Whole genome sequencing uses for foodborne contamination and compliance: Discovery of an emerging contamination event in an ice cream facility using whole genome sequencing

Precision public health in the era of genomics and big data

Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.

Genomic epidemiology of hypervirulent Listeria monocytogenes CC619: Population structure, phylodynamics and virulence

Listeria monocytogenes is a ubiquitous foodborne pathogen causing human and animal listeriosis with high mortality. Neurological and maternal-neonatal listeriosis outbreaks in Europe and the United States were frequently associated with clonal complexes CC1, CC2 and CC6 harboring Listeria Pathogenicity Island-1 (LIPI-1), as well as CC4 carrying both LIPI-1 and LIPI-4. However, human listeriosis in China was predominantly linked to CC87 and CC619 from serotype 1/2b. To understand the genetic evolution and distribution patterns of CC619, we characterized the epidemic history, population structure, and transmission feature of CC619 strains through analysis of 49,421 L. monocytogenes genomes globally. We found that CC619 was uniquely distributed in China, and closely related with perinatal infection. As CC619 strains were being mainly isolated from livestock and poultry products, we hypothesized that pigs and live chicken were the reservoirs of CC619. Importantly, all CC619 strains not only harbored the intact LIPI-1 and LIPI-4, but these also carried LIPI-3 that could facilitate host colonization and invasion. The deficiency of LIPI-3 or LIPI-4 markedly decreased L. monocytogenes colonization capacity in a model of intragastric infection in the mouse. Altogether, our findings suggest that the hypervirulent CC619 harboring three pathogenicity islands LIPI-1, LIPI-3 and LIPI-4 is a putatively persistent population in various foods, environment, and human population, warranting the further research for deciphering its pathogenicity and strengthening epidemiological surveillance.

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.

Making food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and emerging risk identification tools

To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify emerging food safety risks and to provide early warning signals in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things as part of early warning and emerging risk identification tools and methods in the food safety domain. There is an ongoing rapid development of systems fed by numerous, real-time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real-time food safety risk early warning systems. Although these developments increase the feasibility and effectiveness of prospective early warning and emerging risk identification tools, their implementation may prove challenging, particularly for low- and middle-income countries due to low connectivity and data availability. It is advocated to overcome these challenges by improving the capability and capacity of national authorities, as well as by enhancing their collaboration with the private sector and international organizations.

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities

IMPORTANCE

In developed countries, the human diet is predominated by food commodities, which have been manufactured, processed, and stored in a food production facility. Little is known about the application of metagenomic sequencing approaches for detecting foodborne pathogens, such as L. monocytogenes, and characterizing microbial diversity in food production ecosystems. In this work, we investigated the utility of 16S rRNA amplicon and quasimetagenomic sequencing for the taxonomic and phylogenetic classification of Listeria culture enrichments of environmental swabs collected from dairy and seafood production facilities. We demonstrated that single-nucleotide polymorphism (SNP) analyses of L. monocytogenes metagenome-assembled genomes (MAGs) from quasimetagenomic data sets can achieve similar resolution as culture isolate whole-genome sequencing. To further understand the impact of genome coverage on MAG SNP cluster resolution, an in silico downsampling approach was employed to reduce the percentage of target pathogen sequence reads, providing an initial estimate of required MAG coverage for subtyping resolution of L. monocytogenes.

An Overview of Foodborne Sample-Initiated Retrospective Outbreak Investigations and Interagency Collaboration in the United States

Foodborne outbreak investigations have traditionally included the detection of a cluster of illnesses first, followed by an epidemiologic investigation to identify a food of interest. The increasing use of whole genome sequencing (WGS) subtyping technology for clinical, environmental, and food isolates of foodborne pathogens, and the ability to share and compare the data on public platforms, present new opportunities to identify earlier links between illnesses and their potential sources. We describe a process called sample-initiated retrospective outbreak investigations (SIROI) used by federal public health and regulatory partners in the United States. SIROIs begin with an evaluation of the genomic similarity between bacterial isolates recovered from food or environmental samples and clusters of clinical isolates while subsequent and parallel epidemiologic and traceback investigations are initiated to corroborate their connection. SIROIs allow for earlier hypothesis generation, followed by targeted collection of information about food exposures and the foods and manufacturer of interest, to confirm a link between the illnesses and their source. This often leads to earlier action that could reduce the breadth and burden of foodborne illness outbreaks. We describe two case studies of recent SIROIs and present the benefits and challenges. Benefits include insight into foodborne illness attribution, international collaboration, and opportunities for enhanced food safety efforts in the food industry. Challenges include resource intensiveness, variability of epidemiologic and traceback data, and an increasingly complex food supply chain. SIROIs are valuable in identifying connections among small numbers of illnesses that may span significant time periods; detecting early signals for larger outbreaks or food safety issues associated with manufacturers; improving our understanding of the scope of contamination of foods; and identifying novel pathogen/commodity pairs.

Pervasive Listeria monocytogenes Is Common in the Norwegian Food System and Is Associated with Increased Prevalence of Stress Survival and Resistance Determinants

To investigate the diversity, distribution, persistence, and prevalence of stress survival and resistance genes of Listeria monocytogenes clones dominating in food processing environments in Norway, genome sequences from 769 L. monocytogenes isolates from food industry environments, foods, and raw materials (512 of which were sequenced in the present study) were subjected to whole-genome multilocus sequence typing (wgMLST), single-nucleotide polymorphism (SNP), and comparative genomic analyses. The data set comprised isolates from nine meat and six salmon processing facilities in Norway collected over a period of three decades. The most prevalent clonal complex (CC) was CC121, found in 10 factories, followed by CC7, CC8, and CC9, found in 7 factories each. Overall, 72% of the isolates were classified as persistent, showing 20 or fewer wgMLST allelic differences toward an isolate found in the same factory in a different calendar year. Moreover, over half of the isolates (56%) showed this level of genetic similarity toward an isolate collected from a different food processing facility. These were designated as pervasive strains, defined as clusters with the same level of genetic similarity as persistent strains but isolated from different factories. The prevalence of genetic determinants associated with increased survival in food processing environments, including heavy metal and biocide resistance determinants, stress response genes, and inlA truncation mutations, showed a highly significant increase among pervasive isolates but not among persistent isolates. Furthermore, these genes were significantly more prevalent among the isolates from food processing environments compared to in isolates from natural and rural environments (n = 218) and clinical isolates (n = 111) from Norway.

IMPORTANCEListeria monocytogenes can persist in food processing environments for months to decades and spread through the food system by, e.g., contaminated raw materials. Knowledge of the distribution and diversity of L. monocytogenes is important in outbreak investigations and is essential to effectively track and control this pathogen in the food system. The present study presents a comprehensive overview of the prevalence of persistent clones and of the diversity of L. monocytogenes in Norwegian food processing facilities. The results demonstrate extensive spread of highly similar strains throughout the Norwegian food system, in that 56% of the 769 collected isolates from food processing factories belonged to clusters of L. monocytogenes identified in more than one facility. These strains were associated with an overall increase in the prevalence of plasmids and determinants of heavy metal and biocide resistance, as well as other genetic elements associated with stress survival mechanisms and persistence.

Genetic diversity of Listeria monocytogenes isolates from farm products in Shanghai, China

Farm products are considered important vehicles for the transmission of Listeria monocytogenes. The typing of L. monocytogenes from farm products contributes to the surveillance and source tracing of the pathogen. In this study, 77 L. monocytogenes strains from seven farm product categories in Shanghai were analyzed by serological typing, multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE) and whole-genome nucleotide polymorphism (wgSNP). The results showed that the 77 isolates were classified into four serovars (1/2a, 1/2c, 1/2b and 4b), and of these, 1/2a (n=47) was the most prevalent. Seventeen sequence types (STs) were generated by MLST with two novel STs (ST1402 and ST1403), and 20 of 77 L. monocytogenes isolates had high genetic identity with previously documented outbreak isolates according to the minimum spanning tree from the MLST results. Moreover, 34 PFGE patterns (PF1-PF34) were differentiated, and based on a similarity value higher than 80% by the UPGMA dendrogram, the discriminatory index was relatively low (equal to 0.775). Furthermore, 14 isolates were chosen and further analyzed by wgSNP based on the previous typing results, which demonstrated that wgSNP and MLST yielded mostly consistent typing results but higher resolution than PFGE. In conclusion, 77 L. monocytogenes isolates from farm products collected in nine districts in Shanghai were highly genetically diverse, and 20 of these isolates had high relatedness with previously documented outbreak strains worldwide. The results indicate a possible cross-contamination risk of L. monocytogenes and a potential public health concern resulting from farm products during the supply chain in Shanghai, China.

WGS analysis of Listeria monocytogenes from rural, urban, and farm environments in Norway: Genetic diversity, persistence, and relation to clinical and food isolates

Listeria monocytogenes is a ubiquitous environmental bacterium associated with a wide variety of natural and human-made environments, such as soil, vegetation, livestock, food processing environments, and urban areas. It is also among the deadliest foodborne pathogens, and knowledge about its presence and diversity in potential sources is crucial to effectively track and control it in the food chain. Isolation of L. monocytogenes from various rural and urban environments showed higher prevalence in agricultural and urban developments than in forest or mountain areas, and that detection was positively associated with rainfall. Whole-genome sequencing (WGS) was performed for the collected isolates and for L. monocytogenes from Norwegian dairy farms and slugs (218 isolates in total). The data were compared to available data sets from clinical and food-associated sources in Norway collected within the last decade. Multiple examples of clusters of isolates with 0 to 8 whole-genome multilocus sequence typing (wgMLST) allelic differences were collected over time in the same location, demonstrating persistence of L. monocytogenes in natural, urban, and farm environments. Furthermore, several clusters with 6 to 20 wgMLST allelic differences containing isolates collected across different locations, times, and habitats were identified, including nine clusters harboring clinical isolates. The most ubiquitous clones found in soil and other natural and animal ecosystems (CC91, CC11, and CC37) were distinct from clones predominating among both clinical (CC7, CC121, and CC1) and food (CC9, CC121, CC7, and CC8) isolates. The analyses indicated that ST91 was more prevalent in Norway than other countries and revealed a high proportion of the hypovirulent ST121 among Norwegian clinical cases.

IMPORTANCEListeria monocytogenes is a deadly foodborne pathogen that is widespread in the environment. For effective management, both public health authorities and food producers need reliable tools for source tracking, surveillance, and risk assessment. For this, whole-genome sequencing (WGS) is regarded as the present and future gold standard. In the current study, we use WGS to show that L. monocytogenes can persist for months and years in natural, urban, and dairy farm environments. Notably, clusters of almost identical isolates, with genetic distances within the thresholds often suggested for defining an outbreak cluster, can be collected from geographically and temporally unrelated sources. The work highlights the need for a greater knowledge of the genetic relationships between clinical isolates and isolates of L. monocytogenes from a wide range of environments, including natural, urban, agricultural, livestock, food production, and food processing environments, to correctly interpret and use results from WGS analyses.

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.

The Persistence of Bacterial Pathogens in Surface Water and Its Impact on Global Food Safety

Water is vital to agriculture. It is essential that the water used for the production of fresh produce commodities be safe. Microbial pathogens are able to survive for extended periods of time in water. It is critical to understand their biology and ecology in this ecosystem in order to develop better mitigation strategies for farmers who grow these food crops. In this review the prevalence, persistence and ecology of four major foodborne pathogens, Shiga toxin-producing Escherichia coli (STEC), Salmonella, Campylobacter and closely related Arcobacter, and Listeria monocytogenes, in water are discussed. These pathogens have been linked to fresh produce outbreaks, some with devastating consequences, where, in a few cases, the contamination event has been traced to water used for crop production or post-harvest activities. In addition, antimicrobial resistance, methods improvements, including the role of genomics in aiding in the understanding of these pathogens, are discussed. Finally, global initiatives to improve our knowledge base of these pathogens around the world are touched upon.

Listeria monocytogenes Contamination Characteristics in Two Ready-to-Eat Meat Plants From 2019 to 2020 in Shanghai

Listeria monocytogenes is a ubiquitous foodborne pathogen that causes listeriosis and is mostly linked to consumption of ready-to-eat (RTE) foods. Lack of hygiene in food processing environments may be a primary reason for contamination by L. monocytogenes isolates. In this study, L. monocytogenes strains isolated from two RTE meat processing plants in the Shanghai municipality, China, were characterized during 2019–2020 using pulsed-field gel electrophoresis and whole-genome sequencing. Results showed that 29 samples (12.2%) out of 239 were positive for L. monocytogenes, with 21 (18.9%) and 8 (6.25%) isolates from plants A and B, respectively. The packaging room at plant A had the most contamination (14, 48.3%; p < 0.05), with a peak occurrence of 76.5% in processing environments. Nineteen L. monocytogenes isolates belonging to the pulsotype (PT) 7 group were indistinguishable (≥ 95.7%). Furthermore, core-genome multiple loci sequencing typing identified up to nine allelic differences, and the closet pairwise differences among these ST5 isolates included 0–16 small nucleotide polymorphisms. Therefore, L. monocytogenes likely persisted at plant A during 2019–2020 with ongoing clone transmission. In contrast, no L. monocytogenes isolates were identified from processing environments at plant B. Most L. monocytogenes isolates were sampled from raw materials (62.5%). Several isolates (ST378, ST8, and ST120) were detected only once in 2020 and were considered as transient isolates. However, three ST121 isolates with the same PT (PT2) were detected in 2020 and should be noted for their stronger survival ability in harsh environments. These results suggest that continuous monitoring, stringent surveillance, and source tracking are crucial to guaranteeing food safety in RTE food plants.

Prevalence and Genetic Diversity of Listeria monocytogenes Isolated From Retail Pork in Wuhan, China

Listeria monocytogenes is a ubiquitous bacteria and causative agent of zoonotic listeriosis with high mortality. The consumption of contaminated animal-derived foods has been linked with both epidemic and sporadic listeriosis. In this work, a total of 64 L. monocytogenes isolates from 259 pork samples sold in 11 supermarket chains were identified and characterized by comparative whole-genome analysis. All isolates were delineated into eight clonal complexes (CCs), namely CC2, CC8, CC9, CC11, CC155, CC121, CC204, and CC619, spanning two lineages (I and II) and carrying 3–5 antibiotic-resistant genes (fosX, lnu, mprF, tetM, and dhfR). It is noted that Listeria pathogenicity island (LIPI)-1, LIPI-3, and LIPI-4 were distributed in all ST619 isolates from two supermarket chains that were closely related with clinical isolates (<40 SNP). Some of the isolates from different supermarket chains with 0 SNP difference indicated a common pork supply source. Notably, 57.81% of the strains carried types IB, IIA, or IIIB CRISPR-Cas system, CC121 isolates carried both types IB and IIA CRISPR-Cas systems, Cas proteins of CC155 isolates located between two CRISPR loci, each CC has unique organization of Cas proteins as well as CRISPR loci. CRISPR-Cas system-based subtyping improved discrimination of pork-derived L. monocytogenes isolates. Comparisons at the genome level contributed to understand the genetic diversities and variations among the isolates and provided insights into the genetic makeup and relatedness of these pathogens.

Determination of Genomic Epidemiology of Historical Clostridium perfringens Outbreaks in New York State by Use of Two Web-Based Platforms: National Center for Biotechnology Information Pathogen Detection and FDA GalaxyTrakr

Clostridium perfringens is the second leading cause of bacterial foodborne illness in the United States. The Wadsworth Center (WC) at the New York State Department of Health enumerates infectious dose from primary patient and food samples and, until recently, identified C. perfringens to the species level only. We investigated whether whole-genome sequence-based subtyping could benefit epidemiological investigations of this pathogen, as it has with other enteric organisms. We retrospectively sequenced 76 patient and food samples received between May 2010 and February 2020, including 52 samples linked epidemiologically to 13 outbreaks and 24 sporadic samples not linked to other samples. Phylogenetic trees were built using two Web-based platforms: National Centers for Biotechnology Information Pathogen Detection (NCBI-PD) and GalaxyTrakr (a Galaxy instance supported by the GenomeTrakr initiative). For GalaxyTrakr analyses, single nucleotide polymorphism (SNP) matrices and maximum-likelihood (ML) trees were generated using 3 different reference genomes. Across the four separate analyses, phylogenetic clustering was generally concordant with epidemiologically identified outbreaks. SNP diversity among phylogenetically linked samples from an outbreak ranged from 0 to 20 SNPs, excepting one outbreak ranging from 4 to 62 SNPs. Importantly, four of the 13 outbreak isolates harbored one or more samples that were phylogenetic outliers, and for two outbreaks, no samples were closely related. Two specimens were found harboring two distinct genotypes. For samples below CDC enumeration dose threshold, phylogenetic clustering was robust and linked patient and/or food samples. We concluded that WGS phylogenetic clusters (i) are largely concordant with epidemiologically defined outbreaks, irrespective of analysis platform or reference genome we employed; (ii) have limited pairwise SNP diversity, allowing phylogenetic clusters to be distinguished from sporadic cases; and (iii) can aid in epidemiological investigations by identifying outlier and polyclonal samples.

Food Safety Genomics and Connections to One Health and the Clinical Microbiology Laboratory

This article describes the potential for one health surveillance of foodborne pathogens and disease using the revolutionary methodologies of whole genome sequencing. Whole genome sequencing of viral and bacterial pathogens is a natural fit to a one health perspective because these pathogens reside and are shared by humans, animals, and the environment and their genomes are compared easily regardless of where or from what host the pathogen was isolated. A genome provides a huge amount of data that can be analyzed for numerous applications. Sharing data coordinates surveillance efforts across the various disciplines.

Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring

The laboratory identification of antibacterial resistance is a cornerstone of infectious disease medicine. In vitro antimicrobial susceptibility testing has long been based on the growth response of organisms in pure culture to a defined concentration of antimicrobial agents. By comparing individual isolates to wild-type susceptibility patterns, strains with acquired resistance can be identified. Acquired resistance can also be detected genetically. After many decades of research, the inventory of genes underlying antimicrobial resistance is well known for several pathogenic genera including zoonotic enteric organisms such as Salmonella and Campylobacter and continues to grow substantially for others. With the decline in costs for large scale DNA sequencing, it is now practicable to characterize bacteria using whole genome sequencing, including the carriage of resistance genes in individual microorganisms and those present in complex biological samples. With genomics, we can generate comprehensive, detailed information on the bacterium, the mechanisms of antibiotic resistance, clues to its source, and the nature of mobile DNA elements by which resistance spreads. These developments point to a new paradigm for antimicrobial resistance detection and tracking for both clinical and public health purposes.

In-Depth Longitudinal Study of Listeria monocytogenes ST9 Isolates from the Meat Processing Industry: Resolving Diversity and Transmission Patterns Using Whole-Genome Sequencing

Listeria monocytogenes is a deadly foodborne pathogen that is widespread in the environment, and certain types can be established in food factories. The sequence type ST9 dominates in meat processing environments, and this work was undertaken to obtain data needed for the tracking of this subtype. By using whole-genome sequencing (WGS), we revealed the presence of cross-contamination routes between meat factories as well as within a single factory, including the spread from different reservoirs within the same room. It was also possible to estimate the time frame of persistence in the factory, as well as when and how new clones had entered. The present work contributes valuable information about the diversity of ST9 and exemplifies the potential power of WGS in food safety management, allowing the determination of relationships between strains both in an international context and locally between and within factories.

Listeria monocytogenes is a pathogen mostly associated with the consumption of ready-to-eat foods and can cause severe disease and death. It can be introduced into food chains from raw materials, but often the contamination source is the food production environment, where certain clones can persist for years. In the meat chain, ST9 is one of the most commonly encountered L. monocytogenes sequence types, and for effective source tracking, the divergence and spread of ST9 must be understood. In this study, whole-genome sequencing (WGS) was used to characterize and track 252 L. monocytogenes ST9 isolates collected from four Norwegian meat processing plants between 2009 and 2017. The isolates formed distinct clusters relative to genomes found in public databases, and all but three isolates clustered into two major clonal populations. Different contamination patterns were revealed, e.g., evidence of contamination of two factories with a clone that diverged from its ancestor in the late 1990s through a common source of raw materials; breach of hygienic barriers within a factory, leading to repeated detection of two clones in the high-risk zone during a 4- to 6-year period; entry through the purchase and installation of second-hand equipment harboring a previously established clonal population; and spreading and diversification of two clones from two reservoirs within the same production room over a 9-year period. The present work provides data on the diversity of ST9, which is crucial for epidemiological investigations and highlights how WGS can be used for source tracking within food processing factories.

IMPORTANCEListeria monocytogenes is a deadly foodborne pathogen that is widespread in the environment, and certain types can be established in food factories. The sequence type ST9 dominates in meat processing environments, and this work was undertaken to obtain data needed for the tracking of this subtype. By using whole-genome sequencing (WGS), we revealed the presence of cross-contamination routes between meat factories as well as within a single factory, including the spread from different reservoirs within the same room. It was also possible to estimate the time frame of persistence in the factory, as well as when and how new clones had entered. The present work contributes valuable information about the diversity of ST9 and exemplifies the potential power of WGS in food safety management, allowing the determination of relationships between strains both in an international context and locally between and within factories.

Microevolution and Gain or Loss of Mobile Genetic Elements of Outbreak-Related Listeria monocytogenes in Food Processing Environments Identified by Whole Genome Sequencing Analysis

Whole genome sequencing (WGS) analyses have been instrumental in traceback investigations of Listeria monocytogenes (Lm). To demonstrate how long-read sequencing analysis can capture and describe relationships among isolates from clinical, food, and environmental sources, we analyzed 366 long-read- and shotgun-sequenced isolates from 16 Lm outbreak strains associated with cantaloupe, leafy green, stone fruit, caramel apple, mung bean sprout, multiple cheese products, multiple ice cream products, and their production environments. The analyses demonstrated that outbreak strains could be distributed in different areas and zones of food production environments through persistent or repeated contamination. Multi-strain and multi-clone contamination were common. Further, WGS could differentiate among isolates collected at different time points or from different production lines in the same facility, revealing microevolution events in processing environments. Our comparison between complete and shotgun genomes showed that isolates of the same outbreak strain diversified mostly by gain/loss of plasmids and chromosome-borne prophages that constitute 2 to 5% of the chromosome. In contrast, other genes missing in the shotgun genomes were randomly scattered, constituting ~0.5% of the chromosome. Among different outbreak strains of the same CC, most gene-scale differences were due to gain/loss of mobile genetic elements, such as plasmids, chromosome-borne prophages, a Tn916 like transposon, and Listeria Genomic Island 2. The nucleotide variations in the same prophage and the same plasmid shared among isolates of the same outbreak strain were limited, which enabled different WGS tools to unambiguously cluster isolates of the same outbreak strain. In some outbreak strains, correlation between prophage gain/loss and single nucleotide polymorphism (SNP) accumulations in the genome backbone were observed.

Comparative genomic provides insight into the virulence and genetic diversity of Vibrio parahaemolyticus associated with shrimp acute hepatopancreatic necrosis disease

Acute hepatopancreatic necrosis disease (AHPND) is an important shrimp disease of economic importance which causes mass mortality of cultivated penaeid shrimps in Southeast Asian countries, Mexico and South America. This disease was originally caused by Vibrio parahaemolyticus (VP_AHPND) which is reported to harbour a transferable plasmid carrying the virulent PirAB-like toxin genes (pirAB^vp). However, little is known about the pathogenicity of VP_AHPND. To extend our understanding, comparative genomic analyses was performed in this study to identify the genetic differences and to understand the phylogenetic relationship of VP_AHPND strains. Seven Vibrio parahaemolyticus strains (five VP_AHPND strains and two non-VP_AHPND strains) were sequenced and 31 draft genomes of V. parahaemolyticus were retrieved from NCBI database and incorporated into the genomic comparison to elucidate their genomic diversity. The study showed that the genome sizes of the VP_AHPND strains were approximately 5 Mbp. Ten sequence types (STs) were identified among the VP_AHPND strains using in silico-Multilocus Sequence Typing analysis (MLST) and ST 970 was the predominant ST. Phylogenetic analysis based on MLST and single nucleotide polymorphisms (SNP) showed that the VP_AHPND strains were genetically diverse. Based on the comparative genomic analysis, several functional proteins were identified from diiferent categories associated with virulence-related proteins, secretory proteins, conserved domain proteins, transporter proteins, and phage proteins. The CRISPR analysis showed that VP_AHPND strains contained less number of CRISPRs elements than non-VP_AHPND strains while six prophages regions were identified in the genomes, suggested the lack of CRISPR might promote prophage insertion. The genomic information in this study provide improved understanding of the virulence of these VP_AHPND strains.