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.

Increased Multidrug-Resistant Salmonella enterica I Serotype 4,[5],12:i:- Infections Associated with Pork, United States, 2009-2018.

Reports of Salmonella enterica I serotype 4,[5],12:i:- infections resistant to ampicillin, streptomycin, sulphamethoxazole, and tetracycline (ASSuT) have been increasing. We analyzed data from 5 national surveillance systems to describe the epidemiology, resistance traits, and genetics of infections with this Salmonella strain in the United States. We found ASSuT-resistant Salmonella 4,[5],12:i:- increased from 1.1% of Salmonella infections during 2009-2013 to 2.6% during 2014-2018; the proportion of Salmonella 4,[5],12:i:- isolates without this resistance pattern declined from 3.1% to 2.4% during the same timeframe. Among isolates sequenced during 2015-2018, a total of 69% were in the same phylogenetic clade. Within that clade, 77% of isolates had genetic determinants of ASSuT resistance, and 16% had genetic determinants of decreased susceptibility to ciprofloxacin, ceftriaxone, or azithromycin. Among outbreaks related to the multidrug-resistant clade, 63% were associated with pork consumption or contact with swine. Preventing Salmonella 4,[5],12:i:- carriage in swine would likely avert human infections with this strain.

Reoccurring Escherichia coli O157:H7 Strain Linked to Leafy Greens-Associated Outbreaks, 2016-2019.

Genomic characterization of an Escherichia coli O157:H7 strain linked to leafy greens-associated outbreaks dates its emergence to late 2015. One clade has notable accessory genomic content and a previously described mutation putatively associated with increased arsenic tolerance. This strain is a reoccurring, emerging, or persistent strain causing illness over an extended period.

Cronobacter sakazakii Infections in Two Infants Linked to Powdered Infant Formula and Breast Pump Equipment - United States, 2021 and 2022.

Cronobacter sakazakii, a species of gram-negative bacteria belonging to the Enterobacteriaceae family, is known to cause severe and often fatal meningitis and sepsis in young infants. C. sakazakii is ubiquitous in the environment, and most reported infant cases have been attributed to contaminated powdered infant formula (powdered formula) or breast milk that was expressed using contaminated breast pump equipment (1-3). Previous investigations of cases and outbreaks have identified C. sakazakii in opened powdered formula, breast pump parts, environmental surfaces in the home, and, rarely, in unopened powdered formula and formula manufacturing facilities (2,4-6). This report describes two infants with C. sakazakii meningitis reported to CDC in September 2021 and February 2022. CDC used whole genome sequencing (WGS) analysis to link one case to contaminated opened powdered formula from the patient's home and the other to contaminated breast pump equipment. These cases highlight the importance of expanding awareness about C. sakazakii infections in infants, safe preparation and storage of powdered formula, proper cleaning and sanitizing of breast pump equipment, and using WGS as a tool for C. sakazakii investigations.

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.

Pathogen Genomics in Public Health.

Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies.

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.

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.

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.

Implications of Mobile Genetic Elements for Salmonella enterica Single-Nucleotide Polymorphism Subtyping and Source Tracking Investigations.

Single-nucleotide polymorphisms (SNPs) are widely used for whole-genome sequencing (WGS)-based subtyping of foodborne pathogens in outbreak and source tracking investigations. Mobile genetic elements (MGEs) are commonly present in bacterial genomes and may affect SNP subtyping results if their evolutionary history and dynamics differ from that of the bacterial chromosomes. Using Salmonella enterica as a model organism, we surveyed major categories of MGEs, including plasmids, phages, insertion sequences, integrons, and integrative and conjugative elements (ICEs), in 990 genomes representing 21 major serotypes of S. enterica We evaluated whether plasmids and chromosomal MGEs affect SNP subtyping with 9 outbreak clusters of different serotypes found in the United States in 2018. The median total length of chromosomal MGEs accounted for 2.5% of a typical S. enterica chromosome. Of the 990 analyzed S. enterica isolates, 68.9% contained at least one assembled plasmid sequence. The median total length of assembled plasmids in these isolates was 93,671 bp. Plasmids that carry high densities of SNPs were found to substantially affect both SNP phylogenies and SNP distances among closely related isolates if they were present in the reference genome for SNP subtyping. In comparison, chromosomal MGEs were found to have limited impact on SNP subtyping. We recommend the identification of plasmid sequences in the reference genome and the exclusion of plasmid-borne SNPs from SNP subtyping analysis.IMPORTANCE Despite increasingly routine use of WGS and SNP subtyping in outbreak and source tracking investigations, whether and how MGEs affect SNP subtyping has not been thoroughly investigated. Besides chromosomal MGEs, plasmids are frequently entangled in draft genome assemblies and yet to be assessed for their impact on SNP subtyping. This study provides evidence-based guidance on the treatment of MGEs in SNP analysis for Salmonella to infer phylogenetic relationship and SNP distance between isolates.

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.

Metagenomic Approaches for Public Health Surveillance of Foodborne Infections: Opportunities and Challenges.

Foodborne disease surveillance in the United States is at a critical point. Clinical and diagnostic laboratories are using culture-independent diagnostic tests (CIDTs) to identify the pathogen causing foodborne illness from patient specimens. CIDTs are molecular tests that allow doctors to rapidly identify the bacteria causing illness within hours. CIDTs, unlike previous gold standard methods such as bacterial culture, do not produce an isolate that can be subtyped as part of the national molecular subtyping network for foodborne disease surveillance, PulseNet. Without subtype information, cases can no longer be linked using molecular data to identify potentially related cases that are part of an outbreak. In this review, we discuss the public health needs for a molecular subtyping approach directly from patient specimen and highlight different approaches, including amplicon and shotgun metagenomic sequencing.

Whole Genome and Core Genome Multilocus Sequence Typing and Single Nucleotide Polymorphism Analyses of Listeria monocytogenes Isolates Associated with an Outbreak Linked to Cheese, United States, 2013.

Epidemiological findings of a listeriosis outbreak in 2013 implicated Hispanic-style cheese produced by company A, and pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) were performed on clinical isolates and representative isolates collected from company A cheese and environmental samples during the investigation. The results strengthened the evidence for cheese as the vehicle. Surveillance sampling and WGS 3 months later revealed that the equipment purchased by company B from company A yielded an environmental isolate highly similar to all outbreak isolates. The whole genome and core genome multilocus sequence typing and single nucleotide polymorphism (SNP) analyses results were compared to demonstrate the maximum discriminatory power obtained by using multiple analyses, which were needed to differentiate outbreak-associated isolates from a PFGE-indistinguishable isolate collected in a nonimplicated food source in 2012. This unrelated isolate differed from the outbreak isolates by only 7 to 14 SNPs, and as a result, the minimum spanning tree from the whole genome analyses and certain variant calling approach and phylogenetic algorithm for core genome-based analyses could not provide differentiation between unrelated isolates. Our data also suggest that SNP/allele counts should always be combined with WGS clustering analysis generated by phylogenetically meaningful algorithms on a sufficient number of isolates, and the SNP/allele threshold alone does not provide sufficient evidence to delineate an outbreak. The putative prophages were conserved across all the outbreak isolates. All outbreak isolates belonged to clonal complex 5 and serotype 1/2b and had an identical inlA sequence which did not have premature stop codons.IMPORTANCE In this outbreak, multiple analytical approaches were used for maximum discriminatory power. A PFGE-matched, epidemiologically unrelated isolate had high genetic similarity to the outbreak-associated isolates, with as few as 7 SNP differences. Therefore, the SNP/allele threshold should not be used as the only evidence to define the scope of an outbreak. It is critical that the SNP/allele counts be complemented by WGS clustering analysis generated by phylogenetically meaningful algorithms to distinguish outbreak-associated isolates from epidemiologically unrelated isolates. Careful selection of a variant calling approach and phylogenetic algorithm is critical for core-genome-based analyses. The whole-genome-based analyses were able to construct the highly resolved phylogeny needed to support the findings of the outbreak investigation. Ultimately, epidemiologic evidence and multiple WGS analyses should be combined to increase confidence levels during outbreak investigations.

PulseNet International: Vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance.

PulseNet International is a global network dedicated to laboratory-based surveillance for food-borne diseases. The network comprises the national and regional laboratory networks of Africa, Asia Pacific, Canada, Europe, Latin America and the Caribbean, the Middle East, and the United States. The PulseNet International vision is the standardised use of whole genome sequencing (WGS) to identify and subtype food-borne bacterial pathogens worldwide, replacing traditional methods to strengthen preparedness and response, reduce global social and economic disease burden, and save lives. To meet the needs of real-time surveillance, the PulseNet International network will standardise subtyping via WGS using whole genome multilocus sequence typing (wgMLST), which delivers sufficiently high resolution and epidemiological concordance, plus unambiguous nomenclature for the purposes of surveillance. Standardised protocols, validation studies, quality control programmes, database and nomenclature development, and training should support the implementation and decentralisation of WGS. Ideally, WGS data collected for surveillance purposes should be publicly available, in real time where possible, respecting data protection policies. WGS data are suitable for surveillance and outbreak purposes and for answering scientific questions pertaining to source attribution, antimicrobial resistance, transmission patterns, and virulence, which will further enable the protection and improvement of public health with respect to food-borne disease.

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

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.

Two Listeria monocytogenes Pseudo-outbreaks Caused by Contaminated Laboratory Culture Media.

Listeriosis is a serious foodborne infection that disproportionately affects elderly adults, pregnant women, newborns, and immunocompromised individuals. Diagnosis is made by culturing Listeria monocytogenes from sterile body fluids or from products of conception. This report describes the investigations of two listeriosis pseudo-outbreaks caused by contaminated laboratory media made from sheep blood.

Notes from the field: listeriosis associated with stone fruit--United States, 2014.

On July 19, 2014, a packing company in California (company A) voluntarily recalled certain lots of stone fruits, including whole peaches, nectarines, plums, and pluots, because of concern about contamination with Listeria monocytogenes based on internal company testing. On July 31, the recall was expanded to cover all fruit packed at their facility during June 1-July 17. After the initial recall, clinicians, state and local health departments, CDC, and the Food and Drug Administration (FDA) received many inquiries about listeriosis from concerned consumers, many of whom had received automated telephone calls informing them that they had purchased recalled fruit. During July 19-31, the CDC Listeria website received >500,000 page views, more than seven times the views received during the previous 52 weeks. However, no molecular information from L. monocytogenes isolates was available to assess whether human illnesses might be linked to these products.

Invisible no more: a scoping review of the health care aide workforce literature.

BACKGROUND: Healthcare aides (HCAs) are the primary caregivers for vulnerable older persons. They have many titles and are largely unregulated, which contributes to their relative invisibility. The objective of this scoping review was to evaluate the breadth and depth of the HCA workforce literature. METHODS: We conducted a search of seven online bibliographic databases. Studies were included if published since 1995 in English, peer-reviewed journals. Results were iteratively synthesized within and across the following five categories: education, supply, use, demand and injury and illness. RESULTS: Of 5,045 citations screened, 82 studies met inclusion criteria. Few examined HCA education; particularly trainee characteristics, program location, length and content. Results in supply indicated that the average HCA was female, 36-45 years and had an education level of high school or less. Home health HCAs were, on average, older and were more likely to be immigrants than those working in other settings. The review of studies exploring HCA use revealed that their role was unclear - variation in duties, level of autonomy and work setting make describing "the" role of an HCA near impossible. Projected increased demand for HCAs and high rates of turnover, both at the profession and facility-level, elicit predictions of future HCA shortages. Home health HCAs experienced comparatively lower job stability, earned less, worked the fewest hours and were less likely to have fringe benefits than HCAs employed in hospitals and nursing homes. The review of studies related to HCA illness and injury revealed that they were at comparatively higher risk of injury than registered nurses and licensed practical nurses. CONCLUSIONS: This is the largest, most comprehensive scoping review of HCA workforce literature to date. Our results indicate that the HCA workforce is both invisible and ubiquitous; as long as this is the case, governments and healthcare organizations will be limited in their ability to develop and implement feasible, effective HCA workforce plans. The continued undervaluation of HCAs adversely impacts care providers, the institutions they work for and those who depend on their care. Future workforce planning and research necessitates national HCA registries, or at minimum, directories.

Genetic Diversity in Salmonella enterica in Outbreaks of Foodborne and Zoonotic Origin in the USA in 2006-2017.

Whole genome sequencing is replacing traditional laboratory surveillance methods as the primary tool to track and characterize clusters and outbreaks of the foodborne and zoonotic pathogen Salmonella enterica (S. enterica). In this study, 438 S. enterica isolates representing 35 serovars and 13 broad vehicle categories from one hundred epidemiologically confirmed outbreaks were evaluated for genetic variation to develop epidemiologically relevant interpretation guidelines for Salmonella disease cluster detection. The Illumina sequences were analyzed by core genome multi-locus sequence typing (cgMLST) and screened for antimicrobial resistance (AR) determinants and plasmids. Ninety-three of the one hundred outbreaks exhibited a close allele range (less than 10 allele differences with a subset closer than 5). The remaining seven outbreaks showed increased variation, of which three were considered polyclonal. A total of 16 and 28 outbreaks, respectively, showed variations in the AR and plasmid profiles. The serovars Newport and I 4,[5],12:i:-, as well as the zoonotic and poultry product vehicles, were overrepresented among the outbreaks, showing increased variation. A close allele range in cgMLST profiles can be considered a reliable proxy for epidemiological relatedness for the vast majority of S. enterica outbreak investigations. Variations associated with mobile elements happen relatively frequently during outbreaks and could be reflective of changing selective pressures.