coli

Cited by 20 publications

References 32 publications

Culture‐positive shigellosis cases are epidemiologically different to culture‐negative/PCR‐positive cases

Culture‐positive shigellosis cases are epidemiologically different to culture‐negative/PCR‐positive cases

Accurate differentiation of Escherichia coli and Shigella serogroups: challenges and strategies

In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

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