Implementation of Nationwide Real-time Whole-genome Sequencing to Enhance Listeriosis Outbreak Detection and Investigation

Foodborne bacterial pathogens: genome-based approaches for enduring and emerging threats in a complex and changing world

Foodborne illnesses pose a substantial health and economic burden, presenting challenges in prevention due to the diverse microbial hazards that can enter and spread within food systems. Various factors, including natural, political and commercial drivers, influence food production and distribution. The risks of foodborne illness will continue to evolve in step with these drivers and with changes to food systems. For example, climate impacts on water availability for agriculture, changes in food sustainability targets and evolving customer preferences can all have an impact on the ecology of foodborne pathogens and the agrifood niches that can carry microorganisms. Whole-genome and metagenome sequencing, combined with microbial surveillance schemes and insights from the food system, can provide authorities and businesses with transformative information to address risks and implement new food safety interventions across the food chain. In this Review, we describe how genome-based approaches have advanced our understanding of the evolution and spread of enduring bacterial foodborne hazards as well as their role in identifying emerging foodborne hazards. Furthermore, foodborne hazards exist in complex microbial communities across the entire food chain, and consideration of these co-existing organisms is essential to understanding the entire ecology supporting pathogen persistence and transmission in an evolving food system.

Listeria monocytogenes in beef: a hidden risk

Listeria monocytogenes in beef receives less attention compared to other pathogens such as Salmonella and Escherichia coli. To address this gap, we conducted a literature review focusing on the presence of L. monocytogenes in beef. This review encompasses the pathogenic mechanisms, routes of contamination, prevalence rates, and the laws and regulations employed in various countries. Our findings reveal a prevalence of L. monocytogenes in beef and beef products ranging from 2.5% to 59.4%. Notably, serotype 4b was most frequently isolated in cases of beef contamination during food processing, with the skinning and evisceration stages identified as critical points of contamination.

RIPS (rapid intuitive pathogen surveillance): a tool for surveillance of genome sequence data from foodborne bacterial pathogens

Monitoring data submitted to the National Center for Biotechnology Information's Pathogen Detection whole-genome sequence database, which includes the foodborne bacterial pathogens Listeria monocytogenes, Salmonella enterica, and Escherichia coli, has proven effective for detecting emerging outbreaks. As part of the submission process, new sequence data are typed using a whole-genome multi-locus sequence typing scheme and clustered with sequences already in the database. Publicly available text files contain the results of these analyses. However, contextualizing and interpreting this information is complex. We present the Rapid Intuitive Pathogen Surveillance (RIPS) tool, which shows the results of the NCBI Rapid Reports, along with appropriate metadata, in a graphical, interactive dashboard. RIPS makes the information in the Rapid Reports useful for real-time surveillance of genome sequence databases.

[Molecular characterization of Listeria monocytogenes isolates from human and food sources in Argentina, 2018-2023]

Human listeriosis is an infectious disease caused by Listeria monocytogenes. The invasive form of this disease leads to a high rate of hospitalizations and fatality. The main mode of transmission is through contaminated ready-to-eat foods such as dairy, vegetables and meat products. The knowledge of the diversity and population dynamics of isolates collected from human and food sources is essential for the detection of clusters and the identification of common sites of infection. The aim of this study was the molecular characterization of L. monocytogenes isolates in Argentina. We sequenced a total of 63 isolates, 35 from human and 28 from food sources, collected between 2018 and 2023. Our genomic study divided the isolates into two lineages, four serogroups, 17 sequence types and 15 clonal complexes (CCs). The hypervirulent clone CC1 (lineage I; serogroup IVb) predominated in human and food samples. The phylogenomic analysis showed a high and possible epidemiological relationship between isolates from human and/or food sources, suggesting the presence of transmission chains in our country. These findings highlight the need to strengthen genomic surveillance of L. monocytogenes in Argentina. The identification of geographic distribution and characteristics of predominant and emerging clones from human and food sources might help to focus action plans and public health policies better directed at the control and prevention of listeriosis.

Empowering public health: building advanced molecular surveillance in resource-limited settings through collaboration and capacity-building

The rapid detection and continuous surveillance of infectious diseases are important components of an effective public health response. However, establishing advanced molecular surveillance systems, crucial for monitoring and mitigating pandemics, poses significant challenges in resource-limited developing countries. In a collaborative effort, research institutions from Benin joined forces with Mali's National Institute of Public Health to implement a state-of-the-art molecular surveillance system in Mali. This approach was characterized by collaboration, multidisciplinarity, and tutoring. Key activities included a comprehensive assessment of infrastructure and human resources through document reviews, interviews, and laboratory visits; the development and validation of Standard Operating Procedures (SOPs) for advanced molecular surveillance following an inclusive approach; capacity-building initiatives for 25 biologists in Mali on sequencing techniques; and international tutoring sessions for eight Malian professionals held in Benin. These collective efforts enabled Mali to establish an advanced molecular surveillance system aligned with the WHO's global strategy for genomic surveillance. This manuscript aims to share experiences, insights, and outcomes from this initiative, with the hope of contributing to the broader discussion on strengthening global health security through collaborative approaches and capacity-building efforts, particularly in developing countries.

Genomic perspectives on foodborne illness

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. We analyzed clusters of sequenced clinical isolates of Salmonella, Escherichia coli, Campylobacter, and Listeria that differ by only a small number of mutations to provide a new understanding of the underlying contamination episodes. These analyses provide new evidence that the youngest age groups have greater susceptibility to infection from Salmonella, Escherichia coli, and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. Analysis of these clusters reveals significant regional variations in relative frequencies of Salmonella serovars across the United States. A large fraction of the contamination episodes causing sickness appear to have long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost three years. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. The vast majority of Salmonella cases among infants < 6 months of age appear to be caused by cross-contamination from foods consumed by older age groups or by environmental bacteria rather than infant formula contaminated at production sites.

Closing the gap: Oxford Nanopore Technologies R10 sequencing allows comparable results to Illumina sequencing for SNP-based outbreak investigation of bacterial pathogens

Whole-genome sequencing has become the method of choice for bacterial outbreak investigation, with most clinical and public health laboratories currently routinely using short-read Illumina sequencing. Recently, long-read Oxford Nanopore Technologies (ONT) sequencing has gained prominence and may offer advantages over short-read sequencing, particularly with the recent introduction of the R10 chemistry, which promises much lower error rates than the R9 chemistry. However, limited information is available on its performance for bacterial single-nucleotide polymorphism (SNP)-based outbreak investigation. We present an open-source workflow, Prokaryotic Awesome variant Calling Utility (PACU) (https://github.com/BioinformaticsPlatformWIV-ISP/PACU), for constructing SNP phylogenies using Illumina and/or ONT R9/R10 sequencing data. The workflow was evaluated using outbreak data sets of Shiga toxin-producing Escherichia coli and Listeria monocytogenes by comparing ONT R9 and R10 with Illumina data. The performance of each sequencing technology was evaluated not only separately but also by integrating samples sequenced by different technologies/chemistries into the same phylogenomic analysis. Additionally, the minimum sequencing time required to obtain accurate phylogenetic results using nanopore sequencing was evaluated. PACU allowed accurate identification of outbreak clusters for both species using all technologies/chemistries, but ONT R9 results deviated slightly more from the Illumina results. ONT R10 results showed trends very similar to Illumina, and we found that integrating data sets sequenced by either Illumina or ONT R10 for different isolates into the same analysis produced stable and highly accurate phylogenomic results. The resulting phylogenies for these two outbreaks stabilized after ~20 hours of sequencing for ONT R9 and ~8 hours for ONT R10. This study provides a proof of concept for using ONT R10, either in isolation or in combination with Illumina, for rapid and accurate bacterial SNP-based outbreak investigation.

Intensive Environmental Sampling and Whole Genome Sequence-based Characterization of Listeria in Small- and Medium-sized Dairy Facilities Reveal Opportunities for Simplified and Size-appropriate Environmental Monitoring Strategies

Small- and medium-sized dairy processing facilities (SMDFs) may face unique challenges with respect to controlling Listeria in their processing environments, e.g., due to limited resources. The aim of this study was to implement and evaluate environmental monitoring programs (EMPs) for Listeria control in eight SMDFs in a ∼1-year longitudinal study; this included a comparison of pre-operation (i.e., after cleaning and sanitation and prior to production) and mid-operation (i.e., at least 4 h into production) sampling strategies. Among 2,072 environmental sponge samples collected across all facilities, 272 (13%) were positive for Listeria. Listeria prevalence among pre- and mid-operation samples (15% and 17%, respectively), was not significantly different. Whole genome sequencing (WGS) performed on select isolates to characterize Listeria persistence patterns revealed repeated isolation of closely related Listeria isolates (i.e., ≤20 high-quality single nucleotide polymorphism [hqSNP] differences) in 5/8 facilities over >6 months, suggesting Listeria persistence and/or reintroduction was relatively common among the SMDFs evaluated here. WGS furthermore showed that for 41 sites where samples collected pre- and mid-operation were positive for Listeria, Listeria isolates obtained were highly related (i.e., ≤10 hqSNP differences), suggesting that pre-operation sampling alone may be sufficient and more effective for detecting sites of Listeria persistence. Importantly, our data also showed that only 1/8 of facilities showed a significant decrease in Listeria prevalence over 1 year, indicating continued challenges with Listeria control in at least some SMDFs. We conclude that options for simplified Listeria EMPs (e.g., with a focus on pre-operation sampling, which allows for more rapid identification of likely persistence sites) may be valuable for improved Listeria control in SMDFs.

Whole genome enrichment approach for genomic surveillance of Toxoplasma gondii

Pathogenic bacteria, viruses, fungi, and protozoa can cause food and waterborne diseases. Surveillance methods must therefore screen for these pathogens at various stages of water distribution and of food from production to consumption. Detection using nucleic acid amplification methods offer rapid identification, but such methods have limited utility for characterizing populations, variant types or virulence traits of pathogens. Whole genome sequencing (WGS) can be used to determine this information. However, pathogens must be isolated and cultured to yield sufficient DNA for WGS, which is laborious or not feasible for certain stages of parasites like oocysts of Toxoplasma gondii. We previously developed the Circular Nucleic acid Enrichment Reagent (CNER) method to make whole genome enrichment (WGE) baits for difficult-to-grow bacterial pathogens. WGE using CNERs facilitates direct sequencing of pathogens from samples without the need to isolate and grow them. Here, we made WGE-CNERs for T. gondii to demonstrate the use of the CNER method to make baits to enrich the large genomes of water and foodborne protozoan pathogens. By sequencing, we detected as few as 50 parasites spiked in an oyster hemolymph matrix. We discuss the use of WGE-CNERs for genomic surveillance of food and waterborne pathogens.

Automated centrifugal microfluidic system for the preparation of adaptor-ligated sequencing libraries

The intensive workload associated with the preparation of high-quality DNA libraries remains a key obstacle toward widespread deployment of sequencing technologies in remote and resource-limited areas. We describe the development of single-use microfluidic devices driven by an advanced pneumatic centrifugal microfluidic platform, the PowerBlade, to automate the preparation of Illumina-compatible libraries based on adaptor ligation methodology. The developed on-chip workflow includes enzymatic DNA fragmentation coupled to end-repair, adaptor ligation, first DNA cleanup, PCR amplification, and second DNA cleanup. This complex workflow was successfully integrated into simple thermoplastic microfluidic devices that are amenable to mass production with injection molding. The system was validated by preparing, on chip, libraries from a mixture of genomic DNA extracted from three common foodborne pathogens (Listeria monocytogenes, Escherichia coli and Salmonella enterica serovar Typhimurium) and comparing them with libraries made via a manual procedure. The two types of libraries were found to exhibit similar quality control metrics (including genome coverage, assembly, and relative abundances) and led to nearly uniform coverage independent of GC content. This microfluidic technology offers a time-saving and cost-effective alternative to manual procedures and robotic-based automation, making it suitable for deployment in remote environments where technical expertise and resources might be scarce. Specifically, it facilitates field practices that involve mid- to low-throughput sequencing, such as tasks related to foodborne pathogen detection, characterization, and microbial profiling.

Clinical Findings of Listeria monocytogenes Infections with a Special Focus on Bone Localizations

Listeria monocytogenes is a Gram-positive pathogenic bacterium which can be found in soil or water. Infection with the microorganism can occur after ingestion of contaminated food products. Small and large outbreaks of listeriosis have been described in the past. L. monocytogenes can cause a number of different clinical syndromes, most frequently sepsis, meningitis, and rhombencephalitis, particularly in immunocompromised hosts. L. monocytogenes systemic infections can develop following tissue penetration across the gastrointestinal tract or to hematogenous spread to sterile sites, possibly evolving towards bacteremia. L. monocytogenes only rarely causes bone or joint infections, usually in the context of prosthetic material that can provide a site for bacterial seeding. We describe here the clinical findings of invasive listeriosis, mainly focusing on the diagnosis, clinical management, and treatment of bone and vertebral infections occurring in the context of invasive listeriosis.

SARS-CoV-2 lineage assignments using phylogenetic placement/UShER are superior to pangoLEARN machine-learning method

With the rapid spread and evolution of SARS-CoV-2, the ability to monitor its transmission and distinguish among viral lineages is critical for pandemic response efforts. The most commonly used software for the lineage assignment of newly isolated SARS-CoV-2 genomes is pangolin, which offers two methods of assignment, pangoLEARN and pUShER. PangoLEARN rapidly assigns lineages using a machine-learning algorithm, while pUShER performs a phylogenetic placement to identify the lineage corresponding to a newly sequenced genome. In a preliminary study, we observed that pangoLEARN (decision tree model), while substantially faster than pUShER, offered less consistency across different versions of pangolin v3. Here, we expand upon this analysis to include v3 and v4 of pangolin, which moved the default algorithm for lineage assignment from pangoLEARN in v3 to pUShER in v4, and perform a thorough analysis confirming that pUShER is not only more stable across versions but also more accurate. Our findings suggest that future lineage assignment algorithms for various pathogens should consider the value of phylogenetic placement.

Role of Whole Genome Sequencing in Assessing Resident and Transient Listeria monocytogenes in a Produce Packinghouse

Whole genome sequencing (WGS) is a powerful tool that may be used to assist in identifying Listeria contamination sources and movement within environments, and to assess persistence. This study investigated sites in a produce packinghouse where Listeria had been historically isolated; and aimed to characterize dispersal patterns and identify cases of transient and resident Listeria. Environmental swab samples (n = 402) were collected from 67 sites at two time-points on three separate visits. Each sample was tested for Listeria, and Listeria isolates were characterized by partial sigB sequencing to determine species and allelic type (AT). Representative isolates from the three most common L. monocytogenes ATs (n = 79) were further characterized by WGS. Of the 144 Listeria species positive samples (35.8%), L. monocytogenes was the most prevalent species. L. monocytogenes was often coisolated with another species of Listeria. WGS identified cases of sporadic and continued reintroduction of L. monocytogenes from the cold storages into the packinghouse and demonstrated cases of L. monocytogenes persistence over 2 years in cold storages, drains, and on a forklift. Nine distinct clusters were found in this study. Two clusters showed evidence of persistence. Isolates in these two clusters (N = 11, with one historical isolate) were obtained predominantly and over multiple samplings from cold storages, with sporadic movement to sites in the packing area, suggesting residence in cold storages with opportunistic dispersal within the packinghouse. The other seven clusters demonstrated evidence of transient Listeria, as isolation was sporadic over time and space during the packing season. Our data provide important insights into likely L. monocytogenes harborage points and transfer in a packinghouse, which is key to root cause analysis. While results support Listeria spp. as a suitable indicator organism for environmental monitoring surveys, findings were unable to establish a specific species as an index organism for L. monocytogenes. Findings also suggest long-term persistence with substantial SNP diversification, which may assist in identifying potential contamination sources and implementing control measures.

Molecular characterization of Listeria monocytogenes strains isolated from imported food in China from 14 countries/regions, 2003-2018

Listeria monocytogenes (Lm) is associated with severe foodborne infections and ubiquitous in the nature. Identification of characteristics of Lm transmission through trading of food products is essential for rapidly tracking Lm sources and controlling dissemination of listeriosis. In this study, a total of 44 Lm strains were isolated from food products originating from 14 countries/regions during 2003-2018 at the Shanghai port. The genomes of these Lm strains were sequenced by high-throughput sequencing. Multilocus sequence typing (MLST) analysis showed that 43 isolates were divided into 17 sequence types (STs). The distribution of STs was decentralized, with the dominant ST2 accounting for only 18.18% of the strains. The LM63 strain did not match with any of the existing STs. Core-genome MLST (cgMLST) analysis based on 1748 core genes categorized the 44 strains into 30 cgMLST types (CTs), with CT10153 and CT7892 as the most predominant CTs. Notably, LM63 and LM67 shared the same CT in the cgMLST analysis. The phylogenetic analysis based on single-copy homologous genes revealed that the 44 Lm strains were primarily classified into two lineages. The SNP analysis also indicated that these strains were roughly divided into two clades, with strains in the first clade mainly collected earlier than those in the second clade, which were predominantly collected from 2010 onwards. The analysis using the virulence factor database (VFDB) indicated that the virulence gene inlJ was the most prevalent among these 44 strains. Notably, ddrA, msbA, and sugC were enriched in this dataset, requiring further clarification of their roles in Listeria through future studies. These results might provide a clue for understanding of the global epidemiology and surveillance of Lm and present insights for implementing effective measures to reduce or prevent Listeria contamination outbreaks in imported food products.

Predicting Food Sources of Listeria monocytogenes Based on Genomic Profiling Using Random Forest Model

Listeria monocytogenes can cause severe foodborne illness, including miscarriage during pregnancy or death in newborn infants. When outbreaks of L. monocytogenes illness occur, it may be possible to determine the food source of the outbreak. However, most reported L. monocytogenes illnesses do not occur as part of a recognized outbreak and most of the time the food source of sporadic L. monocytogenes illness in people cannot be determined. In the United States, L. monocytogenes isolates from patients, foods, and environments are routinely sequenced and analyzed by whole genome multilocus sequence typing (wgMLST) for outbreak detection by PulseNet, the national molecular surveillance system for foodborne illnesses. We investigated whether machine learning approaches applied to wgMLST allele call data could assist in attribution analysis of food source of L. monocytogenes isolates. We compiled isolates with a known source from five food categories (dairy, fruit, meat, seafood, and vegetable) using the metadata of L. monocytogenes isolates in PulseNet, deduplicated closely genetically related isolates, and developed random forest models to predict the food sources of isolates. Prediction accuracy of the final model varied across the food categories; it was highest for meat (65%), followed by fruit (45%), vegetable (45%), dairy (44%), and seafood (37%); overall accuracy was 49%, compared with the naive prediction accuracy of 28%. Our results show that random forest can be used to capture genetically complex features of high-resolution wgMLST for attribution of isolates to their sources.

Putting everything in its place: using the INSDC compliant Pathogen Data Object Model to better structure genomic data submitted for public health applications

Fast, efficient public health actions require well-organized and coordinated systems that can supply timely and accurate knowledge. Public databases of pathogen genomic data, such as the International Nucleotide Sequence Database Collaboration (INSDC), have become essential tools for efficient public health decisions. However, these international resources began primarily for academic purposes, rather than for surveillance or interventions. Now, queries need to access not only the whole genomes of multiple pathogens but also make connections using robust contextual metadata to identify issues of public health relevance. Databases that over time developed a patchwork of submission formats and requirements need to be consistently organized and coordinated internationally to allow effective searches.To help resolve these issues, we propose a common pathogen data structure called the Pathogen Data Object Model (DOM) that will formalize the minimum pieces of sequence data and contextual data necessary for general public health uses, while recognizing that submitters will likely withhold a wide range of non-public contextual data. Further, we propose contributors use the Pathogen DOM for all pathogen submissions (bacterial, viral, fungal, and parasites), which will simplify data submissions and provide a consistent and transparent data structure for downstream data analyses. We also highlight how improved submission tools can support the Pathogen DOM, offering users additional easy-to-use methods to ensure this structure is followed.

Evaluation of whole and core genome multilocus sequence typing allele schemes for Salmonella enterica outbreak detection in a national surveillance network, PulseNet USA

Salmonella enterica is a leading cause of bacterial foodborne and zoonotic illnesses in the United States. For this study, we applied four different whole genome sequencing (WGS)-based subtyping methods: high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multilocus sequence typing using either all loci [wgMLST (all loci)] and only chromosome-associated loci [wgMLST (chrom)], and core genome multilocus sequence typing (cgMLST) to a dataset of isolate sequences from 9 well-characterized Salmonella outbreaks. For each outbreak, we evaluated the genomic and epidemiologic concordance between hqSNP and allele-based methods. We first compared pairwise genomic differences using all four methods. We observed discrepancies in allele difference ranges when using wgMLST (all loci), likely caused by inflated genetic variation due to loci found on plasmids and/or other mobile genetic elements in the accessory genome. Therefore, we excluded wgMLST (all loci) results from any further comparisons in the study. Then, we created linear regression models and phylogenetic tanglegrams using the remaining three methods. K-means analysis using the silhouette method was applied to compare the ability of the three methods to partition outbreak and sporadic isolate sequences. Our results showed that pairwise hqSNP differences had high concordance with cgMLST and wgMLST (chrom) allele differences. The slopes of the regressions for hqSNP vs. allele pairwise differences were 0.58 (cgMLST) and 0.74 [wgMLST (chrom)], and the slope of the regression was 0.77 for cgMLST vs. wgMLST (chrom) pairwise differences. Tanglegrams showed high clustering concordance between methods using two statistical measures, the Baker's gamma index (BGI) and cophenetic correlation coefficient (CCC), where 9/9 (100%) of outbreaks yielded BGI values ≥ 0.60 and CCCs were ≥ 0.97 across all nine outbreaks and all three methods. K-means analysis showed separation of outbreak and sporadic isolate groups with average silhouette widths ≥ 0.87 for outbreak groups and ≥ 0.16 for sporadic groups. This study demonstrates that Salmonella isolates clustered in concordance with epidemiologic data using three WGS-based subtyping methods and supports using cgMLST as the primary method for national surveillance of Salmonella outbreak clusters.

Investigation of a Multistate Outbreak of Listeria monocytogenes Infections Linked to Frozen Vegetables Produced at Individually Quick-Frozen Vegetable Manufacturing Facilities

In 2016, the U.S. Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), and state partners investigated nine Listeria monocytogenes infections linked to frozen vegetables. The investigation began with two environmental L. monocytogenes isolates recovered from Manufacturer A, primarily a processor of frozen onions, that were a match by whole genome sequencing (WGS) to eight clinical isolates and historical onion isolates with limited collection details. Epidemiologic information, product distribution, and laboratory evidence linked suspect food items, including products sourced from Manufacturer B, also a manufacturer of frozen vegetable/fruit products, with an additional illness. The environmental isolates were obtained during investigations at Manufacturers A and B. State and federal partners interviewed ill people, analyzed shopper card data, and collected household and retail samples. Nine ill persons between 2013 and 2016 were reported in four states. Of four ill people with information available, frozen vegetable consumption was reported by three, with shopper cards confirming purchases of Manufacturer B brands. Two identified outbreak strains of L. monocytogenes (Outbreak Strain 1 and Outbreak Strain 2) were a match to environmental isolates from Manufacturer A and/or isolates from frozen vegetables recovered from open and unopened product samples sourced from Manufacturer B; the investigation resulted in extensive voluntary recalls. The close genetic relationship between isolates helped investigators determine the source of the outbreak and take steps to protect public health. This is the first known multistate outbreak of listeriosis in the United States linked to frozen vegetables and highlights the significance of sampling and WGS analyses when there is limited epidemiologic information. Additionally, this investigation emphasizes the need for further research regarding food safety risks associated with frozen foods.

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.

Enteric fever cluster identification in South Africa using genomic surveillance of Salmonella enterica serovar Typhi

The National Institute for Communicable Diseases in South Africa participates in national laboratory-based surveillance for human isolates of Salmonella species. Laboratory analysis includes whole-genome sequencing (WGS) of isolates. We report on WGS-based surveillance of Salmonella enterica serovar Typhi (Salmonella Typhi) in South Africa from 2020 through 2021. We describe how WGS analysis identified clusters of enteric fever in the Western Cape Province of South Africa and describe the epidemiological investigations associated with these clusters. A total of 206 Salmonella Typhi isolates were received for analysis. Genomic DNA was isolated from bacteria and WGS was performed using Illumina NextSeq technology. WGS data were investigated using multiple bioinformatics tools, including those available at the Centre for Genomic Epidemiology, EnteroBase and Pathogenwatch. Core-genome multilocus sequence typing was used to investigate the phylogeny of isolates and identify clusters. Three major clusters of enteric fever were identified in the Western Cape Province; cluster one (n=11 isolates), cluster two (n=13 isolates), and cluster three (n=14 isolates). To date, no likely source has been identified for any of the clusters. All isolates associated with the clusters, showed the same genotype (4.3.1.1.EA1) and resistome (antimicrobial resistance genes: bla _TEM-1B, catA1, sul1, sul2, dfrA7). The implementation of genomic surveillance of Salmonella Typhi in South Africa has enabled rapid detection of clusters indicative of possible outbreaks. Cluster identification allows for targeted epidemiological investigations and a timely, coordinated public health response.

Whole-Genome Sequencing of Shiga Toxin-Producing Escherichia coli for Characterization and Outbreak Investigation

Shiga toxin-producing Escherichia coli (STEC) causes high frequencies of foodborne infections worldwide and has been linked to numerous outbreaks each year. Pulsed-field gel electrophoresis (PFGE) has been the gold standard for surveillance until the recent transition to whole-genome sequencing (WGS). To further understand the genetic diversity and relatedness of outbreak isolates, a retrospective analysis of 510 clinical STEC isolates was conducted. Among the 34 STEC serogroups represented, most (59.6%) belonged to the predominant six non-O157 serogroups. Core genome single nucleotide polymorphism (SNP) analysis differentiated clusters of isolates with similar PFGE patterns and multilocus sequence types (STs). One serogroup O26 outbreak strain and another non-typeable (NT) strain, for instance, were identical by PFGE and clustered together by MLST; however, both were distantly related in the SNP analysis. In contrast, six outbreak-associated serogroup O5 strains clustered with five ST-175 serogroup O5 isolates, which were not part of the same outbreak as determined by PFGE. The use of high-quality SNP analyses enhanced the discrimination of these O5 outbreak strains into a single cluster. In all, this study demonstrates how public health laboratories can more rapidly use WGS and phylogenetics to identify related strains during outbreak investigations while simultaneously uncovering important genetic attributes that can inform treatment practices.

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.

An Outbreak Investigation of Vibrio parahaemolyticus Infections in the United States Linked to Crabmeat Imported from Venezuela: 2018

Vibrio parahaemolyticus is the leading cause of seafood-related foodborne illness globally. In 2018, the U.S. federal, state, and local public health and regulatory partners investigated a multistate outbreak of V. parahaemolyticus infections linked to crabmeat that resulted in 26 ill people and nine hospitalizations. State and U.S. Food and Drug Administration (FDA) laboratories recovered V. parahaemolyticus, Salmonella spp., and Listeria monocytogenes isolates from crabmeat samples collected from various points of distribution and conducted phylogenetic analyses of whole-genome sequencing data. Federal, state, and local partners conducted traceback investigations to determine the source of crabmeat. Multiple Venezuelan processors that supplied various brands of crabmeat were identified, but a sole firm was not confirmed as the source of the outbreak. Travel restrictions between the United States and Venezuela prevented FDA officials from conducting on-site inspections of cooked crabmeat processors. Based on investigation findings, partners developed public communications advising consumers not to eat crabmeat imported from Venezuela and placed potentially implicated firms on import alerts. While some challenges limited the scope of the investigation, epidemiologic, traceback, and laboratory evidence identified the contaminated food and country of origin, and contributed to public health and regulatory actions, preventing additional illnesses. This multistate outbreak illustrates the importance of adhering to appropriate food safety practices and regulations for imported seafood.

Human Listeriosis

Listeria monocytogenes is a Gram-positive facultative intracellular pathogen that can cause severe invasive infections upon ingestion with contaminated food. Clinically, listerial disease, or listeriosis, most often presents as bacteremia, meningitis or meningoencephalitis, and pregnancy-associated infections manifesting as miscarriage or neonatal sepsis. Invasive listeriosis is life-threatening and a main cause of foodborne illness leading to hospital admissions in Western countries. Sources of contamination can be identified through international surveillance systems for foodborne bacteria and strains' genetic data sharing. Large-scale whole genome studies have increased our knowledge on the diversity and evolution of L. monocytogenes, while recent pathophysiological investigations have improved our mechanistic understanding of listeriosis. In this article, we present an overview of human listeriosis with particular focus on relevant features of the causative bacterium, epidemiology, risk groups, pathogenesis, clinical manifestations, and treatment and prevention.

Listeria monocytogenes Illness and Deaths Associated With Ongoing Contamination of a Multiregional Brand of Ice Cream Products, United States, 2010-2015

BACKGROUND

Frozen foods have rarely been linked to Listeria monocytogenes illness. We describe an outbreak investigation prompted by both hospital clustering of illnesses and product testing.

METHODS

We identified outbreak-associated listeriosis cases using whole-genome sequencing (WGS), product testing results, and epidemiologic linkage to cases in the same Kansas hospital. We reviewed hospital medical and dietary records, product invoices, and molecular subtyping results. Federal and state officials tested product and environmental samples for L. monocytogenes.

RESULTS

Kansas officials were investigating 5 cases of listeriosis at a single hospital when, simultaneously, unrelated sampling for a study in South Carolina identified L. monocytogenes in Company A ice cream products made in Texas. Isolates from 4 patients and Company A products were closely related by WGS, and the 4 patients with known exposures had consumed milkshakes made with Company A ice cream while hospitalized. Further testing identified L. monocytogenes in ice cream produced in a second Company A production facility in Oklahoma; these isolates were closely related by WGS to those from 5 patients in 3 other states. These 10 illnesses, involving 3 deaths, occurred from 2010 through 2015. Company A ultimately recalled all products.

CONCLUSIONS

In this US outbreak of listeriosis linked to a widely distributed brand of ice cream, WGS and product sampling helped link cases spanning 5 years to 2 production facilities, indicating longstanding contamination. Comprehensive sanitation controls and environmental and product testing for L. monocytogenes with regulatory oversight should be implemented for ice cream production.

[Assessment of available and currently applied typing methods of zoonotic pathogens using the example of Shiga toxin-producing and enterohemorrhagic Escherichia coli (STEC/EHEC)]

INTRODUCTION

In order to improve patient care and to increase food safety within the framework of One Health, the project "Integrated Genomic Surveillance of Zoonotic Agents (IGS-Zoo)" aims to develop concepts for a genomic surveillance of Shiga toxin(Stx)-producing and enterohemorrhagic Escherichia coli (STEC/EHEC) in Germany.

METHODS

An online survey was conducted to assess the currently available and applied STEC/EHEC typing methods in the federal laboratories of veterinary regulation, food control, and public health service.

RESULTS

Twenty-six questionnaires from 33 participants were evaluated with regard to STEC/EHEC. The number of STEC/EHEC-suspected samples that the laboratories process per year ranges between 10 and 3500, and out of these they obtain between 3 and 1000 pathogenic isolates. Currently the most frequently used typing method is the determination of Stx- and intimin-coding genes using polymerase chain reaction (PCR). Whole genome sequencing (WGS) is currently used by eight federal state laboratories, and nine are planning to implement it in the future. The most common obstacle for further typing of STEC/EHEC is that isolation from sample material is often unsuccessful despite apparent PCR detection of the stx genes.

DISCUSSION

The results of the survey should facilitate the integration of the analysis methods developed in the project and emphasize the target groups' individual needs for corresponding training concepts.

Computational biology: Role and scope in taming antimicrobial resistance

BACKGROUND

Infectious diseases pose many challenges due to increasing threat of antimicrobial resistance, which necessitates continuous research to develop novel strategies for development of new molecules with antibacterial activity. In the era of computational biology there are tools and techniques available to address and solve the disease management issues in the field of clinical microbiology. The sequencing techniques, structural biology and machine learning can be implemented collectively to tackle infectious diseases e.g. for the diagnosis, epidemiological typing, pathotyping, antimicrobial resistance detection as well as the discovery of novel drugs and vaccine biomarkers.

OBJECTIVES

The present review is a narrative review representing a comprehensive literature-based assessment regarding the use of whole genome sequencing, structural biology and machine learning for the diagnosis, molecular typing and antibacterial drug discovery.

CONTENT

Here, we seek to present an overview of molecular and structural basis of resistance to antibiotics, while focusing on the recent bioinformatics approaches in whole genome sequencing and structural biology. The application of next generation sequencing in management of bacterial infections focusing on investigation of microbial population diversity, genotypic resistance testing and scope for the identification of targets for novel drug and vaccine candidates, has been addressed along with the use of structural biophysics and artificial intelligence.

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.

Presentation and outcomes of Listeria-affected pregnancies in Johannesburg tertiary hospitals: A 2-year review

OBJECTIVE

To describe maternal risk factors, presentations, peripartum findings, and pregnancy outcomes in Listeria monocytogenes-infected women.

METHODS

A retrospective descriptive case review. The records of 51 pregnant women infected with listeriosis who delivered infants between February 1, 2016 and February 28, 2018 at three academic hospitals in Johannesburg, South Africa, were included. The diagnosis of listeriosis was made on maternal/neonatal-sampled blood or tissue cultures.

RESULTS

Forty-eight (82.3%) Listeria infections of maternal and neonatal listeriosis were diagnosed on blood culture. The median gestational age at diagnosis was at a preterm gestation of 33 (20-43) weeks. Twenty-eight women (54.9%) had normal vaginal deliveries. Precipitous labor was described in 18 (39%) of these women. Fetal distress was the indication for cesarean section in 22 (41.2%) women. Meconium-stained amniotic fluid was found in 21 (61.7%) women at the time of delivery. The category of very low birth weight had 14 (27.4%) neonates with an Apgar score of less than 7 at 5 min. Maternal morbidities included chorioamnionitis (3 [5.8%]) and puerperal infections (7 [13.7%]). The HIV-positive anemic women had a tendency towards listerial infections.

CONCLUSIONS

Symptoms of listeriosis were non-specific and diagnosis was detected on blood culture sampling. Risk factors included HIV seropositivity and were associated with puerperal infections and anemia.

Recent advances in metagenomic analysis of different ecological niches for enhanced biodegradation of recalcitrant lignocellulosic biomass

Lignocellulose wastes stemming from agricultural residues can offer an excellent opportunity as alternative energy solutions in addition to fossil fuels. Besides, the unrestrained burning of agricultural residues can lead to the destruction of the soil microflora and associated soil sterilization. However, the difficulties associated with the biodegradation of lignocellulose biomasses remain as a formidable challenge for their sustainable management. In this respect, metagenomics can be used as an effective option to resolve such dilemma because of its potential as the next generation sequencing technology and bioinformatics tools to harness novel microbial consortia from diverse environments (e.g., soil, alpine forests, and hypersaline/acidic/hot sulfur springs). In light of the challenges associated with the bulk-scale biodegradation of lignocellulose-rich agricultural residues, this review is organized to help delineate the fundamental aspects of metagenomics towards the assessment of the microbial consortia and novel molecules (such as biocatalysts) which are otherwise unidentifiable by conventional laboratory culturing techniques. The discussion is extended further to highlight the recent advancements (e.g., from 2011 to 2022) in metagenomic approaches for the isolation and purification of lignocellulolytic microbes from different ecosystems along with the technical challenges and prospects associated with their wide implementation and scale-up. This review should thus be one of the first comprehensive reports on the metagenomics-based analysis of different environmental samples for the isolation and purification of lignocellulose degrading enzymes.

Invasive listeriosis outbreaks and salmon products: a genomic, epidemiological study

Invasive listeriosis, caused by Listeria (L.) monocytogenes, is a severe foodborne infection, especially for immunocompromised individuals. The aim of our investigation was the identification and analysis of listeriosis outbreaks in Germany with smoked and graved salmon products as the most likely source of infection using whole-genome sequencing (WGS) and patient interviews. In a national surveillance programme, WGS was used for subtyping and core genome multi locus sequence typing (cgMLST) for cluster detection of L. monocytogenes isolates from listeriosis cases as well as food and environmental samples in Germany. Patient interviews were conducted to complement the molecular typing. We identified 22 independent listeriosis outbreaks occurring between 2010 and 2021 that were most likely associated with the consumption of smoked and graved salmon products. In Germany, 228 cases were identified, of 50 deaths (22%) reported 17 were confirmed to have died from listeriosis. Many of these 22 outbreaks were cross-border outbreaks with further cases in other countries. This report shows that smoked and graved salmon products contaminated with L. monocytogenes pose a serious risk for listeriosis infection in Germany. Interdisciplinary efforts including WGS and epidemiological investigations were essential to identifying the source of infection. Uncooked salmon products are high-risk foods frequently contaminated with L. monocytogenes. In order to minimize the risk of infection for consumers, food producers need to improve hygiene measures and reduce the entry of pathogens into food processing. Furthermore, susceptible individuals should be better informed of the risk of acquiring listeriosis from consuming smoked and graved salmon products.

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.

Listeria monocytogenes in foods-From culture identification to whole-genome characteristics

Listeria monocytogenes is an important foodborne pathogen, which is able to persist in the food production environments. The presence of these bacteria in different niches makes them a potential threat for public health. In the present review, the current information on the classical and alternative methods used for isolation and identification of L. monocytogenes in food have been described. Although these techniques are usually simple, standardized, inexpensive, and are routinely used in many food testing laboratories, several alternative molecular-based approaches for the bacteria detection in food and food production environments have been developed. They are characterized by the high sample throughput, a short time of analysis, and cost-effectiveness. However, these methods are important for the routine testing toward the presence and number of L. monocytogenes, but are not suitable for characteristics and typing of the bacterial isolates, which are crucial in the study of listeriosis infections. For these purposes, novel approaches, with a high discriminatory power to genetically distinguish the strains during epidemiological studies, have been developed, e.g., whole-genome sequence-based techniques such as NGS which provide an opportunity to perform comparison between strains of the same species. In the present review, we have shown a short description of the principles of microbiological, alternative, and modern methods of detection of L. monocytogenes in foods and characterization of the isolates for epidemiological purposes. According to our knowledge, similar comprehensive papers on such subject have not been recently published, and we hope that the current review may be interesting for research communities.

First Description of a Yersinia pseudotuberculosis Clonal Outbreak in France, Confirmed Using a New Core Genome Multilocus Sequence Typing Method

Yersinia pseudotuberculosis is an enteric pathogen causing mild enteritis that can lead to mesenteric adenitis in children and septicemia in elderly patients. Most cases are sporadic, but outbreaks have already been described in different countries. We report for the first time a Y. pseudotuberculosis clonal outbreak in France, that occurred in 2020. An epidemiological investigation based on food queries pointed toward the consumption of tomatoes as the suspected source of infection. The Yersinia National Reference Laboratory (YNRL) developed a new cgMLST scheme with 1,921 genes specific to Y. pseudotuberculosis that identified the clustering of isolates associated with the outbreak and allowed to perform molecular typing in real time. In addition, this method allowed to retrospectively identify isolates belonging to this cluster from earlier in 2020. This method, which does not require specific bioinformatic skills, is now used systematically at the YNRL and proves to display an excellent discriminatory power and is available to the scientific community. IMPORTANCE We describe in here a novel core-genome MLST method that allowed to identify in real time, and for the first time in France, a Y. pseudotuberculosis clonal outbreak that took place during the summer 2020 in Corsica. Our method allows to support epidemiological and microbiological investigations to establish a link between patients infected with closely associated Y. pseudotuberculosis isolates, and to identify the potential source of infection. In addition, we made this method available for the scientific community.

The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems

The development and application of modern sequencing technologies have led to many new improvements in food safety and public health. With unprecedented resolution and big data, high-throughput sequencing (HTS) has enabled food safety specialists to sequence marker genes, whole genomes, and transcriptomes of microorganisms almost in real-time. These data reveal not only the identity of a pathogen or an organism of interest in the food supply but its virulence potential and functional characteristics. HTS of amplicons, allow better characterization of the microbial communities associated with food and the environment. New and powerful bioinformatics tools, algorithms, and machine learning allow for development of new models to predict and tackle important events such as foodborne disease outbreaks. Despite its potential, the integration of HTS into current food safety systems is far from complete. Government agencies have embraced this new technology, and use it for disease diagnostics, food safety inspections, and outbreak investigations. However, adoption and application of HTS by the food industry have been comparatively slow, sporadic, and fragmented. Incorporation of HTS by food manufacturers in their food safety programs could reinforce the design and verification of effectiveness of control measures by providing greater insight into the characteristics, origin, relatedness, and evolution of microorganisms in our foods and environment. Here, we discuss this new technology, its power, and potential. A brief history of implementation by public health agencies is presented, as are the benefits and challenges for the food industry, and its future in the context of food safety.

Outbreak dynamics of foodborne pathogen Vibrio parahaemolyticus over a seventeen year period implies hidden reservoirs

Controlling foodborne diseases requires robust outbreak detection and a comprehensive understanding of outbreak dynamics. Here, by integrating large-scale phylogenomic analysis of 3,642 isolates and epidemiological data, we performed 'data-driven' outbreak detection and described the long-term outbreak dynamics of the leading seafood-associated pathogen, Vibrio parahaemolyticus, in Shenzhen, China, over a 17-year period. Contradictory to the widely accepted notion that sporadic patients and independent point-source outbreaks dominated foodborne infections, we found that 71% of isolates from patients grouped into within-1-month clusters that differed by ≤6 single nucleotide polymorphisms, indicating putative outbreaks. Furthermore, we showed that despite the long time spans between clusters, 70% of them were genomically closely related and were inferred to arise from a small number of common sources, which provides evidence that hidden persistent reservoirs generated most of the outbreaks rather than independent point-sources. Phylogeographical analysis further revealed the geographical heterogeneity of outbreaks and identified a coastal district as the potential hotspot of outbreaks and as the hub and major source of cross-district spread events. Our findings provide a comprehensive picture of the long-term spatiotemporal dynamics of foodborne outbreaks and present a different perspective on the major source of foodborne infections, which will inform the design of future disease control strategies.

Sequencing of Enteric Bacteria: Library Preparation Procedure Matters for Accurate Identification and Characterization

Enzymatic library preparation kits are increasingly used for bacterial whole genome sequencing. While they offer a rapid workflow, the transposases used in the kits are recognized to be somewhat biased. The aim of this study was to optimize and validate a protocol for the Illumina DNA Prep kit (formerly Nextera DNA Flex) for sequencing enteric pathogens and compare its performance against the Nextera XT kit. One hundred forty-three strains of Campylobacter, Escherichia, Listeria, Salmonella, Shigella, and Vibrio were prepared with both methods and sequenced on the Illumina MiSeq using 300 and/or 500 cycle chemistries. Sequences were compared using core genome multilocus sequence typing (cgMLST), 7-gene multilocus sequence typing (MLST), and detection of markers encoding serotype, virulence, and antimicrobial resistance. Sequences for one Escherichia strain were downsampled to determine the minimum coverage required for the analyses. While organism-specific differences were observed, the Prep libraries generated longer average read lengths and less fragmented assemblies compared to the XT libraries. In downstream analysis, the most notable difference between the kits was observed for Escherichia, particularly for the 300 cycle sequences. The O group was not predicted in 32% and 4% of XT sequences when using blast and kmer algorithms, respectively, while the O group was predicted from all Prep sequences regardless of the algorithm. In addition, the ehxA gene was not detected in 6% of XT sequences and 34% were missing one or more of the type III secretion systems and/or plasmid-associated genes, which were detected in the Prep sequences. The coverage downsampling revealed that acceptable assembly quality and allele detection was achieved at 30 × coverage with the Prep libraries, whereas 40-50 × coverage was required for the XT libraries. The better performance of the Prep libraries was attributed to more even coverage, particularly in genome regions low in GC content.

Epidemiology and Clinical Features of Listeriosis in Gipuzkoa, Spain, 2010-2020

Background

Listeriosis continues to be one of the most important notifiable foodborne diseases. Nonetheless, in Spain, there are few data on the molecular epidemiology of Listeria monocytogenes infections in recent years.

Aim

To describe clinical features and the molecular epidemiology of human listeriosis over an 11-year period (2010–2020) in Gipuzkoa, Northern Spain.

Methods

A total of 111 isolates, all but one from invasive disease, were studied. Serotyping (agglutination and multiplex polymerase chain reaction [PCR]) and multilocus sequence typing were performed for all isolates. Antibiotic susceptibility was assessed by the broth microdilution method.

Results

The average annual incidence of listeriosis in non-pregnancy-associated cases was 1.55 per 100,000 population, with a 1-month mortality rate of 22.2%. In pregnant women, the average incidence was 0.45 cases per 1,000 pregnancies. Twenty-four sequence types were identified, serotype 4b ST1 (24.3%) being the most frequent followed by 1/2b ST87 (18.9%), which caused two long outbreaks in 2013–2014. A significant association was observed between ST219 and meningitis (p < 0.001). All isolates were susceptible to ampicillin as well as other antibiotics used in listeriosis treatment.

Conclusion

Despite current control measures, listeriosis continues to be an important cause of mortality in the elderly, preterm birth, and miscarriages in pregnant women. Improvements in the control and diagnosis of listeriosis are needed to reduce the impact of this infection on vulnerable populations.

Performance Characteristics of Next-Generation Sequencing for the Detection of Antimicrobial Resistance Determinants in Escherichia coli Genomes and Metagenomes

Short-read sequencing can provide detection of multiple genomic determinants of antimicrobial resistance from single bacterial genomes and metagenomic samples. Despite its increasing application in human, animal, and environmental microbiology, including human clinical trials, the performance of short-read Illumina sequencing for antimicrobial resistance gene (ARG) detection, including resistance-conferring single nucleotide polymorphisms (SNPs), has not been systematically characterized. Using paired-end 2 × 150 bp (base pair) Illumina sequencing and an assembly-based method for ARG prediction, we determined sensitivity, positive predictive value (PPV), and sequencing depths required for ARG detection in an Escherichia coli isolate of sequence type (ST) 38 spiked into a synthetic microbial community at varying abundances. Approximately 300,000 reads or 15× genome coverage was sufficient to detect ARGs in E. coli ST38, with comparable sensitivity and PPV to ~100× genome coverage. Using metagenome assembly of mixed microbial communities, ARG detection at E. coli relative abundances of 1% would require assembly of approximately 30 million reads to achieve 15× target coverage. The minimum sequencing depths were validated using public data sets of 948 E. coli genomes and 10 metagenomic rectal swab samples. A read-based approach using k-mer alignment (KMA) for ARG prediction did not substantially improve minimum sequencing depths for ARG detection compared to assembly of the E. coli ST38 genome or the combined metagenomic samples. Analysis of sequencing depths from recent studies assessing ARG content in metagenomic samples demonstrated that sequencing depths had a median estimated detection frequency of 84% (interquartile range: 30%-92%) for a relative abundance of 1%. IMPORTANCE Systematically determining Illumina sequencing performance characteristics for detection of ARGs in metagenomic samples is essential to inform study design and appraisal of human, animal, and environmental metagenomic antimicrobial resistance studies. In this study, we quantified the performance characteristics of ARG detection in E. coli genomes and metagenomes and established a benchmark of ~15× coverage for ARG detection for E. coli in metagenomes. We demonstrate that for low relative abundances, sequencing depths of ~30 million reads or more may be required for adequate sensitivity for many applications.

Rapid Multilateral and Integrated Public Health Response to a Cross-City Outbreak of Salmonella Enteritidis Infections Combining Analytical, Molecular, and Genomic Epidemiological Analysis

On September 21, 2019, the Shenzhen and Dongguan Centers for Disease Control and Prevention received notification of a large cluster of suspected gastroenteritis involving primarily children who sought medical care at hospitals throughout two adjacent cities in China, Shenzhen, and Dongguan. A joint outbreak response was promptly initiated across jurisdictions in a concerted effort between clinical microbiologists, epidemiologists, and public health scientists. Concurrently, multiplex PCRs were used for rapid laboratory diagnosis of suspected cases; epidemiological investigations were conducted to identify the outbreak source, complemented by near real-time multicenter whole-genome analyses completed within 34 h. Epidemiological evidence indicated that all patients had consumed egg sandwiches served on September 20 as snacks to children and staff at a nursery in Dongguan, located near Shenzhen. Salmonella Enteritidis was isolated from case-patients, food handlers, kitchenware, and sandwiches with kitchen-made mayonnaise. Whole-genome single-nucleotide polymorphism (SNP)-based phylogenetic analysis demonstrated a well-supported cluster with pairwise distances of ≤1 SNP between genomes for outbreak-associated isolates, providing the definitive link between all samples. In comparison with historical isolates from the same geographical region, the minimum pairwise distance was >14 SNPs, suggesting a non-local outbreak source. Genomic source tracing revealed the possible transmission dynamics of a S. Enteritidis clone throughout a multi-provincial egg distribution network. The efficiency and scale with which multidisciplinary and integrated approaches were coordinated in this foodborne disease outbreak response was unprecedented in China, leading to the timely intervention of a large cross-jurisdiction Salmonella outbreak.

Use of Whole Genome Sequencing by the Federal Interagency Collaboration for Genomics for Food and Feed Safety in the United States

ABSTRACT

This multiagency report developed by the Interagency Collaboration for Genomics for Food and Feed Safety provides an overview of the use of and transition to whole genome sequencing (WGS) technology for detection and characterization of pathogens transmitted commonly by food and for identification of their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among the following federal agencies: National Institutes of Health; Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and U.S. Food and Drug Administration (FDA); and the U.S. Department of Agriculture, Food Safety and Inspection Service, Agricultural Research Service, and Animal and Plant Health Inspection Service. We describe single nucleotide polymorphism, core-genome, and whole genome multilocus sequence typing data analysis methods as used in the PulseNet (CDC) and GenomeTrakr (FDA) networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Interagency Collaboration partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles) and source attribution efforts and increase transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information. We also highlight the impact of current trends in the use of culture-independent diagnostic tests for human diagnostic testing on analytical approaches related to food safety and what is next for the use of WGS in the area of food safety.

HIGHLIGHTS

PulseNet International Survey on the Implementation of Whole Genome Sequencing in Low and Middle-Income Countries for Foodborne Disease Surveillance

PulseNet International (PNI) is a global network of 88 countries who work together through their regional and national public health laboratories to track foodborne disease around the world. The vision of PNI is to implement globally standardized surveillance using whole genome sequencing (WGS) for real-time identification and subtyping of foodborne pathogens to strengthen preparedness and response and lower the burden of disease. Several countries in North America and Europe have experienced significant benefits in disease mitigation after implementing WGS. To broaden the routine use of WGS around the world, challenges and barriers must be overcome. We conducted this study to determine the challenges and barriers countries are encountering in their attempts to implement WGS and to identify how PNI can provide support to improve and become a better integrated system overall. A survey was designed with a set of qualitative questions to capture the status, challenges, barriers, and successes of countries in the implementation of WGS and was administered to laboratories in Africa, Asia-Pacific, Latin America and the Caribbean, and Middle East. One-third of respondents do not use WGS, and only 8% reported using WGS for routine, real-time surveillance. The main barriers for implementation of WGS were lack of funding, gaps in expertise, and training, especially for data analysis and interpretation. Features of an ideal system to facilitate implementation and global surveillance were identified as an all-in-one software that is free, accessible, standardized and validated. This survey highlights the minimal use of WGS for foodborne disease surveillance outside the United States, Canada, and Europe to date. Although funding remains a major barrier to WGS-based surveillance, critical gaps in expertise and availability of tools must be overcome. Opportunities to seek sustainable funding, provide training, and identify solutions for a globally standardized surveillance platform will accelerate implementation of WGS worldwide.

Phylogenetic and Evolutionary Genomic Analysis of Listeria monocytogenes Clinical Strains in the Framework of Foodborne Listeriosis Risk Assessment

Listeria monocytogenes is one of the most important foodborne pathogens responsible for listeriosis, a severe disease with symptoms ranging from septicemia, meningoencephalitis, and abortion. Given the strong impact of listeriosis on human health and the difficulty of controlling L. monocytogenes along the food production chain, listeriosis has become a priority subjected to molecular surveillance in European Union/European Economic Area since 2007. From 2018, surveillance is based on whole-genome sequence using the core genome multilocus sequence type. The complete sequences of 132 clinical strains were used to define the evolutionary relatedness among subtypes of L. monocytogenes isolated in Italy from 2010 to 2016, allowing the identification of clades and/or clusters associated with outbreaks or sporadic cases of listeriosis. All the strains analyzed are clustered in lineages I and II, and the majority of the strains were classified as lineage II. A probable epidemic entrance in different years for every clade and cluster from each different region was defined. The persistence of the same specific clonal complexes of L. monocytogenes has been found over long periods; this may be related to the fact that some strains are able to survive better than others in a food production environment. Phylogenic studies, using whole-genome sequence data, are able to identify the emergence of highly persistent pathogenic variants, contributing to improving the hazard characterization of L. monocytogenes.

Exploiting genomics to mitigate the public health impact of antimicrobial resistance

Antimicrobial resistance (AMR) is a major global public health threat, which has been largely driven by the excessive use of antimicrobials. Control measures are urgently needed to slow the trajectory of AMR but are hampered by an incomplete understanding of the interplay between pathogens, AMR encoding genes, and mobile genetic elements at a microbial level. These factors, combined with the human, animal, and environmental interactions that underlie AMR dissemination at a population level, make for a highly complex landscape. Whole-genome sequencing (WGS) and, more recently, metagenomic analyses have greatly enhanced our understanding of these processes, and these approaches are informing mitigation strategies for how we better understand and control AMR. This review explores how WGS techniques have advanced global, national, and local AMR surveillance, and how this improved understanding is being applied to inform solutions, such as novel diagnostic methods that allow antimicrobial use to be optimised and vaccination strategies for better controlling AMR. We highlight some future opportunities for AMR control informed by genomic sequencing, along with the remaining challenges that must be overcome to fully realise the potential of WGS approaches for international AMR control.