Michael Pietsch (Wernigerode / DE), Sandra Simon (Wernigerode / DE), Eva Trost (Wernigerode / DE), Anika Meinen (Berlin / DE), Laura Giese (Berlin / DE), Marina C. Lamparter (Berlin / DE), Jennie Fischer (Berlin / DE), Antje Flieger (Wernigerode / DE)
Introduction: In Germany, salmonellosis is the second most frequently reported bacterial diarrheal disease and the zoonotic Salmonella cause many regional and multinational food-borne outbreaks. Among the reported Salmonella serovars in Germany, S. Typhimurium is the 2nd most common, responsible for 20-30% of cases each year and therefore has become one of the prioritized organisms for a comprehensive genome-based surveillance.
Goals: In this study we analyzed S. Typhimurium infection clusters epidemiologically and technically, in order to asses different cluster types, cluster plausibility of an epidemiological link, cross-sectoral relevance, and best suitable thresholds for cluster definition.
Methods: 2020-2023, the NRC for Salmonella received 14,252 unique clinical Salmonella isolates, of which 4,111 were S. Typhimurium (28.8% of all received isolates). Bioinformatic analysis of raw sequencing data and subsequent cgMLST (3.002 alleles) and cluster analysis were performed using Ridom SeqSphere+. Salmonella isolates of animal or food origin, matching clinical Salmonella clusters, were obtained from the NRL for Salmonella at the German Federal Institute for Risk Assessment.
Results: From 2020-2023, a total of 3,320 S. Typhimurium isolates were analyzed, covering 61% of received isolates in 2020 up to 97.5% in 2023. 1,205 isolates were attributed into curated clusters, resulting in 81 clusters of variable size (4-97 isolates per cluster). Plausibility of an epidemiological link has been assessed for these clusters. Matching with isolates of non-human origin was possible in many cases. However, automatically assignment of clusters using variable threshold settings led to expanded and deviating clusters, highlighting the need for carefully selected and constantly reviewed cluster definitions.
Summary: Intensified genome-based surveillance of S. Typhimurium led to an increase in cluster observations and cluster size. The number of clusters, their growth kinetics and regional distribution varied between different years of analysis and depended on the ratio of sequenced/received isolates and are strongly influenced by cluster definitions and detection methods.