Evaluation of a Culture-Dependent Algorithm and a Molecular Algorithm for Identification of Shigella spp., Escherichia coli, and Enteroinvasive E. coli.

Identification of Shigella spp., Escherichia coli, and enteroinvasive E. coli (EIEC) is challenging because of their close relatedness. Distinction is vital, as infections with Shigella spp. are under surveillance of health authorities, in contrast to EIEC infections. In this study, a culture-dependent identification algorithm and a molecular identification algorithm were evaluated. Discrepancies between the two algorithms and original identification were assessed using whole-genome sequencing (WGS). After discrepancy analysis with the molecular algorithm, 100% of the evaluated isolates were identified in concordance with the original identification. However, the resolution for certain serotypes was lower than that of previously described methods and lower than that of the culture-dependent algorithm. Although the resolution of the culture-dependent algorithm is high, 100% of noninvasive E. coli, Shigella sonnei, and Shigella dysenteriae, 93% of Shigella boydii and EIEC, and 85% of Shigella flexneri isolates were identified in concordance with the original identification. Discrepancy analysis using WGS was able to confirm one of the used algorithms in four discrepant results. However, it failed to clarify three other discrepant results, as it added yet another identification. Both proposed algorithms performed well for the identification of Shigella spp. and EIEC isolates and are applicable in low-resource settings, in contrast to previously described methods that require WGS for daily diagnostics. Evaluation of the algorithms showed that both algorithms are capable of identifying Shigella species and EIEC isolates. The molecular algorithm is more applicable in clinical diagnostics for fast and accurate screening, while the culture-dependent algorithm is more suitable for reference laboratories to identify Shigella spp. and EIEC up to the serotype level.

MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not Differentiate Shigella spp. and Escherichia coli.

Shigella spp. and E. coli are closely related and cannot be distinguished using matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) with commercially available databases. Here, three alternative approaches using MALDI-TOF MS to identify and distinguish Shigella spp., E. coli, and its pathotype EIEC were explored and evaluated using spectra of 456 Shigella spp., 42 E. coli, and 61 EIEC isolates. Identification with a custom-made database resulted in >94% Shigella identified at the genus level and >91% S. sonnei and S. flexneri at the species level, but the distinction of S. dysenteriae, S. boydii, and E. coli was poor. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although specificity was low. Discriminating markers for S. dysenteriae, S. boydii, and E. coli were not assigned at all. Classification models using machine learning correctly identified Shigella in 96% of isolates, but most E. coli isolates were also assigned to Shigella. None of the proposed alternative approaches were suitable for clinical diagnostics for identifying Shigella spp., E. coli, and EIEC, reflecting their relatedness and taxonomical classification. We suggest the use of MALDI-TOF MS for the identification of the Shigella spp./E. coli complex, but other tests should be used for distinction.

Multicenter evaluation of molecular and culture-dependent diagnostics for Shigella species and Entero-invasive Escherichia coli in the Netherlands.

An inter-laboratory collaborative trial for the evaluation of diagnostics for detection and identification of Shigella species and Entero-invasive Escherichia coli (EIEC) was performed. Sixteen Medical Microbiological Laboratories (MMLs) participated. MMLs were interviewed about their diagnostic methods and a sample panel, consisting of DNA-extracts and spiked stool samples with different concentrations of Shigella flexneri, was provided to each MML. The results of the trial showed an enormous variety in culture-dependent and molecular diagnostic techniques currently used among MMLs. Despite the various molecular procedures, 15 out of 16 MMLs were able to detect Shigella species or EIEC in all the samples provided, showing that the diversity of methods has no effect on the qualitative detection of Shigella flexneri. In contrast to semi quantitative analysis, the minimum and maximum values per sample differed by approximately five threshold cycles (Ct-value) between the MMLs included in the study. This indicates that defining a uniform Ct-value cut-off for notification to health authorities is not advisable.

Prevalence and Risk Factors for Colonization With Extended-Spectrum Cephalosporin-Resistant Escherichia coli in Children Attending Daycare Centers: A Cohort Study in the Netherlands.

BACKGROUND: The purpose of this study was to determine the prevalence and risk factors for colonization with extended-spectrum cephalosporin-resistant (ESC-R) Escherichia coli in daycare center (DCC)-attending children. METHODS: This is a prospective cohort study including 44 DCCs in the Netherlands, combining DCC characteristics and monthly collected stool samples from their attendees, and was performed in 2010-2012. During a 22-month study period, 852 stool samples were collected and screened for ESC-R E coli. Risk factors were studied using logistic regression analysis. RESULTS: In DCC-attending children (<4 years old), the overall prevalence of ESC-R E coli was 4.5%, and it was 8% in <1-year-old attendees. Among the 38 children carrying ESC-R E coli, the most common types were blaCMY-2 (26%), blaCTX-M-1 (16%), and chromosomal AmpC type 3 promoter mutants (13%). Extended-spectrum cephalosporin-resistant E coli was less common in DCCs where stricter hygiene protocols were enforced, eg, not allowing ill children to enter the DCC (odds ratio [OR], 0.34; 95% confidence interval [CI], 0.14-0.84), performing extra checks on handwashing of ill children (OR, 0.42; 95% CI, 0.20-0.87), and reporting suspected outbreaks to local health authorities (OR, 0.27; 95% CI, 0.11-0.69). CONCLUSIONS: The distribution of ESC-R E coli types in DCCs differs from that of the general population. Extended-spectrum cephalosporin-resistant E coli carriage in DCC-attending children is associated with the hygiene policies enforced in the DCC. Although our results are not conclusive enough to change current DCC practice beyond ensuring compliance with standing policies, they generated hypotheses and defined the degree of ESC resistance among DCC attendees, which may influence empiric antibiotic therapy choices, and tracked the increasing trend in ESC resistance.