Listeria monocytogenes (Lm) is a major foodborne pathogen widely distributed in nature, often associated with outbreaks of fatal listeriosis. In Israel, listeriosis is a notifiable disease and all strains from human cases and food samples are submitted to the Listeria National Reference Center (LNRC) for subtyping, facilitating the identification of molecular clusters that reflect outbreaks and the sources of contamination.
Since 2016, we implemented and evaluated whole genome sequencing (WGS) for routine molecular typing and epidemiologic surveillance. Lm isolates from human (N=101) and food sources (N=28) were analyzed by WGS in parallel with the previous standard method, pulsed-field gel electrophoresis (PFGE). WGS significantly improved and refined isolate discrimination, reflected population phylogeny, and enabled in-depth characterization and comparison with global strains.
Whole genome multi locus sequence typing (wgMLST) based on 4,804 loci enabled detection in high resolution of 78 separate profiles compared with 53 profiles by PFGE, thus eliminating pseudo-clusters. Notably, 3 wgMLST clusters included more than one PFGE profile. Among 24 (86%) food isolates suspected to be the source of clinical cases by PFGE, only 5 (18%) clustered together with clinical cases by wgMLST. This data was instrumental in traceback investigations of major outbreaks in Israel during the study period.
The Lm population included 18 different STs, of which the most common among clinical isolates were ST3 (27%), ST517 (15%), ST2 (15%), ST1 (9%) and ST5 (8%). The presence of survival and virulence genes, extracted from WGS analysis, was associated with specific lineages and sequence types.
Our results demonstrate major benefits for WGS based surveillance in terms of accuracy, phylogeny, and comparability with global data. Our work highlights the utility of routine Lm WGS in focusing and informing epidemiological investigations essential for early detection of outbreaks and prevention of food contamination.