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. 2025 Apr 2;80(4):1011-1021.
doi: 10.1093/jac/dkaf028.

One day in Denmark: whole-genome sequence-based analysis of Escherichia coli isolates from clinical settings

Ana Rita Rebelo  1 , Valeria Bortolaia  1 , Pimlapas Leekitcharoenphon  1 , Dennis Schrøder Hansen  2 , Hans Linde Nielsen  3   4 , Svend Ellermann-Eriksen  5 , Michael Kemp  6 , Bent Løwe Røder  7 , Niels Frimodt-Møller  8 , Turid Snekloth Søndergaard  9 , John Eugenio Coia  10 , Claus Østergaard  11 , Henrik Westh  12   13 , Frank M Aarestrup  1
Affiliations

One day in Denmark: whole-genome sequence-based analysis of Escherichia coli isolates from clinical settings

Ana Rita Rebelo et al. J Antimicrob Chemother. .

Abstract

Background: WGS can potentially be routinely used in clinical microbiology settings, especially with the increase in sequencing accuracy and decrease in cost. Escherichia coli is the most common bacterial species analysed in those settings, thus fast and accurate diagnostics can lead to reductions in morbidity, mortality and healthcare costs.

Objectives: To evaluate WGS for diagnostics and surveillance in a collection of clinical E. coli; to examine the pool of antimicrobial resistance (AMR) determinants circulating in Denmark and the most frequent STs; and to evaluate core-genome MLST (cgMLST) and SNP-based clustering approaches for detecting genetically related isolates.

Methods: We analysed the genomes of 699 E. coli isolates collected throughout all Danish Clinical Microbiology Laboratories. We used rMLST and KmerFinder for species identification, ResFinder for prediction of AMR, and PlasmidFinder for plasmid identification. We used Center for Genomic Epidemiology MLST, cgMLSTFinder and CSI Phylogeny to perform typing and clustering analysis.

Results: Genetic AMR determinants were detected in 56.2% of isolates. We identified 182 MLSTs, most frequently ST-69, ST-73, ST-95 and ST-131. Using a maximum 15-allele difference as the threshold for genetic relatedness, we identified 23 clusters. SNP-based phylogenetic analysis within clusters revealed from 0 to 13 SNPs, except two cases with 111 and 461 SNPs.

Conclusions: WGS data are useful to characterize clinical E. coli isolates, including predicting AMR profiles and subtyping in concordance with surveillance data. We have shown that it is possible to adequately cluster isolates through a cgMLST approach, but it remains necessary to define proper interpretative criteria.

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Figures

Figure 1.
Figure 1.
Number (and percentage) of E. coli isolates harbouring ARGs or PMs mediating resistance to antimicrobial agents belonging to one, two, three, four, five, six or seven antimicrobial classes.
Figure 2.
Figure 2.
cgMLST tree of the 699 E. coli isolates and respective sample source (inner coloured ring) and DCM laboratory of origin (outer coloured ring). The 23 clusters with ≤15 alleles of dissimilarities are highlighted in blue. The high resolution file is available as Figure S1.
See this image and copyright information in PMC

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