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New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020)
INTRODUCTION: Listeriosis, caused by infection with Listeria monocytogenes (Lm), is a relatively rare but severe disease with one of the highest mortality rates among bacterial foodborne illnesses. A better understanding on the degree of Lm clustering, the temporal distribution of the clusters, and...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10118018/ https://www.ncbi.nlm.nih.gov/pubmed/37089559 http://dx.doi.org/10.3389/fmicb.2023.1147137 |
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author | Coipan, Claudia E. Friesema, Ingrid H. M. van Hoek, Angela H. A. M. van den Bosch, Tijs van den Beld, Maaike Kuiling, Sjoerd Gras, Lapo Mughini Bergval, Indra Bosch, Thijs Wullings, Bart van der Voort, Menno Franz, Eelco |
author_facet | Coipan, Claudia E. Friesema, Ingrid H. M. van Hoek, Angela H. A. M. van den Bosch, Tijs van den Beld, Maaike Kuiling, Sjoerd Gras, Lapo Mughini Bergval, Indra Bosch, Thijs Wullings, Bart van der Voort, Menno Franz, Eelco |
author_sort | Coipan, Claudia E. |
collection | PubMed |
description | INTRODUCTION: Listeriosis, caused by infection with Listeria monocytogenes (Lm), is a relatively rare but severe disease with one of the highest mortality rates among bacterial foodborne illnesses. A better understanding on the degree of Lm clustering, the temporal distribution of the clusters, and their association with the various food sources is expected to lead to improved source tracing and risk-based sampling. METHODS: We investigated the genomic epidemiology of Lm in the Netherlands between 2010 and 2020 by analyzing whole-genome-sequencing (WGS) data of isolates from listerioss patients and food sources from nationwide integrated surveillance and monitoring. WGS data of 756 patient and 770 food/environmental isolates was assessed using core-genome multi-locus sequence typing (cgMLST) with Hamming distance as measure for pairwise distances. Associations of genotype with the epidemiological variables such as patient’s age and gender, and systematic use of specific drugs were tested by multinomial logistic regressions. Genetic differentiation of the Lm within and between food categories was calculated based on allele frequencies at the 1701 cgMLST loci in each food category. RESULTS: We confirmed previous results that some clonal complexes (CCs) are overrepresented among clinical isolates but could not identify any epidemiological risk factors. The main findings of this study include the observation of a very weak attribution of Lm types to food categories and a much better attribution to the producer level. In addition, we identified a high degree of temporal persistence of food, patient and mixed clusters, with more than half of the clusters spanning over more than 1 year and up to 10 years. DISCUSSION: Taken together this would indicate that identifying persistent contamination in food production settings, and producers that process a wide variety of raw food produce, could significantly contribute to lowering the Lm disease burden. |
format | Online Article Text |
id | pubmed-10118018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101180182023-04-21 New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) Coipan, Claudia E. Friesema, Ingrid H. M. van Hoek, Angela H. A. M. van den Bosch, Tijs van den Beld, Maaike Kuiling, Sjoerd Gras, Lapo Mughini Bergval, Indra Bosch, Thijs Wullings, Bart van der Voort, Menno Franz, Eelco Front Microbiol Microbiology INTRODUCTION: Listeriosis, caused by infection with Listeria monocytogenes (Lm), is a relatively rare but severe disease with one of the highest mortality rates among bacterial foodborne illnesses. A better understanding on the degree of Lm clustering, the temporal distribution of the clusters, and their association with the various food sources is expected to lead to improved source tracing and risk-based sampling. METHODS: We investigated the genomic epidemiology of Lm in the Netherlands between 2010 and 2020 by analyzing whole-genome-sequencing (WGS) data of isolates from listerioss patients and food sources from nationwide integrated surveillance and monitoring. WGS data of 756 patient and 770 food/environmental isolates was assessed using core-genome multi-locus sequence typing (cgMLST) with Hamming distance as measure for pairwise distances. Associations of genotype with the epidemiological variables such as patient’s age and gender, and systematic use of specific drugs were tested by multinomial logistic regressions. Genetic differentiation of the Lm within and between food categories was calculated based on allele frequencies at the 1701 cgMLST loci in each food category. RESULTS: We confirmed previous results that some clonal complexes (CCs) are overrepresented among clinical isolates but could not identify any epidemiological risk factors. The main findings of this study include the observation of a very weak attribution of Lm types to food categories and a much better attribution to the producer level. In addition, we identified a high degree of temporal persistence of food, patient and mixed clusters, with more than half of the clusters spanning over more than 1 year and up to 10 years. DISCUSSION: Taken together this would indicate that identifying persistent contamination in food production settings, and producers that process a wide variety of raw food produce, could significantly contribute to lowering the Lm disease burden. Frontiers Media S.A. 2023-04-06 /pmc/articles/PMC10118018/ /pubmed/37089559 http://dx.doi.org/10.3389/fmicb.2023.1147137 Text en Copyright © 2023 Coipan, Friesema, van Hoek, van den Bosch, van den Beld, Kuiling, Mughini Gras, Bergval, Bosch, Wullings, van der Voort and Franz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Coipan, Claudia E. Friesema, Ingrid H. M. van Hoek, Angela H. A. M. van den Bosch, Tijs van den Beld, Maaike Kuiling, Sjoerd Gras, Lapo Mughini Bergval, Indra Bosch, Thijs Wullings, Bart van der Voort, Menno Franz, Eelco New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) |
title | New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) |
title_full | New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) |
title_fullStr | New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) |
title_full_unstemmed | New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) |
title_short | New insights into the epidemiology of Listeria monocytogenes – A cross-sectoral retrospective genomic analysis in the Netherlands (2010–2020) |
title_sort | new insights into the epidemiology of listeria monocytogenes – a cross-sectoral retrospective genomic analysis in the netherlands (2010–2020) |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10118018/ https://www.ncbi.nlm.nih.gov/pubmed/37089559 http://dx.doi.org/10.3389/fmicb.2023.1147137 |
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