PulseNet and the Changing Paradigm of Laboratory-Based Surveillance for Foodborne Diseases

Outbreak of multidrug-resistant Salmonella infections in people linked to pig ear pet treats, United States, 2015-2019: results of a multistate investigation

Background

International distribution of contaminated foods can be a source of Salmonella infections in people and can contribute to the spread of antimicrobial-resistant bacteria across countries. We report an investigation led by the United States Centers for Disease Control and Prevention, the Food and Drug Administration (FDA), and state governmental officials into a multistate outbreak of salmonellosis linked to pig ear pet treats.

Methods

Pig ear treats and companion dogs were tested for Salmonella by state officials and the FDA. Products were traced back to the country of origin when possible. Cases were defined as outbreak illnesses in people associated with one of seven Salmonella serotypes genetically related to samples from pig ear pet treats, with isolation dates from June 2015 to September 2019. Whole genome sequencing (WGS) of isolates was used to predict antimicrobial resistance.

Findings

The outbreak included 154 human cases in 34 states. Of these, 107 of 122 (88%) patients reported dog contact, and 65 of 97 (67%) reported contact with pig ear pet treats. Salmonella was isolated from 137 pig ear treats, including some imported from Argentina, Brazil, and Colombia, and from four dogs. WGS predicted 77% (105/137) of human and 43% (58/135) of pig ear treat isolates were resistant to ≥3 antimicrobial classes.

Interpretation

This was the first documented United States multistate outbreak of Salmonella infections linked to pig ear pet treats. This multidrug-resistant outbreak highlights the interconnectedness of human health and companion animal ownership and the need for zoonotic pathogen surveillance to prevent human illness resulting from internationally transported pet food products.

Funding

Animal Feed Regulatory Program Standards award. Animal and product testing conducted by FDA Vet-LIRN was funded by Vet-LIRN infrastructure grants (PAR-22-063).

Multistate outbreaks of salmonellosis linked to contact with backyard poultry-United States, 2015-2022

AIMS

Contact with backyard poultry (i.e., privately-owned, non-commercial poultry) was first associated with a multistate outbreak of salmonellosis in 1955. In recent years, backyard poultry-associated salmonellosis outbreaks have caused more illnesses in the United States than salmonellosis outbreaks linked to any other type of animal. Here, we describe the epidemiology of outbreaks from 2015-2022 to inform prevention efforts.

METHODS AND RESULTS

During 2015-2022, there were 88 multistate backyard poultry-associated salmonellosis outbreaks and 7866 outbreak-associated illnesses caused by 21 different Salmonella serotypes. Salmonella Enteritidis accounted for the most outbreaks (n = 21) and illnesses (n = 2400) of any serotype. Twenty-four percent (1840/7727) of patients with available information were <5 years of age. In total, 30% (1710/5644) of patients were hospitalized, and nine deaths were attributed to Salmonella infection. Throughout this period, patients reported behaviours that have a higher risk of Salmonella transmission, including kissing or snuggling poultry or allowing poultry inside their home.

CONCLUSIONS

Despite ongoing efforts to reduce the burden of salmonellosis associated with backyard poultry, outbreak-associated illnesses have nearly tripled and hospitalizations more than quadrupled compared with those in 1990-2014. Because this public health problem is largely preventable, government officials, human and veterinary healthcare providers, hatcheries, and retailers might improve the prevention of illnesses by widely disseminating health and safety recommendations to the public and by continuing to develop and implement prevention measures to reduce zoonotic transmission of Salmonella by backyard poultry.

Trends in Salmonella Infantis human illness incidence and chicken carcass prevalence in the United States; 1996-2019

The incidence of human illness due to Salmonella Infantis reported to Foodborne Diseases Active Surveillance Network and the prevalence of Infantis on chicken carcasses reported by the United States Department of Agriculture Food Safety and Inspection Service have increased significantly in the past decade. However, the trends do not appear coincident, as would be expected if the increased prevalence in chicken led to the increase in the incidence of human illness. Salmonella Infantis incidence and prevalence trends are analyzed using penalized B-spline methods for generalized additive regression models. The association between the two time series is analyzed using time-lagged rank-order cross-correlation. Geographic variations in reported incidence and trends are also explored. The increase in human incidence of Salmonella Infantis began circa 2011. The increase in chicken carcass prevalence began circa 2015. A 4-year lag on chicken carcass prevalence maximizes the rank-order cross-correlation with the incidence of illness. While chicken consumption undoubtedly contributes to the incidence of human illness due to Salmonella Infantis, the initial increase in reported illness was likely due to one or more other transmission pathways. Other potential transmission pathways include non-chicken foodborne, waterborne, person-to-person, animal contact, and environmental.

Implementation of a high-throughput whole genome sequencing approach with the goal of maximizing efficiency and cost effectiveness to improve public health

This manuscript describes the development of a streamlined, cost-effective laboratory workflow to meet the demands of increased whole genome sequence (WGS) capacity while achieving mandated quality metrics. From 2020 to 2021, the Wadsworth Center Bacteriology Laboratory (WCBL) used a streamlined workflow to sequence 5,743 genomes that contributed sequence data to nine different projects. The combined use of the QIAcube HT, Illumina DNA Prep using quarter volume reactions, and the NextSeq allowed the WCBL to process all samples that required WGS while also achieving a median turn-around time of 7 days (range 4 to 10 days) and meeting minimum sequence quality requirements. Public Health Laboratories should consider implementing these methods to aid in meeting testing requirements within budgetary restrictions.

IMPORTANCE

Public Health Laboratories that implement whole genome sequencing (WGS) technologies may struggle to find the balance between sample volume and cost effectiveness. We present a method that allows for sequencing of a variety of bacterial isolates in a cost-effective manner. This report provides specific strategies to implement high-volume WGS, including an innovative, low-cost solution utilizing a novel quarter volume sequencing library preparation. The methods described support the use of high-throughput DNA extraction and WGS within budgetary constraints, strengthening public health responses to outbreaks and disease surveillance.

Clinical Outcomes of Patients With Nontyphoidal Salmonella Infections by Isolate Resistance-Foodborne Diseases Active Surveillance Network, 10 US Sites, 2004-2018

BACKGROUND

Nontyphoidal Salmonella causes an estimated 1.35 million US infections annually. Antimicrobial-resistant strains are a serious public health threat. We examined the association between resistance and the clinical outcomes of hospitalization, length-of-stay ≥3 days, and death.

METHODS

We linked epidemiologic data from the Foodborne Diseases Active Surveillance Network with antimicrobial resistance data from the National Antimicrobial Resistance Monitoring System (NARMS) for nontyphoidal Salmonella infections from 2004 to 2018. We defined any resistance as resistance to ≥1 antimicrobial and clinical resistance as resistance to ampicillin, azithromycin, ceftriaxone, ciprofloxacin, or trimethoprim-sulfamethoxazole (for the subset of isolates tested for all 5 agents). We compared outcomes before and after adjusting for age, state, race/ethnicity, international travel, outbreak association, and isolate serotype and source.

RESULTS

Twenty percent of isolates (1105/5549) had any resistance, and 16% (469/2969) had clinical resistance. Persons whose isolates had any resistance were more likely to be hospitalized (31% vs 28%, P = .01) or have length-of-stay ≥3 days (20% vs 16%, P = .01). Deaths were rare but more common among those with any than no resistance (1.0% vs 0.4%, P = .01). Outcomes for patients whose isolates had clinical resistance did not differ significantly from those with no resistance. After adjustment, any resistance (adjusted odds ratio 1.23, 95% confidence interval 1.04-1.46) remained significantly associated with hospitalization.

CONCLUSIONS

We observed a significant association between nontyphoidal Salmonella infections caused by resistant pathogens and likelihood of hospitalization. Clinical resistance was not associated with poorer outcomes, suggesting that factors other than treatment failure (eg, strain virulence, strain source, host factors) may be important.

Foodborne Illness Complaint Systems Detect, and Restaurant Inspection Programs Prevent Restaurant-Associated Foodborne Illness Outbreaks

Restaurants are important settings for foodborne illness transmission. Environmental health agencies routinely inspect restaurants to assess compliance with food safety regulations. They also evaluate foodborne illness complaints from consumers to detect potential outbreaks of foodborne illness. Local environmental health agencies were surveyed to identify methods used to conduct surveillance for consumer complaints of foodborne illness, link them to inspection grading and disclosure practices, and evaluate the association between these practices and the number of foodborne illness outbreaks in restaurant settings reported to the Centers for Disease Control and Prevention. We developed a novel framework for assessing the effectiveness of restaurant inspection grading and disclosure of inspection results while accounting for any biases introduced by surveillance factors that affect outbreak detection. Our findings showed the importance of routine restaurant inspection grading and disclosure practices as prevention measures and having a centralized database to manage consumer complaints as a useful surveillance tool for detecting outbreaks. Improving consumer complaint system structure and management can bolster outbreak detection and maximize limited public health resources while increasing the efficiency of complaint-based surveillance.

Towards a post-pandemic future for global pathogen genome sequencing

Pathogen genome sequencing has become a routine part of our response to active outbreaks of infectious disease and should be an important part of our preparations for future epidemics. In this Essay, we discuss the innovations that have enabled routine pathogen genome sequencing, as well as how genome sequences can be used to understand and control the spread of infectious disease. We also explore the impact of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic on the field of pathogen genomics and outline the challenges we must address to further improve the utility of pathogen genome sequencing in the future.

Retrospective evaluation of an integrated molecular-epidemiological approach to cyclosporiasis outbreak investigations - United States, 2021

Cyclosporiasis results from an infection of the small intestine by Cyclospora parasites after ingestion of contaminated food or water, often leading to gastrointestinal distress. Recent developments in temporally linking genetically related Cyclospora isolates demonstrated effectiveness in supporting epidemiological investigations. We used 'temporal-genetic clusters' (TGCs) to investigate reported cyclosporiasis cases in the United States during the 2021 peak-period (1 May - 31 August 2021). Our approach split 655 genotyped isolates into 55 genetic clusters and 31 TGCs. We linked two large multi-state epidemiological clusters (Epidemiologic Cluster 1 [n = 136 cases, 54 genotyped] and Epidemiologic Cluster 2 [n = 42 cases, 15 genotyped]) to consumption of lettuce varieties; however, product traceback did not identify a specific product for either cluster due to the lack of detailed product information. To evaluate the utility of TGCs, we performed a retrospective case study comparing investigation outcomes of outbreaks first detected using epidemiological methods with those of the same outbreaks had TGCs been used to first detect them. Our study results indicate that adjustments to routine epidemiological approaches could link additional cases to epidemiological clusters of cyclosporiasis. Overall, we show that CDC's integrated genotyping and epidemiological investigations provide valuable insights into cyclosporiasis outbreaks in the United States.

Evaluation of the Illumina iSeq whole genome sequencing system for enteric disease surveillance and outbreak detection

The Illumina iSeq low-capacity sequencing platform was evaluated for use in foodborne disease surveillance and outbreak detection. The platform produced high quality sequence data comparable to that of the Illumina MiSeq and was cost-effective with fast turn-around time in low sample volume environments.

Epidemiological Features of Foodborne Disease Outbreaks in Catering Service Facilities - China, 2010-2020

Introduction

In terms of food preparation settings, catering service facilities have been identified as locations with the highest incidence of foodborne disease outbreaks in China. Since 2010, the China National Center for Food Safety Risk Assessment has established the Foodborne Disease Outbreak Surveillance System (FDOSS) to monitor foodborne disease outbreaks. Consequently, data from the FDOSS has provided a more accurate depiction of the epidemic characteristics of outbreaks within these facilities.

Methods

From 2010 to 2020, the FDOSS gathered data related to the prevalence of outbreaks, cases, hospitalizations, and deaths linked to foodborne disease outbreaks in catering service facilities. This study examined the temporal and geographical distribution, pathogenic factors, and contributing variables of these outbreaks over the course of the decade.

Results

From 2010 to 2020, China's catering service facilities reported 18,331 outbreaks, which resulted in 206,718 illnesses, 68,561 hospitalizations, and 201 deaths. The second and third quarters of the year accounted for 76.12% of the outbreaks and 72.93% of the cases. The primary pathogenic factors were pathogenic organisms, which caused 4,883 (26.64%) outbreaks, 94,047 (45.50%) cases, 32,170 (46.92%) hospitalizations, and 21 (10.45%) deaths. There were 5,607 (30.59%) outbreaks in restaurants, 2,876 (15.69%) outbreaks from street vendors, and 2,560 (13.97%) outbreaks in employee canteens in China.

Conclusions

The implementation of relevant control methods, including health education and promotion, is critical for addressing foodborne diseases in catering service facilities. Regular food safety training sessions for restaurant personnel and managers are essential to ensuring the effective management of these health risks.

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.

Challenges Associated with Investigating Salmonella Enteritidis with Low Genomic Diversity in New York State: The Impact of Adjusting Analytical Methods and Correlation with Epidemiological Data

Defining investigation-worthy genomic clusters among strains of Salmonella Enteritidis is challenging because of their highly clonal nature. We investigated a cluster identified by core genome multilocus sequence typing (cgMLST) consisting of 265 isolates with isolation dates spanning two and a half years. This cluster experienced chaining, growing to a range of 14 alleles. The volume of isolates and broad allele range of this cluster made it difficult to ascertain whether it represented a common-source outbreak. We explored laboratory-based methods to subdivide and refine this cluster. These methods included using cgMLST with a narrower allele range, whole genome multilocus sequence typing (wgMLST) and high-quality single-nucleotide polymorphism (hqSNP) analysis. At each analysis level, epidemiologists retroactively reviewed exposures, geography, and temporality for potential commonalities. Lowering the threshold to 0 alleles using cgMLST proved an effective method to refine this analysis, resulting in this large cluster being subdivided into 34 smaller clusters. Additional analysis by wgMLST and hqSNP provided enhanced cluster resolution, with the majority of clusters being further refined. These analysis methods combined with more stringent allele thresholds and layering of epidemiologic data proved useful in helping to subdivide this large cluster into actionable subclusters.

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.

Planning For The Next Pandemic: Lab Systems Need Policy Shift To Speed Emerging Infectious Disease Warning And Tracking

Early detection and ongoing monitoring of infectious diseases depends on diagnostic testing. The US has a large, diverse system of public, academic, and private laboratories that develop new diagnostic tests; perform routine testing; and conduct specialized reference testing, such as genomic sequencing. These laboratories operate under a complex mix of laws and regulations at the federal, state, and local levels. The COVID-19 pandemic exposed major weaknesses in the nation's laboratory system, some of which were seen again during the global mpox outbreak in 2022. In this article we review how the US laboratory system has been designed to detect and monitor emerging infections, describe what gaps were revealed during COVID-19, and propose specific steps that policy makers can take both to strengthen the current system and to prepare the US for the next pandemic.

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.

Public health genomics capacity assessment: readiness for large-scale pathogen genomic surveillance in Canada’s public health laboratories

Background

Along with rapid diagnostic testing, contact tracing, and public health measures, an effective pandemic response incorporates genomics-based surveillance. Large-scale SARS-CoV-2 genome sequencing is a crucial component of the global response to COVID-19. Characterizing the state of genomics readiness among Canada’s public health laboratories was necessary to inform strategic planning and deployment of capacity-building resources in the early stages of the pandemic.

Methods

We used a qualitative study design and focus group discussions, encompassing both technical and leadership perspectives, to perform an in-depth evaluation of the state of pathogen genomics readiness in Canada.

Results

We found substantial diversity in the state of readiness for SARS-CoV-2 genomic surveillance across Canada. Despite this variability, we identified common barriers and needs in the areas of specimen access, data flow and sharing, computing infrastructure, and access to highly qualified bioinformatics personnel.

Conclusions

These findings enable the strategic prioritization and deployment of resources to increase Canada’s ability to perform effective public health genomic surveillance for COVID-19 and prepare for future emerging infectious diseases. They also provide a unique qualitative research model for use in capacity building.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14210-9.

Activity of antibacterial phytochemicals and their potential use as natural food preservatives

The risk to human health from bacterial foodborne infection is presently controlled by the addition of antimicrobial preservatives to food. However, the use of chemical preservatives such as sodium nitrite poses a health risk in themselves with concerns around carcinogenic effects. This makes the development of improved preservatives a priority for the food industry. One promising source of novel antimicrobial compounds can be found in nature; phytochemicals, in particular polyphenols are secondary metabolites produced by plants for numerous purposes including antimicrobial defence. There has been significant study of phytochemicals; including quantifying their antimicrobial activity, potential to synergise with current antibiotics and the feasibility of their application as natural food preservatives. However, there remains significant uncertainty about the relative antimicrobial efficacy of different phytochemicals, their mechanisms of action (MOA) and the potential for emergence of bacterial resistance to their effects. This review summarizes recent work relevant to the potential development of phytochemicals as antimicrobial agents.

Changing Diagnostic Testing Practices for Foodborne Pathogens, Foodborne Diseases Active Surveillance Network, 2012-2019

BACKGROUND

Pathogen detection has changed with increased use of culture-independent diagnostic tests (CIDTs). CIDTs do not yield isolates, which are necessary to detect outbreaks using whole-genome sequencing. The Foodborne Diseases Active Surveillance Network (FoodNet) monitors clinical laboratory testing practices to improve interpretation of surveillance data and assess availability of isolates. We describe changes in practices over 8 years.

METHODS

During 2012-2019, 10 FoodNet sites collected standardized data about practices in clinical laboratories (range, 664-723 laboratories) for select enteric pathogens. We assessed changes in practices.

RESULTS

During 2012-2019, the percentage of laboratories that used only culture methods decreased, with the largest declines for Vibrio (99%-57%) and Yersinia (99%-60%). During 2019, the percentage of laboratories using only CIDTs was highest for Shiga toxin-producing Escherichia coli (43%), Campylobacter (34%), and Vibrio (34%). From 2015 to 2019, the percentage of laboratories that performed reflex culture after a positive CIDT decreased, with the largest declines for Shigella (75%-42%) and Salmonella (70%-38%). The percentage of laboratories that routinely submitted isolates to a public health laboratory decreased for all bacterial pathogens examined from 2015 to 2019.

CONCLUSIONS

By increasing use of CIDTs and decreasing reflex culture, clinical laboratories have transferred the burden of isolate recovery to public health laboratories. Until technologies allow for molecular subtyping directly from a patient specimen, state public health laboratories should consider updating enteric disease reporting requirements to include submission of isolates or specimens. Public health laboratories need resources for isolate recovery.

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.

Public-Public Collaboration for Food Safety Risk Management: Essence, Modes, and Identification of Key Influencing Factors Using DANP

Objective

Food safety risk management is an important cross-boundary issue from both theoretical and practical standpoints. Because food safety has the social attributes of public goods, public-public collaboration can be considered a particularly important mode of cross-boundary governance. The study aims to provide a theoretical basis for the Chinese government to promote public-public collaboration for food safety risk management by identifying key factors.

Methods

Based on a review of literature across diverse fields, such as political science, sociology, and new public governance, this study discusses the essence, modes, and dilemma of public-public collaboration for food safety risk management using practical explorations in various countries as the main thread and taking into account the actual situation in China. Moreover, this study quantitatively analyzes the relationships between the dimensions and factors affecting public-public collaboration and identifies key dimensions and factors using the Decision-making Trial and Evaluation Laboratory-based Analytic Network Process (DANP).

Results

Among the 20 factors in the calculation results of DANP, Lawmaking has the highest value of (fi+ei) (7.022) and ranks sixth in terms of influence weight. The (fi+ei)value of Professionalism (6.993) ranks second and its influence weight ranks fourth. The (fi+ei) value of Administrative enforcement (6.722) ranks fifth, and its influence weight ranks seventh. The (fi+ei) value of Improvement of the social environment (6.699) ranks sixth, and its influence weight ranks fifth. The (fi+ei) value of Legal authorization (6.614) ranks seventh, and its influence weight ranks tenth. Data analysis indicated that these are the five key factors affecting the governance capacity in public-public collaboration for food safety risk management.

Conclusion

The legal basis is the most important dimension affecting public-public collaboration. Legislation-based governance, administrative law enforcement–based governance, and social environment improvement–based governance in the behavior and capabilities dimension, professionalism in the basic characteristics dimension, and laws and regulations in the legal basis dimension are the five key factors.

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.

Outbreak of Multidrug-Resistant Salmonella Heidelberg Infections Linked to Dairy Calf Exposure, United States, 2015-2018

In August 2016, the Wisconsin Department of Health Services notified the U.S. Centers for Disease Control and Prevention of multidrug-resistant (MDR) Salmonella enterica serovar Heidelberg infections in people who reported contact with dairy calves. Federal and state partners investigated this to identify the source and scope of the outbreak and to prevent further illnesses. Cases were defined as human Salmonella Heidelberg infection caused by a strain that had one of seven pulsed-field gel electrophoresis (PFGE) patterns or was related by whole genome sequencing (WGS), with illness onset from January 1, 2015, through July 2, 2018. Patient exposure and calf purchase information was collected and analyzed; calves were traced back from the point of purchase. Isolates obtained from animal and environmental samples collected on-farm were supplied by veterinary diagnostic laboratories and compared with patient isolates using PFGE and WGS. Antimicrobial susceptibility testing by standardized broth microdilution was performed. Sixty-eight patients from 17 states were identified. Forty (63%) of 64 patients noted cattle contact before illness. Thirteen (33%) of 40 patients with exposure to calves reported that calves were sick or had died. Seven individuals purchased calves from a single Wisconsin livestock market. One hundred forty cattle from 14 states were infected with the outbreak strain. WGS indicated that human, cattle, and environmental isolates from the livestock market were genetically closely related. Most isolates (88%) had resistance or reduced susceptibility to antibiotics of ≥5 antibiotic classes. This resistance profile included first-line antibiotic treatments for patients with severe salmonellosis, including ampicillin, ceftriaxone, and ciprofloxacin. In this outbreak, MDR Salmonella Heidelberg likely spread from sick calves to humans, emphasizing the importance of illness surveillance in animal populations to prevent future spillover of this zoonotic disease.

Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package

Background

The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard.

Results

As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories.

Conclusions

Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database.

Multistate outbreak of Salmonella Typhimurium linked to pet hedgehogs, United States, 2018-2019

In December 2018, PulseNet, the national laboratory network for enteric disease surveillance, identified an increase in Salmonella Typhimurium isolates with an uncommon pulsed-field gel electrophoresis pattern which was previously isolated from hedgehogs. CDC, state, and local health partners interviewed patients with a questionnaire that focused on hedgehog exposures, conducted traceback of patients' hedgehog purchases, and collected hedgehog faecal pellets and environmental samples. Isolates in this outbreak were analysed using core-genome multi-locus sequence typing (cgMLST) and compared to sequence data from historic clinical isolates from a 2011-2013 outbreak of Salmonella Typhimurium illnesses linked to pet hedgehogs. Fifty-four illnesses in 23 states were identified between October 2018 and September 2019. Patients ranged from <1 to 95 years, and 65% were female. Eight patients were hospitalized. Eighty-one per cent (29/36) of patients interviewed reported contact with a hedgehog before becoming ill; of these, 21 (72%) reported owning a hedgehog. Analysis of 53 clinical, 11 hedgehog, and two hedgehog bedding isolates from this outbreak, seven hedgehog isolates obtained prior to this outbreak, and two clinical isolates from the 2011-2013 outbreak fell into three distinct groupings (37 isolates in Clade 1 [0-10 alleles], 28 isolates in Clade 2 [0-7 alleles], and eight isolates in Clade 3 [0-12 alleles]) and were collectively related within 0-31 alleles by cgMLST. Purchase information available from 20 patients showed hedgehogs were purchased from multiple breeders across nine states, a pet store, and through an online social media website; a single source of hedgehogs was not identified. This outbreak highlights the ability of genetic sequencing analysis to link historic and ongoing Salmonella illness outbreaks and demonstrates the strain of Salmonella linked to hedgehogs might continue to be a health risk to hedgehog owners unless measures are taken to prevent transmission.

Assessment of Genetic Stability During Serial In Vitro Passage and In Vivo Carriage

In this study, our objective was to evaluate the genetic stability of foodborne bacterial pathogens during serial passage in vitro and persistent in vivo carriage. Six strains of Listeria, Campylobacter, Escherichia, Salmonella, and Vibrio were serially passaged 20 times. Three colonies were picked for whole-genome sequencing (WGS) from passes P0, P5, P10, P15, and P20. In addition, isolates of Salmonella and Escherichia from three patients with persistent infections were sequenced. Genetic stability was evaluated in terms of variations detected in high-quality single-nucleotide polymorphism (hqSNP), core genome multilocus sequence typing (cgMLST), seven-gene MLST, and determinants encoding serotype, antimicrobial resistance (AMR), and virulence. During serial passage, increasing diversity was observed in Listeria, Salmonella, and Vibrio as measured by hqSNPs (from median of 0 SNPs to median of 3-5 SNPs, depending on the organism) and to a lesser extent with cgMLST (from median of 0 alleles to median of 0-5 alleles), while Escherichia and Campylobacter genomes showed minimal variation. The serotype, AMR, and virulence markers remained stable in all organisms. Isolates from persistent infections lasting up to 10 weeks remained genetically stable. However, isolates from a persistent Salmonella enterica ser. Montevideo infection spanning 9 years showed early heterogeneity leading to the emergence of one predominant genotype that continued to evolve over the years, including gains and losses of AMR markers. While the hqSNP and cgMLST variation observed during the serial passage was minimal, culture passages should be limited to as few times as possible before WGS. Our WGS data show that in vivo carriage lasting for a few weeks did not appear to alter the genotype. Longer persistent infections spanning for years, particularly in the presence of selective pressure, may cause changes in the genotype making it challenging to differentiate persistent infections from reinfections.

Multilocus Variable-Number Tandem-Repeat Analysis of Enterohemorrhagic Escherichia coli Serogroups O157, O26, and O111 Based on a De Novo Look-Up Table Constructed by Regression Analysis

Multilocus variable-number tandem-repeat analysis (MLVA) is a widely accepted molecular typing tool for enterohemorrhagic Escherichia coli (EHEC). However, ensuring the accuracy of MLVA data among multiple laboratories remains difficult. We developed a method of constructing adjusted look-up tables, which are necessary for MLVA profiling, at each laboratory using a regression analysis based on electrophoresis data from 24 in-house reference strains. On performing MLVA against 51 EHEC O157 isolates, the repeat numbers of 46 isolates were determined accurately using the look-up table with a 99% prediction interval, an outcome superior to that when using a 95% prediction interval. For the remaining five isolates, although the electrophoresis size fell outside the look-up table, we were able to predict the repeat number accurately by extrapolation or the nearest values of the look-up table. Our approach provides more accurate results than a nonadjusted conventional look-up table for calibrating MLVA profiles.

Development and evaluation of an outbreak surveillance system integrating whole genome sequencing data for non-typhoidal Salmonella in London and South East of England, 2016-17

An outbreak surveillance system for Salmonella integrating whole genome sequencing (WGS) and epidemiological data was developed in South East and London in 2016–17 to assess local WGS clusters for triage and investigation. Cases genetically linked within a 5 single-nucleotide polymorphism (SNP) single linkage cluster were assessed using a set of locally agreed thresholds based on time, person and place, for reporting to local health protection teams (HPTs). Between September 2016 and September 2017, 230 unique 5-SNP clusters (442 weekly reports) of non-typhoidal Salmonella 5-SNP WGS clusters were identified, of which 208 unique 5-SNP clusters (316 weekly reports) were not reported to the HPTs. In the remaining 22 unique clusters (126 weekly clusters) reported to HPTs, nine were known active outbreak investigations, seven were below locally agreed thresholds and six exceeded local thresholds. A common source or vehicle was identified in four of six clusters that exceeded locally agreed thresholds. This work demonstrates that a threshold-based surveillance system, taking into account time, place and genetic relatedness, is feasible and effective in directing the use of local public health resources for risk assessment and investigation of non-typhoidal Salmonella clusters.

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.

WGS-Based Prediction and Analysis of Antimicrobial Resistance in Campylobacter jejuni Isolates From Israel

Rapid developments in the field of whole genome sequencing (WGS) make in silico antimicrobial resistance (AMR) a target within reach. Campylobacter jejuni is a leading cause of foodborne infections in Israel with increasing rates of resistance. We applied WGS analysis to study the prevalence and genetic basis of AMR in 263 C. jejuni human and veterinary representative isolates retrieved from a national collection during 2003–2012. We evaluated the prediction of phenotypic AMR from genomic data. Genomes were screened by the NCBI AMRFinderPlus and the BioNumerics tools for acquired AMR genes and point mutations. The results were compared to phenotypic resistance determined by broth microdilution. The most prevalent resistant determinants were the multi-drug efflux transporter gene cmeABC (100%), the tetracycline resistance tet(O) gene (82.1%), the quinolone resistance gyrA T861 point mutation (75.7%), and the aadE streptomycin resistance gene. A variety of 12 known β lactam resistance genes (bla_OXA variants) were detected in 241 (92%) isolates, the most prevalent being bla_OXA−193, bla_OXA−461, and bla_OXA−580 (56, 16, and 7%, respectively). Other aminoglycoside resistance genes and the macrolide resistance point mutation were rare (<1%). The overall correlation rate between WGS-based genotypic prediction and phenotypic resistance was 98.8%, sensitivity, specificity, positive, and negative predictive values being 98.0, 99.3, 99.1, and 98.5%, respectively. wgMLST-based phylogeny indicated a high level of clonality and clustering among the studied isolates. Closely related isolates that were part of a genetic cluster (single linkage distance ≤ 15 alleles) based on wgMLST phylogeny mostly shared a homogenous AMR determinant profile. This was observed in 18 of 20 (90.0%) clusters within clonal complex-21, suggesting clonal expansion of resistant isolates. Strong association to lineage was noted for the aadE gene and the various bla_OXA genes. High resistance rates to tetracycline and quinolones and a low resistance rate to macrolides were detected among the Israeli C. jejuni isolates. While a high genotypic-phenotypic correlation was found, some resistance phenotypes could not be predicted by the presence of AMR determinants, and particularly not the level of resistance. WGS-based prediction of antimicrobial resistance in C. jejuni requires further optimization in order to integrate this approach in the routine workflow of public health laboratories for foodborne surveillance.

Digital microbiology

BACKGROUND

Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects.

OBJECTIVE

This review article summarizes the most important concepts of digital microbiology. The article gives microbiologists, clinicians and data scientists a viewpoint and practical examples along the diagnostic process.

SOURCES

We used peer-reviewed literature identified by a PubMed search for digitalization, machine learning, artificial intelligence and microbiology.

CONTENT

We describe the opportunities and challenges of digitalization in microbiological diagnostic processes with various examples. We also provide in this context key aspects of data structure and interoperability, as well as legal aspects. Finally, we outline the way for applications in a modern microbiology laboratory.

IMPLICATIONS

We predict that digitalization and the usage of machine learning will have a profound impact on the daily routine of laboratory staff. Along the analytical process, the most important steps should be identified, where digital technologies can be applied and provide a benefit. The education of all staff involved should be adapted to prepare for the advances in digital microbiology.