A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

Genomic Characterization of Escherichia coli O157:H7 Associated with Multiple Sources, United States

In the United States, Shiga toxin-producing Escherichia coli (STEC) outbreaks cause >265,000 infections and cost $280 million annually. We investigated REPEXH01, a persistent strain of STEC O157:H7 associated with multiple sources, including romaine lettuce and recreational water, that has caused multiple outbreaks since emerging in late 2015. By comparing the genomes of 729 REPEXH01 isolates with those of 2,027 other STEC O157:H7 isolates, we identified a highly conserved, single base pair deletion in espW that was strongly linked to REPEXH01 membership. The biological consequence of that deletion remains unclear; further studies are needed to elucidate its role in REPEXH01. Additional analyses revealed that REPEXH01 isolates belonged to Manning clade 8; possessed the toxins stx2a, stx2c, or both; were predicted to be resistant to several antimicrobial compounds; and possessed a diverse set of plasmids. Those factors underscore the need to continue monitoring REPEXH01 and clarify aspects contributing to its emergence and persistence.

Multi-country and intersectoral assessment of cluster congruence between pipelines for genomics surveillance of foodborne pathogens

Different laboratories employ different Whole-Genome Sequencing (WGS) pipelines for Food and Waterborne disease (FWD) surveillance, casting doubt on the comparability of their results and hindering optimal communication at intersectoral and international levels. Through a collaborative effort involving eleven European institutes spanning the food, animal, and human health sectors, we aimed to assess the inter-pipeline clustering congruence across all resolution levels and perform an in-depth comparative analysis of cluster composition at outbreak level for four important foodborne pathogens: Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni. We found a general concordance between allele-based pipelines for all species, except for C. jejuni, where the different resolution power of allele-based schemas led to marked discrepancies. Still, we identified non-negligible differences in outbreak detection and demonstrated how a threshold flexibilization favors the detection of similar outbreak signals by different laboratories. These results, together with the observation that different traditional typing groups (e.g., serotypes) exhibit a remarkably different genetic diversity, represent valuable information for future outbreak case-definitions and WGS-based nomenclature design. This study reinforces the need, while demonstrating the feasibility, of conducting continuous pipeline comparability assessments, and opens good perspectives for a smoother international and intersectoral cooperation towards an efficient One Health FWD surveillance.

Salmonella serotypes in the genomic era: simplified Salmonella serotype interpretation from DNA sequence data

In the era of genomic characterization of strains for public health microbiology, whole genome sequencing (WGS)-enabled subtyping of Salmonella provides superior discrimination of strains compared to traditional methods such as serotyping. Nonetheless, serotypes are still very useful; they maintain historical continuity and facilitate clear communication. Genetic determination of serotypes from WGS data is now routine. Genetic determination of rarer serotypes can be problematic due to a lack of sequences for rare antigen types and alleles, a lack of understanding of the genetic basis for some antigens, or some inconsistencies in the White-Kauffmann-Le Minor (WKL) Scheme for Salmonella serotype designation. Here, we present a simplified interpretation of serotypes to address the shortcomings of genetic methods, which will allow the streamlined integration of serotype determination into the WGS workflow. The simplification represents a consensus perspective among major U.S. public health agencies and serves as a WGS-oriented interpretation of the WKL Scheme. We also present SeqSero2S, a bioinformatics tool for WGS-based serotype prediction using the simplified interpretation.IMPORTANCEThe utility of Salmonella serotyping has evolved from a primary subtyping method, where the need for strain discrimination justified its complexity, to a supplemental subtyping scheme and nomenclature convention, where clarity and simplicity in communication have become important for its continued use. Compared to phenotypic methods like serotyping, whole genome sequencing (WGS)-based subtyping methods excel in recognizing natural populations, which avoids grouping together strains from different genetic backgrounds or splitting genetically related strains into different groups. This simplified interpretation of serotypes addresses a shortcoming of the original scheme by combining some serotypes that are known to be genetically related. Our simplified interpretation of the White-Kauffmann-Le Minor (WKL) Scheme facilitates a complete and smooth transition of serotyping's role, especially from the public health perspective that has been shaped by the routine use of WGS.

Average Nucleotide Identity and Digital DNA-DNA Hybridization Analysis Following PromethION Nanopore-Based Whole Genome Sequencing Allows for Accurate Prokaryotic Typing

Whole-genome sequencing (WGS) is revolutionizing clinical bacteriology. However, bacterial typing remains investigated by reference techniques with inherent limitations. This stresses the need for alternative methods providing robust and accurate sequence type (ST) classification. This study optimized and evaluated a GridION nanopore sequencing protocol, adapted for the PromethION platform. Forty-eight Escherichia coli clinical isolates with diverse STs were sequenced to assess two alternative typing methods and resistance profiling applications. Multi-locus sequence typing (MLST) was used as the reference typing method. Genomic relatedness was assessed using Average Nucleotide Identity (ANI) and digital DNA-DNA Hybridization (DDH), and cut-offs for discriminative strain resolution were evaluated. WGS-based antibiotic resistance prediction was compared to reference Minimum Inhibitory Concentration (MIC) assays. We found ANI and DDH cut-offs of 99.3% and 94.1%, respectively, which correlated well with MLST classifications and demonstrated potentially higher discriminative resolution than MLST. WGS-based antibiotic resistance prediction showed categorical agreements of ≥ 93% with MIC assays for amoxicillin, ceftazidime, amikacin, tobramycin, and trimethoprim-sulfamethoxazole. Performance was suboptimal (68.8-81.3%) for amoxicillin-clavulanic acid, cefepime, aztreonam, and ciprofloxacin. A minimal sequencing coverage of 12× was required to maintain essential genomic features and typing accuracy. Our protocol allows the integration of PromethION technology in clinical laboratories, with ANI and DDH proving to be accurate and robust alternative typing methods, potentially offering superior resolution. WGS-based antibiotic resistance prediction holds promise for specific antibiotic classes.

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.

The Next Frontier in Tuberculosis Investigation: Automated Whole Genome Sequencing for Mycobacterium tuberculosis Analysis

A fully automated bacteria whole genome sequencing (WGS) assay was evaluated to characterize Mycobacterium tuberculosis (MTB) and non-tuberculosis Mycobacterium (NTM) clinical isolates. The results generated were highly reproducible, with 100% concordance in species and sub-lineage classification and 92% concordance between antimicrobial resistance (AMR) genotypic and phenotypic profiles. Using extracted deoxyribonucleic acid (DNA) from MTB clinical isolates as starting material, these findings demonstrate that a fully automated WGS assay, with a short turnaround time of 24.5 hours, provides timely and valuable insights into MTB outbreak investigation while providing reliable genotypic AMR profiling consistent with traditional antimicrobial susceptibility tests (AST). This study establishes a favorable proposition for the adoption of end-to-end fully automated WGS solutions for decentralized MTB diagnostics, thereby aiding in World Health Organization's (WHO) vision of tuberculosis eradication.

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).

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

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

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

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

Genomic characterization of a unique Panton-Valentine leucocidin-positive community-associated methicillin-resistant Staphylococcus aureus lineage increasingly impacting on Australian indigenous communities

In 2010 a single isolate of a trimethoprim-resistant multilocus sequence type 5, Panton-Valentine leucocidin-positive, community-associated methicillin-resistant Staphylococcus aureus (PVL-positive ST5 CA-MRSA), colloquially named WA121, was identified in northern Western Australia (WA). WA121 now accounts for ~14 % of all WA MRSA infections. To gain an understanding of the genetic composition and phylogenomic structure of WA121 isolates we sequenced the genomes of 155 WA121 isolates collected 2010-2021 and present a detailed genomic description. WA121 was revealed to be a single clonally expanding lineage clearly distinct from sequenced ST5 strains reported outside Australia. WA121 strains were typified by the presence of the distinct PVL phage φSa2wa-st5, the recently described methicillin resistance element SCCmecIVo carrying the trimethoprim resistance (dfrG) transposon Tn4791, the novel β-lactamase transposon Tn7702 and the epidermal cell differentiation inhibitor (EDIN-A) plasmid p2010-15611-2. We present evidence that SCCmecIVo together with Tn4791 has horizontally transferred to Staphylococcus argenteus and evidence of intragenomic movement of both Tn4791 and Tn7702. We experimentally demonstrate that p2010-15611-2 is capable of horizontal transfer by conjugative mobilization from one of several WA121 isolates also harbouring a pWBG749-like conjugative plasmid. In summary, WA121 is a distinct and clonally expanding Australian PVL-positive CA-MRSA lineage that is increasingly responsible for infections in indigenous communities in northern and western Australia. WA121 harbours a unique complement of mobile genetic elements and is capable of transferring antimicrobial resistance and virulence determinants to other staphylococci.

Building Phylogenetic Trees From Genome Sequences With kSNP4

Performing phylogenetic analysis with genome sequences maximizes the information used to estimate phylogenies and the resolution of closely related taxa. The use of single-nucleotide polymorphisms (SNPs) permits estimating trees without genome alignments and permits the use of data sets of hundreds of microbial genomes. kSNP4 is a program that identifies SNPs without using a reference genome, estimates parsimony, maximum likelihood, and neighbor-joining trees, and is able to annotate the discovered SNPs. kSNP4 is a command-line program that does not require any additional programs or dependencies to install or use. kSNP4 does not require any programming experience or bioinformatics experience to install and use. It is suitable for use by students through senior investigators. It includes a detailed user guide that explains all of the many features of kSNP4. In this study, we provide a detailed step-by-step protocol for downloading, installing, and using kSNP4 to build phylogenetic trees from genome sequences.

Human Salmonellosis Outbreak Linked to Salmonella Typhimurium Epidemic in Wild Songbirds, United States, 2020-2021

Salmonella infection causes epidemic death in wild songbirds, with potential to spread to humans. In February 2021, public health officials in Oregon and Washington, USA, isolated a strain of Salmonella enterica serovar Typhimurium from humans and a wild songbird. Investigation by public health partners ultimately identified 30 illnesses in 12 states linked to an epidemic of Salmonella Typhimurium in songbirds. We report a multistate outbreak of human salmonellosis associated with songbirds, resulting from direct handling of sick and dead birds or indirect contact with contaminated birdfeeders. Companion animals might have contributed to the spread of Salmonella between songbirds and patients; the outbreak strain was detected in 1 ill dog, and a cat became ill after contact with a wild bird. This outbreak highlights a One Health issue where actions like regular cleaning of birdfeeders might reduce the health risk to wildlife, companion animals, and humans.

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.

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.

Using Genomics To Investigate an Outbreak of Vancomycin-Resistant Enterococcus faecium ST78 at a Large Tertiary Hospital in Queensland

To investigate an outbreak of vancomycin-resistant Enterococcus faecium (VREfm) sequence type 78 (ST78) in a large tertiary Australian hospital. A collection of 63 VREfm ST78 isolates, identified during a routine genomic surveillance program, were subjected to genomic epidemiological analysis based on whole-genome sequencing (WGS) data. The population structure was reconstructed using phylogenetic analysis, and a collection of publicly available VREfm ST78 genomes were used to provide global context. Core genome single nucleotide polymorphism (SNP) distances and available clinical metadata were used to characterize outbreak clusters and reconstruct transmission events. In silico genotyping confirmed that all study isolates were vanB-type VREfm carrying virulence characteristics of the hospital-associated E. faecium. Phylogenetic analysis identified two distinct phylogenetic clades, only one of which was responsible for a hospital outbreak. Four outbreak subtypes could be defined with examples of recent transmissions. Inference on transmission trees suggested complex transmission routes with unknown environmental reservoirs mediating the outbreak. WGS-based cluster analysis with publicly available genomes identified closely related Australian ST78 and ST203 isolates, highlighting the capacity for WGS to resolve complex clonal relationships between the VREfm lineages. Whole genome-based analysis has provided a high-resolution description of an outbreak of vanB-type VREfm ST78 in a Queensland hospital. Combined routine genomic surveillance and epidemiological analysis have facilitated better understanding of the local epidemiology of this endemic strain, providing valuable insight for better targeted control of VREfm. IMPORTANCE Vancomycin-resistant Enterococcus faecium (VREfm) is a leading cause of health care-associated infections (HAIs) globally. In Australia, the spread of hospital-adapted VREfm is largely driven by a single clonal group (clonal complex [CC]), CC17, to which the lineage ST78 belongs. While implementing a genomic surveillance program in Queensland, we observed increased incidence of ST78 colonizations and infections among patients. Here, we demonstrate the use of real-time genomic surveillance as a tool to support and enhance infection control (IC) practices. Our results show that real-time whole-genome sequencing (WGS) can efficiently disrupt outbreaks by identifying transmission routes that in turn can be targeted using resource-limited interventions. Additionally, we demonstrate that by placing local outbreaks in a global context, high-risk clones can be identified and targeted prior to them becoming established within clinical environments. Finally, the persistence of these organism within the hospital highlights the need for routine genomic surveillance as a management tool to control VRE transmission.

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

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

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.

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

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

First molecular characterization of Escherichia coli O157:H7 isolates from clinical samples in Paraguay using whole-genome sequencing

Escherichia coli O157:H7 is a foodborne pathogen implicated in numerous outbreaks worldwide that has the ability to cause extra-intestinal complications in humans. The Enteropathogens Division of the Central Public Health Laboratory (CPHL) in Paraguay is working to improve the genomic characterization of Shiga toxin-producing E. coli (STEC) to enhance laboratory-based surveillance and investigation of foodborne disease outbreaks. Whole genome sequencing (WGS) is proposed worldwide to be used in the routine laboratory as a high-resolution tool that allows to have all the results in a single workflow. This study aimed to carry out for the first time, the genomic characterization by WGS of nine STEC O157:H7 strains isolated from human samples in Paraguay. We were able to identify virulence and resistance mechanisms, MLST subtype, and even establish the phylogenetic relationships between isolates. Furthermore, we detected the presence of strains belonging to hypervirulent clade 8 in most of the isolates studied.

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

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

Application of MinION sequencing as a tool for the rapid detection and characterization of Listeria monocytogenes in smoked salmon

Microbial pathogens may be present in different types of foods, and hence the development of novel methods to assure consumers' safeness is of great interest. Molecular methods are known to provide sensitive and rapid results; however, they are typically targeted approaches. In recent years, the advent of non-targeted approaches based on next-generation sequencing (NGS) has emerged as a rational way to proceed. This technology allows for the detection of several pathogens simultaneously. Furthermore, with the same set of data, it is possible to characterize the microorganisms in terms of serotype, virulence, and/ or resistance genes, among other molecular features. In the current study, a novel method for the detection of Listeria monocytogenes based on the "quasimetagenomics" approach was developed. Different enrichment media and immunomagnetic separation (IMS) strategies were compared to determine the best approach in terms of L. monocytogenes sequences generated from smoked salmon samples. Finally, the data generated were analyzed with a user-friendly workflow that simultaneously provided the species identification, serotype, and antimicrobial resistance genes. The new method was thoroughly evaluated against a culture-based approach, using smoked salmon inoculated with L. monocytogenes as the matrix of choice. The sequencing method reached a very low limit of detection (LOD50, 1.2 CFU/ 25 g) along with high diagnostic sensitivity and specificity (100%), and a perfect correlation with the culture-based method (Cohen's k = 1.00). Overall, the proposed method overcomes all the major limitations reported for the implementation of NGS as a routine food testing technology and paves the way for future developments taking its advantage into consideration.

Subtyping Evaluation of Salmonella Enteritidis Using Single Nucleotide Polymorphism and Core Genome Multilocus Sequence Typing with Nanopore Reads

Whole-genome sequencing (WGS) for public health surveillance and epidemiological investigation of foodborne pathogens predominantly relies on sequencing platforms that generate short reads. Continuous improvement of long-read nanopore sequencing, such as Oxford nanopore technologies (ONT), presents a potential for leveraging multiple advantages of the technology in public health and food industry settings, including rapid turnaround and onsite applicability in addition to superior read length. Using an established cohort of Salmonella Enteritidis isolates for subtyping evaluation, we assessed the technical readiness of nanopore long read sequencing for single nucleotide polymorphism (SNP) analysis and core-genome multilocus sequence typing (cgMLST) of a major foodborne pathogen. By multiplexing three isolates per flow cell, we generated sufficient sequencing depths in <7 h of sequencing for robust subtyping. SNP calls by ONT and Illumina reads were highly concordant despite homopolymer errors in ONT reads (R9.4.1 chemistry). In silico correction of such errors allowed accurate allelic calling for cgMLST and allelic difference measurements to facilitate heuristic detection of outbreak isolates. IMPORTANCE Evaluation, standardization, and implementation of the ONT approach to WGS-based, strain-level subtyping is challenging, in part due to its relatively high base-calling error rates and frequent iterations of sequencing chemistry and bioinformatic analytics. Our study established a baseline for the continuously evolving nanopore technology as a viable solution to high-quality subtyping of Salmonella, delivering comparable subtyping performance when used standalone or together with short-read platforms. This study paves the way for evaluating and optimizing the logistics of implementing the ONT approach for foodborne pathogen surveillance in specific settings.

Heavy Rainfall, Sewer Overflows, and Salmonellosis in Black Skimmers (Rynchops niger)

Extreme weather events, particularly heavy rainfall, are occurring at greater frequency with climate change. Although adverse human health effects from heavy rainfall are often publicized, impacts to free-ranging wildlife populations are less well known. We first summarize documented associations of heavy rainfall on wildlife health. We then report a novel investigation of a salmonellosis outbreak in a colony of black skimmers (Rynchops niger) in Florida, USA. During June-September 2016, heavy rainfall resulted in the discharge of millions of gallons of untreated wastewater into the Tampa Bay system, contaminating the water body, where adult skimmers foraged. At least 48 fledglings died, comprising 39% of the colony's nesting season's offspring. Of eight examined deceased birds from the colony, six had a systemic salmonellosis infection. Isolates were identified as Salmonella enterica serotype Typhimurium. Their pulsed-field gel electrophoresis patterns were identical to each other and matched those from several human Salmonella sp. infections. Differences among whole-genome sequences were negligible. These findings and the outbreak's epidemic curve suggest propagated transmission occurred within the colony. A multidisciplinary and One Health approach is recommended to mitigate any adverse effects of climate change-driven stochastic events, especially when they place already imperiled wildlife at further risk.

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

ABSTRACT

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

HIGHLIGHTS

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.

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.

Evaluating whole-genome sequencing quality metrics for enteric pathogen outbreaks

Background

Whole genome sequencing (WGS) has gained increasing importance in responses to enteric bacterial outbreaks. Common analysis procedures for WGS, single nucleotide polymorphisms (SNPs) and genome assembly, are highly dependent upon WGS data quality.

Methods

Raw, unprocessed WGS reads from Escherichia coli, Salmonella enterica, and Shigella sonnei outbreak clusters were characterized for four quality metrics: PHRED score, read length, library insert size, and ambiguous nucleotide composition. PHRED scores were strongly correlated with improved SNPs analysis results in E. coli and S. enterica clusters.

Results

Assembly quality showed only moderate correlations with PHRED scores and library insert size, and then only for Salmonella. To improve SNP analyses and assemblies, we compared seven read-healing pipelines to improve these four quality metrics and to see how well they improved SNP analysis and genome assembly. The most effective read healing pipelines for SNPs analysis incorporated quality-based trimming, fixed-width trimming, or both. The Lyve-SET SNPs pipeline showed a more marked improvement than the CFSAN SNP Pipeline, but the latter performed better on raw, unhealed reads. For genome assembly, SPAdes enabled significant improvements in healed E. coli reads only, while Skesa yielded no significant improvements on healed reads.

Conclusions

PHRED scores will continue to be a crucial quality metric albeit not of equal impact across all types of analyses for all enteric bacteria. While trimming-based read healing performed well for SNPs analyses, different read healing approaches are likely needed for genome assembly or other, emerging WGS analysis methodologies.

Agritourism and Kidding Season: A Large Outbreak of Human Shiga Toxin-Producing Escherichia coli O157 (STEC O157) Infections Linked to a Goat Dairy Farm-Connecticut, 2016

The objective of this study was to determine sources of Shiga toxin-producing Escherichia coli O157 (STEC O157) infection among visitors to Farm X and develop public health recommendations. A case-control study was conducted. Case-patients were defined as the first ill child (aged <18 years) in the household with laboratory-confirmed STEC O157, or physician-diagnosed hemolytic uremic syndrome with laboratory confirmation by serology, who visited Farm X in the 10 days prior to illness. Controls were selected from Farm X visitors aged <18 years, without symptoms during the same time period as case-patients. Environment and animal fecal samples collected from Farm X were cultured; isolates from Farm X were compared with patient isolates using whole genome sequencing (WGS). Case-patients were more likely than controls to have sat on hay bales at the doe barn (adjusted odds ratio: 4.55; 95% confidence interval: 1.41–16.13). No handwashing stations were available; limited hand sanitizer was provided. Overall, 37% (29 of 78) of animal and environmental samples collected were positive for STEC; of these, 62% (18 of 29) yielded STEC O157 highly related by WGS to patient isolates. STEC O157 environmental contamination and fecal shedding by goats at Farm X was extensive. Farms should provide handwashing stations with soap, running water, and disposable towels. Access to animal areas, including animal pens and enclosures, should be limited for young children who are at risk for severe outcomes from STEC O157 infection. National recommendations should be adopted to reduce disease transmission.

Evaluation of whole-genome sequencing-based subtyping methods for the surveillance of Shigella spp. and the confounding effect of mobile genetic elements in long-term outbreaks

Many public health laboratories across the world have implemented whole-genome sequencing (WGS) for the surveillance and outbreak detection of foodborne pathogens. PulseNet-affiliated laboratories have determined that most single-strain foodborne outbreaks are contained within 0–10 multi-locus sequence typing (MLST)-based allele differences and/or core genome single-nucleotide variants (SNVs). In addition to being a food- and travel-associated outbreak pathogen, most Shigella spp. cases occur through continuous person-to-person transmission, predominantly involving men who have sex with men (MSM), leading to long-term and recurrent outbreaks. Continuous transmission patterns coupled to genetic evolution under antibiotic treatment pressure require an assessment of existing WGS-based subtyping methods and interpretation criteria for cluster inclusion/exclusion. An evaluation of 4 WGS-based subtyping methods [SNVPhyl, coreMLST, core genome MLST (cgMLST) and whole-genome MLST (wgMLST)] was performed on 9 foodborne-, travel- and MSM-related retrospective outbreaks from a collection of 91 Shigella flexneri and 232  Shigella sonnei isolates to determine the methods’ epidemiological concordance, discriminatory power, robustness and ability to generate stable interpretation criteria. The discriminatory powers were ranked as follows: coreMLST<SNVPhyl<cgMLST<wgMLST (range: 0.970–1.000). The genetic differences observed for non-MSM-related Shigella spp. outbreaks respect the standard 0–10 allele/SNV guideline; however, mobile genetic element (MGE)-encoded loci caused inflated genetic variation and discrepant phylogenies for prolonged MSM-related S. sonnei outbreaks via wgMLST. The S. sonnei correlation coefficients of wgMLST were also the lowest at 0.680, 0.703 and 0.712 for SNVPhyl, coreMLST and cgMLST, respectively. Plasmid maintenance, mobilization and conjugation-associated genes were found to be the main source of genetic distance inflation in addition to prophage-related genes. Duplicated alleles arising from the repeated nature of IS elements were also responsible for many false cg/wgMLST differences. The coreMLST approach was shown to be the most robust, followed by SNVPhyl and wgMLST for inter-laboratory comparability. Our results highlight the need for validating species-specific subtyping methods based on microbial genome plasticity and outbreak dynamics in addition to the importance of filtering confounding MGEs for cluster detection.

Genome-Enabled Molecular Subtyping and Serotyping for Shiga Toxin-Producing Escherichia coli

Foodborne pathogens are a major public health burden in the United States, leading to 9.4 million illnesses annually. Since 1996, a national laboratory-based surveillance program, PulseNet, has used molecular subtyping and serotyping methods with the aim to reduce the burden of foodborne illness through early detection of emerging outbreaks. PulseNet affiliated laboratories have used pulsed-field gel electrophoresis (PFGE) and immunoassays to subtype and serotype bacterial isolates. Widespread use of serotyping and PFGE for foodborne illness surveillance over the years has resulted in the accumulation of a wealth of routine surveillance and outbreak epidemiological data. This valuable source of data has been used to understand seasonal frequency, geographic distribution, demographic information, exposure information, disease severity, and source of foodborne isolates. In 2019, PulseNet adopted whole genome sequencing (WGS) at a national scale to replace PFGE with higher-resolution methods such as the core genome multilocus sequence typing. Consequently, PulseNet's recent shift to genome-based subtyping methods has rendered the vast collection of historic surveillance data associated with serogroups and PFGE patterns potentially unusable. The goal of this study was to develop a bioinformatics method to associate the WGS data that are currently used by PulseNet for bacterial pathogen subtyping to previously characterized serogroup and PFGE patterns. Previous efforts to associate WGS to PFGE patterns relied on predicting DNA molecular weight based on restriction site analysis. However, these approaches failed owing to the non-uniform usage of genomic restriction sites by PFGE restriction enzymes. We developed a machine learning approach to classify isolates to their most probable serogroup and PFGE pattern, based on comparisons of genomic k-mer signatures. We applied our WGS classification method to 5,970 Shiga toxin-producing Escherichia coli (STEC) isolates collected as part of PulseNet's routine foodborne surveillance activities between 2003 and 2018. Our machine learning classifier is able to associate STEC WGS to higher-level serogroups with very high accuracy and lower-level PFGE patterns with somewhat lower accuracy. Taken together, these classifications support the ability of public health investigators to associate currently generated WGS data with historical epidemiological knowledge linked to serogroups and PFGE patterns in support of outbreak surveillance for food safety and public health.

Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel

Hierarchical genotyping approaches can provide insights into the source, geography and temporal distribution of bacterial pathogens. Multiple hierarchical SNP genotyping schemes have previously been developed so that new isolates can rapidly be placed within pre-computed population structures, without the need to rebuild phylogenetic trees for the entire dataset. This classification approach has, however, seen limited uptake in routine public health settings due to analytical complexity and the lack of standardized tools that provide clear and easy ways to interpret results. The BioHansel tool was developed to provide an organism-agnostic tool for hierarchical SNP-based genotyping. The tool identifies split k-mers that distinguish predefined lineages in whole genome sequencing (WGS) data using SNP-based genotyping schemes. BioHansel uses the Aho-Corasick algorithm to type isolates from assembled genomes or raw read sequence data in a matter of seconds, with limited computational resources. This makes BioHansel ideal for use by public health agencies that rely on WGS methods for surveillance of bacterial pathogens. Genotyping results are evaluated using a quality assurance module which identifies problematic samples, such as low-quality or contaminated datasets. Using existing hierarchical SNP schemes for Mycobacterium tuberculosis and Salmonella Typhi, we compare the genotyping results obtained with the k-mer-based tools BioHansel and SKA, with those of the organism-specific tools TBProfiler and genotyphi, which use gold-standard reference-mapping approaches. We show that the genotyping results are fully concordant across these different methods, and that the k-mer-based tools are significantly faster. We also test the ability of the BioHansel quality assurance module to detect intra-lineage contamination and demonstrate that it is effective, even in populations with low genetic diversity. We demonstrate the scalability of the tool using a dataset of ~8100 S. Typhi public genomes and provide the aggregated results of geographical distributions as part of the tool’s output. BioHansel is an open source Python 3 application available on PyPI and Conda repositories and as a Galaxy tool from the public Galaxy Toolshed. In a public health context, BioHansel enables rapid and high-resolution classification of bacterial pathogens with low genetic diversity.

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.

MRSA strains with distinct accessory genes predominate at different ages in cystic fibrosis

RATIONALE

Methicillin resistant Staphylococcus aureus (MRSA) is prevalent and consequential in cystic fibrosis (CF). Whole genome sequencing (WGS) could reveal genomic differences in MRSA associated with poorer outcomes or detect MRSA transmission.

OBJECTIVES

To identify MRSA genes associated with low lung function and potential MRSA transmission in CF.

METHODS

We collected 97 MRSA isolates from 74 individuals with CF from 2017 and performed short-read WGS. We determined sequence type (ST) and the phylogenetic relationship between isolates. We aligned accessory genes from 25 reference genomes to genome assemblies, classified isolates by accessory gene content, and correlated the accessory genome to clinical outcomes.

RESULTS

The most prevalent ST were ST5 (N = 55), ST8 (N = 15), and ST105 (N = 14). Closely related MRSA strains were shared by family members with CF, but rarely between unrelated individuals. Three clusters of MRSA were identified by accessory genome content. Cluster A, including ST5 and ST105, was highly prevalent at all ages. Cluster B, including ST8, was more limited to younger patients. Cluster C included 6 distantly related strains. Patients 20 years old and younger infected with Cluster A had lower forced expiratory volume in the first second (FEV₁ ) and higher sputum biomass compared to similar-aged patients with Cluster B.

CONCLUSIONS

In this CF cohort, we identified MRSA subtypes that predominate at different ages and differ by accessory gene content. The most prevalent cluster of MRSA, including ST5 and ST105, was associated with lower FEV₁ . ST8 MRSA was more common in younger patients and thus has the potential to rise in prevalence as these patients age.

Mobile Elements Harboring Heavy Metal and Bacitracin Resistance Genes Are Common among Listeria monocytogenes Strains Persisting on Dairy Farms

Listeria monocytogenes is a foodborne pathogen and a resilient environmental saprophyte. Dairy farms are a reservoir of L. monocytogenes, and strains can persist on farms for years. Here, we sequenced the genomes of 250 L. monocytogenes isolates to investigate the persistence and mobile genetic elements (MGEs) of Listeria strains inhabiting dairy farms. We performed a single-nucleotide polymorphism (SNP)-based phylogenomic analysis to identify 14 monophyletic clades of L. monocytogenes persistent on the farms for ≥6 months. We found that prophages and other mobile genetic elements were, on average, more numerous among isolates in persistent than nonpersistent clades, and we demonstrated that resistance genes against bacitracin, arsenic, and cadmium were significantly more prevalent among isolates in persistent than nonpersistent clades. We identified a diversity of mobile elements among the 250 farm isolates, including three novel plasmids, three novel transposons, and a novel prophage harboring cadmium resistance genes. Several of the mobile elements we identified in Listeria were identical to the mobile elements of enterococci, which is indicative of recent transfer between these genera. Through a genome-wide association study, we discovered that three putative defense systems against invading prophages and plasmids were negatively associated with persistence on farms. Our findings suggest that mobile elements support the persistence of L. monocytogenes on dairy farms and that L. monocytogenes inhabiting the agroecosystem is a potential reservoir of mobile elements that may spread to the food industry. IMPORTANCE Animal-derived raw materials are an important source of L. monocytogenes in the food industry. Knowledge of the factors contributing to the pathogen's transmission and persistence on farms is essential for designing effective strategies against the spread of the pathogen from farm to fork. An increasing body of evidence suggests that mobile genetic elements support the adaptation and persistence of L. monocytogenes in the food industry, as these elements contribute to the dissemination of genes encoding favorable phenotypes, such as resilience against biocides. Understanding of the role of farms as a potential reservoir of these elements is needed for managing the transmission of mobile elements across the food chain. Because L. monocytogenes coinhabits the farm ecosystem with a diversity of other bacterial species, it is important to assess the degree to which genetic elements are exchanged between Listeria and other species, as such exchanges may contribute to the rise of novel resistance phenotypes.

Clostridium botulinum Type B Isolated From a Wound Botulism Case Due to Injection Drug Use Resembles Other Local Strains Originating From Hawaii

Clostridium botulinum produces botulinum neurotoxin (BoNT), which can lead to death if untreated. In the United States, over 90% of wound botulism cases are associated with injection drug use of black tar heroin. We sought to determine the phylogenetic relatedness of C. botulinum isolated from an injection drug use wound botulism case and isolates from endogenous infant botulism cases in Hawaii. Nineteen C. botulinum type B isolates from Hawaii and one type B isolate from California were analyzed by whole-genome sequencing. The botulinum toxin gene (bont) subtype was determined using CLC Genomics Workbench, and the seven-gene multi-locus sequence type (MLST) was identified by querying PubMLST. Mashtree and pairwise average nucleotide identity were used to find nearest neighbors, and Lyve-SET approximated a phylogeny. Eighteen of the isolates harbored the bont/B5 gene: of those, 17 were classified as sequence type ST36 and one was classified as ST104. A single isolate from Hawaii harbored bont/B1 and was determined to belong to ST110, and the isolate from California harbored bont/B1 and belonged to ST30. A tree constructed with Lyve-SET showed a high degree of homology among all the Hawaiian C. botulinum isolates that harbor the bont/B5 gene. Our results indicate that the bont/B-expressing isolates recovered from Hawaii are closely related to each other, suggesting local contamination of the drug paraphernalia or the wound itself with spores rather than contamination of the drug at manufacture or during transport. These findings may assist in identifying interventions to decrease wound botulism among persons who inject drugs.

Genomic Characterization of Strains From a Cluster of Infant Botulism Type A in a Small Town in Colorado, United States

Three cases of infant botulism were reported in a small Colorado town between 1981 and 1984. The first two cases occurred in 1981, 6 months apart, and the third case occurred in 1984. Clostridium botulinum type A was isolated from stool of all three case patients and from environmental samples of the patient's homes. An epidemiological investigation and follow-up study were conducted from 1981 to 1986 and concluded the cases were likely related. In this study, we sought to determine whether the C. botulinum type A clinical isolates were related to each other and to isolates obtained from environmental samples. We performed whole genome sequencing (WGS) for 17 isolates associated with this potential cluster of infant botulism. Fifteen isolates were confirmed to be C. botulinum type A(B) and contained botulinum toxin gene subtypes A1 and B5 by WGS; these strains formed a monophyletic cluster in a phylogeny and were considered closely related to each other (0-18 high-quality single-nucleotide polymorphisms), but distinct from other C. botulinum type A(B) in Colorado and elsewhere in the United States. Results of our study suggest that the three infant botulism cases could have represented a cluster due to a C. botulinum type A(B) strain present in the environment.

A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

Multispecies Outbreak of Verona Integron-Encoded Metallo-ß-Lactamase-Producing Multidrug Resistant Bacteria Driven by a Promiscuous Incompatibility Group A/C2 Plasmid

BACKGROUND

Antibiotic resistance is often spread through bacterial populations via conjugative plasmids. However, plasmid transfer is not well recognized in clinical settings because of technical limitations, and health care-associated infections are usually caused by clonal transmission of a single pathogen. In 2015, multiple species of carbapenem-resistant Enterobacteriaceae (CRE), all producing a rare carbapenemase, were identified among patients in an intensive care unit. This observation suggested a large, previously unrecognized plasmid transmission chain and prompted our investigation.

METHODS

Electronic medical record reviews, infection control observations, and environmental sampling completed the epidemiologic outbreak investigation. A laboratory analysis, conducted on patient and environmental isolates, included long-read whole-genome sequencing to fully elucidate plasmid DNA structures. Bioinformatics analyses were applied to infer plasmid transmission chains and results were subsequently confirmed using plasmid conjugation experiments.

RESULTS

We identified 14 Verona integron-encoded metallo-ß-lactamase (VIM)-producing CRE in 12 patients, and 1 additional isolate was obtained from a patient room sink drain. Whole-genome sequencing identified the horizontal transfer of blaVIM-1, a rare carbapenem resistance mechanism in the United States, via a promiscuous incompatibility group A/C2 plasmid that spread among 5 bacterial species isolated from patients and the environment.

CONCLUSIONS

This investigation represents the largest known outbreak of VIM-producing CRE in the United States to date, which comprises numerous bacterial species and strains. We present evidence of in-hospital plasmid transmission, as well as environmental contamination. Our findings demonstrate the potential for 2 types of hospital-acquired infection outbreaks: those due to clonal expansion and those due to the spread of conjugative plasmids encoding antibiotic resistance across species.

Genomic diversity of Salmonella enterica isolated from papaya samples collected during multiple outbreaks in 2017

In 2017, the US Food and Drug Administration investigated the sources of multiple outbreaks of salmonellosis. Epidemiologic and traceback investigations identified Maradol papayas as the suspect vehicles. During the investigations, the genomes of 55 Salmonella enterica that were isolated from papaya samples were sequenced. Serovar assignments and phylogenetic analysis placed the 55 isolates into ten distinct groups, each representing a different serovar. Within-serovar SNP differences are generally between 0 and 20 SNPs, while the median between-serovar distance is 51 812 SNPs. We observed two groups with SNP distances between 21 and 100 SNPs. These relatively large within-serovar SNP distances may indicate that the isolates represent either diverse populations or multiple, genetically distinct subpopulations. Further inspection of these cases with traceback evidence allowed us to identify an 11th population. We observed that high levels of genomic diversity from individual firms is possible, with one firm yielding five of the ten serovars. Also, high levels of diversity are possible within small geographic regions, as five of the serovars were isolated from papayas that originated from farms located in Armería and Tecomán, Colima. In addition, we identified AMR genes that are present in three of the serovars studied here (aph(3')-lb, aph(6)-ld, tet(C), fosA7, and qnrB19) and we detected the presence of the plasmid IncHI2A among S. Urbana isolates.

Molecular Epidemiology of Salmonellosis in Florida, USA, 2017-2018

The state of Florida reports a high burden of non-typhoidal Salmonella enterica with approximately two times higher than the national incidence. We retrospectively analyzed the population structure and molecular epidemiology of 1,709 clinical isolates from 2017 and 2018. We found 115 different serotypes. Rarefaction suggested that the serotype richness did not differ between children under 2 years of age and older children and adults and, there are ~22 well-characterized dominant serotypes. There were distinct differences in dominant serotypes between Florida and the USA as a whole, even though S. Enteritidis and S. Newport were the dominant serotypes in Florida and nationally. S. Javiana, S. Sandiego, and S. IV 50:z4, z23:- occurred more frequently in Florida than nationally. Legacy Multi Locus Sequence Typing (MLST) was of limited use for differentiating clinical Salmonella isolates beyond the serotype level. We utilized core genome MLST (cgMLST) hierarchical clusters (HC) to identify potential outbreaks and compared them to outbreaks detected by Pulse Field Gel Electrophoresis (PFGE) surveillance for five dominant serotypes (Enteritidis, Newport, Javiana, Typhimurium, and Bareilly). Single nucleotide polymorphism (SNP) phylogenetic-analysis of cgMLST HC at allelic distance 5 or less (HC5) corroborated PFGE detected outbreaks and generated well-segregated SNP distance-based clades for all studied serotypes. We propose “combination approach” comprising “HC5 clustering,” as efficient tool to trigger Salmonella outbreak investigations, and “SNP-based analysis,” for higher resolution phylogeny to confirm an outbreak. We also applied this approach to identify case clusters, more distant in time and place than traditional outbreaks but may have been infected from a common source, comparing 176 Florida clinical isolates and 1,341 non-clinical isolates across USA, of most prevalent serotype Enteritidis collected during 2017–2018. Several clusters of closely related isolates (0–4 SNP apart) within HC5 clusters were detected and some included isolates from poultry from different states in the US, spanning time periods over 1 year. Two SNP-clusters within the same HC5 cluster included isolates with the same multidrug-resistant profile from both humans and poultry, supporting the epidemiological link. These clusters likely reflect the vertical transmission of Salmonella clones from higher levels in the breeding pyramid to production flocks.

Genetic changes are introduced by repeated exposure of Salmonella spiked in low water activity and high fat matrix to heat

WGS is used to define if isolates are "in" or "out" of an outbreak and/or microbial root cause investigation. No threshold of genetic differences is fixed and the conclusions on similarity between isolates are mainly based on the knowledge generated from previous outbreak investigations and reported mutation rates. Mutation rates in Salmonella when exposed to food processing conditions are lacking. Thus, in this study, the ability of heat and dry stress to cause genetic changes in two Salmonella serotypes frequently isolated from low moisture foods was investigated. S. enterica serovars S. Agona ATCC 51,957 and S. Mbandaka NCTC 7892 (ATCC 51,958) were repeatedly exposed to heat (90 °C for 5 min) in a low water activity and high fat matrix. No increased fitness of the strains was observed after 10 repeated heat treatments. However, genetic changes were introduced and the number of genetic differences increased with every heat treatment cycle. The genetic changes appeared randomly in the genome and were responsible for a population of diverse isolates with 0 to 28 allelic differences (0 to 38 SNPs) between them. This knowledge is key to interpret WGS results for source tracking investigations as part of a root cause analysis in a contamination event as isolates are exposed to stress conditions.

Rapid Open-Source SNP-Based Clustering Offers an Alternative to Core Genome MLST for Outbreak Tracing in a Hospital Setting

Traditional genotyping methods for infection control of antimicrobial-resistant bacteria in healthcare settings have been supplemented by whole-genome sequencing (WGS), often relying on a gene-based approach, e.g., core genome multilocus sequence typing (cgMLST), to cluster-related samples. In this study, we compared clusters of methicillin-resistant Staphylococcus aureus (MRSA) and Enterococcus faecium analyzed with the commercial cgMLST software Ridom SeqSphere+ and with an open-source single-nucleotide polymorphism (SNP)-based phylogenetic analysis pipeline (PAPABAC). A total of 5,655 MRSA and 2,572 E. faecium patient isolates, collected between 2013 and 2018, were processed. Clusters of 1,844 MRSA and 1,355 E. faecium isolates were compared to cgMLST results, and epidemiological data were included when available. The phylogenies inferred by the two different technologies were highly concordant, and the MRSA SNP tree re-captured known hospital-related outbreaks and epidemiologically linked samples. PAPABAC has the advantage over Ridom SeqSphere+ to generate stable, referable clusters without the need for sequence assembly, and it is a free-of-charge, open-source alternative to the commercial software.

Validation strategy of a bioinformatics whole genome sequencing workflow for Shiga toxin-producing Escherichia coli using a reference collection extensively characterized with conventional methods

Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast+, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a 'push-button' pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups.

Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme

Paenibacillus larvae causes the American foulbrood (AFB), a highly contagious and devastating disease of honeybees. Whole-genome sequencing (WGS) has been increasingly used in bacterial pathogen typing, but rarely applied to study the epidemiology of P. larvae. To this end, we used 125 P. larvae genomes representative of a species-wide diversity to construct a stable whole-genome multilocus sequence typing (wgMLST) scheme consisting of 5745 loci. A total of 51 P. larvae isolates originating from AFB outbreaks in Slovenia were used to assess the epidemiological applicability of the developed wgMLST scheme. In addition, wgMLST was compared with the core-genome MLST (cgMLST) and whole-genome single nucleotide polymorphism (wgSNP) analyses. All three approaches successfully identified clusters of outbreak-associated strains, which were clearly separated from the epidemiologically unlinked isolates. High levels of backward comparability of WGS-based analyses with conventional typing methods (ERIC-PCR and MLST) were revealed; however, both conventional methods lacked sufficient discriminatory power to separate the outbreak clusters. The developed wgMLST scheme provides an improved understanding of the intra- and inter-outbreak genetic diversity of P. larvae and represents an important progress in unraveling the genomic epidemiology of this important honeybee pathogen.

An Open-Source Program (Haplo-ST) for Whole-Genome Sequence Typing Shows Extensive Diversity among Listeria monocytogenes Isolates in Outdoor Environments and Poultry Processing Plants

A reliable and standardized classification of Listeria monocytogenes is important for accurate strain identification during outbreak investigations. Current whole-genome sequencing (WGS)-based approaches for strain characterization are either difficult to standardize, rendering them less suitable for data exchange, or are not freely available. Thus, we developed a portable and open-source tool, Haplo-ST, to improve standardization and provide maximum discriminatory potential to WGS data tied to a multilocus sequence typing (MLST) framework. Haplo-ST performs whole-genome MLST (wgMLST) for L. monocytogenes while allowing for data exchangeability worldwide. This tool takes in (i) raw WGS reads as input, (ii) cleans the raw data according to user-specified parameters, (iii) assembles genes across loci by mapping to genes from reference strains, and (iv) assigns allelic profiles to assembled genes and provides a wgMLST subtyping for each isolate. Data exchangeability relies on the tool assigning allelic profiles based on a centralized nomenclature defined by the widely used BIGSdb-Lm database. Tests of Haplo-ST's performance with simulated reads from L. monocytogenes reference strains demonstrated high sensitivity (97.5%), and coverage depths of ≥20× were found to be sufficient for wgMLST profiling. We then used Haplo-ST to characterize and differentiate between two groups of L. monocytogenes isolates derived from the natural environment and poultry processing plants. Phylogenetic reconstruction identified lineages within each group, and no lineage specificity was observed with isolate phenotypes (transient versus persistent) or origins. Genetic differentiation analyses between isolate groups identified 21 significantly differentiated loci, potentially enriched for adaptation and persistence of L. monocytogenes within poultry processing plants.IMPORTANCE We have developed an open-source tool (https://github.com/swarnalilouha/Haplo-ST) that provides allele-based subtyping of L. monocytogenes isolates at the whole-genome level. Along with allelic profiles, this tool also generates allele sequences and identifies paralogs, which is useful for phylogenetic tree reconstruction and deciphering relationships between closely related isolates. More broadly, Haplo-ST is flexible and can be adapted to characterize the genome of any haploid organism simply by installing an organism-specific gene database. Haplo-ST also allows for scalable subtyping of isolates; fewer reference genes can be used for low-resolution typing, whereas higher resolution can be achieved by increasing the number of genes used in the analysis. Our tool enabled clustering of L. monocytogenes isolates into lineages and detection of potential loci for adaptation and persistence in food processing environments. Findings from these analyses highlight the effectiveness of Haplo-ST in subtyping and evaluating relationships among isolates in studies of bacterial population genetics.

Genomic characterization and phylogenetic analysis of Salmonella enterica serovar Javiana

Salmonella enterica serovar Javiana is the fourth most reported serovar of laboratory-confirmed human Salmonella infections in the U.S. and in Tennessee (TN). Although Salmonella ser. Javiana is a common cause of human infection, the majority of cases are sporadic in nature rather than outbreak-associated. To better understand Salmonella ser. Javiana microbial population structure in TN, we completed a phylogenetic analysis of 111 Salmonella ser. Javiana clinical isolates from TN collected from Jan. 2017 to Oct. 2018. We identified mobile genetic elements and genes known to confer antibiotic resistance present in the isolates, and performed a pan-genome-wide association study (pan-GWAS) to compare gene content between clades identified in this study. The population structure of TN Salmonella ser. Javiana clinical isolates consisted of three genetic clades: TN clade I (n = 54), TN clade II (n = 4), and TN clade III (n = 48). Using a 5, 10, and 25 hqSNP distance threshold for cluster identification, nine, 12, and 10 potential epidemiologically-relevant clusters were identified, respectively. The majority of genes that were found to be over-represented in specific clades were located in mobile genetic element (MGE) regions, including genes encoding integrases and phage structures (91.5%). Additionally, a large portion of the over-represented genes from TN clade II (44.9%) were located on an 87.5 kb plasmid containing genes encoding a toxin/antitoxin system (ccdAB). Additionally, we completed phylogenetic analyses of global Salmonella ser. Javiana datasets to gain a broader insight into the population structure of this serovar. We found that the global phylogeny consisted of three major clades (one of which all of the TN isolates belonged to) and two cgMLST eBurstGroups (ceBGs) and that the branch length between the two Salmonella ser. Javiana ceBGs (1,423 allelic differences) was comparable to those from other serovars that have been reported as polyphyletic (929–2,850 allelic differences). This study demonstrates the population structure of TN and global Salmonella ser. Javiana isolates, a clinically important Salmonella serovar and can provide guidance for phylogenetic cluster analyses for public health surveillance and response.