Whole Genome Sequencing Based Surveillance of L. monocytogenes for Early Detection and Investigations of Listeriosis Outbreaks

Surveillance and genetic characterization of Listeria monocytogenes in the food chain in Montenegro during the period 2014-2022

Introduction

Listeria monocytogenes is an ubiquitous foodborne pathogen that represents a serious threat to public health and the food industry.

Methods

In this study Whole Genome Sequencing (WGS) was used to characterize 160 L. monocytogenes isolates obtained from 22,593 different food sources in Montenegro during the years 2014-2022.

Results

Isolates belonged to 21 different clonal complexes (CCs), 22 sequence types (STs) and 73 core genome multilocus sequence types (cgMLST) revealing a high diversity. The most prevalent STs were ST8 (n = 29), ST9 (n = 31), ST121 (n = 19) and ST155 (n = 20). All isolates carried virulence genes (VGs), 111 isolates carried mobile genetic elements (MGEs) (ranging from 1 to 7 MGEs) and 101 isolates carried plasmids (ranging from 1 to 3 plasmids). All isolates carried the intrinsic resistance genes fosX and lin. None of the isolates carried acquired antimicrobial resistance genes (ARGs).

Discussion/conclusion

Continuous monitoring and surveillance of L. monocytogenes is needed for improving and ameliorating the public health.

A Comprehensive Methodology for Microbial Strain Typing Using Fourier-Transform Infrared Spectroscopy

Timely and accurate detection and characterization of microbial threats is crucial for effective infection and outbreak management. Additionally, in food production, rapid microbe identification is indispensable for maintaining quality control and hygiene standards. Current methods for typing microbial strains often rely on labor-intensive, time-consuming, and expensive DNA- and sera-serotyping techniques, limiting their applicability in rapid-response scenarios. In this context, the IR Biotyper®, utilizing Fourier-transform infrared (FTIR) spectroscopy, offers a novel approach, providing specific spectra for fast strain typing within 3 h. This methodology article serves as a comprehensive resource for researchers and technicians aiming to utilize FTIR spectroscopy for microbial strain typing. It encompasses detailed guidelines on sample preparation, data acquisition, and analysis techniques, ensuring the generation of reliable and reproducible results. We highlight the IR Biotyper®'s rapid and accurate discrimination capabilities, showcasing its potential for real-time pathogen monitoring and source-tracking to enhance public health and food safety. We propose its integration as an early screening method, followed by more detailed analysis with whole-genome sequencing, to optimize detection accuracy and response efficiency in microbial surveillance systems.

Genomic analysis of Listeria monocytogenes CC7 associated with clinical infections and persistence in the food industry

Listeria monocytogenes clonal complex 7 (CC7), belonging to lineage II, is the most common subtype among clinical listeriosis isolates in Norway, and is also commonly found in Norwegian food industry and outdoor environments. In the present study, the relative prevalence of CCs among clinical isolates of L. monocytogenes in European countries during 2010-2015 was determined. Then, phylogenomic and comparative genomic analyses was performed for 115 Norwegian and 255 international reference genomes from various sources, to examine potential explanations underlying the high prevalence of CC7 among Norwegian listeriosis cases. Selected isolates were also compared using in vitro virulence assays. The results showed a high relative prevalence of CC7 in clinical isolates from Norway and the neighboring Nordic countries Sweden and Finland. In contrast to in most other European countries, lineage II dominated among clinical isolates in these countries. Phylogenetic analysis of the 370 CC7 isolates separated the genomes into four clades, with the majority of Norwegian isolates (69 %) clustered in one of these clades, estimated to have diverged from the other clades around year 1830. The Norwegian isolates within this clade were widely distributed in different habitats; several (poultry) meat processing factories, a salmon processing plant, in nature, farms, and slugs, and among human clinical isolates. In particular, one pervasive CC7 clone was found across three poultry processing plants and one salmon processing plant, and also included three clinical isolates. All analysed CC7 isolates harbored the same set of 72 genes involved in both general and specific stress responses. Divergence was observed for plasmid-encoded genes including genes conferring resistance against arsenic (Tn554-arsCBADR), cadmium (cadA1C1 and cadA2C2), and the biocide benzalkonium chloride (bcrABC). No significant difference in prevalence of these genes was seen between isolates from different habitats or sources. Virulence attributes were highly conserved among the CC7 isolates. In vitro virulence studies of five representative CC7 isolates revealed a virulence potential that, in general, was not significantly lower than that of the control strain EGDe, with isolate-dependent differences that could not be correlated with genetic determinants. The study shows that CC7 is widespread in Norway, and that a pervasive CC7 clone was present in food processing plants. The study highlights the importance of CC7 and lineage II strains in causing listeriosis and shows that more research is needed to understand the reasons behind geographical differences in CC prevalence.

Combining Whole Genome Sequencing Data from Human and Non-Human Sources: Tackling Listeria monocytogenes Outbreaks

Listeria monocytogenes (Lm) is ubiquitous in nature and known for its ability to contaminate foods during production processes. Near real-time monitoring of whole genome sequences from food and human isolates, complemented with epidemiological data, has been used in the Netherlands since 2019 to increase the speed and success rate of source finding in the case of (active) clusters. Nine clusters with 4 to 19 human cases investigated between January 2019 and May 2023 are described. Fish production sites were most often linked to outbreaks of listeriosis (six clusters), though other types of food businesses can face similar Lm problems, as the production processes and procedures determine risk. The results showed that low levels of Lm in food samples can still be linked to disease. Therefore, the investigation of a cluster of cases and deployment of the precautionary principle helps to focus on safe food and to prevent further cases. Good practice of environmental monitoring within a food business allows early detection of potential issues with food safety and helps food businesses to take appropriate measures such as cleaning to prevent regrowth of Lm and thus future outbreaks.

Recent Advances in Electrochemical Biosensors for the Detection of Foodborne Pathogens: Current Perspective and Challenges

Foodborne pathogens cause many diseases and significantly impact human health and the economy. Foodborne pathogens mainly include Salmonella spp., Escherichia coli, Staphylococcus aureus, Shigella spp., Campylobacter spp. and Listeria monocytogenes, which are present in agricultural products, dairy products, animal-derived foods and the environment. Various pathogens in many different types of food and water can cause potentially life-threatening diseases and develop resistance to various types of antibiotics. The harm of foodborne pathogens is increasing, necessitating effective and efficient methods for early monitoring and detection. Traditional methods, such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA) and culture plate, are time-consuming, labour-intensive and expensive and cannot satisfy the demands of rapid food testing. Therefore, new fast detection methods are urgently needed. Electrochemical biosensors provide consumer-friendly methods to quickly detect foodborne pathogens in food and the environment and achieve extensive accuracy and reproducible results. In this paper, by focusing on various mechanisms of electrochemical transducers, we present a comprehensive overview of electrochemical biosensors for the detection of foodborne pathogens. Furthermore, the review introduces the hazards of foodborne pathogens, risk analysis methods and measures of control. Finally, the review also emphasizes the recent research progress and solutions regarding the use of electrochemical biosensors to detect foodborne pathogens in food and the environment, evaluates limitations and challenges experienced during the development of biosensors to detect foodborne pathogens and discusses future possibilities.

Genetic population structure of Listeria monocytogenes strains isolated from salmon and trout sectors in France

Smoked salmon and smoked trout are ready-to-eat and potentially contaminated with the pathogenic bacterium Listeria monocytogenes making them high risk for the consumer. This raises questions about the presence of hypervirulent or persistent strains in the salmon and trout industries. Knowledge of the genetic diversity of circulating strains in these sectors is essential to evaluate the risk associated with this pathogen and improve food safety. We analyzed the genetic structure of 698 strains of L. monocytogenes isolated from 2006 to 2017 in France, based on their serogroup, lineage and clonal complexes (CCs) determined by Multilocus sequence typing (MLST). Most of the CCs were identified by mapping the strains PFGE profiles and a novel high-throughput real-time PCR method for CC identification. We identified thirteen CCs and one sequence type (ST) with variable distribution in salmon and trout samples (food, environment). The three most prevalent CCs were CC121, CC26 and CC204. Strains from ST191 and CC54 were detected for the first time in these sectors, while less than 0.6% of the isolates belonged to the hyper-virulent CC1, CC6 and CC20. No CC was exclusively associated with the salmon sector. This project allowed us to assess the population diversity of CCs of L. monocytogenes in the salmon and trout industries.

Large Multicountry Outbreak of Invasive Listeriosis by a Listeria monocytogenes ST394 Clone Linked to Smoked Rainbow Trout, 2020 to 2021

Whole-genome sequencing (WGS) has revolutionized surveillance of infectious diseases. Disease outbreaks can now be detected with high precision, and correct attribution of infection sources has been improved. Listeriosis, caused by the bacterium Listeria monocytogenes, is a foodborne disease with a high case fatality rate and a large proportion of outbreak-related cases. Timely recognition of listeriosis outbreaks and precise allocation of food sources are important to prevent further infections and to promote public health. We report the WGS-based identification of a large multinational listeriosis outbreak with 55 cases that affected Germany, Austria, Denmark, and Switzerland during 2020 and 2021. Clinical isolates formed a highly clonal cluster (called Ny9) based on core genome multilocus sequence typing (cgMLST). Routine and ad hoc investigations of food samples identified L. monocytogenes isolates from smoked rainbow trout filets from a Danish producer grouping with the Ny9 cluster. Patient interviews confirmed consumption of rainbow trout as the most likely infection source. The Ny9 cluster was caused by a MLST sequence type (ST) ST394 clone belonging to molecular serogroup IIa, forming a distinct clade within molecular serogroup IIa strains. Analysis of the Ny9 genome revealed clpY, dgcB, and recQ inactivating mutations, but phenotypic characterization of several virulence-associated traits of a representative Ny9 isolate showed that the outbreak strain had the same pathogenic potential as other serogroup IIa strains. Our report demonstrates that international food trade can cause multicountry outbreaks that necessitate cross-border outbreak collaboration. It also corroborates the relevance of ready-to-eat smoked fish products as causes for listeriosis. IMPORTANCE Listeriosis is a severe infectious disease in humans and characterized by an exceptionally high case fatality rate. The disease is transmitted through consumption of food contaminated by the bacterium Listeria monocytogenes. Outbreaks of listeriosis often occur but can be recognized and stopped through implementation of whole-genome sequencing-based pathogen surveillance systems. We here describe the detection and management of a large listeriosis outbreak in Germany and three neighboring countries. This outbreak was caused by rainbow trout filet, which was contaminated by a L. monocytogenes clone belonging to sequence type ST394. This work further expands our knowledge on the genetic diversity and transmission routes of an important foodborne pathogen.

Identification by High-Throughput Real-Time PCR of 30 Major Circulating Listeria monocytogenes Clonal Complexes in Europe

Listeria monocytogenes is a ubiquitous bacterium that causes a foodborne illness, listeriosis. Most strains can be classified into major clonal complexes (CCs) that account for the majority of outbreaks and sporadic cases in Europe. In addition to the 20 CCs known to account for the majority of human and animal clinical cases, 10 CCs are frequently reported in food production, thereby posing a serious challenge for the agrifood industry. Therefore, there is a need for a rapid and reliable method to identify these 30 major CCs. The high-throughput real-time PCR assay presented here provides accurate identification of these 30 CCs and eight genetic subdivisions within four CCs, splitting each CC into two distinct subpopulations, along with the molecular serogroup of a strain. Based on the BioMark high-throughput real-time PCR system, our assay analyzes 46 strains against 40 real-time PCR arrays in a single experiment. This European study (i) designed the assay from a broad panel of 3,342 L. monocytogenes genomes, (ii) tested its sensitivity and specificity on 597 sequenced strains collected from 24 European countries, and (iii) evaluated its performance in the typing of 526 strains collected during surveillance activities. The assay was then optimized for conventional multiplex real-time PCR for easy implementation in food laboratories. It has already been used for outbreak investigations. It represents a key tool for assisting food laboratories to establish strain relatedness with human clinical strains during outbreak investigations and for helping food business operators by improving their microbiological management plans. IMPORTANCE Multilocus sequence typing (MLST) is the reference method for Listeria monocytogenes typing but is expensive and takes time to perform, from 3 to 5 days for laboratories that outsource sequencing. Thirty major MLST clonal complexes (CCs) are circulating in the food chain and are currently identifiable only by sequencing. Therefore, there is a need for a rapid and reliable method to identify these CCs. The method presented here enables the rapid identification, by real-time PCR, of 30 CCs and eight genetic subdivisions within four CCs, splitting each CC into two distinct subpopulations. The assay was then optimized on different conventional multiplex real-time PCR systems for easy implementation in food laboratories. The two assays will be used for frontline identification of L. monocytogenes isolates prior to whole-genome sequencing. Such assays are of great interest for all food industry stakeholders and public agencies for tracking L. monocytogenes food contamination.

Genomic and pathogenicity islands of Listeria monocytogenes-overview of selected aspects

Listeria monocytogenes causes listeriosis, a disease characterized by a high mortality rate (up to 30%). Since the pathogen is highly tolerant to changing conditions (high and low temperature, wide pH range, low availability of nutrients), it is widespread in the environment, e.g., water, soil, or food. L. monocytogenes possess a number of genes that determine its high virulence potential, i.e., genes involved in the intracellular cycle (e.g., prfA, hly, plcA, plcB, inlA, inlB), response to stress conditions (e.g., sigB, gadA, caspD, clpB, lmo1138), biofilm formation (e.g., agr, luxS), or resistance to disinfectants (e.g., emrELm, bcrABC, mdrL). Some genes are organized into genomic and pathogenicity islands. The islands LIPI-1 and LIPI-3 contain genes related to the infectious life cycle and survival in the food processing environment, while LGI-1 and LGI-2 potentially ensure survival and durability in the production environment. Researchers constantly have been searching for new genes determining the virulence of L. monocytogenes. Understanding the virulence potential of L. monocytogenes is an important element of public health protection, as highly pathogenic strains may be associated with outbreaks and the severity of listeriosis. This review summarizes the selected aspects of L. monocytogenes genomic and pathogenicity islands, and the importance of whole genome sequencing for epidemiological purposes.

Duplex real-time PCR assay with high-resolution melt analysis for the detection and quantification of Listeria species and Listeria monocytogenes in meat products

Listeria contamination in foods of animal origin is one of the most concerning food safety issues. A duplex, SYBR green-based, real-time PCR assay was developed with high-resolution melting analysis-based differentiation of the genus Listeria and Listeria monocytogenes. The primers were designed and tested against other related foodborne pathogens. The assay was optimized for standard parameters in a non-orthogonal fashion and validated following international standards. The LODabs and LOQ of the assay were calculated to be 0.78 and 1.56 ng of the target DNA. The LODrel of the assay was found to be 1% Listeria DNA in background DNA. The assay was evaluated for applicability in artificially spiked samples, providing a 120 CFU/ml detection. The assay was validated with proficiency test samples and also with samples collected for surveillance analysis. This well-established and validated assay can be utilized as a qualitative and quantitative tool for addressing the Listeria contamination in the food safety contexts.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05695-2.

Wholegenome sequencing as the gold standard approach for control of Listeria monocytogenes in the food chain

Listeria monocytogenes has been implicated in numerous outbreaks and related deaths of listeriosis. In food production, L. monocytogenes occurs in raw food material and above all, through postprocessing contamination. The use of next-generation sequencing technologies such as whole-genome sequencing (WGS) facilitates foodborne outbreak investigations, pathogen source tracking and tracing geographic distributions of different clonal complexes, routine microbiological/epidemiological surveillance of listeriosis, and quantitative microbial risk assessment. WGS can also be used to predict various genetic traits related to virulence, stress, or antimicrobial resistance, which can be of great benefit for improving food safety management as well as public health.

Whole-Genome Sequence Comparisons of Listeria monocytogenes Isolated from Meat and Fish Reveal High Inter- and Intra-Sample Diversity

Interpretation of whole-genome sequencing (WGS) data for foodborne outbreak investigations is complex, as the genetic diversity within processing plants and transmission events need to be considered. In this study, we analyzed 92 food-associated Listeria monocytogenes isolates by WGS-based methods. We aimed to examine the genetic diversity within meat and fish production chains and to assess the applicability of suggested thresholds for clustering of potentially related isolates. Therefore, meat-associated isolates originating from the same samples or processing plants as well as fish-associated isolates were analyzed as distinct sets. In silico serogrouping, multilocus sequence typing (MLST), core genome MLST (cgMLST), and pangenome analysis were combined with screenings for prophages and genetic traits. Isolates of the same subtypes (cgMLST types (CTs) or MLST sequence types (STs)) were additionally compared by SNP calling. This revealed the occurrence of more than one CT within all three investigated plants and within two samples. Analysis of the fish set resulted in predominant assignment of isolates from pangasius catfish and salmon to ST2 and ST121, respectively, potentially indicating persistence within the respective production chains. The approach not only allowed the detection of distinct subtypes but also the determination of differences between closely related isolates, which need to be considered when interpreting WGS data for surveillance.

Whole-Genome Sequencing-Based Characterization of Listeria Isolates from Produce Packinghouses and Fresh-Cut Facilities Suggests Both Persistence and Reintroduction of Fully Virulent L. monocytogenes

The contamination of ready-to-eat produce with Listeria monocytogenes (LM) can often be traced back to environmental sources in processing facilities and packinghouses. To provide an improved understanding of Listeria sources and transmission in produce operations, we performed whole-genome sequencing (WGS) of LM (n = 169) and other Listeria spp. (n = 107) obtained from 13 produce packinghouses and three fresh-cut produce facilities. Overall, a low proportion of LM isolates (9/169) had inlA premature stop codons, and a large proportion (83/169) had either or both of the LIPI-3 or LIPI-4 operons, which have been associated with hypervirulence. The further analysis of the WGS data by operation showed a reisolation (at least 2 months apart) of highly related isolates (<10 hqSNP differences) in 7/16 operations. Two operations had highly related strains reisolated from samples that were collected at least 1 year apart. The identification of isolates collected during preproduction (i.e., following sanitation but before the start of production) that were highly related to isolates collected during production (i.e., after people or products have entered and begun moving through the operation) provided evidence that some strains were able to survive standard sanitation practices. The identification of closely related isolates (<20 hqSNPs differences) in different operations suggests that cross-contamination between facilities or introductions from common suppliers may also contribute to Listeria transmission. Overall, our data suggest that the majority of LM isolates collected from produce operations are fully virulent and that both persistence and reintroduction may lead to the repeat isolation of closely related Listeria in produce operations.

IMPORTANCEListeria monocytogenes is of particular concern to the produce industry due to its frequent presence in natural environments as well as its ability to survive in packinghouses and fresh-cut processing facilities over time. The use of whole-genome sequencing, which provides high discriminatory power for the characterization of Listeria isolates, along with detailed source data (isolation date and sample location) shows that the presence of Listeria in produce operations appears to be due to random and continued reintroduction as well as to the persistence of highly related strains in both packinghouses and fresh-cut facilities. These findings indicate the importance of using high-resolution characterization approaches for root cause analyses of Listeria contamination issues. In cases of repeat isolation of closely related Listeria in a given facility, both persistence and reintroduction need to be considered as possible root causes.

Reinfection or relapse? A case study of whole genome sequencing guided genomic characterization of Mycobacterium abscessus chronic infection in a cystic fibrosis patient

A 7-year-old cystic fibrosis patient with increased cough, new pulmonary infiltrate, and declining pulmonary function was diagnosed with clarithromycin resistant Mycobacterium abscessus infection. Treatment was initiated with clofazimine, linezolid and cefoxitin; she responded well to therapy and achieved microbiological clearance after completion of 12-month treatment. One year later, she had re-emergence of worsening symptoms and her sputum culture again grew clarithromycin resistant M. abscessus. Using a laboratory developed whole genome sequencing (WGS) test, the bacterium was determined to be the same strain with the same resistance mechanisms, indicating a relapse. This was deemed a critical element of clinical information, as the isolation of a genetically distinct organism would have indicated a new infection and would have served as evidence that a 12-month regimen was likely sufficient to achieve eradication. The confirmation of a relapse prompted the prolongation of the therapy plan to a goal of 24 months. Reinfection and relapse are great challenges in patients with cystic fibrosis who may acquire new strain of M. abscessus from the environment, may harbor multiple subpopulations of bacteria, or may have persistent infections but intermittent bacteria shedding that could not be eradicated. WGS has emerged as a powerful molecular tool to accurately differentiate re-infection from relapse thus solving this conundrum.

In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes

Background

Whole genome sequencing analyzed by core genome multi-locus sequence typing (cgMLST) is widely used in surveillance of the pathogenic bacteria Listeria monocytogenes. Given the heterogeneity of available bioinformatics tools to define cgMLST alleles, our aim was to identify parameters influencing the precision of cgMLST profiles.

Methods

We used three L. monocytogenes reference genomes from different phylogenetic lineages and assessed the impact of in vitro (i.e. tested genomes, successive platings, replicates of DNA extraction and sequencing) and in silico parameters (i.e. targeted depth of coverage, depth of coverage, breadth of coverage, assembly metrics, cgMLST workflows, cgMLST completeness) on cgMLST precision made of 1748 core loci. Six cgMLST workflows were tested, comprising assembly-based (BIGSdb, INNUENDO, GENPAT, SeqSphere and BioNumerics) and assembly-free (i.e. kmer-based MentaLiST) allele callers. Principal component analyses and generalized linear models were used to identify the most impactful parameters on cgMLST precision.

Results

The isolate’s genetic background, cgMLST workflows, cgMLST completeness, as well as depth and breadth of coverage were the parameters that impacted most on cgMLST precision (i.e. identical alleles against reference circular genomes). All workflows performed well at ≥40X of depth of coverage, with high loci detection (> 99.54% for all, except for BioNumerics with 97.78%) and showed consistent cluster definitions using the reference cut-off of ≤7 allele differences.

Conclusions

This highlights that bioinformatics workflows dedicated to cgMLST allele calling are largely robust when paired-end reads are of high quality and when the sequencing depth is ≥40X.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08437-4.

Surveillance of Listeria monocytogenes: Early Detection, Population Dynamics, and Quasimetagenomic Sequencing during Selective Enrichment

In this study, we addressed different aspects regarding the implementation of quasimetagenomic sequencing as a hybrid surveillance method in combination with enrichment for early detection of Listeria monocytogenes in the food industry. Different experimental enrichment cultures were used, comprising seven L. monocytogenes strains of different sequence types (STs), with and without a background microbiota community. To assess whether the proportions of the different STs changed over time during enrichment, the growth and population dynamics were assessed using dapE colony sequencing and dapE and 16S rRNA amplicon sequencing. There was a tendency of some STs to have a higher relative abundance during the late stage of enrichment when L. monocytogenes was enriched without background microbiota. When coenriched with background microbiota, the population dynamics of the different STs was more consistent over time. To evaluate the earliest possible time point during enrichment that allows the detection of L. monocytogenes and at the same time the generation of genetic information that enables an estimation regarding the strain diversity in a sample, quasimetagenomic sequencing was performed early during enrichment in the presence of the background microbiota using Oxford Nanopore Technologies Flongle and Illumina MiSeq sequencing. The application of multiple displacement amplification (MDA) enabled detection of L. monocytogenes (and the background microbiota) after only 4 h of enrichment using both applied sequencing approaches. The MiSeq sequencing data additionally enabled the prediction of cooccurring L. monocytogenes strains in the samples.

IMPORTANCE We showed that a combination of a short primary enrichment combined with MDA and Nanopore sequencing can accelerate the traditional process of cultivation and identification of L. monocytogenes. The use of Illumina MiSeq sequencing additionally allowed us to predict the presence of cooccurring L. monocytogenes strains. Our results suggest quasimetagenomic sequencing is a valuable and promising hybrid surveillance tool for the food industry that enables faster identification of L. monocytogenes during early enrichment. Routine application of this approach could lead to more efficient and proactive actions in the food industry that prevent contamination and subsequent product recalls and food destruction, economic and reputational losses, and human listeriosis cases.

Phylogenetic Analysis and Genome-Wide Association Study Applied to an Italian Listeria monocytogenes Outbreak

From May 2015 to March 2016, a severe outbreak due to Listeria monocytogenes ST7 strain occurred in Central Italy and caused 24 confirmed clinical cases. The epidemic strain was deeply investigated using whole-genome sequencing (WGS) analysis. In the interested area, the foodborne outbreak investigation identified a meat food-producing plant contaminated by the outbreak strain, carried by pork-ready-to-eat products. In the same region, in March 2018, the epidemic strain reemerged causing one listeriosis case in a 10-month-old child. The aim of this study was to investigate the phylogeny of the epidemic and reemergent strains over time and to compare them with a closer ST7 clone, detected during the outbreak and with different pulsed-field gel electrophoresis (PFGE) profiles, in order to identify genomic features linked to the persistence and the reemergence of the outbreak. An approach combining phylogenetic analysis and genome-wide association study (GWAS) revealed that the epidemic and reemergent clones were genetically closer to the ST7 clone with different PFGE profiles and strictly associated with the pork production chain. The repeated detection of both clones was probably correlated with (i) the presence of truly persistent clones and the repeated introduction of new ones and (ii) the contribution of prophage genes in promoting the persistence of the epidemic clones. Despite that no significant genomic differences were detected between the outbreak and the reemergent strain, the two related clones detected during the outbreak can be differentiated by transcriptional factor and phage genes associated with the phage LP-114.

A machine learning-based typing scheme refinement for Listeria monocytogenes core genome multilocus sequence typing with high discriminatory power for common source outbreak tracking

Background

As whole-genome sequencing for pathogen genomes becomes increasingly popular, the typing methods of gene-by-gene comparison, such as core genome multilocus sequence typing (cgMLST) and whole-genome multilocus sequence typing (wgMLST), are being routinely implemented in molecular epidemiology. However, some intrinsic problems remain. For example, genomic sequences with varying read depths, read lengths, and assemblers influence the genome assemblies, introducing error or missing alleles into the generated allelic profiles. These errors and missing alleles might create “specious discrepancy” among closely related isolates, thus making accurate epidemiological interpretation challenging. In addition, the rapid growth of the cgMLST allelic profile database can cause problems related to storage and maintenance as well as long query search times.

Methods

We attempted to resolve these issues by decreasing the scheme size to reduce the occurrence of error and missing alleles, alleviate the storage burden, and improve the query search time. The challenge in this approach is maintaining the typing resolution when using fewer loci. We achieved this by using a popular artificial intelligence technique, XGBoost, coupled with Shapley additive explanations for feature selection. Finally, 370 loci from the original 1701 cgMLST loci of Listeria monocytogenes were selected.

Results

Although the size of the final scheme (LmScheme_370) was approximately 80% lower than that of the original cgMLST scheme, its discriminatory power, tested for 35 outbreaks, was concordant with that of the original cgMLST scheme. Although we used L. monocytogenes as a demonstration in this study, the approach can be applied to other schemes and pathogens. Our findings might help elucidate gene-by-gene–based epidemiology.

Genomic Diversity of Listeria monocytogenes Isolates From Slovakia (2010 to 2020)

Over the past 11 years, the Slovak National Reference Laboratory has collected a panel of 988 Listeria monocytogenes isolates in Slovakia, which were isolated from various food sectors (61%), food-processing environments (13.7%), animals with listeriosis symptoms (21.2%), and human cases (4.1%). We serotyped these isolates by agglutination method, which revealed the highest prevalence (61.1%) of serotype 1/2a and the lowest (4.7%) of serotype 1/2c, although these represented the majority of isolates from the meat sector. The distribution of CCs analyzed on 176 isolates demonstrated that CC11-ST451 (15.3%) was the most prevalent CC, particularly in food (14.8%) and animal isolates (17.5%). CC11-ST451, followed by CC7, CC14, and CC37, were the most prevalent CCs in the milk sector, and CC9 and CC8 in the meat sector. CC11-ST451 is probably widely distributed in Slovakia, mainly in the milk and dairy product sectors, posing a possible threat to public health. Potential persistence indication of CC9 was observed in one meat facility between 2014 and 2018, highlighting its general meat-related distribution and potential for persistence worldwide.

Identification of the source of a Listeria monocytogenes outbreak by investigational tracing

The number of identified listeriosis outbreaks has increased since the sequence typing of Listeria monocytogenes isolates was established in Germany. Due to the nature of the disease, listeriosis outbreaks are difficult to solve. We present investigational tracing as a simple and rapid method to conduct outbreak investigations. The method was applied in 2019 to stop a prolonged listeriosis outbreak in Germany. The starting point for the investigational tracing was nine health care facilities (HCF). Single cases developed listeriosis while they were staying at the nine facilities. Data were collected from companies that delivered foods to HCF and from ready-to-eat (RTE) foods that were consumed there. Following a step-wise approach, data analysis identified similarities in the food supply of the HCF. Food data were heterogeneous and needed to be standardised. Own brands and changing article numbers were challenging aspects during the identification of manufacturers. The analysis of the delivering companies revealed no similarities. Detailed information about the consumed risk foods for Listeria contamination became available for six HCF. All facilities served a wide variety of cold cut meat products to their in-patients. Investigational tracing revealed that only meat products from one out of 29 food business operators had been consumed in all six HCF. Further activities of the authorities enabled the identification of the outbreak strain on food products and in the processing environment of this company. A product recall and the measures taken stopped the listeriosis outbreak. Thus, investigational tracing can be crucial for the clarification of listeriosis outbreaks.

Whole Genome Sequencing Applied to Pathogen Source Tracking in Food Industry: Key Considerations for Robust Bioinformatics Data Analysis and Reliable Results Interpretation

Whole genome sequencing (WGS) has arisen as a powerful tool to perform pathogen source tracking in the food industry thanks to several developments in recent years. However, the cost associated to this technology and the degree of expertise required to accurately process and understand the data has limited its adoption at a wider scale. Additionally, the time needed to obtain actionable information is often seen as an impairment for the application and use of the information generated via WGS. Ongoing work towards standardization of wet lab including sequencing protocols, following guidelines from the regulatory authorities and international standardization efforts make the technology more and more accessible. However, data analysis and results interpretation guidelines are still subject to initiatives coming from distinct groups and institutions. There are multiple bioinformatics software and pipelines developed to handle such information. Nevertheless, little consensus exists on a standard way to process the data and interpret the results. Here, we want to present the constraints we face in an industrial setting and the steps we consider necessary to obtain high quality data, reproducible results and a robust interpretation of the obtained information. All of this, in a time frame allowing for data-driven actions supporting factories and their needs.

Backtracking and forward checking of human listeriosis clusters identified a multiclonal outbreak linked to Listeria monocytogenes in meat products of a single producer

Due to its high case fatality rate, foodborne listeriosis is considered a major public health concern worldwide. We describe one of the largest listeriosis outbreaks in Germany with 83 cases of invasive listeriosis between 2013 and 2018. As part of the outbreak investigation, we identified a highly diverse Listeria monocytogenes population at a single producer of ready-to-eat meat products. Strikingly, the extensive sampling after identification of a first match between a cluster of clinical isolates and a food isolate allowed for a linkage between this producer and a second, previously unmatched cluster of clinical isolates. Bacterial persistence in the processing plant and indications of cross-contamination events explained long-term contamination of food that led to the protracted outbreak. Based on screening for virulence factors, a pathogenic phenotype could not be ruled out for other strains circulating in the plant, suggesting that the outbreak could have been even larger. As most isolates were sensitive to common biocides used in the plant, hard to clean niches in the production line may have played a major role in the consolidation of the contamination. Our study demonstrates how important it is to search for the origin of infection when cases of illness have occurred (backtracking), but also clearly highlights that it is equally important to check whether a contamination at food or production level has caused disease (forward checking). Only through this two-sided control strategy, foodborne disease outbreaks such as listeriosis can be minimized, which could be a real improvement for public health.

Co-Occurrence of Listeria spp. and Spoilage Associated Microbiota During Meat Processing Due to Cross-Contamination Events

A large part of foodborne outbreaks related to Listeria monocytogenes are linked to meat and meat products. Especially, recontamination of meat products and deli-meat during slicing, packaging, and repackaging is in the focus of food authorities. In that regard, L. monocytogenes persistence in multi-species biofilms is one major issue, since they survive elaborate cleaning and disinfection measures. Here, we analyzed the microbial community structure throughout a meat processing facility using a combination of high-throughput full-length 16S ribosomal RNA (rRNA) gene sequencing and traditional microbiological methods. Samples were taken at different stages during meat cutting as well as from multiple sites throughout the facility environment to capture the product and the environmental associated microbiota co-occurring with Listeria spp. and L. monocytogenes. The listeria testing revealed a widely disseminated contamination (50%; 88 of 176 samples were positive for Listeria spp. and 13.6%; 24 of 176 samples were positive for L. monocytogenes). The pulsed-field gel electrophoresis (PFGE) typing evidenced 14 heterogeneous L. monocytogenes profiles with PCR-serogroup 1/2a, 3a as most dominant. PFGE type MA3-17 contributed to the resilient microbiota of the facility environment and was related to environmental persistence. The core in-house microbiota consisted mainly of the genera Acinetobacter, Pseudomonas, Psychrobacter (Proteobacteria), Anaerobacillus, Bacillus (Firmicutes), and Chryseobacterium (Bacteroidota). While the overall microbial community structure clearly differed between product and environmental samples, we were able to discern correlation patterns regarding the presence/absence of Listeria spp. in both sample groups. Specifically, our longitudinal analysis revealed association of Listeria spp. with known biofilm-producing Pseudomonas, Acinetobacter, and Janthinobacterium species on the meat samples. Similar patterns were also observed on the surface, indicating dispersal of microorganisms from this multispecies biofilm. Our data provided a better understanding of the built environment microbiome in the meat processing context and promoted more effective options for targeted disinfection in the analyzed facility.

Oxford nanopore sequencing in clinical microbiology and infection diagnostics

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

Multilocus Sequence Typing (MLST) and Whole Genome Sequencing (WGS) of Listeria monocytogenes and Listeria innocua

Nucleotide sequence-based methods focusing on the single-nucleotide polymorphisms (SNPs) of Listeria monocytogenes and L. innocua housekeeping genes (multilocus sequence typing) and in the core genome (core genome MLST) facilitate the rapid and interlaboratory comparison in open accessible databases as provided by Institute Pasteur ( https://bigsdb.web.pasteur.fr/listeria/listeria.html ). Strains can be compared on a global level and help to track forward and trace backward pathogen contamination events in food processing facilities and in outbreak scenarios.

Translatability of WGS typing results can simplify data exchange for surveillance and control of Listeria monocytogenes

Where classical epidemiology has proven to be inadequate for surveillance and control of foodborne pathogens, molecular epidemiology, using genomic typing methods, can add value. However, the analysis of whole genome sequencing (WGS) data varies widely and is not yet fully harmonised. We used genomic data on 494 Listeria monocytogenes isolates from ready-to-eat food products and food processing environments deposited in the strain collection of the German National Reference Laboratory to compare various procedures for WGS data analysis and to evaluate compatibility of results. Two different core genome multilocus sequence typing (cgMLST) schemes, different reference genomes in single nucleotide polymorphism (SNP) analysis and commercial as well as open-source software were compared. Correlation of allele distances from the different cgMLST approaches was high, ranging from 0.97 to 1, and unified thresholds yielded higher clustering concordance than scheme-specific thresholds. The number of detected SNP differences could be increased up to a factor of 3.9 using a specific reference genome compared with a general one. Additionally, specific reference genomes improved comparability of SNP analysis results obtained using different software tools. The use of a closed or a draft specific reference genome did not make a difference. The harmonisation of WGS data analysis will finally guarantee seamless data exchange, but, in the meantime, knowledge on threshold values that lead to comparable clustering of isolates by different methods may improve communication between laboratories. We therefore established a translation code between commonly applied cgMLST and SNP methods based on optimised clustering concordances. This code can work as a first filter to identify WGS-based typing matches resulting from different methods, which opens up a new perspective for data exchange and thereby accelerates time-critical analyses, such as in outbreak investigations.

An Open-Source Program (Haplo-ST) for Whole-Genome Sequence Typing Shows Extensive Diversity among Listeria monocytogenes Isolates in Outdoor Environments and Poultry Processing Plants

A reliable and standardized classification of Listeria monocytogenes is important for accurate strain identification during outbreak investigations. Current whole-genome sequencing (WGS)-based approaches for strain characterization are either difficult to standardize, rendering them less suitable for data exchange, or are not freely available. Thus, we developed a portable and open-source tool, Haplo-ST, to improve standardization and provide maximum discriminatory potential to WGS data tied to a multilocus sequence typing (MLST) framework. Haplo-ST performs whole-genome MLST (wgMLST) for L. monocytogenes while allowing for data exchangeability worldwide. This tool takes in (i) raw WGS reads as input, (ii) cleans the raw data according to user-specified parameters, (iii) assembles genes across loci by mapping to genes from reference strains, and (iv) assigns allelic profiles to assembled genes and provides a wgMLST subtyping for each isolate. Data exchangeability relies on the tool assigning allelic profiles based on a centralized nomenclature defined by the widely used BIGSdb-Lm database. Tests of Haplo-ST's performance with simulated reads from L. monocytogenes reference strains demonstrated high sensitivity (97.5%), and coverage depths of ≥20× were found to be sufficient for wgMLST profiling. We then used Haplo-ST to characterize and differentiate between two groups of L. monocytogenes isolates derived from the natural environment and poultry processing plants. Phylogenetic reconstruction identified lineages within each group, and no lineage specificity was observed with isolate phenotypes (transient versus persistent) or origins. Genetic differentiation analyses between isolate groups identified 21 significantly differentiated loci, potentially enriched for adaptation and persistence of L. monocytogenes within poultry processing plants.IMPORTANCE We have developed an open-source tool (https://github.com/swarnalilouha/Haplo-ST) that provides allele-based subtyping of L. monocytogenes isolates at the whole-genome level. Along with allelic profiles, this tool also generates allele sequences and identifies paralogs, which is useful for phylogenetic tree reconstruction and deciphering relationships between closely related isolates. More broadly, Haplo-ST is flexible and can be adapted to characterize the genome of any haploid organism simply by installing an organism-specific gene database. Haplo-ST also allows for scalable subtyping of isolates; fewer reference genes can be used for low-resolution typing, whereas higher resolution can be achieved by increasing the number of genes used in the analysis. Our tool enabled clustering of L. monocytogenes isolates into lineages and detection of potential loci for adaptation and persistence in food processing environments. Findings from these analyses highlight the effectiveness of Haplo-ST in subtyping and evaluating relationships among isolates in studies of bacterial population genetics.

10-Year Molecular Surveillance of Listeria monocytogenes Using Whole-Genome Sequencing in Shanghai, China, 2009-2019

Listeria monocytogenes is an etiologic agent of listeriosis, and has emerged as an important foodborne pathogen worldwide. In this study, the molecular characteristics of 155 L. monocytogenes isolates from seven food groups in Shanghai, the biggest city in China, were identified using whole-genome sequencing (WGS). Most L. monocytogenes isolates (79.3%) were obtained between May and October from 2009 to 2019. The serogroups and clonal complexes (CCs) of L. monocytogenes were found useful for identifying potential health risks linked to foods. Differences in distributions of serogroups and CCs among different food groups were analyzed using t-test. The results showed that the IIa and IVb serogroups were identified among most of food groups. However, the prevalence of serogroup IIb was significantly higher in ready-to-eat (RTE) food and raw seafood than in other food groups, similar to group IIc in raw meat and raw poultry than others. Meanwhile, the prevalence of CC9 in raw meat and raw poultry, CC8 in raw poultry, and CC87 in raw seafood significantly exceeded that of in other food groups. Specially, CC87 was the predominant CC in foodborne and clinical isolates in China, indicating that raw seafood may induce a high-risk to food safety. Also, hypervirulence pathogenicity islands LIPI-3 and LIPI-4 were found in CC3, CC1, and CC87, respectively. The clonal group CC619 carried LIPI-3 and LIPI-4, as previously reported in China. Core genome multilocus sequence typing (cgMLST) analysis suggested that CC87 isolates from the same food groups in different years had no allelic differences, indicating that L. monocytogenes could persist over years. These 10-year results in Shanghai underscore the significance of molecular epidemiological surveillance of L. monocytogenes in foodborne products in assessing the potential risk of this pathogen, and further address food safety issues in China.

A Real-Time PCR Screening Assay for Rapid Detection of Listeria Monocytogenes Outbreak Strains

From January 2015 to March 2016, an outbreak of 23 human cases of listeriosis in the Marche region and one human case in the Umbria region of Italy was caused by Listeria monocytogenes strains showing a new pulsotype never described before in Italy. A total of 37 clinical strains isolated from patients exhibiting listeriosis symptoms and 1374 strains correlated to the outbreak were received by the Italian National Reference Laboratory for L. monocytogenes (It NRL Lm) of Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise (IZSAM) for outbreak investigation. A real-time PCR assay was purposely designed for a rapid screening of the strains related to the outbreak. PCR-positive strains were successively typed through molecular serogrouping, pulsed field gel electrophoresis (PFGE), and Next Generation Sequencing (NGS). Applying the described strategy, based on real-time PCR screening, we were able to considerably reduce time and costs during the outbreak investigation activities.

A Simple and Robust Statistical Method to Define Genetic Relatedness of Samples Related to Outbreaks at the Genomic Scale - Application to Retrospective Salmonella Foodborne Outbreak Investigations

The investigation of foodborne outbreaks (FBOs) from genomic data typically relies on inspecting the relatedness of samples through a phylogenomic tree computed on either SNPs, genes, kmers, or alleles (i.e., cgMLST and wgMLST). The phylogenomic reconstruction is often time-consuming, computation-intensive and depends on hidden assumptions, pipelines implementation and their parameterization. In the context of FBO investigations, robust links between isolates are required in a timely manner to trigger appropriate management actions. Here, we propose a non-parametric statistical method to assert the relatedness of samples (i.e., outbreak cases) or whether to reject them (i.e., non-outbreak cases). With typical computation running within minutes on a desktop computer, we benchmarked the ability of three non-parametric statistical tests (i.e., Wilcoxon rank-sum, Kolmogorov-Smirnov and Kruskal-Wallis) on six different genomic features (i.e., SNPs, SNPs excluding recombination events, genes, kmers, cgMLST alleles, and wgMLST alleles) to discriminate outbreak cases (i.e., positive control: C+) from non-outbreak cases (i.e., negative control: C-). We leveraged four well-characterized and retrospectively investigated FBOs of Salmonella Typhimurium and its monophasic variant S. 1,4,[5],12:i:- from France, setting positive and negative controls in all the assays. We show that the approaches relying on pairwise SNP differences distinguished all four considered outbreaks in contrast to the other tested genomic features (i.e., genes, kmers, cgMLST alleles, and wgMLST alleles). The freely available non-parametric method written in R has been designed to be independent of both the phylogenomic reconstruction and the detection methods of genomic features (i.e., SNPs, genes, kmers, or alleles), making it widely and easily usable to anybody working on genomic data from suspected samples.

Temporal analysis of the Listeria monocytogenes population structure in floor drains during reconstruction and expansion of a meat processing plant

Due to a higher probability for violation of hygiene measures, reconstruction work is a substantial food safety challenge for food business operators (FBOs). Here, we monitored a Listeria monocytogenes contamination scenario during a timely enduring reconstruction period that aimed at an expansion of the main building of a leading meat processing facility. Reconstruction took place while food production was ongoing. We used a longitudinal sampling scheme targeting 40 floor water drains distributed over the food processing environment (FPE) over a five year period. The population structure of L. monocytogenes was determined by PCR-serogrouping, pulsed-field gel electrophoresis (PFGE) and multi-locus sequence typing (MLST). While the first sampling deciphered a baseline of contamination (45%), intensified sanitation measures decreased L. monocytogenes prevalence before commencement of work (5%). The reconstruction activities increased the prevalence of L. monocytogenes in the FPE (20.5%) and changed the population structure to a higher proportion of disease-associated genotypes (61%). During the first sampling ST121 was prevalent throughout the FPE, even in the packaging area. After the second and third sampling, following increased application of hypochlorite during sanitation, ST121 was only present in the raw material preparation area. A resilient flora was detected during three sampling events (ST8, ST9 and ST37) which might have not been exposed to daily cleaning in the floor drains. After the accomplishment of reconstruction work, the L. monocytogenes population structure shifted to the condition initially found (45% and 20.5% during the first and sixth sampling event). This paper indicates that reconstruction phases are high risk episodes for food safety in FPEs. Special precautions must be taken to avoid cross-contamination of products since reconstruction is usually ongoing for extended periods of time.

Isolate-Based Surveillance of Listeria monocytogenes by Whole Genome Sequencing in Austria

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.