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

The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic

The One Health approach, recognizing the interconnectedness of human, animal, and environmental health, has gained significance amid emerging zoonotic diseases and antibiotic resistance concerns. This paper aims to demonstrate the utility of a collaborative tool, the SIEGA, for monitoring infectious diseases across domains, fostering a comprehensive understanding of disease dynamics and risk factors, highlighting the pivotal role of One Health surveillance systems. Raw whole-genome sequencing is processed through different species-specific open software that additionally reports the presence of genes associated to anti-microbial resistances and virulence. The SIEGA application is a Laboratory Information Management System, that allows customizing reports, detect transmission chains, and promptly alert on alarming genetic similarities. The SIEGA initiative has successfully accumulated a comprehensive collection of more than 1900 bacterial genomes, including Salmonella enterica, Listeria monocytogenes, Campylobacter jejuni, Escherichia coli, Yersinia enterocolitica and Legionella pneumophila, showcasing its potential in monitoring pathogen transmission, resistance patterns, and virulence factors. SIEGA enables customizable reports and prompt detection of transmission chains, highlighting its contribution to enhancing vigilance and response capabilities. Here we show the potential of genomics in One Health surveillance when supported by an appropriate bioinformatic tool. By facilitating precise disease control strategies and antimicrobial resistance management, SIEGA enhances global health security and reduces the burden of infectious diseases. The integration of health data from humans, animals, and the environment, coupled with advanced genomics, underscores the importance of a holistic One Health approach in mitigating health threats.

Overcoming Microbial Inhibition of S. Sonnei Through the Exploitation of Genomically Predicted Antibiotic Resistance Profiles for the Development of Food Enrichment Media

Linking outbreaks of Shigella spp. to specific foods is challenging due to poor selectivity of current enrichment media. We have previously shown that enrichment media, tailored to the genomically-predicted antimicrobial resistance (AMR) of Shiga toxigenic E. coli strains, enhances their isolation from foods. This study investigates the application of this approach for Shigella isolation. The AMR gene profiles of 21,908 published S. sonnei genomes indicated a high prevalence of genes conferring resistance to streptomycin (aadA, aph(3″)-Ib, aph(6)-Id, 92.8%), sulfonamides (sul1, sul2, 74.8%), and/or trimethoprim (dfrA, 96.2%). Genomic analysis and antibiotic susceptibility testing conducted with a panel of 17 outbreak-associated S. sonnei strains confirmed the correlation of AMR gene detection with resistance phenotypes. Supplementation of Shigella Broth (SB) with up to 400 µg/mL of trimethoprim or sulfadiazine did not suppress the growth of sensitive strains, whereas 100 µg/mL of streptomycin increased the selectivity of this broth. All three antibiotics increased the selectivity of modified Tryptone Soya Broth (mTSB). Based on these results, supplemented media formulations were developed and assessed by measuring the relative growth of S. sonnei in cultures coinoculated with a strain of bacteriocin-producing E. coli that is inhibitory to Shigella growth. S. sonnei was not recovered from cocultures grown in SB or mTSB without antibiotics. In contrast, media supplemented with streptomycin at 50 and 100 µg/mL, trimethoprim at 25 and 50 µg/mL, and sulfadiazine at 100 µg/mL increased the relative proportion of S. sonnei in postenrichment cultures. The enhanced recovery of resistant S. sonnei strains achieved in this study indicates that, in cases where genomic data are available for clinical S. sonnei isolates, customization of selective enrichment media based on AMR gene detection could be a valuable tool for supporting the investigation of foodborne shigellosis outbreaks.

Strain-specific Recovery of S. sonnei from Artificially Contaminated Baby Carrots: Enhancing Food-safety Investigations with a Customized Shigella Detection Method Based on Genomically predicted Antibiotic Resistance Traits

Shigella spp. are Gram-negative gastrointestinal bacterial pathogens that cause bacillary dysentery or shigellosis in humans. Isolation of Shigella from outbreak-associated foods is often problematic due to the lack of selectivity of cultural enrichment broths. To facilitate Shigella recovery from foods, we have developed strain-specific enrichment media based on the genomically-predicted antimicrobial resistance (AMR) features of an outbreak-associated Shigella sonnei strain harboring resistance genes for streptomycin (STR) and trimethoprim (TMP). To assess performance of the method, baby carrots were artificially contaminated with the S. sonnei strain at low (2.4 CFU), medium (23.5 CFU), and high levels (235 CFU) along with 10-fold higher levels of a Shigella-inhibiting Escherichia coli strain. The target S. sonnei strain was successfully recovered from artificially-contaminated baby carrots when enriched in modified Tryptone Soya Broth (mTSB) supplemented with TMP, whereas Shigella was not recovered from Shigella broth (SB) or SB supplemented with STR. Quantitative PCR analysis indicated that supplementation of the enrichment broths with TMP or STR increased the relative proportion of S. sonnei in enrichment cultures, except at the lowest inoculation level for STR. Microbiome profiling of the baby carrot enrichment cultures conducted by 16S rRNA gene sequencing indicated that both SB-STR and mTSB-TMP repressed the growth of competing Enterobacteriaceae in the enrichment cultures, relative to SB without supplementation. Overall, improved Shigella recovery was achieved with the addition of the appropriate custom selective agent during cultural enrichments demonstrating that genomically informed custom selective enrichment of Shigella could be a valuable tool for supporting future foodborne shigellosis outbreak investigations.

An outbreak of Salmonella Infantis linked to shredded pork products from an unlicensed source in multiple health districts, Ontario, Canada, 2021

Background

An outbreak of Salmonella Infantis was associated with the consumption of shredded pork products at multiple restaurants in Ontario between July 2021 and October 2021. The outbreak involved 36 case-patients from six public health units. The implicated shredded pork products were obtained from an unlicensed source. This is the largest reported outbreak of Salmonella Infantis linked to restaurant food exposures in Ontario, with complexities related to the investigation of unlicensed foods. This article aims to describe the epidemiological, food safety and laboratory investigations that led to the identification and removal of the source of the outbreak from implicated restaurants, including the challenges encountered while investigating an outbreak related to an unlicensed source of food.

Methods

Epidemiological and laboratory analyses were conducted to identify the source of the outbreak. Food safety investigations were conducted to ascertain the origin and distribution of the implicated food.

Results

Whole-genome sequencing identified the outbreak strain from the isolates of 36 case-patients across six public health units in Ontario. Seven case-patients (19%) were hospitalized. No deaths were reported. The outbreak was linked to shredded pork products (i.e., rinds or skins) that were distributed by an unlicensed meat processor and consumed at various restaurants that served Southeast Asian fusion cuisine concentrated in the Greater Toronto Area. The product was removed from implicated restaurants.

Conclusion

Historically, foods from unlicensed sources have been implicated in multiple large outbreaks and continue to be of significant public health risk. The outbreak investigation emphasized the threat of food from unlicensed sources to the public's health and the importance of additional public health interventions to prevent outbreaks linked to unlicensed sources.

Genomic insights of Salmonella isolated from dry fermented sausage production chains in Spain and France

The presence of Salmonella in dry fermented sausages is source of recalls and outbreaks. The genomic diversity of 173 Salmonella isolates from the dry fermented sausage production chains (pig carcasses, pork, and sausages) from France and Spain were investigated through their core phylogenomic relationships and accessory genome profiles. Ten different serovars and thirteen sequence type profiles were identified. The most frequent serovar from sausages was the monophasic variant of S. Typhimurium (1,4,[5],12:i:-, 72%) while S. Derby was in pig carcasses (51%). Phylogenomic clusters found in S. 1,4,[5],12:i:-, S. Derby, S. Rissen and S. Typhimurium serovars identified closely related isolates, with less than 10 alleles and 20 SNPs of difference, displaying Salmonella persistence along the pork production chain. Most of the S. 1,4,[5],12:i:- contained the Salmonella genomic island-4 (SGI-4), Tn21 and IncFIB plasmid. More than half of S. Derby strains contained the SGI-1 and Tn7. S. 1,4,[5],12:i:- genomes carried the most multidrug resistance genes (91% of the strains), whereas extended-spectrum β-lactamase genes were found in Typhimurium and Derby serovars. Salmonella monitoring and characterization in the pork production chains, specially S. 1,4,[5],12:i:- serovar, is of special importance due to its multidrug resistance capacity and persistence in dry fermented sausages.

Toward Characterizing Environmental Sources of Non-tuberculous Mycobacteria (NTM) at the Species Level: A Tutorial Review of NTM Phylogeny and Phylogenetic Classification

Nontuberculous mycobacteria (NTM) are any mycobacteria that do not cause tuberculosis or leprosy. While the majority of NTM are harmless and some of them are considered probiotic, a growing number of people are being diagnosed with NTM infections. Therefore, their detection in the environment is of interest to clinicians, environmental microbiologists, and water quality researchers alike. This review provides a tutorial on the foundational approaches for taxonomic classifications, with a focus on the phylogenetic relationships among NTM revealed by the 16S rRNA gene, rpoB gene, and hsp65 gene, and by genome-based approaches. Recent updates on the Mycobacterium genus taxonomy are also provided. A synthesis on the habitats of 189 mycobacterial species in a genome-based taxonomy framework was performed, with attention paid to environmental sources (e.g., drinking water, aquatic environments, and soil). The 16S rRNA gene-based classification accuracy for various regions was evaluated (V3, V3-V4, V3-V5, V4, V4-V5, and V1-V9), revealing overall excellent genus-level classification (up to 100% accuracy) yet only modest performance (up to 63.5% accuracy) at the species level. Future research quantifying NTM species in water systems, determining the effects of water treatment and plumbing conditions on their variations, developing high throughput species-level characterization tools for use in the environment, and incorporating the characterization of functions in a phylogenetic framework will likely fill critical knowledge gaps. We believe this tutorial will be useful for researchers new to the field of molecular or genome-based taxonomic profiling of environmental microbiomes. Experts may also find this review useful in terms of the selected key findings of the past 30 years, recent updates on phylogenomic analyses, as well as a synthesis of the ecology of NTM in a phylogenetic framework.

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

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

IMPORTANCE

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

Whole genome enrichment approach for genomic surveillance of Toxoplasma gondii

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

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

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

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.

Escherichia coli O157:H7 tir 255 T > A allele strains differ in chromosomal and plasmid composition

Shiga toxin-producing Escherichia coli (STEC) O157:H7 strains with the T allele in the translocated intimin receptor polymorphism (tir) 255 A > T gene associate with human disease more than strains with an A allele; however, the allele is not thought to be the direct cause of this difference. We sequenced a diverse set of STEC O157:H7 strains (26% A allele, 74% T allele) to identify linked differences that might underlie disease association. The average chromosome and pO157 plasmid size and gene content were significantly greater within the tir 255 A allele strains. Eighteen coding sequences were unique to tir 255 A allele chromosomes, and three were unique to tir 255 T allele chromosomes. There also were non-pO157 plasmids that were unique to each tir 255 allele variant. The overall average number of prophages did not differ between tir 255 allele strains; however, there were different types between the strains. Genomic and mobile element variation linked to the tir 255 polymorphism may account for the increased frequency of the T allele isolates in human disease.

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

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

Whole genome sequencing-based identification of human tuberculosis caused by animal-lineage Mycobacterium orygis

A recently described member of the Mycobacterium tuberculosis complex (MTBC) is Mycobacterium orygis, which can cause disease primarily in animals but also in humans. Although M. orygis has been reported from different geographic regions around the world, due to a lack of proper identification techniques, the contribution of this emerging pathogen to the global burden of zoonotic tuberculosis is not fully understood. In the present work, we report single nucleotide polymorphism (SNP) analysis using whole genome sequencing (WGS) that can accurately identify M. orygis and differentiate it from other members of the MTBC species. WGS-based SNP analysis was performed for 61 isolates from different provinces in Canada that were identified as M. orygis. A total of 56 M. orygis sequences from the public databases were also included in the analysis. Several unique SNPs in the gyrB, PPE55, Rv2042c, leuS, mmpL6, and mmpS6 genes were used to determine their effectiveness as genetic markers for the identification of M. orygis. To the best of our knowledge, five of these SNPs, viz., gyrB 277 (A→G), gyrB 1478 (T→C), leuS 1064 (A→T), mmpL6 486 (T→C), and mmpS6 334 (C→G), are reported for the first time in this study. Our results also revealed several SNPs specific to other species within MTBC. The phylogenetic analysis shows that the studied genomes were genetically diverse and clustered with M. orygis sequences of human and animal origin reported from different geographic locations. Therefore, the present study provides a new insight into the high-confidence identification of M. orygis from MTBC species based on WGS data, which can be useful for reference and diagnostic laboratories.

Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review

Whole-genome sequencing (WGS) has resulted in improvements to pathogen characterisation for the rapid investigation and management of disease outbreaks and surveillance. We conducted a systematic review to synthesise the economic evidence of WGS implementation for pathogen identification and surveillance. Of the 2285 unique publications identified through online database searches, 19 studies met the inclusion criteria. The economic evidence to support the broader application of WGS as a front-line pathogen characterisation and surveillance tool is insufficient and of low quality. WGS has been evaluated in various clinical settings, but these evaluations are predominantly investigations of a single pathogen. There are also considerable variations in the evaluation approach. Economic evaluations of costs, effectiveness, and cost-effectiveness are needed to support the implementation of WGS in public health settings.

Whole-genome sequencing-based analysis of antimicrobial resistance, virulence factors, and genetic diversity in Yersinia isolated in Wenzhou, China 2020

Yersinia spp. vary significantly in their ability to cause diseases that threaten public health. Their pathogenicity is frequently associated with increasing antimicrobial resistance (AMR) and various virulence factors. The aim of the study was to investigate the AMR genes, virulence factors, and genetic diversity of Yersinia strains isolated from meats and fish in Wenzhou in 2020 by using whole-genome sequencing (WGS). A total of 50 isolates were collected. The phylogenetic relationships among the Yersinia species were also analyzed using multilocus sequence typing (MLST), core genome multi-locus sequence typing (cgMLST), and single nucleotide polymorphism (SNP) analysis. According to the results, all the strains could be classified into five species, with most isolated from beef, followed by poultry, pork, and fish. AMR genes were identified in 23 strains. And the qnrD1 genes were all located in the Col3M plasmid. Virulence genes, such as yaxA, ystB, pla, and yplA, were also found in the 15 Y. enterocolitica strains. And this study also found the presence of icm/dot type IVB-related genes in one Yersinia massiliensis isolate. MLST analysis identified 43 sequence types (STs), 19 of which were newly detected in Yersinia. Moreover, cgMLST analysis revealed that no dense genotype clusters were formed (cgMLST 5341, 5344, 5346-5350, 5353-5390). Instead, the strains appeared to be dispersed over large distances, except when multiple isolates shared the same ST. Isolates Y4 and Y26 were closely related to strains originating from South Korea and Denmark. This study showed considerable diversity in Yersinia spp. isolated from local areas (Wenzhou City). The data generated in our study may enrich the molecular traceability database of Yersinia and provide a basis for the development of more effective antipathogen control strategies.

A hybridization target enrichment approach for pathogen genomics

IMPORTANCE

Emerging infectious diseases require continuous pathogen monitoring. Rapid clinical diagnosis by nucleic acid amplification is limited to a small number of targets and may miss target detection due to new mutations in clinical isolates. Whole-genome sequencing (WGS) identifies genome-wide variations that may be used to determine a pathogen's drug resistance patterns and phylogenetically characterize isolates to track disease origin and transmission. WGS is typically performed using DNA isolated from cultured clinical isolates. Culturing clinical specimens increases turn-around time and may not be possible for fastidious bacteria. To overcome some of these limitations, direct sequencing of clinical specimens has been attempted using expensive capture probes to enrich the entire genomes of target pathogens. We present a method to produce a cost-effective, time-efficient, and large-scale synthesis of probes for whole-genome enrichment. We envision that our method can be used for direct clinical sequencing of a wide range of microbial pathogens for genomic epidemiology.

Salmonella Infection in Pigs: Disease, Prevalence, and a Link between Swine and Human Health

Salmonella is one of the most spread foodborne pathogens worldwide, and Salmonella infections in humans still represent a global health burden. The main source of Salmonella infections in humans is represented by contaminated animal-derived foodstuffs, with pork products being one of the most important players. Salmonella infection in swine is critical not only because it is one of the main causes of economic losses in the pork industry, but also because pigs can be infected by several Salmonella serovars, potentially contaminating the pig meat production chain and thus posing a significant threat to public health globally. As of now, in Europe and in the United States, swine-related Salmonella serovars, e.g., Salmonella Typhimurium and its monophasic variant Salmonella enterica subsp. enterica 1,4,[5],12:i:-, are also frequently associated with human salmonellosis cases. Moreover, multiple outbreaks have been reported in the last few decades which were triggered by the consumption of Salmonella-contaminated pig meat. Throughout the years, changes and evolution across the pork industry may have acted as triggers for new issues and obstacles hindering Salmonella control along the food chain. Gathered evidence reinforces the importance of coordinating control measures and harmonizing monitoring programs for the efficient control of Salmonella in swine. This is necessary in order to manage outbreaks of clinical disease in pigs and also to protect pork consumers by controlling Salmonella subclinical carriage and shedding. This review provides an update on Salmonella infection in pigs, with insights on Salmonella ecology, focusing mainly on Salmonella Choleraesuis, S. Typhimurium, and S. 1,4,[5],12:i:-, and their correlation to human salmonellosis cases. An update on surveillance methods for epidemiological purposes of Salmonella infection in pigs and humans, in a "One Health" approach, will also be reported.

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.

Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes

Background

The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000).

Methods

This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch.

Results

Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal 'sentinel' surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes.

Conclusions

The consortium's aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies.

Funding

No specific funding was awarded for this meta-analysis. Coordinators were supported by fellowships from the European Union (ZAD received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council (DJI is supported by an NHMRC Investigator Grant [GNT1195210]).

Genomic typing and virulence gene profile analysis of Salmonella Derby from different sources

Salmonella enterica serovar Derby (S. Derby) is one of the most common Salmonella serovars which can infect poultry, swine, and humans. With the reduction of the sequencing cost and the improvement of sequencing technology, whole genome sequencing (WGS) has become an important method for bacterial determination, molecular investigation, and pathogenic tracing analysis. In this study, we investigated S. Derby isolates from different sources in China using in-silico multilocus sequence typing (MLST), core genome MLST (cgMLST) and whole genome MLST (wgMLST) analysis based on WGS. The results showed that 21 S. Derby strains were divided into 3 STs using MLST analysis, including ST40 (n = 19, accounting for 90.48%), ST71 (n = 1, accounting for 4.76%) and ST8016 (n = 1, accounting for 4.76%). cgMLST and wgMLST analysis categorized the tested strains into 13 cgSTs and 21 wgSTs, respectively. The minimum spanning trees of cgMLST and wgMLST both divided these strains into 3 clusters and 4 singletons. In addition, virulence gene profiles of S. Derby isolates were also analyzed, and a total of 174 virulence genes belonged to 8 categories were identified. In summary, we studied genomic typing, phylogenetic relationship and virulence gene profiles of S. Derby strains from different sources in China. These findings were beneficial for the epidemiology and pathogenesis of Salmonella.

#AMRrounds: a systematic educational approach for navigating bench to bedside antimicrobial resistance

Antimicrobial resistance (AMR) continues to serve as a major global health crisis. Clinicians practising in this modern era are faced with ongoing challenges in the therapeutic management of patients suffering from antimicrobial-resistant infections. A strong educational understanding and synergistic application of clinical microbiology, infectious disease and pharmacological concepts can assist the adventuring clinician in the navigation of such cases. Important items include mobilizing laboratory testing for pathogen identification and susceptibility data, harnessing an understanding of intrinsic pathogen resistance, acknowledging epidemiological resistance trends, recognizing acquired AMR mechanisms, and consolidating these considerations when constructing an ideal pharmacological plan. In this article, we outline a novel framework by which to systematically approach clinical AMR, encourage AMR-related education and optimize therapeutic decision-making in AMR-related illnesses.

Towards a post-pandemic future for global pathogen genome sequencing

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

Alternate Antimicrobial Therapies and Their Companion Tests

New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with the emergence of resistance, resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies with clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers, and phages. Clinical diagnostics optimize the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic-based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious diseases include detection, monitoring of response, and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy, this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives with the use of alternate therapeutics, with a particular focus on companion diagnostic applications in infectious diseases.

ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data

BACKGROUND

Genomics-informed pathogen surveillance strengthens public health decision-making, playing an important role in infectious diseases' prevention and control. A pivotal outcome of genomics surveillance is the identification of pathogen genetic clusters and their characterization in terms of geotemporal spread or linkage to clinical and demographic data. This task often consists of the visual exploration of (large) phylogenetic trees and associated metadata, being time-consuming and difficult to reproduce.

RESULTS

We developed ReporTree, a flexible bioinformatics pipeline that allows diving into the complexity of pathogen diversity to rapidly identify genetic clusters at any (or all) distance threshold(s) or cluster stability regions and to generate surveillance-oriented reports based on the available metadata, such as timespan, geography, or vaccination/clinical status. ReporTree is able to maintain cluster nomenclature in subsequent analyses and to generate a nomenclature code combining cluster information at different hierarchical levels, thus facilitating the active surveillance of clusters of interest. By handling several input formats and clustering methods, ReporTree is applicable to multiple pathogens, constituting a flexible resource that can be smoothly deployed in routine surveillance bioinformatics workflows with negligible computational and time costs. This is demonstrated through a comprehensive benchmarking of (i) the cg/wgMLST workflow with large datasets of four foodborne bacterial pathogens and (ii) the alignment-based SNP workflow with a large dataset of Mycobacterium tuberculosis. To further validate this tool, we reproduced a previous large-scale study on Neisseria gonorrhoeae, demonstrating how ReporTree is able to rapidly identify the main species genogroups and characterize them with key surveillance metadata, such as antibiotic resistance data. By providing examples for SARS-CoV-2 and the foodborne bacterial pathogen Listeria monocytogenes, we show how this tool is currently a useful asset in genomics-informed routine surveillance and outbreak detection of a wide variety of species.

CONCLUSIONS

In summary, ReporTree is a pan-pathogen tool for automated and reproducible identification and characterization of genetic clusters that contributes to a sustainable and efficient public health genomics-informed pathogen surveillance. ReporTree is implemented in python 3.8 and is freely available at https://github.com/insapathogenomics/ReporTree .

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

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

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

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

Genomic Surveillance of Salmonella from the Comunitat Valenciana (Spain)

Salmonella enterica subspecies enterica is one of the most important foodborne pathogens and the causative agent of salmonellosis, which affects both humans and animals producing numerous infections every year. The study and understanding of its epidemiology are key to monitoring and controlling these bacteria. With the development of whole-genome sequencing (WGS) technologies, surveillance based on traditional serotyping and phenotypic tests of resistance is being replaced by genomic surveillance. To introduce WGS as a routine methodology for the surveillance of food-borne Salmonella in the region, we applied this technology to analyze a set of 141 S. enterica isolates obtained from various food sources between 2010 and 2017 in the Comunitat Valenciana (Spain). For this, we performed an evaluation of the most relevant Salmonella typing methods, serotyping and sequence typing, using both traditional and in silico approaches. We extended the use of WGS to detect antimicrobial resistance determinants and predicted minimum inhibitory concentrations (MICs). Finally, to understand possible contaminant sources in this region and their relationship to antimicrobial resistance (AMR), we performed cluster detection combining single-nucleotide polymorphism (SNP) pairwise distances and phylogenetic and epidemiological data. The results of in silico serotyping with WGS data were highly congruent with those of serological analyses (98.5% concordance). Multi-locus sequence typing (MLST) profiles obtained with WGS information were also highly congruent with the sequence type (ST) assignment based on Sanger sequencing (91.9% coincidence). In silico identification of antimicrobial resistance determinants and minimum inhibitory concentrations revealed a high number of resistance genes and possible resistant isolates. A combined phylogenetic and epidemiological analysis with complete genome sequences revealed relationships among isolates indicative of possible common sources for isolates with separate sampling in time and space that had not been detected from epidemiological information. As a result, we demonstrate the usefulness of WGS and in silico methods to obtain an improved characterization of S. enterica enterica isolates, allowing better surveillance of the pathogen in food products and in potential environmental and clinical samples of related interest.

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.

Adaptive Radioresistance of Enterohemorrhagic Escherichia coli O157:H7 Results in Genomic Loss of Shiga Toxin-Encoding Prophages

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 is a foodborne pathogen producing Shiga toxins (Stx1 and Stx2), which can cause hemorrhagic diarrhea and life-threatening infections. O157:H7 strain EDL933 carries prophages CP-933V and BP-933W, which encode Shiga toxin genes (stx1 and stx2, respectively). The aim of this work was to investigate the mechanisms of adaptive resistance of EHEC strain EDL933 to a typically lethal dose of gamma irradiation (1.5 kGy). Adaptive selection through six passages of exposure to 1.5 kGy resulted in the loss of CP-933V and BP-933W prophages from the genome and mutations within three genes: wrbA, rpoA, and Wt_02639 (molY). Three selected EHEC clones that became irradiation adapted to the 1.5-kGy dose (C1, C2, and C3) demonstrated increased resistance to oxidative stress, sensitivity to acid pH, and decreased cytotoxicity to Vero cells. To confirm that loss of prophages plays a role in increased radioresistance, clones C1 and C2 were exposed to bacteriophage-containing lysates. Although phage BP-933W could lysogenize C1, C2, and E. coli K-12 strain MG1655, it was not found to have integrated into the bacterial chromosome in C1-Φ and C2-Φ lysogens. Interestingly, for the E. coli K-12 lysogen (K-12-Φ), BP-933W DNA had integrated at the wrbA gene (K-12-Φ). Both C1-Φ and C2-Φ lysogens regained sensitivity to oxidative stress, were more effectively killed by a 1.5-kGy gamma irradiation dose, and had regained cytotoxicity and acid resistance phenotypes. Further, the K-12-Φ lysogen became cytotoxic, more sensitive to gamma irradiation and oxidative stress, and slightly more acid resistant. IMPORTANCE Gamma irradiation of food products can provide an effective means of eliminating bacterial pathogens such as enterohemorrhagic Escherichia coli (EHEC) O157:H7, a significant foodborne pathogen that can cause severe disease due to the production of Stx. To decipher the mechanisms of adaptive resistance of the O157:H7 strain EDL933, we evolved clones of this bacterium resistant to a lethal dose of gamma irradiation by repeatedly exposing bacterial cells to irradiation following a growth restoration over six successive passages. Our findings provide evidence that adaptive selection involved modifications in the bacterial genome, including deletion of the CP-933V and BP-933W prophages. These mutations in EHEC O157:H7 resulted in loss of stx1 and stx2, loss of cytotoxicity to epithelial cells, and decreased resistance to acidity, critical virulence determinants of EHEC, concomitant with increased resistance to lethal irradiation and oxidative stress. These findings demonstrate that the potential adaptation of EHEC to high doses of radiation would involve elimination of the Stx-encoding phages and likely lead to a substantial attenuation of virulence.

Phenotypic and genotypic characterization of antibiotic resistance of Salmonella Heidelberg in the south of Brazil

Salmonella is the main human pathogen present in the poultry chain. Salmonella Heidelberg is one of the most important serovars for public health since it has been frequently isolated in broiler chickens from different countries and may present multidrug resistance (MDR). This study was carried out with 130 S. Heidelberg isolates collected from pre-slaughter broiler farms in 2019 and 2020 in 18 cities from three Brazilian states to study relevant aspects regarding their genotypic and phenotypic resistance. The isolates were tested and identified using somatic and flagellar antiserum (0:4, H:2, and H:r), and an antimicrobial susceptibility test (AST) was performed against 11 antibiotics for veterinary use. The strains were typed by Enterobacterial Repetitive Intergenic Consensus (ERIC)-PCR, and representatives of the main clusters of the identified profiles were sequenced by Whole Genome Sequencing (WGS). AST results showed that all isolates were resistant to sulfonamide, 54 % (70/130) were resistant to amoxicillin, and only one was sensitive to tetracycline. Twelve isolates (15.4 %) were MDR. The dendrogram obtained from the ERIC-PCR showed that the strains were grouped into 27 clusters with similarity above 90 %, with some isolates showing 100 % similarity but with different phenotypic profiles of antimicrobial resistance. Identical strains collected on the same farm on other dates were identified, indicating that they were residents. WGS identified 66 antibiotic-resistance genes. The sul2 (present in all sequenced samples) and tet(A) genes were highlighted and validated in the experimental analysis. The fosA7 gene was also identified in all sequenced samples, but resistance was not observed in the phenotypic test, possibly due to the heteroresistance of the S. Heidelberg strains evaluated. Considering that chicken meat is one of the most consumed meats in the world, the data obtained in the present study can corroborate the mapping of the origin and trends of antimicrobial resistance.

Genome-based risk assessment for foodborne Salmonella enterica from food animals in China: A One Health perspective

Salmonella is one of the most common causes of foodborne bacterial disease. Animal-borne foods are considered the primary sources of Salmonella transmission to humans. However, genomic assessment of antimicrobial resistance (AMR) and virulence of Salmonella based on One Health approach remains obscure in China. For this reason, we analyzed the whole genome sequencing data of 134 Salmonella isolates recovered from different animal and meat samples in China. The 134 Salmonella were isolated from 2819 samples (4.75 %) representing various sources (pig, chicken, duck, goose, and meat) from five Chinese provinces (Zhejiang, Guangdong, Jiangxi, Hunan, and Qinghai). AMR was evaluated by the broth dilution method using 13 different antimicrobial agents, and results showed that 85.82 % (115/134) of isolates were resistant to three or more antimicrobial classes and were considered multidrug-resistant (MDR). Twelve sequence types (STs) were detected, with a dominance of ST469 (29.85 %, 40/134). The prediction of virulence genes showed the detection of cdtB gene encoding typhoid toxins in one isolate of S. Muenster recovered from chicken, while virulence genes associated with type III secretion systems were detected in all isolates. Furthermore, plasmid-type prediction showed the abundance of IncFII(S) (13/134; 9.7 %) and IncFIB(S) (12/134; 8.95 %) in the studied isolates. Together, this study demonstrated the ability to use whole-genome sequencing (WGS) as a cost-effective method to provide comprehensive knowledge about foodborne Salmonella isolates in One Health surveillance approach.

Whole-Genome Sequencing-Based Resistome Analysis of Nosocomial Multidrug-Resistant Non-Fermenting Gram-Negative Pathogens from the Balkans

Non-fermenting Gram-negative bacilli (NFGNB), such as Pseudomonas aeruginosa and Acinetobacter baumannii, are among the major opportunistic pathogens involved in the global antibiotic resistance epidemic. They are designated as urgent/serious threats by the Centers for Disease Control and Prevention and are part of the World Health Organization’s list of critical priority pathogens. Also, Stenotrophomonas maltophilia is increasingly recognized as an emerging cause for healthcare-associated infections in intensive care units, life-threatening diseases in immunocompromised patients, and severe pulmonary infections in cystic fibrosis and COVID-19 individuals. The last annual report of the ECDC showed drastic differences in the proportions of NFGNB with resistance towards key antibiotics in different European Union/European Economic Area countries. The data for the Balkans are of particular concern, indicating more than 80% and 30% of invasive Acinetobacter spp. and P. aeruginosa isolates, respectively, to be carbapenem-resistant. Moreover, multidrug-resistant and extensively drug-resistant S. maltophilia from the region have been recently reported. The current situation in the Balkans includes a migrant crisis and reshaping of the Schengen Area border. This results in collision of diverse human populations subjected to different protocols for antimicrobial stewardship and infection control. The present review article summarizes the findings of whole-genome sequencing-based resistome analyses of nosocomial multidrug-resistant NFGNBs in the Balkan countries.

Genomic surveillance: a potential shortcut for effective Chagas disease management

Chagas disease is an enduring public health issue in many Latin American countries, receiving insufficient investment in research and development. Strategies for disease control and management currently lack efficient pharmaceuticals, commercial diagnostic kits with improved sensitivity, and vaccines. Genetic heterogeneity of Trypanosoma cruzi is a key aspect for novel drug design since pharmacological technologies rely on the degree of conservation of parasite target proteins. Therefore, there is a need to expand the knowledge regarding parasite genetics which, if fulfilled, could leverage Chagas disease research and development, and improve disease control strategies. The growing capacity of whole-genome sequencing technology and its adoption as disease surveillance routine may be key for solving this long-lasting problem.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

Split k-mer analysis compared to cgMLST and SNP-based core genome analysis for detecting transmission of vancomycin-resistant enterococci: results from routine outbreak analyses across different hospitals and hospitals networks in Berlin, Germany

The increase of Vancomycin-resistant Enterococcus faecium (VREfm) in recent years has been partially attributed to the rise of specific clonal lineages, which have been identified throughout Germany. To date, there is no gold standard for the interpretation of genomic data for outbreak analyses. New genomic approaches such as split k-mer analysis (SKA) could support cluster attribution for routine outbreak investigation. The aim of this project was to investigate frequent clonal lineages of VREfm identified during suspected outbreaks across different hospitals, and to compare genomic approaches including SKA in routine outbreak investigation. We used routine outbreak laboratory data from seven hospitals and three different hospital networks in Berlin, Germany. Short-read libraries were sequenced on the Illumina MiSeq system. We determined clusters using the published Enterococcus faecium-cgMLST scheme (threshold ≤20 alleles), and assigned sequence and complex types (ST, CT), using the Ridom SeqSphere+ software. For each cluster as determined by cgMLST, we used pairwise core-genome SNP-analysis and SKA at thresholds of ten and seven SNPs, respectively, to further distinguish cgMLST clusters. In order to investigate clinical relevance, we analysed to what extent epidemiological linkage backed the clusters determined with different genomic approaches. Between 2014 and 2021, we sequenced 693 VREfm strains, and 644 (93 %) were associated within cgMLST clusters. More than 74 % (n=475) of the strains belonged to the six largest cgMLST clusters, comprising ST117, ST78 and ST80. All six clusters were detected across several years and hospitals without apparent epidemiological links. Core SNP analysis identified 44 clusters with a median cluster size of three isolates (IQR 2-7, min-max 2-63), as well as 197 singletons (41.4 % of 475 isolates). SKA identified 67 clusters with a median cluster size of two isolates (IQR 2-4, min-max 2-19), and 261 singletons (54.9 % of 475 isolates). Of the isolate pairs attributed to clusters, 7 % (n=3064/45 596) of pairs in clusters determined by standard cgMLST, 15 % (n=1222/8500) of pairs in core SNP-clusters and 51 % (n=942/1880) of pairs in SKA-clusters showed epidemiological linkage. The proportion of epidemiological linkage differed between sequence types. For VREfm, the discriminative ability of the widely used cgMLST based approach at ≤20 alleles difference was insufficient to rule out hospital outbreaks without further analytical methods. Cluster assignment guided by core genome SNP analysis and the reference free SKA was more discriminative and correlated better with obvious epidemiological linkage, at least recently published thresholds (ten and seven SNPs, respectively) and for frequent STs. Besides higher overall discriminative power, the whole-genome approach implemented in SKA is also easier and faster to conduct and requires less computational resources.

Comparative Analysis of Salmonella enterica subsp. enterica Serovar Thompson Isolates associated with Outbreaks Using PFGE and wgMLST

The strains associated with foodborne Salmonella enterica Thompson outbreaks in Korea have not been identified. Therefore, we characterized S. Thompson strains isolated from chocolate cakes linked to foodborne outbreaks in Korea. A total of 56 strains were isolated from preserved cake products, products in the supply chain distribution, the manufacturer's apparatus, and egg white liquid products used for cream preparation. Subsequently, serological typing, pathogenic gene-targeted polymerase chain reaction (PCR), pulsed-field gel electrophoresis (PFGE), and whole-genome multi-locus sequence typing (wgMLST) were performed to characterize these isolates. The antigen formula of all isolates was 7:k:1,5, namely Salmonella enterica subsp. enterica Serovar Thompson. All 56 isolates harbored invA, his, hin, and stn, and were negative for sefA and spvC based on gene-targeted PCR analyses. Based on PFGE results, these isolates were classified into one group based on the same SP6X01.011 pattern with 100% similarity. We selected 19 strains based on the region and sample type, which were subjected to wgMLST. Although the examined strains showed 100% similarity, they were classified into seven clusters based on allelic differences. According to our findings, the cause of these outbreaks was chocolate cake manufactured with egg white liquid contaminated with the same Salmonella Thompson. Additionally, comparative analysis of wgMLST on domestic isolates of S. Thompson from the three outbreaks showed genetic similarities of over 99.6%. Based on the results, the PFGE and wgMLST combination can provide highly resolved phylogeny and reliable evidence during Salmonella outbreak investigations.

Comparative genomics of Campylobacter jejuni from clinical campylobacteriosis stool specimens

BACKGROUND

Campylobacter jejuni is a pervasive pathogen of major public health concern with a complex ecology requiring accurate and informative approaches to define pathogen diversity during outbreak investigations. Source attribution analysis may be confounded if the genetic diversity of a C. jejuni population is not adequately captured in a single specimen. The aim of this study was to determine the genomic diversity of C. jejuni within individual stool specimens from four campylobacteriosis patients. Direct plating and pre-culture filtration of one stool specimen per patient was used to culture multiple isolates per stool specimen. Whole genome sequencing and pangenome level analysis were used to investigate genomic diversity of C. jejuni within a patient.

RESULTS

A total 92 C. jejuni isolates were recovered from four patients presenting with gastroenteritis. The number of isolates ranged from 13 to 30 per patient stool. Three patients yielded a single C. jejuni multilocus sequence type: ST-21 (n = 26, patient 4), ST-61 (n = 30, patient 1) and ST-2066 (n = 23, patient 2). Patient 3 was infected with two different sequence types [ST-51 (n = 12) and ST-354 (n = 1)]. Isolates belonging to the same sequence type from the same patient specimen shared 12-43 core non-recombinant SNPs and 0-20 frameshifts with each other, and the pangenomes of each sequence type consisted of 1406-1491 core genes and 231-264 accessory genes. However, neither the mutation nor the accessory genes were connected to a specific functional gene category.

CONCLUSIONS

Our findings show that the C. jejuni population recovered from an individual patient's stool are genetically diverse even within the same ST and may have shared common ancestors before specimens were obtained. The population is unlikely to have evolved from a single isolate at the time point of initial patient infection, leading us to conclude that patients were likely infected with a heterogeneous C. jejuni population. The diversity of the C. jejuni population found within individual stool specimens can inform future methodological approaches to attribution and outbreak investigations.

Genome characteristics of clinical Salmonella enterica population from a state public health laboratory, New Hampshire, USA, 2017–2020

Background

The implementation of whole genome sequencing (WGS) by PulseNet, the molecular subtyping network for foodborne diseases, has transformed surveillance, outbreak detection, and public health laboratory practices in the United States. In 2017, the New Hampshire Public Health Laboratories, a member of PulseNet, commenced the use of WGS in tracking foodborne pathogens across the state. We present some of the initial results of New Hampshire’s initiative to transition to WGS in tracking Salmonella enterica, a bacterial pathogen that is responsible for non-typhoidal foodborne infections and enteric fever. We characterize the population structure and evolutionary history of 394 genomes of isolates recovered from human clinical cases in New Hampshire from 2017 to 2020.

Results

The New Hampshire S. enterica population is phylogenetically diverse, consisting of 78 sequence types (ST) and 67 serotypes. Six lineages dominate the population: ST 11 serotype Enteritidis, ST 19 Typhimurium, ST 32 Infantis, ST 118 Newport, ST 22 Braenderup, and ST 26 Thompson. Each lineage is derived from long ancestral branches in the phylogeny, suggesting their extended presence in the region and recent clonal expansion. We detected 61 genes associated with resistance to 14 antimicrobial classes. Of these, unique genes of five antimicrobial classes (aminocoumarins, aminoglycosides, fluoroquinolones, nitroimidazoles, and peptides) were detected in all genomes. Rather than a single clone carrying multiple resistance genes expanding in the state, we found multiple lineages carrying different combinations of independently acquired resistance determinants. We estimate the time to the most recent common ancestor of the predominant lineage ST 11 serotype Enteritidis (126 genomes) to be 1965 (95% highest posterior density intervals: 1927–1982). Its population size expanded until 1978, followed by a population decline until 1990. This lineage has been expanding since then. Comparison with genomes from other states reveal lack of geographical clustering indicative of long-distance dissemination.

Conclusions

WGS studies of standing pathogen diversity provide critical insights into the population and evolutionary dynamics of lineages and antimicrobial resistance, which can be translated to effective public health action and decision-making. We highlight the need to strengthen efforts to implement WGS-based surveillance and genomic data analyses in state public health laboratories.

Combining analytical epidemiology and genomic surveillance to identify risk factors associated with the spread of antimicrobial resistance in Salmonella enterica subsp. enterica serovar Heidelberg

Antimicrobial resistance (AMR) has become a critical threat to public health worldwide. The use of antimicrobials in food and livestock agriculture, including the production of poultry, is thought to contribute to the dissemination of antibiotic resistant bacteria (ARB) and the genes and plasmids that confer the resistant phenotype (ARG). However, the relative contribution of each of these processes to the emergence of resistant pathogens in poultry production and their potential role in the transmission of resistant pathogens in human infections, requires a deeper understanding of the dynamics of ARB and ARG in food production and the factors involved in the increased risk of transmission.

MGTdb: a web service and database for studying the global and local genomic epidemiology of bacterial pathogens

Multilevel genome typing (MGT) enables the genomic characterization of bacterial isolates and the relationships among them. The MGT system describes an isolate using multiple multilocus sequence typing (MLST) schemes, referred to as levels. Thus, for a new isolate, sequence types (STs) assigned at multiple precisely defined levels can be used to type isolates at multiple resolutions. The MGT designation for isolates is stable, and the assignment is faster than the existing approaches. MGT’s utility has been demonstrated in multiple species. This paper presents a publicly accessible web service called MGTdb, which enables the assignment of MGT STs to isolates, along with their storage, retrieval and analysis. The MGTdb web service enables upload of genome data as sequence reads or alleles, which are processed and assigned MGT identifiers. Additionally, any newly sequenced isolates deposited in the National Center for Biotechnology Information’s Sequence Read Archive are also regularly retrieved (currently daily), processed, assigned MGT identifiers and made publicly available in MGTdb. Interactive visualization tools are presented to assist analysis, along with capabilities to download publicly available isolates and assignments for use with external software. MGTdb is currently available for Salmonella enterica serovars Typhimurium and Enteritidis and Vibrio cholerae. We demonstrate the usability of MGTdb through three case studies — to study the long-term national surveillance of S. Typhimurium, the local epidemiology and outbreaks of S. Typhimurium, and the global epidemiology of V. cholerae. Thus, MGTdb enables epidemiological and microbiological investigations at multiple levels of resolution for all publicly available isolates of these pathogens.

Database URL: https://mgtdb.unsw.edu.au

Comparing Multiple Locus Variable-Number Tandem Repeat Analyses with Whole-Genome Sequencing as Typing Method for Salmonella Enteritidis Surveillance in The Netherlands, January 2019 to March 2020

In the Netherlands, whole-genome sequencing (WGS) was implemented as routine typing tool for Salmonella Enteritidis isolates in 2019. Multiple locus variable-number tandem repeat analyses (MLVA) was performed in parallel. The objective was to determine the concordance of MLVA and WGS as typing methods for S. Enteritidis isolates. We included S. Enteritidis isolates from patients that were subtyped using MLVA and WGS-based core-genome Multilocus Sequence Typing (cgMLST) as part of the national laboratory surveillance of Salmonella during January 2019 to March 2020. The concordance of clustering based on MLVA and cgMLST, with a distance of ≤5 alleles, was assessed using the Fowlkes-Mallows (FM) index, and their discriminatory power using Simpson's diversity index. Of 439 isolates in total, 404 (92%) were typed as 32 clusters based on MLVA, with a median size of 4 isolates (range:2 to 141 isolates). Based on cgMLST, 313 (71%) isolates were typed as 48 clusters, with a median size of 3 isolates (range:2 to 39 isolates). The FM index was 0.34 on a scale from 0 to 1, where a higher value indicates greater similarity between the typing methods. The Simpson's diversity index of MLVA and cgMLST was 0.860 and 0.974, respectively. The median cgMLST distance between isolates with the same MLVA type was 27 alleles (interquartile range [IQR]:17 to 34 alleles), and 2 alleles within cgMLST clusters (IQR:1-5 alleles). This study shows the higher discriminatory power of WGS over MLVA and a poor concordance between both typing methods regarding clustering of S. Enteritidis isolates. IMPORTANCE Salmonella is the most frequently reported agent causing foodborne outbreaks and the second most common zoonoses in the European Union. The incidence of the most dominant serotype Enteritidis has increased in recent years. To differentiate between Salmonella isolates, traditional typing methods such as pulsed-field gel electrophoresis (PFGE) and multiple locus variable-number tandem repeat analyses (MLVA) are increasingly replaced with whole-genome sequencing (WGS). This study compared MLVA and WGS-based core-genome Multilocus Sequence Typing (cgMLST) as typing tools for S. Enteritidis isolates that were collected as part of the national Salmonella surveillance in the Netherlands. We found a higher discriminatory power of WGS-based cgMLST over MLVA, as well as a poor concordance between both typing methods regarding clustering of S. Enteritidis isolates. This is especially relevant for cluster delineation in outbreak investigations and confirmation of the outbreak source in trace-back investigations.

Whole-Genome Sequencing-Based Characterization of Listeria Isolates from Produce Packinghouses and Fresh-Cut Facilities Suggests Both Persistence and Reintroduction of Fully Virulent L. monocytogenes

The contamination of ready-to-eat produce with Listeria monocytogenes (LM) can often be traced back to environmental sources in processing facilities and packinghouses. To provide an improved understanding of Listeria sources and transmission in produce operations, we performed whole-genome sequencing (WGS) of LM (n = 169) and other Listeria spp. (n = 107) obtained from 13 produce packinghouses and three fresh-cut produce facilities. Overall, a low proportion of LM isolates (9/169) had inlA premature stop codons, and a large proportion (83/169) had either or both of the LIPI-3 or LIPI-4 operons, which have been associated with hypervirulence. The further analysis of the WGS data by operation showed a reisolation (at least 2 months apart) of highly related isolates (<10 hqSNP differences) in 7/16 operations. Two operations had highly related strains reisolated from samples that were collected at least 1 year apart. The identification of isolates collected during preproduction (i.e., following sanitation but before the start of production) that were highly related to isolates collected during production (i.e., after people or products have entered and begun moving through the operation) provided evidence that some strains were able to survive standard sanitation practices. The identification of closely related isolates (<20 hqSNPs differences) in different operations suggests that cross-contamination between facilities or introductions from common suppliers may also contribute to Listeria transmission. Overall, our data suggest that the majority of LM isolates collected from produce operations are fully virulent and that both persistence and reintroduction may lead to the repeat isolation of closely related Listeria in produce operations.

IMPORTANCEListeria monocytogenes is of particular concern to the produce industry due to its frequent presence in natural environments as well as its ability to survive in packinghouses and fresh-cut processing facilities over time. The use of whole-genome sequencing, which provides high discriminatory power for the characterization of Listeria isolates, along with detailed source data (isolation date and sample location) shows that the presence of Listeria in produce operations appears to be due to random and continued reintroduction as well as to the persistence of highly related strains in both packinghouses and fresh-cut facilities. These findings indicate the importance of using high-resolution characterization approaches for root cause analyses of Listeria contamination issues. In cases of repeat isolation of closely related Listeria in a given facility, both persistence and reintroduction need to be considered as possible root causes.

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

Background

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

Methods

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

Results

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

Conclusions

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

Supplementary Information

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

Polyphyly in widespread Salmonella enterica serovars and using genomic proximity to choose the best reference genome for bioinformatics analyses

Salmonella is the most common cause of gastroenteritis in the world. Over the past 5 years, whole-genome analysis has led to the high-resolution characterization of clinical and foodborne Salmonella responsible for typhoid fever, foodborne illness or contamination of the agro-food chain. Whole-genome analyses are simplified by the availability of high-quality, complete genomes for mapping analysis and for calculating the pairwise distance between genomes, but unfortunately some difficulties may still remain. For some serovars, the complete genome is not available, or some serovars are polyphyletic and knowing the serovar alone is not sufficient for choosing the most appropriate reference genome. For these serovars, it is essential to identify the genetically closest complete genome to be able to carry out precise genome analyses. In this study, we explored the genomic proximity of 650 genomes of the 58 Salmonella enterica subsp. enterica serovars most frequently isolated in humans and from the food chain in the United States (US) and in Europe (EU), with a special focus on France. For each serovar, to take into account their genomic diversity, we included all the multilocus sequence type (MLST) profiles represented in EnteroBase with 10 or more genomes (on 19 July 2021). A phylogenetic analysis using both core- and pan-genome approaches was carried out to identify the genomic proximity of all the Salmonella studied and 20 polyphyletic serovars that have not yet been described in the literature. This study determined the genetic proximity between all 58 serovars studied and revealed polyphyletic serovars, their genomic lineages and MLST profiles. Finally, we enhanced the open-access databases with 73 new genomes and produced a list of high-quality complete reference genomes for 48 S. enterica subsp. enterica serovars among the most isolated in the US, EU, and France.

Genomic surveillance of Salmonella spp. in the Philippines during 2013-2014

BACKGROUND

Increasing antimicrobial resistance (AMR) in Salmonella has been observed in the Philippines. We aimed to characterise the population and AMR mechanisms of Salmonella with whole genome sequencing (WGS) and compare it with laboratory surveillance methods.

METHODS

The serotype, multilocus sequence type, AMR genes and relatedness between isolates were determined from the genomes of 148 Salmonella Typhi (S. Typhi) and 65 non-typhoidal Salmonella (NTS) collected by the Antimicrobial Resistance Surveillance Program during 2013-2014. Genotypic serotypes and AMR prediction were compared with phenotypic data.

RESULTS

AMR rates in S. Typhi were low, with sparse acquisition of mutations associated with reduced susceptibility to fluoroquinolones or extended-spectrum beta-lactamases (ESBL) genes. By contrast, 75% of NTS isolates were insusceptible to at least one antimicrobial, with more than half carrying mutations and/or genes linked to fluoroquinolone resistance. ESBL genes were detected in five genomes, which also carried other AMR determinants. The population of S. Typhi was dominated by likely endemic genotype 3.0, which caused a putative local outbreak. The main NTS clades were global epidemic S. Enteritidis ST11 and S. Typhimurium monophasic variant (I,4,[5],12: i: -) ST34.

CONCLUSION

We provide the first genomic characterisation of Salmonella from the Philippines and evidence of WGS utility for ongoing surveillance.

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.

Comparative Genomics of Escherichia coli Serotype O55:H7 Using Complete Closed Genomes

Escherichia coli O55:H7 is a human foodborne pathogen and is recognized as the progenitor strain of E. coli O157:H7. While this strain is important from a food safety and genomic evolution standpoint, much of the genomic diversity of E. coli O55:H7 has been demonstrated using draft genomes. Here, we combine the four publicly available E. coli O55:H7 closed genomes with six newly sequenced closed genomes to provide context to this strain’s genomic diversity. We found significant diversity within the 10 E. coli O55:H7 strains that belonged to three different sequence types. The prophage content was about 10% of the genome, with three prophages common to all strains and seven unique to one strain. Overall, there were 492 insertion sequences identified within the six new sequence strains, with each strain on average containing 75 insertions (range 55 to 114). A total of 31 plasmids were identified between all isolates (range 1 to 6), with one plasmid (pO55) having an identical phylogenetic tree as the chromosome. The release and comparison of these closed genomes provides new insight into E. coli O55:H7 diversity and its ability to cause disease in humans.

Genetic diversity and virulence gene profiles of Escherichia coli from diarrhoeal rabbits in Sichuan Province, China

Escherichia coli (E. coli) can cause diarrhoea in a wide range of hosts. Moreover, some trains with high virulence and drug resistance pose a serious threat to public health and livestock products. Diarrhoea caused by E. coli outbreaks in rabbitries result in serious economic losses. The aim of this study was to investigate the distribution of virulence genes and molecular genetic characteristics of E. coli from diarrhoeal rabbits in the main rearing areas of Sichuan province, China in 2015-2017. In total, 39 E. coli isolates were identified and undivided divided into 17 sequence types by multilocus sequence typing (MLST) and grouped in 22 clusters by pulsed-field gel electrophoresis. Polymerase chain reaction tests detected 6 virulence genes: eae (41.0%), ler (41.0%), ral (33.3%), afr2 (10.3%), irp2 (15.4%) and astA (7.7%) of the tested 17 virulence genes identifying 16 enteropathogenic E. coli (EPEC) isolates. The main sequence types U328, ST328 and ST20 carried rabbit EPEC associated virulence genes (eae, ler, ral and afr2). The results showed that the distribution of virulence genes varied by year and area; genotype had major types in local rearing areas but was of high diversity in Sichuan province.