Rise and Fall of a Superbug: Analyzing the epidemic success of a distinct clone of vancomycin-resistant Enterococcus faecium ST117/CT71 in Germany, 2017 - 2024.
Year: 2026
Type: preprint
Abstract: Vancomycin-resistant Enterococcus faecium (VR Efm ) is a major cause of healthcare-associated infections, yet outbreak analysis remains challenging, particularly for prevalent lineages. One of the most striking examples is the Sequence Type (ST) 117/Complex Type (CT) 71/ vanB lineage, whose rapid expansion across Germany coincided with a sharp rise in VRE prevalence observed around 2019. Defining reliable genomic thresholds remains particularly difficult, as current core-genome Multi-Locus Sequence Typing (cgMLST) cutoffs are based largely on expert consensus or limited case series. Here, we evaluate the discriminatory performance of cgMLST and split k-mer analysis (SKA) for resolving relatedness within ST117/CT71 and investigate whether low core-genome diversity represents a lineage-specific trait or a population-wide property of E. faecium . While cgMLST captures the overall population structure of ST117/CT71, SKA provided higher resolution, distinguishing isolates identical by cgMLST. Analysis of 2,505 genomes showed that ST117/CT71 does not exhibit reduced allelic variability compared with other hospital-adapted lineages, suggesting that limited core-genome diversity is a broader population characteristic. Complementary transposon analyses further identified two temporally distinct ST117/CT71 sublineages carrying different Tn1549-like structures. To assess allelic variation within confirmed transmission events, we analyzed 138 outbreak clusters from 96 hospitals. Outbreak-associated isolates showed sharply compressed allelic differences (median = 1), with 90% of pairwise comparisons falling within ≤9 alleles. Thus, the commonly applied ≤20-allele threshold risks overestimating genomic relatedness and grouping unrelated isolates. Based on these data, we propose lowering the cgMLST alert threshold to ≤9 alleles for initial cluster detection of local outbreaks, followed by confirmatory high-resolution analyses such as SKA.
Institution: Robert Koch Institute
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225821504
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