Evaluation of a Culture-Dependent Algorithm and a Molecular Algorithm for Identification ofShigellaspp.,Escherichia coli, and EnteroinvasiveE. coli
ABSTRACTIdentification ofShigellaspp.,Escherichia coli, and enteroinvasiveE. coli(EIEC) is challenging because of their close relatedness. Distinction is vital, as infections withShigellaspp. 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 noninvasiveE. coli,Shigella sonnei, andShigella dysenteriae, 93% ofShigella boydiiand EIEC, and 85% ofShigella flexneriisolates 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 ofShigellaspp. 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 identifyingShigellaspecies 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 identifyShigellaspp. and EIEC up to the serotype level.