Abstract

Listeria monocytogenes (L. monocytogenes) is a ubiquitous organism that can easily enter the food chain. Infection with L. monocytogenes can cause invasive listeriosis. Since 2014, in Austria, L. monocytogenes isolates from human and food/food-associated samples have been provided on a mandatory basis by food producers and laboratories to the National Reference Laboratory. Since 2017, isolates undergo routinely whole genome sequencing (WGS) and core genome Multilocus Sequence Typing (cgMLST) for cluster analyses. Aims of this study were to characterize isolates and clusters of 2017 by using WGS data and to assess the usefulness of this isolate-based surveillance for generating hypotheses on sources of invasive listeriosis in real-time. WGS data from 31 human and 1744 non-human isolates originating from 2017, were eligible for the study. A cgMLST-cluster was defined as two or more isolates differing by ≤10 alleles. We extracted the sequence types (STs) from the WGS data and analyzed the food subcategories meat, fish, vegetable and diary for associations with the ten most prevalent STs among food, through calculating prevalence ratios (PR) with 95% confidence intervals (CI). The three most frequent STs among the human isolates were ST1 (7/31; 22.6%), ST155 (4/31; 12.9%) and ST451 (3/31; 9.7%) and among the non-human isolates ST451 (614/1744; 35.2%), ST8 (173/1744, 10.0%) and ST9 (117/1744; 6.7%). We found ST21 associated with vegetables (PR: 11.39, 95% CI: 8.32–15.59), ST121 and ST155 with fish (PR: 7.05, 95% CI: 4.88–10.17, PR: 3.29, 95% CI: 1.86–5.82), and ST511, ST7 and ST451 with dairy products (PR: 8.55, 95% CI: 6.65–10.99; PR: 5.05, 95% CI: 3.83–6.66, PR: 3.03, 95% CI: 2.02–4.55). We identified 132 cgMLST-clusters. Six clusters contained human isolates (ST155, ST1, ST101, ST177, ST37 and ST7) and for five of those cgMLST-based cluster analyses solely was able to hypothesize the source: an Austrian meat processing company, two Austrian cheese manufacturers and two vegetable processing companies, one based in Austria and the other in Belgium. Determining routinely STs in food isolates by WGS allows to associate STs with food products. Real-time WGS of L. monocytogenes isolates provided mandatorily, proved to be useful in promptly generating hypotheses on sources of invasive listeriosis.

Highlights

  • Listeria monocytogenes (L. monocytogenes) is a Gram positive bacterium, able to survive in extreme environmental conditions, which enables the microorganism to cause food-borne infections and outbreaks (Buchanan et al, 2017)

  • Rapid and accurate typing methods of L. monocytogenes isolates are indispensable for timely identification of molecular clusters of isolates originating from food products, foodassociated surfaces and patients with listeriosis (Radoshevich and Cossart, 2017)

  • Routine Whole Genome Sequence (WGS) of obligatorily provided isolates of L. monocytogenes showed to be useful in promptly generating hypotheses on the sources of invasive listeriosis

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Summary

Introduction

Listeria monocytogenes (L. monocytogenes) is a Gram positive bacterium, able to survive in extreme environmental conditions, which enables the microorganism to cause food-borne infections and outbreaks (Buchanan et al, 2017). Contamination with L. monocytogenes can occur at any stage of the food chain (farm, production and retail). Rapid and accurate typing methods of L. monocytogenes isolates are indispensable for timely identification of molecular clusters of isolates originating from food products, foodassociated surfaces and patients with listeriosis (Radoshevich and Cossart, 2017). Whole Genome Sequence (WGS)-based typing, and especially core genome (cg)Multilocus Sequence-based Typing, is nowadays the preferred method for characterization of L. monocytogenes by genoserogroup (SG), clonal complex (CC), sequence type (ST), complex type (CT) and for cluster analyses to hypothesize the sources of invasive listeriosis, in particular, when information on patients’ food exposure is lacking (Buchanan et al, 2017; Moura et al, 2017; Lüth et al, 2018). In Austria, in the year 2017, WGS replaced PFGE for typing and cluster analyses, using the cgMLST scheme established by Ruppitsch and coworkers (Ruppitsch et al, 2015)

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