Abstract
Abstract Background Listeriosis is a life-threatening disease in human as well as animals, cows and sheep are the most sensible to the disease. Correlation to feed is well documented (silage). Some clonal complexes (CCs) are more virulent than others and frequently involved in animal and human listeriosis. Whole genome sequencing (WGS) and in silico CCs identification and core genome multilocus sequence typing (cgMLST) determination are the best way to characterize isolates and confirm connection between clinical strains and source of contamination. This work aimed to demonstrate the advantages of using WGS to find the source of Listeria monocytogenes (Lm), causing an outbreak in an ovine farm in Abruzzo region. Methods Lm was detected according to ISO 11290-1:2017. Serogroup was determined by multiplex PCR. WGS data were obtained using Illumina platform. Sequences were used to assess CCs and cgMLST according to BIGSdb Pasteur platform. Two brain samples and 1 lymph node from 2 sheep, one sample of silage (15 analytical portion), and 1 sample of hay were tested. Results Lm was detected in all animal specimens and in 2 analytical portions of feed (silage) tested. Out of 35 colonies detected 28 were identified as Lm (27 serogoup IVb and 1 sample of silage serogroup IIa). Five colonies were selected for WGS (one from each animal brain, one from the lymph node and one from each positive analytical portion of silage), among them only one colony from the silage showed the same CC of the strains isolated from sheep (CC1). cgMLST revealed no allelic distances between these strains. Conclusions CC1 is the main virulent clone among Lm isolates often involved in human and animal outbreak. Feed may be a vehicle for Lm and could be the outbreak source. Cases ceased after removing the silage. Use of WGS is a definitive help in source attribution when feed is available and the sampling is done in a correct manner. Key messages Silage can be cause of listeriosis in livestock. WGS can improve source attribution of outbreaks detecting the relatedness of the strains and improving the epidemiological investigation in case of outbreak.
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