Antimicrobial resistance in multistate outbreaks of nontyphoidal Salmonella infections linked to animal contact-United States, 2015-2018.

Animal contact is an established risk factor for nontyphoidal Salmonella infections and outbreaks. During 2015-2018, the U.S. Centers for Disease Control and Prevention (CDC) and other U.S. public health laboratories began implementing whole-genome sequencing (WGS) of Salmonella isolates. WGS was used to supplement the traditional methods of pulsed-field gel electrophoresis for isolate subtyping, outbreak detection, and antimicrobial susceptibility testing (AST) for the detection of resistance. We characterized the epidemiology and antimicrobial resistance (AMR) of multistate salmonellosis outbreaks linked to animal contact during this time period. An isolate was considered resistant if AST yielded a resistant (or intermediate, for ciprofloxacin) interpretation to any antimicrobial tested by the CDC or if WGS showed a resistance determinant in its genome for one of these agents. We identified 31 outbreaks linked to contact with poultry (n = 23), reptiles (n = 6), dairy calves (n = 1), and guinea pigs (n = 1). Of the 26 outbreaks with resistance data available, we identified antimicrobial resistance in at least one isolate from 20 outbreaks (77%). Of 1,309 isolates with resistance information, 247 (19%) were resistant to ≥1 antimicrobial, and 134 (10%) were multidrug-resistant to antimicrobials from ≥3 antimicrobial classes. The use of resistance data predicted from WGS increased the number of isolates with resistance information available fivefold compared with AST, and 28 of 43 total resistance patterns were identified exclusively by WGS; concordance was high (>99%) for resistance determined by AST and WGS. The use of predicted resistance from WGS enhanced the characterization of the resistance profiles of outbreaks linked to animal contact by providing resistance information for more isolates.

Multistate Outbreak of Salmonella Thompson Infections Linked to Seafood Exposure - United States, 2021.

In July 2021, the Colorado Department of Public Health and Environment (CDPHE) laboratory identified a cluster of five Salmonella enterica serotype Thompson isolates related to one another within one allele difference, using whole genome multilocus sequence typing (wgMLST). These five isolates, submitted to the public health laboratory as is routine process for confirmatory testing of Salmonella, were highly related to those identified in a 2020 multistate investigation, during which traceback was conducted for sushi-grade tuna and salmon; a common supplier was not identified. The 2021 investigation commenced on August 5, 2021, with five patients living in Colorado, and one each in Missouri, Washington, and Wisconsin. During August-December 2021, CDC, CDPHE, public health and regulatory officials in several states, and the Food and Drug Administration (FDA) conducted epidemiologic, environmental, and laboratory investigations of this multistate outbreak of Salmonella Thompson. Isolates were genetically related to one another and to 2020 isolates within zero to one allele difference. Implicated seafood products were traced to a single seafood distributor, in which the outbreak strain was identified through environmental sampling, and in which inspection identified inadequate sanitization and opportunities for cross-contamination of raw fish. The distributor issued a voluntary recall of 16 seafood items with high potential for contamination and completed remediation actions. This outbreak illustrated the importance of effective cleaning and sanitizing procedures and implementation of controls. When multiple products are recalled during an outbreak investigation, collaboration between public health agencies and implicated facilities can help provide food safety information to restaurants, retailers, and consumers, and to ensure disposal of all recalled products.

Analysis of Salmonella enterica Isolated from a Mixed-Use Watershed in Georgia, USA: Antimicrobial Resistance, Serotype Diversity, and Genetic Relatedness to Human Isolates.

As the cases of Salmonella enterica infections associated with contaminated water are increasing, this study was conducted to address the role of surface water as a reservoir of S. enterica serotypes. We sampled rivers and streams (n = 688) over a 3-year period (2015 to 2017) in a mixed-use watershed in Georgia, USA, and 70.2% of the total stream samples tested positive for Salmonella. A total of 1,190 isolates were recovered and characterized by serotyping, antimicrobial susceptibility testing, and pulsed-field gel electrophoresis (PFGE). A wide range of serotypes was identified, including those commonly associated with humans and animals, with S. enterica serotype Muenchen being predominant (22.7%) and each serotype exhibiting a high degree of strain diversity by PFGE. About half (46.1%) of the isolates had PFGE patterns indistinguishable from those of human clinical isolates in the CDC PulseNet database. A total of 52 isolates (4.4%) were resistant to antimicrobials, out of which 43 isolates were multidrug resistant (MDR; resistance to two or more classes of antimicrobials). These 52 resistant Salmonella isolates were screened for the presence of antimicrobial resistance genes, plasmid replicons, and class 1 integrons, out of which four representative MDR isolates were selected for whole-genome sequencing analysis. The results showed that 28 MDR isolates resistant to 10 antimicrobials had blacmy-2 on an A/C plasmid. Persistent contamination of surface water with a high diversity of Salmonella strains, some of which are drug resistant and genetically indistinguishable from human isolates, supports a role of environmental surface water as a reservoir for and transmission route of this pathogen. IMPORTANCE Salmonella has been traditionally considered a foodborne pathogen, as it is one of the most common etiologies of foodborne illnesses worldwide; however, recent Salmonella outbreaks attributed to fresh produce and water suggest a potential environmental source of Salmonella that causes some human illnesses. Here, we investigated the prevalence, diversity, and antimicrobial resistance of Salmonella isolated from a mixed-use watershed in Georgia, USA, in order to enhance the overall understanding of waterborne Salmonella. The persistence and widespread distribution of Salmonella in surface water confirm environmental sources of the pathogen. A high proportion of waterborne Salmonella with clinically significant serotypes and genetic similarity to strains of human origin supports the role of environmental water as a significant reservoir of Salmonella and indicates a potential waterborne transmission of Salmonella to humans. The presence of antimicrobial-resistant and MDR Salmonella demonstrates additional risks associated with exposure to contaminated environmental water.

Comparison of Molecular Subtyping and Antimicrobial Resistance Detection Methods Used in a Large Multistate Outbreak of Extensively Drug-Resistant Campylobacter jejuni Infections Linked to Pet Store Puppies.

Campylobacter jejuni is a leading cause of enteric bacterial illness in the United States. Traditional molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST), provided limited resolution to adequately identify C. jejuni outbreaks and separate out sporadic isolates during outbreak investigations. Whole-genome sequencing (WGS) has emerged as a powerful tool for C. jejuni outbreak detection. In this investigation, 45 human and 11 puppy isolates obtained during a 2016-2018 outbreak linked to pet store puppies were sequenced. Core genome multilocus sequence typing (cgMLST) and high-quality single nucleotide polymorphism (hqSNP) analysis of the sequence data separated the isolates into the same two clades containing minor within-clade differences; however, cgMLST analysis does not require selection of an appropriate reference genome, making the method preferable to hqSNP analysis for Campylobacter surveillance and cluster detection. The isolates were classified as sequence type 2109 (ST2109)-a rarely seen MLST sequence type. PFGE was performed on 38 human and 10 puppy isolates; PFGE patterns did not reliably predict clustering by cgMLST analysis. Genetic detection of antimicrobial resistance determinants predicted that all outbreak-associated isolates would be resistant to six drug classes. Traditional antimicrobial susceptibility testing (AST) confirmed a high correlation between genotypic and phenotypic antimicrobial resistance determinations. WGS analysis linked C. jejuni isolates in humans and pet store puppies even when canine exposure information was unknown, aiding the epidemiological investigation during the outbreak. WGS data were also used to quickly identify the highly drug-resistant profile of these outbreak-associated C. jejuni isolates.

Analysis of Escherichia coli and Listeria monocytogenes Isolate Subtyping and Reporting Capacity by Public Health Laboratories, United States (2013-2017).

OBJECTIVES: To demonstrate the performance of 53 laboratories required to submit 90% or more of their pulsed-field gel electrophoresis (PFGE) subtyping results for Escherichia coli O157:H7 (E coli O157:H7) and Listeria monocytogenes (L monocytogenes) to the PulseNet national databases at the Centers for Disease Control and Prevention (CDC) within 4 working days of receiving isolates. METHODS: We examined data from 53 laboratories during 2013-2017 to ascertain whether E. coli O157:H7 and L monocytogenes PFGE data were reported to the PulseNet national databases within 4 working days. RESULTS: In the study period, 45 laboratories that submitted reports during the period (86.8%) met the target for timely submission of 10 606 (94.85%) E coli O157:H7 isolates into the PulseNet national database. For L monocytogenes isolates, 32 laboratories submitted reports (76.95%) that achieved timely submission of 3119 (93.35%) isolates. CONCLUSIONS: This study uncovered areas for improvement to advance public health in the CDC-funded laboratories.

PulseNet: Entering the Age of Next-Generation Sequencing.

Since 1996, PulseNet has served as the national laboratory-based surveillance system for the rapid detection of outbreaks caused by foodborne bacterial pathogens in the United States. For the past two decades, pulsed-field gel electrophoresis was the gold standard subtyping method for the pathogens tracked by PulseNet. A new gold standard is now being implemented with the introduction of cost-effective whole genome sequencing (WGS) for analysis of all the organisms tracked by PulseNet. This transformation is a major undertaking that touches every functional aspect of PulseNet, including laboratory workflows, data storage, analysis management and data interpretation, and language used to communicate information (sequence profile nomenclature system). The benefits of implementing WGS go beyond improved discrimination and precision of the data; it provides an opportunity to determine strain characteristics typically obtained through resource-intensive traditional methodologies, for example, species identification, serotyping, virulence, and antimicrobial resistance profiling, all of which can be consolidated into a single WGS workflow. Such a strategy represents a major shift in the workflows currently practiced in most public health laboratories, but one that brings opportunities for streamlining surveillance activities for the network as a whole. In this study, we provide a brief summary of PulseNet's evolution the past decade along with a general description of the challenges and opportunities that lie ahead.

Interpretation of Whole-Genome Sequencing for Enteric Disease Surveillance and Outbreak Investigation.

The routine use of whole-genome sequencing (WGS) as part of enteric disease surveillance is substantially enhancing our ability to detect and investigate outbreaks and to monitor disease trends. At the same time, it is revealing as never before the vast complexity of microbial and human interactions that contribute to outbreak ecology. Since WGS analysis is primarily used to characterize and compare microbial genomes with the goal of addressing epidemiological questions, it must be interpreted in an epidemiological context. In this article, we identify common challenges and pitfalls encountered when interpreting sequence data in an enteric disease surveillance and investigation context, and explain how to address them.

An Overview of PulseNet USA Databases.

PulseNet USA is the molecular surveillance network for foodborne disease in the United States. The network consists of state and local public health laboratories, as well as food regulatory agencies, that follow PulseNet's standardized protocols to perform pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) and analyze the results using standardized software. The raw sequences are uploaded to the GenomeTrakr or PulseNet bioprojects at the National Center for Biotechnology Information. The PFGE patterns and analyzed sequence data are uploaded in real time with associated demographic data to the PulseNet national databases managed at the Centers for Disease Control and Prevention. The PulseNet databases are organism specific and provide a central storage location for molecular and demographic data related to an isolate. Sequences are compared in the databases, thereby facilitating the rapid detection of clusters of foodborne diseases that may represent widespread outbreaks. WGS genotyping data, for example, antibiotic resistance and virulence profiles, are also uploaded in real time to the PulseNet databases to improve food safety surveillance activities.

Protracted Outbreak of Salmonella Newport Infections Linked to Ground Beef: Possible Role of Dairy Cows - 21 States, 2016-2017.

In January 2017, CDC identified a cluster of Salmonella enterica serotype Newport infections with isolates sharing an indistinguishable pulsed-field gel electrophoresis (PFGE) pattern, JJPX01.0010 (pattern 10), through PulseNet, the national molecular subtyping network for foodborne disease surveillance. This report summarizes the investigation by CDC, state and local health and agriculture departments, and the U.S. Department of Agriculture's Food Safety and Inspection Service (USDA-FSIS) and discusses the possible role of dairy cows as a reservoir for strains of Salmonella that persistently cause human illness. This investigation combined epidemiologic and whole genome sequencing (WGS) data to link the outbreak to contaminated ground beef; dairy cows were hypothesized to be the ultimate source of Salmonella contamination.

Pulsotype Diversity of Clostridium botulinum Strains Containing Serotypes A and/or B Genes.

Clostridium botulinum strains are prevalent in the environment and produce a potent neurotoxin that causes botulism, a rare but serious paralytic disease. In 2010, a national PulseNet database was established to curate C. botulinum pulsotypes and facilitate epidemiological investigations, particularly for serotypes A and B strains frequently associated with botulism cases in the United States. Between 2010 and 2014 we performed pulsed-field gel electrophoresis (PFGE) using a PulseNet protocol, uploaded the resulting PFGE patterns into a national database, and analyzed data according to PulseNet criteria (UPGMA clustering, Dice coefficient, 1.5% position tolerance, and 1.5% optimization). A retrospective data analysis was undertaken on 349 entries comprised of type A and B strains isolated from foodborne and infant cases to determine epidemiological relevance, resolution of the method, and the diversity of the database. Most studies to date on the pulsotype diversity of C. botulinum have encompassed very small sets of isolates; this study, with over 300 isolates, is more comprehensive than any published to date. Epidemiologically linked isolates had indistinguishable patterns, except in four instances and there were no obvious geographic trends noted. Simpson's Index of Diversity (D) has historically been used to demonstrate species diversity and abundance within a group, and is considered a standard descriptor for PFGE databases. Simpson's Index was calculated for each restriction endonuclease (SmaI, XhoI), the pattern combination SmaI-XhoI, as well as for each toxin serotype. The D values indicate that both enzymes provided better resolution for serotype B isolates than serotype A. XhoI as the secondary enzyme provided little additional discrimination for C. botulinum. SmaI patterns can be used to exclude unrelated isolates during a foodborne outbreak, but pulsotypes should always be considered concurrently with available epidemiological data.

Increase in Multistate Foodborne Disease Outbreaks-United States, 1973-2010.

INTRODUCTION: Changes in food production and distribution have increased opportunities for foods contaminated early in the supply chain to be distributed widely, increasing the possibility of multistate outbreaks. In recent decades, surveillance systems for foodborne disease have been improved, allowing officials to more effectively identify related cases and to trace and identify an outbreak's source. MATERIALS AND METHODS: We reviewed multistate foodborne disease outbreaks reported to the Centers for Disease Control and Prevention's Foodborne Disease Outbreak Surveillance System during 1973-2010. We calculated the percentage of multistate foodborne disease outbreaks relative to all foodborne disease outbreaks and described characteristics of multistate outbreaks, including the etiologic agents and implicated foods. RESULTS: Multistate outbreaks accounted for 234 (0.8%) of 27,755 foodborne disease outbreaks, 24,003 (3%) of 700,600 outbreak-associated illnesses, 2839 (10%) of 29,756 outbreak-associated hospitalizations, and 99 (16%) of 628 outbreak-associated deaths. The median annual number of multistate outbreaks increased from 2.5 during 1973-1980 to 13.5 during 2001-2010; the number of multistate outbreak-associated illnesses, hospitalizations, and deaths also increased. Most multistate outbreaks were caused by Salmonella (47%) and Shiga toxin-producing Escherichia coli (26%). Foods most commonly implicated were beef (22%), fruits (13%), and leafy vegetables (13%). CONCLUSIONS: The number of identified and reported multistate foodborne disease outbreaks has increased. Improvements in detection, investigation, and reporting of foodborne disease outbreaks help explain the increasing number of reported multistate outbreaks and the increasing percentage of outbreaks that were multistate. Knowing the etiologic agents and foods responsible for multistate outbreaks can help to identify sources of food contamination so that the safety of the food supply can be improved.

Characterization of blaCMY plasmids and their possible role in source attribution of Salmonella enterica serotype Typhimurium infections.

Salmonella is an important cause of foodborne illness; however, identifying the source of these infections can be difficult. This is especially true for Salmonella serotype Typhimurium, which is found in diverse agricultural niches. Extended-spectrum cephalosporins (ESC) are one of the primary treatment choices for complicated Salmonella infections. In Salmonella, ESC resistance in the United States is mainly mediated by blaCMY genes carried on various plasmids. In this study, we examined whether the characterization of blaCMY plasmids, along with additional information, can help us identify potential sources of infection by Salmonella, and used serotype Typhimurium as a model. In the United States, monitoring of retail meat, food animals, and ill persons for antimicrobial-resistant Salmonella is conducted by the National Antimicrobial Resistance Monitoring System. In 2008, 70 isolates (70/581; 12.0%) (34 isolates from retail meat, 23 food animal, and 13 human) were resistant to ceftriaxone and amoxicillin/clavulanic acid. All were polymerase chain reaction (PCR)-positive for blaCMY and 59/70 (84.3%) of these genes were plasmid encoded. PCR-based replicon typing identified 42/59 (71.2%) IncI1-blaCMY plasmids and 17/59 (28.8%) IncA/C-blaCMY plasmids. Isolates from chickens or chicken products with blaCMY plasmids primarily had IncI1-blaCMY plasmids (37/40; 92.5%), while all isolates from cattle had IncA/C-blaCMY plasmids. Isolates from humans had either IncA/C- blaCMY (n=8/12; [66.7%]) or IncI1- blaCMY (n=4/12 [33.3%]) plasmids. All of the IncI1-blaCMY plasmids were ST12 or were closely related to ST12. Antimicrobial susceptibility patterns (AST) and pulsed-field gel electrophoresis (PFGE) patterns of the isolates were also compared and differences were identified between isolate sources. When the source of a Typhimurium outbreak or sporadic illness is unknown, characterizing the outbreak isolate's blaCMY plasmids, AST, and PFGE patterns may help identify it.

Evaluation of core genome and whole genome multilocus sequence typing schemes for Campylobacter jejuni and Campylobacter coli outbreak detection in the USA.

Campylobacter is a leading causing of bacterial foodborne and zoonotic illnesses in the USA. Pulsed-field gene electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST) have been historically used to differentiate sporadic from outbreak Campylobacter isolates. Whole genome sequencing (WGS) has been shown to provide superior resolution and concordance with epidemiological data when compared with PFGE and 7-gene MLST during outbreak investigations. In this study, we evaluated epidemiological concordance for high-quality SNP (hqSNP), core genome (cg)MLST and whole genome (wg)MLST to cluster or differentiate outbreak-associated and sporadic Campylobacter jejuni and Campylobacter coli isolates. Phylogenetic hqSNP, cgMLST and wgMLST analyses were also compared using Baker's gamma index (BGI) and cophenetic correlation coefficients. Pairwise distances comparing all three analysis methods were compared using linear regression models. Our results showed that 68/73 sporadic C. jejuni and C. coli isolates were differentiated from outbreak-associated isolates using all three methods. There was a high correlation between cgMLST and wgMLST analyses of the isolates; the BGI, cophenetic correlation coefficient, linear regression model R 2 and Pearson correlation coefficients were >0.90. The correlation was sometimes lower comparing hqSNP analysis to the MLST-based methods; the linear regression model R 2 and Pearson correlation coefficients were between 0.60 and 0.86, and the BGI and cophenetic correlation coefficient were between 0.63 and 0.86 for some outbreak isolates. We demonstrated that C. jejuni and C. coli isolates clustered in concordance with epidemiological data using WGS-based analysis methods. Discrepancies between allele and SNP-based approaches may reflect the differences between how genomic variation (SNPs and indels) are captured between the two methods. Since cgMLST examines allele differences in genes that are common in most isolates being compared, it is well suited to surveillance: searching large genomic databases for similar isolates is easily and efficiently done using allelic profiles. On the other hand, use of an hqSNP approach is much more computer intensive and not scalable to large sets of genomes. If further resolution between potential outbreak isolates is needed, wgMLST or hqSNP analysis can be used.

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.

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 (SIROIs) 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.

Prediction system for rapid identification of Salmonella serotypes based on pulsed-field gel electrophoresis fingerprints.

A classification model is presented for rapid identification of Salmonella serotypes based on pulsed-field gel electrophoresis (PFGE) fingerprints. The classification model was developed using random forest and support vector machine algorithms and was then applied to a database of 45,923 PFGE patterns, randomly selected from all submissions to CDC PulseNet from 2005 to 2010. The patterns selected included the top 20 most frequent serotypes and 12 less frequent serotypes from various sources. The prediction accuracies for the 32 serotypes ranged from 68.8% to 99.9%, with an overall accuracy of 96.0% for the random forest classification, and ranged from 67.8% to 100.0%, with an overall accuracy of 96.1% for the support vector machine classification. The prediction system improves reliability and accuracy and provides a new tool for early and fast screening and source tracking of outbreak isolates. It is especially useful to get serotype information before the conventional methods are done. Additionally, this system also works well for isolates that are serotyped as "unknown" by conventional methods, and it is useful for a laboratory where standard serotyping is not available.