Introduction: Salmonella (S.) Enteritidis, the most prevalent clinical Salmonella serovar worldwide, is responsible for ~50% of human salmonellosis cases in Europe (~4,000 reported cases p.a. in Germany) and frequently causes large, often multinational food-borne outbreaks. Due to the inherent clonality of this serovar unambiguous case assignment and source identification was often impeded by the insufficient discriminatory power of former subtyping methods.

Objectives: Therefore, S. Enteritidis is one of the prioritized organisms for a comprehensive genome-based surveillance at the NRC, aiming to enhance the discrimination, thus resulting in a more accurate differentiation of potential outbreak events and definite identification of the causative (food) source.

Methods: Bacterial genomic DNA is prepared for Illumina short read sequencing. Raw Reads are analyzed with Ridom SeqSphere+. Core genome (cg)MLST (EnteroBase scheme) is used to determine the phylogenetic relationship and potential cluster affiliation. Genomes from clinical clusters are compared with strains of non-human origin, especially from the food production chain (provided by the NRL for Salmonella at BfR) on a regular basis.

Results: In the period 2018-2023 about 3,900 S. Enteritidis genomes have been analyzed at the NRC. Applying a max. pairwise distance of 3 AD, cgMLST revealed 186 genomic clusters (24 of them comprising >30 isolates and 80 <5 isolates). The biggest cluster contains 282 isolates. Out of those, matching food or animal isolates were identified for 29 clusters. Nevertheless, even cgMLST sometimes provides ambiguous results, highlighting the need for confirmatory epidemiological data.

Summary: WGS-based methods for depicting relationships within the S. Enteritidis population give a comprehensive overview about the circulating lineages and in general reliably point out developing clusters allowing more focused outbreak investigations and facilitating subsequent control measures and preventive activities. Here, we share our experiences from six years of WGS-based surveillance for S. Enteritidis, illustrating the benefits but also describing the challenges that evolved with this new method.