TY - JOUR
T1 - Evaluation of a Culture-Dependent Algorithm and a Molecular Algorithm for Identification of Shigella spp., Escherichia coli, and Enteroinvasive E. coli
AU - van den Beld, Maaike J. C.
AU - de Boer, Richard F.
AU - Reubsaet, Frans A. G.
AU - Rossen, John W. A.
AU - Zhou, Kai
AU - Kuiling, Sjoerd
AU - Friedrich, Alexander W.
AU - Kooistra-Smidb, Mirjam A. M. D.
N1 - Copyright © 2018 van den Beld et al.
PY - 2018/10
Y1 - 2018/10
N2 - 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.
AB - 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.
KW - EIEC
KW - Escherichia coli
KW - Shigella
KW - whole-genome sequencing
KW - enteroinvasive E. coli
KW - identification
KW - molecular methods
KW - phenotypic methods
KW - POLYMERASE-CHAIN-REACTION
KW - REAL-TIME PCR
KW - O-ANTIGENS
KW - COMPARATIVE GENOMICS
KW - FLEXNERI
KW - DIFFERENTIATION
KW - RELATEDNESS
KW - DIAGNOSTICS
KW - SEQUENCES
KW - GENES
U2 - 10.1128/JCM.00510-18
DO - 10.1128/JCM.00510-18
M3 - Article
C2 - 30021824
SN - 0095-1137
VL - 56
JO - Journal of Clinical Microbiology
JF - Journal of Clinical Microbiology
IS - 10
M1 - e00510-18
ER -