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Small-Scale Comparative Genomic Analysis of Listeria monocytogenes Isolated from Environments of Salmon Processing Plants and Human Cases in Norway

1
Department of Process Technology, Nofima—Norwegian Institute of Food, Fisheries and Aquaculture Research, Richard Johnsens Gate 4, 4021 Stavanger, Norway
2
Norwegian Institute of Public Health, Lovisenberggata 8, 0456 Oslo, Norway
3
Norwegian Sequencing Centre, Department of Medical Genetics, Oslo University Hospital, 0450 Oslo, Norway
4
Institute of Marine Research, Section for Contaminants and Biohazards, Nordnesgaten 50, 5005 Bergen, Norway
*
Author to whom correspondence should be addressed.
Received: 30 April 2021 / Revised: 7 June 2021 / Accepted: 7 June 2021 / Published: 16 June 2021
(This article belongs to the Section Infectious Disease Epidemiology, Prevention and Control)

Abstract

Listeria monocytogenes is a food-borne bacterium that give rise to the potentially life-threatening disease listeriosis. Listeriosis has been mandatorily notifiable in Norway since 1991. All clinical L. monocytogenes isolates are sent to the Norwegian Institute of Public Health (NIPH) for typing. Since 2005 Multi-Locus Variable number tandem repeats Analysis (MLVA) has been used for typing but was recently replaced by whole genome sequencing using core genome Multi-Locus Sequence Typing (cgMLST). In the present study, L. monocytogenes isolates collected at salmon processing plants in Norway in 2007 (n = 12) and 2015 (n = 14) were first subject to MLVA. Twelve clinical L. monocytogenes isolates with matching MLVA profile and sampling time were selected from the strain collection at NIPH. Twenty-one isolates from the salmon processing plants and all clinical isolates (n = 12) were whole genome sequenced and compared using cgMLST and in silico detection of virulence genes. cgMLST revealed four pairs of environmental–human isolates with ≤10 allelic differences over 1708 genes, indicating that they may be assigned as clonal, with the implication that they are descended from the same recent ancestor. No relevant difference in carriage of virulence genes was found between environmental or human isolates. The present study shows that L. monocytogenes strains that genetically resemble contemporary isolates from human listeriosis circulate in Norwegian salmon slaughterhouses, and carry the same virulence genes.
Keywords: food-borne zoonoses; food safety; infectious disease; Listeria; public health; salmon; whole genome sequencing food-borne zoonoses; food safety; infectious disease; Listeria; public health; salmon; whole genome sequencing

1. Introduction

Listeria monocytogenes is a food-borne pathogen that can cause listeriosis, a severe invasive infection in humans with particularly high lethality (25%–30%) and hospitalization (>92%) rates [1]. It has been estimated that listeriosis resulted in 23,150 illnesses, 5463 deaths and 172,823 disability-adjusted life-years globally in 2010 [2]. A global trend of increasing sporadic listeriosis cases was observed at the beginning of the new millennium, especially in the age group >60 [3,4,5,6], but over the 5-year period during 2015–2019, the trend has been flat after a long period of increase [7]. In addition to the elderly, individuals with impaired immune systems, pregnant women, and new-borns are predisposed to listeriosis [8,9]. In the EU, notifications for L. monocytogenes in food products have increased in numbers since 2009 and is, next to Salmonella, by far the most frequently reported pathogen [10,11]. An extensive European baseline study was conducted in 2010 and 2011, including a total of 10,053 samples of certain ready-to-eat (RTE) foods from 3632 retail outlets in 27 countries [12]. L. monocytogenes were detected in 10.3% of 3052 fresh hot or cold smoked and gravad fish at the end of shelf-life. By the use of whole genome sequencing (WGS), a retrospective study based on the 2010–2011 baseline study indicated that, although all RTE categories were associated with sporadic human listeriosis cases, smoked fish was the dominating source of sporadic human food-borne listeriosis [13]. L. monocytogenes in cold-smoked fish products is still an important cause of food-borne outbreaks [11].
L. monocytogenes is frequently isolated from slaughterhouses processing farmed salmon both in Norway [14,15,16], and abroad [17,18,19]. L. monocytogenes has been found in smoked salmon in several studies [20,21,22]. In Norway, the frequency was 9% in 1991 [22] and 4.9% in 2003 [23]. In a review of 26 publications published between 2000 and 2015, mostly from Europe but also including Japan and North America, it was found that the prevalence in retail cold smoked salmon (CSS) varied between 0 and 61%, with an average of 9.8%, but CSS was never implicated in any confirmed listeriosis outbreaks worldwide up until 2015 [21]. However, after 2015, CSS has been implicated in listeriosis outbreaks in Denmark and France [24,25] and two European multi-country outbreaks [26,27].
The majority of listeriosis cases are sporadic, and the responsible food item is not identified. In Norway, eight foodborne outbreaks have been registered since 2005 [28]. These outbreaks included 47 verified listeriosis cases. Nevertheless, both the number of outbreaks and the number of cases are minimum numbers, because not all outbreaks and cases are discovered and notified. Consequently, epidemiological surveillance becomes increasingly important due to the increase in these sporadic incidents in order to provide critical information about reservoirs and vehicles for the pathogen, and to identify listeriosis food sources, and food safety gaps. Until recently, methods used for typing L. monocytogenes along the food chain and in clinical infections included Pulsed-Field Gel-Electrophoresis (PFGE) and Multi-Locus Variable number tandem repeats Analysis (MLVA). Since the introduction of PFGE in the 1990s and later MLVA, these molecular typing techniques have proven critical for solving outbreaks and identifying clusters that warrant further investigation [29,30]. The discriminatory power of the two methods is, however, inadequate and not always sufficient for outbreak detection and investigation to limit the outbreak and identify the source. It was shown that PFGE was not able to discriminate between pathogenic isolates and pairs of contemporary isolates of human or food origin without any causal relationship [31], thus yielding results of limited value. At present, knowledge of the impact of environmental and food strains on human health is limited. For example, the assumption that all L. monocytogenes strains have a similar virulence, has led to an important lack of data in the dose–response model, as illustrated by Lindqvist and Westöö [32] in the case of RTE salmon and rainbow trout quantitative risk assessment.
WGS has proven to be an invaluable tool for genomic typing of various food-borne pathogens including L. monocytogenes, by providing optimal resolution and enabling comparisons across different epidemiological sectors [13,33]. Coupled to genome-wide gene-by-gene comparisons designated as core genome Multi-Locus Sequence Typing (cgMLST), WGS has become the preferred technology for L. monocytogenes typing, offering an enhanced level of resolution compared to conventional methods. cgMLST has recently been implemented into the routine surveillance of human L. monocytogenes isolates in Norway.
The main objective of the present study was to compare L. monocytogenes isolates collected from Norwegian salmon slaughterhouses, with L. monocytogenes isolates from human cases with the use of WGS, in order to explore the existing L. monocytogenes strains in slaughterhouse environments and their possible association with disease in humans.

2. Materials and Methods

2.1. Bacterial Isolates

Four salmon slaughterhouses designated A, B, C and D, located along the west coast of Norway, were examined for the presence of L. monocytogenes. Plants A–C were visited once during August to September 2015, and plant D was visited in March and September 2015. Sampling was performed as described previously [16]. No L. monocytogenes was found in plant A, but a total of 7 isolates of L. monocytogenes was found at plant B–D, and an additional 7 isolates from plant D isolated during a three-week period in October/November 2015 were acquired from an external laboratory. These 14 samples were genotyped by MLVA. MLVA genotyping was performed as previously described [14] with primer sequences adopted from Lindstedt et al. [34]. All the seven isolates from plant D acquired from the external lab were of the same MLVA genotype. Therefore, only two of these were subject to further analysis, giving nine environmental isolates from 2015. Twelve isolates collected from three other plants in 2007 and previously MLVA typed [14] were re-typed by MLVA and added to the analysis, so that the total number of environmental isolates subject to further analysis was 21.
Medical microbiology laboratories throughout Norway mandatorily forward presumptive L. monocytogenes isolated from clinical specimens to the National Reference Laboratory (NRL) at NIPH for typing. Since 2005 typing has been performed by MLVA [14]. Clinical isolates were selected from the national strain collection at NRL at NIPH. Twelve isolates from 2005 to 2016 corresponding to the different MLVA-profiles identified in the environmental collection were selected for further WGS analysis.

2.2. Library Preparation and Sequencing

DNA was extracted from overnight cultures using the Wizard Genomic DNA purification Kit (Promega, Madison, WI, USA) before Nextera XT DNA Library preparation and paired-end (2 × 300) sequencing on the Illumina MiSeq platform aiming for >50× coverage (Illumina, San Diego, CA, USA). RTA v1.18.54 and bcl2fastq v2.17.1.14 were used for base calling, demultiplexing and converting the data to fastq format. Prior to downstream analyses, adapters used for sequencing and low quality reads were trimmed using Trimmomatic v.033 [35] following the recommendation from the developer. Reads aligning to PhiX genome that was used as spike-in during Illumina sequencing was removed by aligning the data using bbmap v34.56 [36].

2.3. Core Genome Analysis

All analyses performed were integrated into the Ridom SeqSphere+ version 5.1.0 software (Ridom GmbH, Münster, Germany) using the cgMLST scheme developed by Ruppitsch et al. [37]. Briefly, sequenced reads were trimmed until an average base quality of 30 was reached in a window of 20 bases. De novo assembly was performed using Velvet 1.1.04 with default settings. Allele numbers for each gene were assigned automatically in SeqSphere+ and the combination of all alleles in each strain composed the allelic profile. The allelic profiles of the L. monocytogenes strains were based on 1708 genes, 1701 cgMLST genes and seven MLST genes, and were visualised as a neighbour joining tree and a minimum spanning tree using the parameter “pairwise ignoring missing values”. Serogroups were predicted automatically in SeqSphere+ as described by Hyden et al. [38].

2.4. Identification of Virulence Genes

In silico analysis of virulence genes was performed using VirulenceFinder v1.5 (https://cge.cbs.dtu.dk/services/VirulenceFinder/, accessed on 3 May 2021) [39], with default settings (90% ID and 60% minimum length).

2.5. Selection of Reference Genomes

L. monocytogenes EGD-e (NC_003210.1) was used as reference for cgMLST and virulence gene analyses of all isolates.

3. Results

Since 2005, approximately 300 humane L. monocytogenes isolates have been MLVA-typed in Norway, showing more than 100 different MLVA-genotypes. MLVA-profile 7-7-10-10-6 has been the most prevalent, constituting approximately 30% of all clinical isolates. The 21 environmental isolates in the present study divided into 14 different MLVA-genotypes (Table 1). These 14 distinct MLVA genotypes divided into 12 (7-gene) MLST Sequence Types (MLST ST’s) corresponding to 12 CC’s, and 22 cluster types (CT) based on cgMLST. MLVA-profile 7-7-10-10-6 was seen in three environmental isolates. Eight isolates (four environmental and four clinical) belonged to serogroup IVb (Lineage I), and the remaining 23 were in serogroup IIa (Lineage II) (Table 1). Three MLVA-profiles (from four environmental isolates) had never been observed in clinical isolates in Norway.
cgMLST analysis showed that only four of eleven clinical/environmental pairs fell into the same CT (Table 1), and can thus be attributed to the same clone using a cut-off of ≤10 allelic differences over 1708 genes [37]. These pairs were 2HF33-14EP001215 isolated seven years apart and with an allelic difference of four, based on 1708 genes. Further, 3BS29 -1108-0593 were isolated one year apart and with an allelic difference of five, 3BS90-1106-3928 also isolated one year apart and with an allelic difference of five, and finally 3BS44-1110-0057 isolated three years apart and with an allelic difference of ten (Figure 1B).
In order to investigate potential associations of presence/absence of virulence genes with STs or origin of the isolate (environmental versus clinical), virulence genes were predicted in silico using VirulenceFinder in all genome sequences isolated from the environment and clinical cases, as well as in the EGD-e reference genome (GenBank accession no. NC_003210.1). The EGD-e reference genome carried 82 virulence genes, which was the same number found in ST18, ST20 and ST398 isolates. ST7, ST8, and ST101 isolates harboured 80 or 81 virulence genes, whereas the remaining STs isolates carried between 74 and 79 virulence genes (Supplementary Table S1). Out of the 82 virulence genes, 72 were observed in all isolates and with similar frequency in environmental and clinical isolates. There was no statistical difference in the number of virulence genes found between clinical and environmental isolates (Students’ t-test, p = 0.30), and with only very few exceptions, the same virulence gene(s) was missing in environmental and in clinical isolates inside each ST (Supplementary Table S1).

4. Discussion

It is often found that isolates from the seafood and processing environment are identical to clinical isolates based on different subtyping strategies [14,40,41,42]. Rocourt et al. [43] reviewed the data accumulated from phenotypic and molecular typing methods and concluded that strains responsible for most major outbreaks between 1981 and 2000 belonged to a small number of clones consisting of closely related strains as evidenced by ribotyping, isoenzyme pattern and DNA profile analysis. In the Danish fish processing industry, strains belonging to one particular persistent RAPD (random amplification of polymorphic DNA) subtype of L. monocytogenes have been isolated over several years in different processing plants [44]. WGS of two such isolates isolated six years apart, from two different plants with no intertrade relationship, revealed that they were almost identical, as their predicted proteomes differed by only two proteins [45]. However, WGS has also revealed that L. monocytogenes strains that are identical by MLVA and MLST and have indistinguishable PFGE and fAFLP (fluorescent amplified fragment length polymorphism) patterns may not be clonal strains [31,46]. Our data corroborates these earlier finding demonstrating the superior potential of WGS/cgMLST compared to MLVA in genetic discrimination between isolates.
Salmon slaughterhouses and processing plants may be colonized by L. monocytogenes, while others are free of the bacteria [14,16,20]. Although L. monocytogenes is likely to be consistently reintroduced into processing plants from a variety of sources, including fish raw material, water and personnel, there are indications that L. monocytogenes at environmental sites and L. monocytogenes in the raw material represent different bacterial populations [47]. This has led to the hypothesis that persistent L. monocytogenes strains represent the predominant source of environmental contamination in processing plants [47,48,49,50]. Earlier studies have demonstrated that salmon processing plants often harbour their own specific populations of L. monocytogenes subclones (e.g., RAPD types) [44,48]. These persistent strains may be specially adapted to the processing plant environment and be extremely difficult to sanitize by standard hygiene procedures [51,52,53]. Persistence of L. monocytogenes in food processing plants has therefore been hypothesized to be an important factor and the root cause of a number of listeriosis outbreaks [54,55].
No relevant difference in carriage of virulence genes were found in relation to isolates of environmental or clinical origin in the present study. By using VirulenceFinder for the in-silico analysis of virulence potential of ST14, ST121, and ST224 isolates from a rabbit meat processing plant, Palma et al. [56] found that the two genes lmo2026 and InlF were absent or found truncated in all ST14 and ST121 isolates. This is consistent with the current analysis, in that lmo2026 was not detected in any ST14 or ST121 isolates, but was also absent in ST2, ST6, ST8, and ST31 isolates. InlF was absent in ST14 and ST121 isolates, and also in ST2 and ST6 isolates. Among other genes not detected by the in-silico analysis, inlK, gtcA, Aut and Ami (all absent in ST2 and ST6 isolates), ActA (absent in ST31 and ST121 isolates), inlJ (absent in ST14 and ST121 isolates), and vip (absent in ST2, ST6, ST7, ST8, and ST31 isolates) where the most prominent. However, this seems more linked to ST than to origin. The four clones CC1, CC2, CC3, and CC9 represents 50% of food isolates and 68% of clinical isolates globally [57]. Important factors to consider are that the high frequency in clinical manifestations of apparently less virulent strains (when based only on the presence/absence of virulence genes) is highly favoured and correlated to their high prevalence in food sources, and, second, that there may be a relatively high degree of redundancy in L. monocytogenes virulence genes. The small dataset analysed in the present study does not allow us to draw general conclusions on the distribution of virulence genes in environmental compared to clinical isolates. Although based on a limited dataset, the present studies give no evidence to support the hypothesis that virulence genes are differentially distributed in clinical and environmental isolates and is thus in accordance with the large-scale analysis of Painset et al. [58]. It must be noted, however, that the VirulenceFinder analysis is only based on numbers of genes present, not variants or truncated genes. It has been shown that differences in virulence can be associated to lineages and CCs, and specific variants and truncated genes are pointed out as the main features associated with these differences [58,59]. Frequent loss or truncation of genes described to be vital for virulence or pathogenicity has been confirmed as a recurring pattern in L. monocytogenes [60].
We acknowledge that the dataset presented here is limited, and that a larger study is needed to establish a possible epidemiological connection between salmon slaughterhouse derived L. monocytogenes and listeriosis. To establish the most discriminatory epidemiological relationship between environmental and clinical populations, cgMLST analysis of the WGS data must be complemented with Single-Nucleotide Polymorphism (SNP) analysis [61,62], but it was beyond the scope of the present study to further infer any such epidemiological links. It should also be remembered that clinical isolates were selected to match environmental isolates (based on MLVA). Although MLVA subtypes of clinical isolates included here represents approximately 35% of clinical manifestations in Norway from 2005 to 2016, we acknowledge that this may bias the results.
WGS combined with cgMLST has proven to be an invaluable tool for genomic typing of various food-borne pathogens including L. monocytogenes, by providing optimal resolution and enabling comparisons across different epidemiological sectors [13,33]. In addition to molecular typing, WGS may be applied for the identification of genes contributing to persistence of L. monocytogenes in the food production plants and to determine the human virulence potential of these strains [13,45,63]. The use of WGS also in food, agricultural, and environmental L. monocytogenes surveillance, will significantly enhance foodborne L. monocytogenes source identification, risk assessment, and understanding of L. monocytogenes transmission routes. It will allow for comparison between clinical and food/environmental L. monocytogenes strains, and further enable the food and agricultural industry to elucidate factors that leads to L. monocytogenes persistence and biofilm formation, as well as tolerance to chemicals, detergents and food preservatives, heath treatment, etc., and thus make it easier to improve food safety.
The present study is especially relevant considering the recent (2015–2019) outbreaks in Denmark, Germany, France, Estonia, Finland, and Sweden which were linked to Norwegian salmon smoked in Poland and Estonia, where a lack of WGS data complicated identification of the source of the contamination [26,27]. Ultimately, epidemiological evidence and multiple WGS analyses should be combined to elucidate the possible role of environmental L. monocytogenes as the subsequent source of listeriosis.

5. Conclusions

The present study shows that the genetic distance between environmental and clinical isolates may be very short, i.e., ≤10 allelic differences over 1708 genes, indicating that they may be assigned as clonal, with the implication that they are descended from the same recent ancestor. Out of 82 virulence genes, 72 were observed in all isolates and with similar frequency in environmental and clinical isolates, indicating that no relevant difference in carriage of virulence genes were found in relation to environmental or human origin. Even though our data do not show a conclusive epidemiological link between listeriosis patients and commercially produced salmon products in Norway, several outbreaks with salmon as the responsible food source have been documented in the international literature. It is important to stress, however, that it is still a prerequisite in listeriosis source identification and epidemiological surveillance that similar genotypes are found in both incriminated food products and from clinical manifestations and can be coupled to the patients’ history of food intake, and that although identical cgMLST profiles are found both in salmon processing plants and in human isolates, it cannot be concluded that salmon from these plants have served as vehicles for human listeriosis.

Supplementary Materials

The following are available online at https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/hygiene1010005/s1, Table S1: Supplementary_Table_1.xlsx.

Author Contributions

T.L., L.T.B., B.R. and B.T.L. conceived and designed the study. T.L. and B.T.L. sampled the environmental samples, cultivated the isolates, and isolated DNA. L.T.B. collected clinical isolates and performed MLVA analysis. A.Y.M.S. and U.N. performed WGS and cgMLST analysis. T.L. drafted the manuscript. All authors contributed to the writing and approved the final manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

T.L. and B.R. are grateful for financial support from the Research Council of Norway through the project ‘Fillet-O’ (project no. 233689) and the RFF Vest funded project ‘SalmoSave’ (project no. 284667).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All environmental isolate sequences and assembled genomes used in this study are deposited as a Bioproject at DDBJ/ENA/GenBank under the accession JAHHPW000000000. The version described in this paper is version JAHHPW010000000. The accession no.’s of the WGS are CP050023 to CP050030, CP075871 to CP075878, CP050129, and CP076051. All CLINICAL isolate sequences and assembled genomes of this study were used after agreement with NRL, so that restrictions may apply to the use and reproduction of these data. Data are however available from the authors upon reasonable request and with permission of NRL and NIPH.

Acknowledgments

Ingrid B. Eri is acknowledged for technical field and laboratory assistance. The sequencing service was provided by the Norwegian Sequencing Centre (www.sequencing.uio.no, accessed on 3 May 2021), a national technology platform hosted by the University of Oslo.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. ANSES. Data Sheet on Foodborne Biological Hazards—Listeria Monocytogenes; ANSES—French Agency for Food, Environmental and Occupational Health & Safety: Maisons-Alfort, France, 2011; Available online: https://www.anses.fr/en/system/files/MIC2011sa0171FiEN.pdf (accessed on 4 March 2021).
  2. De Noordhout, C.M.; Devleesschauwer, B.; Angulo, F.J.; Verbeke, G.; Haagsma, J.; Kirk, M.; Havelaar, A.; Speybroeck, N. The global burden of listeriosis: A systematic review and meta-analysis. Lancet Infect. Dis. 2014, 14, 1073–1108. [Google Scholar] [CrossRef]
  3. Gillespie, I.A.; Mook, P.; Little, C.L.; Grant, K.; Adak, G.K. Listeria monocytogenes infection in the over-60 s in England between 2005 and 2008: A retrospective case-control study utilizing market research panel data. Foodborne Pathog. Dis. 2010, 7, 1373–1379. [Google Scholar] [CrossRef] [PubMed]
  4. Kvistholm Jensen, A.; Ethelberg, S.; Smith, B.; Moller Nielsen, E.; Larsson, J.; Molbak, K.; Christensen, J.J.; Kemp, M. Substantial increase in listeriosis, Denmark 2009. EuroSurveill. Bull. Eur. Sur Les Mal. Transm. Eur. Commun. Dis. Bull. 2010, 15, 19522. [Google Scholar]
  5. Siegman-Igra, Y.; Levin, R.; Weinberger, M.; Golan, Y.; Schwartz, D.; Samra, Z.; Konigsberger, H.; Yinnon, A.; Rahav, G.; Keller, N.; et al. Listeria monocytogenes infection in Israel and review of cases worldwide. Emerg. Infect. Dis. 2002, 8, 305–310. [Google Scholar] [CrossRef] [PubMed]
  6. Goulet, V.; Hedberg, C.; Le Monnier, A.; de Valk, H. Increasing incidence of listeriosis in France and other European countries. Emerg. Infect. Dis. 2008, 14, 734–740. [Google Scholar] [CrossRef] [PubMed]
  7. EFSA and ECDC. The European Union One Health 2019 zoonoses report. EFSA J. 2021, 19. [Google Scholar] [CrossRef]
  8. Mammina, C.; Parisi, A.; Guaita, A.; Aleo, A.; Bonura, C.; Nastasi, A.; Pontello, M. Enhanced surveillance of invasive listeriosis in the Lombardy region, Italy, in the years 2006–2010 reveals major clones and an increase in serotype 1/2a. BMC Infect. Dis. 2013, 13. [Google Scholar] [CrossRef] [PubMed]
  9. Desai, R.W.; Smith, M.A. Pregnancy-related Listeriosis. Birth Defects Res. 2017, 109, 324–335. [Google Scholar] [CrossRef]
  10. RASFF. The Rapid Alert Systems for Food and Feed. In Annual Report 2014; European Commission—Health and Food Safety: Brussels, Belgium, 2015. [Google Scholar]
  11. RASFF. The Rapid Alert Systems for Food and Feed. In Annual Report 2019; European Commission—Healt and Food Safety: Luxembourg, 2020. [Google Scholar]
  12. EFSA. Analysis of the baseline survey on the prevalence of Listeria monocytogenes in certain ready-to-eat foods in the EU, 2010-2011; Part A: Listeria monocytogenes prevalence estimates. EFSA J. 2013, 11. [Google Scholar] [CrossRef]
  13. Nielsen, E.M.; Björkman, J.T.; Kiil, K.; Grant, K.; Dallman, T.; Painset, A.; Amar, C.; Roussel, S.; Guillier, L.; Felix, B.; et al. Closing Gaps for Performing a Risk Assessment on Listeria Monocytogenes in Ready-to-Eat (RTE) Foods: Activity 3, the Comparison of Isolates from Different Compartments Along the Food Chain, and from Humans Using Whole Genome Sequencing (WGS) Analysis. EFSA Supporting Publ. 2017, 170. [Google Scholar] [CrossRef]
  14. Lunestad, B.T.; Truong, T.T.T.; Lindstedt, B.A. A multiple-locus variable-number tandem repeat analysis (MLVA) of Listeria monocytogenes isolated from Norwegian salmon-processing factories and from listeriosis patients. Epidemiol. Infect. 2013, 141, 2101–2110. [Google Scholar] [CrossRef] [PubMed]
  15. Rørvik, L.M.; Skjerve, E.; Knudsen, B.R.; Yndestad, M. Risk factors for contamination of smoked salmon with Listeria monocytogenes during processing. Int. J. Food Microbiol. 1997, 37, 215–219. [Google Scholar] [CrossRef]
  16. Løvdal, T.; Giske, L.A.L.; Bjørlykhaug, E.; Eri, I.B.; Mork, O.J. Hygienic standards and practices in Norwegian salmon processing plants. J. Hyg. Eng. Des. 2017, 20, 3–11. [Google Scholar]
  17. Rotariu, O.; Thomas, D.J.I.; Goodburn, K.E.; Hutchison, M.L.; Strachan, N.J.C. Smoked salmon industry practices and their association with Listeria monocytogenes. Food Control 2014, 35, 284–292. [Google Scholar] [CrossRef]
  18. Djordjevic, V.; Trbovic, D.; Lakicevic, B.; Nastasijevic, I.; Jankovic, V.; Baltic, T.; Dimitrijevic, M. Microbiological safety and quality of salmon: Health benefits and risk. Meat Technol. 2016, 57, 120–125. [Google Scholar]
  19. Dass, S.C.; Abu-Ghannam, N.; Antony-Babu, S.; Cummins, E.J. Ecology and molecular typing of L. monocytogenes in a processing plant for cold-smoked salmon in the Republic of Ireland. Food Res. Int. 2010, 43, 1529–1536. [Google Scholar] [CrossRef]
  20. Rørvik, L.M. Listeria monocytogenes in the smoked salmon industry. Int. J. Food Microbiol. 2000, 62, 183–190. [Google Scholar] [CrossRef]
  21. Løvdal, T. The microbiology of cold smoked salmon. Food Control 2015, 54, 360–373. [Google Scholar] [CrossRef]
  22. Ben Embarek, P.K. Presence, detection and growth of Listeria monocytogenes in seafoods—A review. Int. J. Food Microbiol. 1994, 23, 17–34. [Google Scholar] [CrossRef]
  23. Hofshagen, M.; Nygård, K.; Kruse, H. (Eds.) Listeriose; Norsk Zoonosesenter: Oslo, Norway, 2004. [Google Scholar]
  24. Schjørring, S.; Lassen, S.G.; Jensen, T.; Moura, A.; Kjeldgaard, J.S.; Mueller, L.; Thielke, S.; Leclercq, A.; Maury, M.M.; Tourdjman, M.; et al. Cross-border outbreak of listeriosis caused by cold-smoked salmon, revealed by integrated surveillance and whole genome sequencing (WGS), Denmark and France, 2015 to 2017. Eurosurveillance 2017, 22, 8–12. [Google Scholar] [CrossRef]
  25. Gillesberg Lassen, S.; Ethelberg, S.; Björkman, J.T.; Jensen, T.; Sørensen, G.; Kvistholm Jensen, A.; Müller, L.; Nielsen, E.M.; Mølbak, K. Two listeria outbreaks caused by smoked fish consumption—Using whole-genome sequencing for outbreak investigations. Clin. Microbiol. Infect. 2016, 22, 620–624. [Google Scholar] [CrossRef]
  26. EFSA; ECDC. Multi-Country Outbreak of Listeria Monocytogenes Clonal Complex 8 Infections Linked to Consumption of Cold-Smoked Fish Products; EFSA (European Food Safety Authority) and ECDC (European Centre for Disesase Prevention and Control): Stockholm, Sweden; Parma, Italy, 2019; p. 18. [Google Scholar]
  27. EFSA; ECDC. Multi-Country Outbreak of Listeria Monocytogenes Sequence Type 8 Infections Linked to Consumption of Salmon Products; EFSA (European Food Safety Authority) and ECDC (European Centre for Disesase Prevention and Control): Stockholm, Sweden; Parma, Italy, 2018; p. 16. [Google Scholar]
  28. Skjerdal, T.; Eckner, K.; Kapperud, G.; Lassen, J.; Grahek-Ogden, D.; Narvhus, J.; Nesbakken, T.; Robertson, L.; Rosnes, J.T.; Skjerve, E.; et al. Listeria Monocytogenes—Vurdering av Helseråd til Gravide og Andre Utsatte Grupper; Uttalelse fra Faggruppe for Hygiene og Smittestoffer i Vitenskapskomiteen for Mat og Miljø: Oslo, Norway, 2018. [Google Scholar]
  29. Jackson, B.R.; Tarr, C.; Strain, E.; Jackson, K.A.; Conrad, A.; Carleton, H.; Katz, L.S.; Stroika, S.; Gould, L.H.; Mody, R.K.; et al. Implementation of nationwide real-time whole-genome sequencing to enhance listeriosis outbreak detection and investigation. Clin. Infect. Dis. 2016, 63, 380–386. [Google Scholar] [CrossRef] [PubMed]
  30. Chenal-Francisque, V.; Diancourt, L.; Cantinelli, T.; Passet, V.; Tran-Hykes, C.; Bracq-Dieye, H.; Leclercq, A.; Pourcel, C.; Lecuit, M.; Brisse, S. Optimized Multilocus Variable-Number Tandem-Repeat Analysis Assay and Its Complementarity with Pulsed-Field Gel Electrophoresis and Multilocus Sequence Typing for Listeria monocytogenes Clone Identification and Surveillance. J. Clin. Microbiol. 2013, 51, 1868–1880. [Google Scholar] [CrossRef] [PubMed]
  31. Schmid, D.; Allerberger, F.; Huhulescu, S.; Pietzka, A.; Amar, C.; Kleta, S.; Prager, R.; Preussel, K.; Aichinger, E.; Mellmann, A. Whole genome sequencing as a tool to investigate a cluster of seven cases of listeriosis in Austria and Germany, 2011–2013. Clin. Microbiol. Infect. 2014, 20, 431–436. [Google Scholar] [CrossRef]
  32. Lindqvist, R.; Westöö, A. Quantitative risk assessment for Listeria monocytogenes in smoked or gravad salmon and rainbow trout in Sweden. Int. J. Food Microbiol. 2000, 58, 181–196. [Google Scholar] [CrossRef]
  33. Moura, A.; Criscuolo, A.; Pouseele, H.; Maury, M.M.; Leclercq, A.; Tarr, C.; Björkman, J.T.; Dallman, T.; Reimer, A.; Enouf, V.; et al. Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes. Nat. Microbiol. 2016, 2, 1–10. [Google Scholar] [CrossRef] [PubMed]
  34. Lindstedt, B.A.; Tham, W.; Danielsson-Tham, M.L.; Vardund, T.; Helmersson, S.; Kapperud, G. Multiple-locus variable-number tandem-repeats analysis of Listeria monocytogenes using multicolour capillary electrophoresis and comparison with pulsed-field gel electrophoresis typing. J. Microbiol. Methods 2008, 72, 141–148. [Google Scholar] [CrossRef]
  35. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef]
  36. Bushnell, B. BBMap Short Read Aligner. Available online: https://sourceforge.net/projects/bbmap/ (accessed on 13 October 2020).
  37. Ruppitsch, W.; Pietzka, A.; Prior, K.; Bletz, S.; Fernandez, H.L.; Allerberger, F.; Harmsen, D.; Mellmann, A. Defining and evaluating a core genome multilocus sequence typing scheme for whole-genome sequence-based typing of Listeria monocytogenes. J. Clin. Microbiol. 2015, 53, 2869–2876. [Google Scholar] [CrossRef]
  38. Hyden, P.; Pietzka, A.; Lennkh, A.; Murer, A.; Springer, B.; Blaschitz, M.; Indra, A.; Huhulescu, S.; Allerberger, F.; Ruppitsch, W.; et al. Whole genome sequence-based serogrouping of Listeria monocytogenes isolates. J. Biotechnol. 2016, 235, 181–186. [Google Scholar] [CrossRef]
  39. Joensen, K.G.; Scheutz, F.; Lund, O.; Hasman, H.; Kaas, R.S.; Nielsen, E.M.; Aarestrup, F.M. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J. Clin. Microbiol. 2014, 52, 1501–1510. [Google Scholar] [CrossRef]
  40. Montero, D.; Bodero, M.; Riveros, G.; Lapierre, L.; Gaggero, A.; Vidal, R.M.; Vidal, M. Molecular epidemiology and genetic diversity of Listeria monocytogenes isolates from a wide variety of ready-to-eat foods and their relationship to clinical strains from listeriosis outbreaks in Chile. Front. Microbiol. 2015, 6, 8. [Google Scholar] [CrossRef]
  41. Lambertz, S.T.; Ivarsson, S.; Lopez-Valladares, G.; Sidstedt, M.; Lindqvist, R. Subtyping of Listeria monocytogenes isolates recovered from retail ready-to-eat foods, processing plants and listeriosis patients in Sweden 2010. Int. J. Food Microbiol. 2013, 166, 186–192. [Google Scholar] [CrossRef] [PubMed]
  42. Martinez, I.; Rørvik, L.M.; Brox, V.; Lassen, J.; Seppola, M.; Gram, L.; Fonnesbech-Vogel, B. Genetic variability among isolates of Listeria monocytogenes from food products, clinical samples and processing environments, estimated by RAPD typing. Int. J. Food Microbiol. 2003, 84, 285–297. [Google Scholar] [CrossRef]
  43. Rocourt, J.; Jacquet, C.; Reilly, A. Epidemiology of human listeriosis and seafoods. Int. J. Food Microbiol. 2000, 62, 197–209. [Google Scholar] [CrossRef]
  44. Wulff, G.; Gram, L.; Ahrens, P.; Vogel, B.F. One group of genetically similar Listeria monocytogenes strains frequently dominates and persists in several fish slaughter- and smokehouses. Appl. Environ. Microbiol. 2006, 72, 4313–4322. [Google Scholar] [CrossRef]
  45. Holch, A.; Webb, K.; Lukjancenko, O.; Ussery, D.; Rosenthal, B.M.; Gram, L. Genome sequencing identifies two nearly unchanged strains of persistent Listeria monocytogenes isolated at two different fish processing plants sampled 6 years apart. Appl. Environ. Microbiol. 2013, 79, 2944–2951. [Google Scholar] [CrossRef] [PubMed]
  46. Kyoui, D.; Takahashi, H.; Miya, S.; Kuda, T.; Igimi, S.; Kimura, B. Genetic distance in the whole-genome perspective on Listeria monocytogenes strains F2-382 and NIHS-28 that show similar subtyping results. BMC Microbiol. 2014, 14, 10. [Google Scholar] [CrossRef]
  47. Hoffman, A.D.; Gall, K.L.; Norton, D.M.; Wiedmann, M. Listeria monocytogenes contamination patterns for the smoked fish processing environment and for raw fish. J. Food Prot. 2003, 66, 52–60. [Google Scholar] [CrossRef] [PubMed]
  48. Rørvik, L.M.; Aase, B.; Alvestad, T.; Caugant, D.A. Molecular epidemiological survey of Listeria monocytogenes in seafoods and seafood-processing plants. Appl. Environ. Microbiol. 2000, 66, 4779–4784. [Google Scholar] [CrossRef] [PubMed]
  49. Autio, T.; Hielm, S.; Miettinen, M.; Sjoberg, A.M.; Aarnisalo, K.; Bjorkroth, J.; Mattila-Sandholm, T.; Korkeala, H. Sources of Listeria monocytogenes contamination in a cold-smoked rainbow trout processing plant detected by pulsed-field gel electrophoresis typing. Appl. Environ. Microbiol. 1999, 65, 150–155. [Google Scholar] [CrossRef] [PubMed]
  50. Rørvik, L.M.; Caugant, D.A.; Yndestad, M. Contamination pattern of Listeria monocytogenes and other Listeria spp in a salmon slaughterhouse and smoked salmon processing plant. Int. J. Food Microbiol. 1995, 25, 19–27. [Google Scholar] [CrossRef]
  51. Porsby, C.H.; Vogel, B.F.; Mohr, M.; Gram, L. Influence of processing steps in cold-smoked salmon production on survival and growth of persistent and presumed non-persistent Listeria monocytogenes. Int. J. Food Microbiol. 2008, 122, 287–295. [Google Scholar] [CrossRef]
  52. Sikorski, Z.E.; Kolodziejska, I. Microbial risks in mild hot smoking of fish. Crit. Rev. Food Sci. Nutr. 2002, 42, 35–51. [Google Scholar] [CrossRef]
  53. Vogel, B.F.; Huss, H.H.; Ojeniyi, B.; Ahrens, P.; Gram, L. Elucidation of Listeria monocytogenes contamination routes in cold-smoked salmon processing plants detected by DNA-based typing methods. Appl. Environ. Microbiol. 2001, 67, 2586–2595. [Google Scholar] [CrossRef]
  54. Ferreira, V.; Wiedmann, M.; Teixeira, P.; Stasiewicz, M.J. Listeria monocytogenes persistence in food-associated environments: Epidemiology, strain characteristics, and implications for public health. J. Food Prot. 2014, 77, 150–170. [Google Scholar] [CrossRef]
  55. Nakari, U.-M.; Rantala, L.; Pihlajasaari, A.; Toikkanen, S.; Johansson, T.; Hellsten, C.; Raulo, S.M.; Kuusi, M.; Siitonen, A.; Rimhanen-Finne, R. Investigation of increased listeriosis revealed two fishery production plants with persistent Listeria contamination in Finland 2010. Epidemiol. Infect. 2014, 142, 2261–2269. [Google Scholar] [CrossRef] [PubMed]
  56. Palma, F.; Pasquali, F.; Lucchi, A.; De Cesare, A.; Manfreda, G. Whole genome sequencing for typing and characterisation of Listeria monocytogenes isolated in a rabbit meat processing plant. Ital. J. Food Saf. 2017, 6, 125–130. [Google Scholar] [CrossRef]
  57. Chenal-Francisque, V.; Lopez, J.; Cantinelli, T.; Caro, V.; Tran, C.; Leclercq, A.; Lecuit, M.; Brisse, S. Worldwide distribution of major clones of Listeria monocytogenes. Emerg. Infect. Dis. 2011, 17, 1110–1112. [Google Scholar] [CrossRef] [PubMed]
  58. Painset, A.; Bjorkman, J.T.; Kiil, K.; Guillier, L.; Mariet, J.F.; Felix, B.; Amar, C.; Rotariu, O.; Roussel, S.; Perez-Reche, F.; et al. LiSEQ—Whole-genome sequencing of a cross-sectional survey of Listeria monocytogenes in ready-to-eat foods and human clinical cases in Europe. Microb. Genom. 2019, 5, 11. [Google Scholar] [CrossRef]
  59. Maury, M.M.; Tsai, Y.H.; Charlier, C.; Touchon, M.; Chenal-Francisque, V.; Leclercq, A.; Criscuolo, A.; Gaultier, C.; Roussel, S.; Brisabois, A.; et al. Uncovering Listeria monocytogenes hypervirulence by harnessing its biodiversity. Nat. Genet. 2016, 48, 308–313. [Google Scholar] [CrossRef]
  60. Kuenne, C.; Billion, A.; Abu Mraheil, M.; Strittmatter, A.; Daniel, R.; Goesmann, A.; Barbuddhe, S.; Hain, T.; Chakraborty, T. Reassessment of the Listeria monocytogenes pan-genome reveals dynamic integration hotspots and mobile genetic elements as major components of the accessory genome. BMC Genom. 2013, 14. [Google Scholar] [CrossRef] [PubMed]
  61. Pightling, A.W.; Pettengill, J.B.; Luo, Y.; Baugher, J.D.; Rand, H.; Strain, E. Interpreting Whole-Genome Sequence Analyses of Foodborne Bacteria for Regulatory Applications and Outbreak Investigations. Front. Microbiol. 2018, 9. [Google Scholar] [CrossRef] [PubMed]
  62. Wang, Y.; Pettengill, J.B.; Pightling, A.W.; Timme, R.; Allard, M.; Strain, E.; Rand, H. Genetic Diversity of Salmonella and Listeria Isolates from Food Facilities. J. Food Prot. 2018, 81, 2082–2089. [Google Scholar] [CrossRef] [PubMed]
  63. Rychli, K.; Mueller, A.; Zaiser, A.; Schoder, D.; Allerberger, F.; Wagner, M.; Schmitz-Esser, S. Genome sequencing of Listeria monocytogenes “Quargel” listeriosis outbreak strains reveals two different strains with distinct in vitro virulence potential. PLoS ONE 2014, 9. [Google Scholar] [CrossRef]
Figure 1. Neighbour Joining Tree (A) and Minimum Spanning Tree (B) illustrating the phylogenetic relationship based on the cgMLST allelic profiles of L. monocytogenes isolates from slaughterhouses (n = 21) and listeriosis patients (n = 12). Each circle represents an allelic profile based on sequence analysis of 1708 genes. Different colours denote the STs.
Figure 1. Neighbour Joining Tree (A) and Minimum Spanning Tree (B) illustrating the phylogenetic relationship based on the cgMLST allelic profiles of L. monocytogenes isolates from slaughterhouses (n = 21) and listeriosis patients (n = 12). Each circle represents an allelic profile based on sequence analysis of 1708 genes. Different colours denote the STs.
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Table 1. Summary of isolates indicating source of isolation (key of clinical isolates in bold type), Year of isolation, MLVA genotype, MLST ST, CC, cgMLST CT, predicted serogroup and predicted Lineage.
Table 1. Summary of isolates indicating source of isolation (key of clinical isolates in bold type), Year of isolation, MLVA genotype, MLST ST, CC, cgMLST CT, predicted serogroup and predicted Lineage.
KeySource of IsolationYear of IsolationMLVAMLST STCCcgMLST CTPredicted PCR Serogroup *Predicted Lineage
S12Environmental—Water tank20156-0-14-6-9113063IVb (2)I
S10Environmental—Floor20157-7-19-6-10224059IVb (3)
1106-0479Clinical—Unknown20064065
S8Environmental—Floor20157-7-22-6-104059
16EP000085Clinical—Blood20161127
3BS29Environmental—Drain20079-4-18-6-9664064IVb (13)
1108-0593Clinical—Unknown2008
1108-3537Clinical—Blood20084039
MB5Environmental—Gutting machine20157-7-10-10-6774060IIa (4)II
MB2Environmental—Gutting machine2015
15EP000821Clinical—Blood2015665
1BR16Environmental—Workers apron and hands20072657
C7Environmental—Gutting machine20156-9-26-18-6884057IIa (2)
C3Environmental—Floor2015
16EP000110Clinical—Blood20164042
CH3K-Environmental—Gutting machine2015unassigned4058
2BR21Environmental—Swab of forceps20075-8-15-10-61414112
MB4Environmental—Conveyor belt2015
1BR5Environmental—Ungutted salmon20075-8-14-10-6
1112-0170Clinical—CSF2012847
3BS27Environmental—Gloves, forceps and knives20078-8-17-19-618182806
2BR25Environmental—Raw salmon fillet2007
14EP001609Clinical—Blood20143562
3BS28Environmental—Run-off water20076-10-5-16-618182806
3BS44Environmental—Gutted salmon200720204061IIa (10)
1110-0057Clinical—Unknown2010
3BS5Environmental—Slaughtering table20076-8-14-18-631314063
1109-1422Clinical—Unknown20094062
2HF15Environmental—Conveyor belt20076-9-4-10-61011013358IIa (14)
2HF33Environmental—Drain20076-7-14-10-61211212278IIa (5)
14EP001215Clinical—CSF2014
3BS90Environmental—Floor20076-10-17-21-63983983510IIa (1)
1106-3928Clinical—Unknown2006
* Predicted PCR serogroup profile IVb corresponds to L. monocytogenes strains of serovars 4b, 4d and 4e, and profile IIa corresponds to serovars 1/2a, 3a, 1/2b and 3b. The numbers in parenthesis refer to different combinations of lmo0737/lmo1118/ORF2110/ORF2819/prs alleles. For example, IIa (4) corresponds to the allelic profile 2/0/0/0/1. All profile definitions and allele profiles can be found at http://bigsdb.pasteur.fr/perl/bigsdb/bigsdb.pl?db=pubmlst_listeria_seqdef_public, accessed on 3 May 2021.
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