Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica

Antimicrobial susceptibility and resistome of Actinobacillus pleuropneumoniae in Taiwan: a next-generation sequencing analysis

Actinobacillus pleuropneumoniae infection causes a high mortality rate in porcine animals. Antimicrobial resistance poses global threats to public health. The current study aimed to determine the antimicrobial susceptibilities and probe the resistome of A. pleuropneumoniae in Taiwan. Herein, 133 isolates were retrospectively collected; upon initial screening, 38 samples were subjected to next-generation sequencing (NGS). Over the period 2017-2022, the lowest frequencies of resistant isolates were found for ceftiofur, cephalexin, cephalothin, and enrofloxacin, while the highest frequencies of resistant isolates were found for oxytetracycline, streptomycin, doxycycline, ampicillin, amoxicillin, kanamycin, and florfenicol. Furthermore, most isolates (71.4%) showed multiple drug resistance. NGS-based resistome analysis revealed aminoglycoside- and tetracycline-related genes at the highest prevalence, followed by genes related to beta-lactam, sulfamethoxazole, florphenicol, and macrolide. A plasmid replicon (repUS47) and insertion sequences (IS10R and ISVAp11) were identified in resistant isolates. Notably, the multiple resistance roles of the insertion sequence IS10R were widely proposed in human medicine; however, this is the first time IS10R has been reported in veterinary medicine. Concordance analysis revealed a high consistency of phenotypic and genotypic susceptibility to florphenicol, tilmicosin, doxycycline, and oxytetracycline. The current study reports the antimicrobial characterization of A. pleuropneumoniae for the first time in Taiwan using NGS.

Identifying factors that influence the use of pathogen genomics in Australia and New Zealand: a protocol

Introduction

Pathogen genomics, where whole genome sequencing technologies are used to produce complete genomic sequences of pathogens, is being increasingly used for infectious disease surveillance and outbreak response. Although proof-of-concept studies have highlighted the viability of using pathogen genomics in public health, few studies have investigated how end-users utilize pathogen genomics in public health. We describe a protocol for a study that aims to identify key factors that influence the use of pathogen genomics to inform public health responses against infectious diseases in Australia and New Zealand.

Methods

We will use qualitative comparative analysis (QCA), a case-oriented methodology that systematically compares and analyses multiple cases (or 'units of analysis'), to identify multiple pathways leading to the use of pathogen genomics results in public health actions. As part of the process, we will develop a rubric to identify and define the use of pathogen genomics and individual factors affecting this process. Simultaneously, we will identify cases where pathogen genomics has been used in public health across Australia and New Zealand. Data for these cases will be collected from document review of publicly available and confidential documents and semi-structured interviews with technicians and end-users and summarized in a case report. These case reports will form the basis for scoring each case on the extent of the use of pathogen genomics data and the presence or absence of specific factors such as the ease of extracting essential information from pathogen genomics reports and perceptions toward pathogen genomics. Using the scores, cases will be analyzed using QCA techniques to identify pathways leading to the use of pathogen genomics data. These pathways will be interpreted alongside the cases to provide rich explanations of the use of pathogen genomics in public health.

Discussion

This study will improve our understanding of the key factors that facilitate or hinder the use of pathogen genomics to inform public health authorities and end-users. These findings may inform ways to enhance the use of pathogen genomics data in public health.

Predominance of OXA-48 carbapenemase-producing Klebsiella pneumoniae strains in tertiary hospital in Sarajevo, Bosnia and Herzegovina

Klebsiella pneumoniae, a member of the Enterobacteriaceae family, demonstrates an increasing trend of resistance to carbapenems and is a common cause of both hospital- and community-acquired infections. The current study provides insights into the genetic characterization of carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates circulating during 2022 in a Sarajevo tertiary hospital. Among the 87 CRKP strains analyzed, real-time polymerase chain reaction (rtPCR) results showed that 85 (97.7%) tested positive for the carbapenem resistance gene. The oxacillinase-48 (OXA-48) gene was detected in 83 (95.4%) isolates, while the Klebsiella pneumoniae carbapenemase (KPC) and the New Delhi metallo-beta-lactamase (NDM) genes were detected in one isolate each. No Verona integron-encoded-metallo-beta-lactamase (VIM) or imipenemase-metallo-beta-lactamase 1 (IMP-1) genes were found in any of the tested isolates. The multilocus sequence typing (MLST) analysis of sequence types (STs) revealed that ST101, an emerging high-risk clone exhibiting extensive drug resistance, was the most prevalent, whereas ST307 was detected in only one isolate. Phylogenetic analysis of the ten CRKP isolates indicated the presence of three clusters that could constitute an outbreak. A comparison of the results of the utilized phenotypic test (the combined-disk test [CDT]) and rtPCR showed high concordance, suggesting that the phenotypic assay may be useful for the early detection of resistance mechanisms as part of routine susceptibility testing. With the increased affordability of next-generation sequencing (NGS), its application in hospital settings has proven highly beneficial, aiding in the implementation of infection control and prevention measures. Given the significant resistance demonstrated by the CRKP isolates to most tested antibiotics, it is imperative to establish effective methods to restrict the spread of these isolates, as well as to carefully monitor the use of carbapenems in clinical practice.

Whole genome-based antimicrobial resistance and virulence profiling of Staphylococcus aureus isolates from chronic leg ulcer patients in Kilimanjaro, Tanzania

BACKGROUND

Chronic leg ulcers are hard to treat and can be a burden, particularly in resource-limited settings where diagnosis is a challenge. Staphylococcus aureus is among the common bacteria isolated from chronic wounds with a great impact on wound healing, particularly in patients with co-morbidities. Antimicrobial resistance genes and virulence factors in Staphylococcus aureus isolates were assessed to support healthcare professionals to make better therapeutic choices, and importantly to curb the development and spread of antibiotic resistance.

METHODS

A cross-sectional study involved both inpatients and outpatients with chronic leg ulcers was conducted from August 2022 to April 2023 in 2 health facilities in Kilimanjaro region in Tanzania. Antimicrobial susceptibility testing was done using the disk diffusion method. Further, whole genome sequencing was performed to study the genotypic characteristics of the isolates.

RESULTS

A total of 92 participants were recruited in which 9 participants were only positive for 10 Staphylococcus aureus isolates upon culture. Five STs among 9 isolates were identified. Most of them belonged to ST8 (44%), with 1 isolate does not belong to any ST. Additionally, 50% of the isolates were methicillin-resistant Staphylococcus aureus (MRSA). All S. aureus isolates had almost similar virulence factors such as hemolysin, proteases and evasions that promote toxin production, protease production and host immune evasion respectively. Moreover, all mecA positive S. aureus isolates were phenotypically susceptible to cefoxitin.

CONCLUSION

Presence of mecA positive S. aureus isolates which are also phenotypically susceptible to cefoxitin implies the possibility of classifying MRSA as MSSA. This may result in the possible emergence of highly cefoxitin - resistant strains in health care and community settings when subsequently exposed to beta-lactam agents. Therefore, combination of whole genome sequencing and conventional methods is important in assessing bacterial resistance and virulence to improve management of patients.

Outbreak detection in Harar town and Kersa district, Ethiopia using phylogenetic analysis and source attribution

BACKGROUND

Foodborne diseases (FBDs) represent a significant risk to public health, with nearly one in ten people falling ill every year globally. The large incidence of foodborne diseases in African low- and middle-income countries (LMIC) shows the immediate need for action, but there is still far to a robust and efficient outbreak detection system. The detection of outbreak heavily relies on clinical diagnosis, which are often delayed or ignored due to resource limitations and inadequate surveillance systems.

METHODS

In total, 68 samples of non-typhoidal Salmonella isolates from human, animal and environmental sources collected between November 2021 and January 2023 were analyzed using sequencing methods to infer phylogenetic relationships between the samples. A source attribution model using a machine-learning logit-boost that predicted the likely source of infection for 20 cases of human salmonellosis was also run and compared with the results of the cluster detection.

RESULTS

Three clusters of samples with close relation (SNP difference < 30) were identified as non-typhoidal Salmonella in Harar town and Kersa district, Ethiopia. These three clusters were comprised of isolates from different sources, including at least two human isolates. The isolates within each cluster showed identical serovar and sequence type (ST), with few exceptions in cluster 3. The close proximity of the samples suggested the occurrence of three potential outbreaks of non-typhoidal Salmonella in the region. The results of the source attribution model found that human cases of salmonellosis could primarily be attributed to bovine meat, which the results of the phylogenetic analysis corroborated.

CONCLUSIONS

The findings of this study suggested the occurrence of three possible outbreaks of non-typhoidal Salmonella in eastern Ethiopia, emphasizing the importance of targeted intervention of food safety protocols in LMICs. It also highlighted the potential of integrated surveillance for detecting outbreak and identifying the most probable source. Source attribution models in combination with other epidemiological methods is recommended as part of a more robust and integrated surveillance system for foodborne diseases.

Emerging Strategies against Non-Typhoidal Salmonella: From Pathogenesis to Treatment

Even with the intensive efforts by public health programs to control and prevent it, non-typhoidal Salmonella (NTS) infection remains an important public health challenge. It is responsible for approximately 150 million illnesses and 60,000 deaths worldwide annually. NTS infection poses significant risks with high rates of morbidity and mortality, leading to potential short- and long-term complications. There is growing concern among health authorities about the increasing incidence of antimicrobial resistance, with multidrug resistance totaling 22.6% in Europe, highlighting an urgent need for new therapeutic approaches. Our review aims to provide a comprehensive overview of NTS infection. We outline the molecular mechanisms involved in the pathogenesis of NTS infection, as well as the events leading to invasive NTS infection and the subsequent complications associated with it. Given the widespread implications of antimicrobial resistance, our review also presents the global landscape of resistance, including multidrug resistance, and delve into the underlying mechanisms driving this resistance. The rising rates of antibiotic resistance frequently lead to treatment failures, emphasizing the importance of investigating alternative therapeutic options. Therefore, in this review we also explore potential alternative therapies that could offer promising approaches to treating NTS infections.

Dual effects of a bacteriocin-producing Lactiplantibacillus pentosus CF-6HA, isolated from fermented aloreña table olives, as potential probiotic and antimicrobial agent

The probiotic potential of Lactiplantibacillus pentosus CF-6HA isolated from traditionally fermented Aloreña table olives was analyzed in vitro and in silico. Results obtained suggested that this strain can be catalogued as "talented" bacterium exhibiting bacteriocin production with antimicrobial activity against human/animal and plant pathogens, such as Pseudomonas syringae and Verticillium dahliae. The robustness, safety and probiotic potential of L. pentosus CF-6HA was confirmed by in silico analysis. In addition, a plethora of coding genes for defense and adaptability to different life styles besides functional properties were identified. In this sense, defense mechanisms of L. pentosus CF-6HA consist of 17 ISI elements, 98 transposases and 13 temperate phage regions as well as a CRISPR (clustered regularly interspaced short palindromic repeats)/cas system. Moreover, the functionality of this strain was confirmed by the presence of genes coding for secondary metabolites, exopolysaccharides and other bioactive molecules. Finally, we demonstrated the ability of L. pentosus CF-6HA to biotransform selenite to nanoparticles (SeNPs) highlighting its potential role in selenium bioremediation to be exploited in foods, agriculture and the environment; but also for the bio-enrichment of fermented foods with selenium.

Salmonella Typhi whole genome sequencing in Rwanda shows a diverse historical population with recent introduction of haplotype H58

Salmonella enterica serovar Typhi (S. Typhi) is the cause of typhoid fever, presenting high rates of morbidity and mortality in low- and middle-income countries. The H58 haplotype shows high levels of antimicrobial resistance (AMR) and is the dominant S. Typhi haplotype in endemic areas of Asia and East sub-Saharan Africa. The situation in Rwanda is currently unknown and therefore to reveal the genetic diversity and AMR of S. Typhi in Rwanda, 25 historical (1984-1985) and 26 recent (2010-2018) isolates from Rwanda were analysed using whole genome sequencing (WGS). WGS was locally implemented using Illumina MiniSeq and web-based analysis tools, thereafter complemented with bioinformatic approaches for more in-depth analyses. Whereas historical S. Typhi isolates were found to be fully susceptible to antimicrobials and show a diversity of genotypes, i.e 2.2.2, 2.5, 3.3.1 and 4.1; the recent isolates showed high AMR rates and were predominantly associated with genotype 4.3.1.2 (H58, 22/26; 84,6%), possibly resulting from a single introduction in Rwanda from South Asia before 2010. We identified practical challenges for the use of WGS in endemic regions, including a high cost for shipment of molecular reagents and lack of high-end computational infrastructure for the analyses, but also identified WGS to be feasible in the studied setting and giving opportunity for synergy with other programs.

Oxford nanopore technologies-a valuable tool to generate whole-genome sequencing data for in silico serotyping and the detection of genetic markers in Salmonella

Bacteria of the genus Salmonella pose a major risk to livestock, the food economy, and public health. Salmonella infections are one of the leading causes of food poisoning. The identification of serovars of Salmonella achieved by their diverse surface antigens is essential to gain information on their epidemiological context. Traditionally, slide agglutination has been used for serotyping. In recent years, whole-genome sequencing (WGS) followed by in silico serotyping has been established as an alternative method for serotyping and the detection of genetic markers for Salmonella. Until now, WGS data generated with Illumina sequencing are used to validate in silico serotyping methods. Oxford Nanopore Technologies (ONT) opens the possibility to sequence ultra-long reads and has frequently been used for bacterial sequencing. In this study, ONT sequencing data of 28 Salmonella strains of different serovars with epidemiological relevance in humans, food, and animals were taken to investigate the performance of the in silico serotyping tools SISTR and SeqSero2 compared to traditional slide agglutination tests. Moreover, the detection of genetic markers for resistance against antimicrobial agents, virulence, and plasmids was studied by comparing WGS data based on ONT with WGS data based on Illumina. Based on the ONT data from flow cell version R9.4.1, in silico serotyping achieved an accuracy of 96.4 and 92% for the tools SISTR and SeqSero2, respectively. Highly similar sets of genetic markers comparing both sequencing technologies were identified. Taking the ongoing improvement of basecalling and flow cells into account, ONT data can be used for Salmonella in silico serotyping and genetic marker detection.

An Overview on Phenotypic and Genotypic Characterisation of Carbapenem-Resistant Enterobacterales

Improper use of antimicrobials has resulted in the emergence of antimicrobial resistance (AMR), including multi-drug resistance (MDR) among bacteria. Recently, a sudden increase in Carbapenem-resistant Enterobacterales (CRE) has been observed. This presents a substantial challenge in the treatment of CRE-infected individuals. Bacterial plasmids include the genes for carbapenem resistance, which can also spread to other bacteria to make them resistant. The incidence of CRE is rising significantly despite the efforts of health authorities, clinicians, and scientists. Many genotypic and phenotypic techniques are available to identify CRE. However, effective identification requires the integration of two or more methods. Whole genome sequencing (WGS), an advanced molecular approach, helps identify new strains of CRE and screening of the patient population; however, WGS is challenging to apply in clinical settings due to the complexity and high expense involved with this technique. The current review highlights the molecular mechanism of development of Carbapenem resistance, the epidemiology of CRE infections, spread of CRE, treatment options, and the phenotypic/genotypic characterisation of CRE. The potential of microorganisms to acquire resistance against Carbapenems remains high, which can lead to even more susceptible drugs such as colistin and polymyxins. Hence, the current study recommends running the antibiotic stewardship programs at an institutional level to control the use of antibiotics and to reduce the spread of CRE worldwide.

Detection and Genomic Characterisation of Clostridioides difficile from Spinach Fields

Despite an increased incidence of Clostridioides difficile infections, data on the reservoirs and dissemination routes of this bacterium are limited. This study examined the prevalence and characteristics of C. difficile isolates in spinach fields. C. difficile was detected in 2/60 (3.3%) of spinach and 6/60 (10%) of soil samples using culture-based techniques. Whole genome sequencing (WGS) analysis identified the spinach isolates as belonging to the hypervirulent clade 5, sequence type (ST) 11, ribotypes (RT) 078 and 126 and carried the genes encoding toxins A, B and CDT. The soil isolates belonged to clade 1 with different toxigenic ST/RT (ST19/RT614, ST12/RT003, ST46/RT087, ST16/RT050, ST49/RT014/0) strains and one non-toxigenic ST79/RT511 strain. Antimicrobial resistance to erythromycin (one spinach isolate), rifampicin (two soil isolates), clindamycin (one soil isolate), both moxifloxacin and rifampicin (one soil isolate), and multi-drug resistance to erythromycin, vancomycin and rifampicin (two soil isolates) were observed using the E test, although a broader range of resistance genes were detected using WGS. Although the sample size was limited, our results demonstrate the presence of C. difficile in horticulture and provide further evidence that there are multiple sources and dissemination routes for these bacteria.

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 Sequence Comparisons of Listeria monocytogenes Isolated from Meat and Fish Reveal High Inter- and Intra-Sample Diversity

Interpretation of whole-genome sequencing (WGS) data for foodborne outbreak investigations is complex, as the genetic diversity within processing plants and transmission events need to be considered. In this study, we analyzed 92 food-associated Listeria monocytogenes isolates by WGS-based methods. We aimed to examine the genetic diversity within meat and fish production chains and to assess the applicability of suggested thresholds for clustering of potentially related isolates. Therefore, meat-associated isolates originating from the same samples or processing plants as well as fish-associated isolates were analyzed as distinct sets. In silico serogrouping, multilocus sequence typing (MLST), core genome MLST (cgMLST), and pangenome analysis were combined with screenings for prophages and genetic traits. Isolates of the same subtypes (cgMLST types (CTs) or MLST sequence types (STs)) were additionally compared by SNP calling. This revealed the occurrence of more than one CT within all three investigated plants and within two samples. Analysis of the fish set resulted in predominant assignment of isolates from pangasius catfish and salmon to ST2 and ST121, respectively, potentially indicating persistence within the respective production chains. The approach not only allowed the detection of distinct subtypes but also the determination of differences between closely related isolates, which need to be considered when interpreting WGS data for surveillance.

Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases

Next-generation sequencing (NGS) technologies have become increasingly available for use in the clinical microbiology diagnostic environment. There are three main applications of these technologies in the clinical microbiology laboratory: whole genome sequencing (WGS), targeted metagenomics sequencing and shotgun metagenomics sequencing. These applications are being utilized for initial identification of pathogenic organisms, the detection of antimicrobial resistance mechanisms and for epidemiologic tracking of organisms within and outside hospital systems. In this review, we analyze these three applications and provide a comprehensive summary of how these applications are currently being used in public health, basic research, and clinical microbiology laboratory environments. In the public health arena, WGS is being used to identify and epidemiologically track food borne outbreaks and disease surveillance. In clinical hospital systems, WGS is used to identify multi-drug-resistant nosocomial infections and track the transmission of these organisms. In addition, we examine how metagenomics sequencing approaches (targeted and shotgun) are being used to circumvent the traditional and biased microbiology culture methods to identify potential pathogens directly from specimens. We also expand on the important factors to consider when implementing these technologies, and what is possible for these technologies in infectious disease diagnosis in the next 5 years.

The application of next generation sequencing technology in medical diagnostics: a perspective

Rapid isolation, characterization, and identification are prerequisites of any successful medical intervention to infectious disease treatment. This is a real challenge to the scientific as well as a medical community to find out a proper and robust method of pathogen detection. Classical cultural, as well as biochemical test-based identification, has its own limitations to their time-consuming and ineffectiveness for closely related pathovars. Molecular diagnostics became a popular alternative to classical techniques for the past couple of decades but it required some prior information to detect the pathogen successfully. Recently, with the advent of next-generation sequencing (NGS) technology identification, and characterization of almost all the pathogenic bacteria become possible without any information a priori. Metagenomic next generation sequencing is another specialized type of NGS that is profoundly utilized in medical biotechnology and diagnostics now a days. Therefore, the present review is focused on a brief introduction to NGS technology, its application in medical microbiology, and possible future aspects for the development of medical sciences.

Antibiotic Resistance Properties among Pseudomonas spp. Associated with Salmon Processing Environments

Continuous monitoring of antimicrobial resistance in bacteria along the food chain is crucial for the assessment of human health risks. Uncritical use of antibiotics in farming over years can be one of the main reasons for increased antibiotic resistance in bacteria. In this study, we aimed to classify 222 presumptive Pseudomonas isolates originating from a salmon processing environment, and to examine the phenotypic and genotypic antibiotic resistance profiles of these isolates. Of all the analyzed isolates 68% belonged to Pseudomonas, and the most abundant species were Pseudomonas fluorescens, Pseudomonas azotoformans, Pseudomonas gessardii, Pseudomonas libanesis, Pseudomonas lundensis, Pseudomonas cedrina and Pseudomonas extremaustralis based on sequencing of the rpoD gene. As many as 27% of Pseudomonas isolates could not be classified to species level. Phenotypic susceptibility analysis by disc diffusion method revealed a high level of resistance towards the antibiotics ampicillin, amoxicillin, cefotaxime, ceftriaxone, imipenem, and the fish farming relevant antibiotics florfenicol and oxolinic acid among the Pseudomonas isolates. Whole genome sequencing and subsequent analysis of AMR determinants by ResFinder and CARD revealed that no isolates harbored any acquired resistance determinants, but all isolates carried variants of genes known from P. aeruginosa to be involved in multidrug efflux pump systems.

Comparative Genomic Analysis Discloses Differential Distribution of Antibiotic Resistance Determinants between Worldwide Strains of the Emergent ST213 Genotype of Salmonella Typhimurium

Salmonella enterica constitutes a global public health concern as one of the main etiological agents of human gastroenteritis. The Typhimurium serotype is frequently isolated from human, animal, food, and environmental samples, with its sequence type 19 (ST19) being the most widely distributed around the world as well as the founder genotype. The replacement of the ST19 genotype with the ST213 genotype that has multiple antibiotic resistance (MAR) in human and food samples was first observed in Mexico. The number of available genomes of ST213 strains in public databases indicates its fast worldwide dispersion, but its public health relevance is unknown. A comparative genomic analysis conducted as part of this research identified the presence of 44 genes, 34 plasmids, and five point mutations associated with antibiotic resistance, distributed across 220 genomes of ST213 strains, indicating the MAR phenotype. In general, the grouping pattern in correspondence to the presence/absence of genes/plasmids that confer antibiotic resistance cluster the genomes according to the geographical origin where the strain was isolated. Genetic determinants of antibiotic resistance group the genomes of North America (Canada, Mexico, USA) strains, and suggest a dispersion route to reach the United Kingdom and, from there, the rest of Europe, then Asia and Oceania. The results obtained here highlight the worldwide public health relevance of the ST213 genotype, which contains a great diversity of genetic elements associated with MAR.

Influence of Genetics, Immunity and the Microbiome on the Prognosis of Inflammatory Bowel Disease (IBD Prognosis Study): the protocol for a Copenhagen IBD Inception Cohort Study

INTRODUCTION

Inflammatory bowel diseases (IBD), encompassing Crohn's disease and ulcerative colitis, are chronic, inflammatory diseases of the gastrointestinal tract. We have initiated a Danish population-based inception cohort study aiming to investigate the underlying mechanisms for the heterogeneous course of IBD, including need for, and response to, treatment.

METHODS AND ANALYSIS

IBD Prognosis Study is a prospective, population-based inception cohort study of unselected, newly diagnosed adult, adolescent and paediatric patients with IBD within the uptake area of Hvidovre University Hospital and Herlev University Hospital, Denmark, which covers approximately 1 050 000 inhabitants (~20% of the Danish population). The diagnosis of IBD will be according to the Porto diagnostic criteria in paediatric and adolescent patients or the Copenhagen diagnostic criteria in adult patients. All patients will be followed prospectively with regular clinical examinations including ileocolonoscopies, MRI of the small intestine, validated patient-reported measures and objective examinations with intestinal ultrasound. In addition, intestinal biopsies from ileocolonoscopies, stool, rectal swabs, saliva samples, swabs of the oral cavity and blood samples will be collected systematically for the analysis of biomarkers, microbiome and genetic profiles. Environmental factors and quality of life will be assessed using questionnaires and, when available, automatic registration of purchase data. The occurrence and course of extraintestinal manifestations will be evaluated by rheumatologists, dermatologists and dentists, and assessed by MR cholangiopancreatography, MR of the spine and sacroiliac joints, ultrasonography of peripheral joints and entheses, clinical oral examination, as well as panoramic radiograph of the jaws. Fibroscans and dual-energy X-ray absorptiometry scans will be performed to monitor occurrence and course of chronic liver diseases, osteopenia and osteoporosis.

ETHICS AND DISSEMINATION

This study has been approved by Ethics Committee of the Capital Region of Denmark (approval number: H-20065831). Study results will be disseminated through publication in international scientific journals and presentation at (inter)national conferences.

K-mer based prediction of Clostridioides difficile relatedness and ribotypes

Comparative analysis of Clostridioides difficile whole-genome sequencing (WGS) data enables fine scaled investigation of transmission and is increasingly becoming part of routine surveillance. However, these analyses are constrained by the computational requirements of the large volumes of data involved. By decomposing WGS reads or assemblies into k-mers and using the dimensionality reduction technique MinHash, it is possible to rapidly approximate genomic distances without alignment. Here we assessed the performance of MinHash, as implemented by sourmash, in predicting single nucleotide differences between genomes (SNPs) and C. difficile ribotypes (RTs). For a set of 1905 diverse C. difficile genomes (differing by 0–168 519 SNPs), using sourmash to screen for closely related genomes, at a sensitivity of 100 % for pairs ≤10 SNPs, sourmash reduced the number of pairs from 1 813 560 overall to 161 934, i.e. by 91 %, with a positive predictive value of 32 % to correctly identify pairs ≤10 SNPs (maximum SNP distance 4144). At a sensitivity of 95 %, pairs were reduced by 94 % to 108 266 and PPV increased to 45 % (maximum SNP distance 1009). Increasing the MinHash sketch size above 2000 produced minimal performance improvement. We also explored a MinHash similarity-based ribotype prediction method. Genomes with known ribotypes (n=3937) were split into a training set (2937) and test set (1000) randomly. The training set was used to construct a sourmash index against which genomes from the test set were compared. If the closest five genomes in the index had the same ribotype this was taken to predict the searched genome’s ribotype. Using our MinHash ribotype index, predicted ribotypes were correct in 780/1000 (78 %) genomes, incorrect in 20 (2 %), and indeterminant in 200 (20 %). Relaxing the classifier to 4/5 closest matches with the same RT improved the correct predictions to 87 %. Using MinHash it is possible to subsample C. difficile genome k-mer hashes and use them to approximate small genomic differences within minutes, significantly reducing the search space for further analysis.

Characterization of Pseudomonas syringae Isolated from Systemic Infection of Zucchini in Australia

Zucchini plants with symptoms including twisted petioles, necrotic leaves, crown rot, and internal fruit rot were found in Bundaberg, Australia, at a commercial field for the first time during late autumn 2016, resulting in direct yield losses of 70 to 80%. Three Pseudomonas syringae strains isolated from symptomatic leaf (KL004-k1), crown (77-4C), and fruit (KFR003-1) were characterized and their pathogenicity evaluated on pumpkin, rockmelon, squash, and zucchini. Biochemical assays showed typical results for P. syringae. The three isolates differed, however, in that two produced fluorescent pigment (KFR003-1 and 77-4C) whereas the third, KL004-k1, was nonfluorescent. Multilocus sequence analysis classified the isolates to phylogroup 2b. The single-nucleotide polymorphism analysis of core genome from the Australian and closely related international isolates of P. syringae showed two separate clusters. The Australian isolates were clustered based on fluorescent phenotype. Pathogenicity tests demonstrated that all three isolates moved systemically within the inoculated plants and induced necrotic leaf symptoms in zucchini plants. Their identities were confirmed with specific PCR assays for P. syringae and phylogroup 2. Pathogenicity experiments also showed that the Eva variety of zucchini was more susceptible than the Rosa variety for all three isolates. Isolate KL004-k1 was more virulent than 77-4C on pumpkin, rockmelon, squash, and zucchini. This study expands the knowledge of P. syringae isolates that infect cucurbits and provides useful information for growers about the relative susceptibility of a range of cucurbit species.

Genomic evidence of environmental and resident Salmonella Senftenberg and Montevideo contamination in the pistachio supply-chain

Pistachios have been implicated in two salmonellosis outbreaks and multiple recalls in the U.S. This study performed an in-depth retrospective data analysis of Salmonella associated with pistachios as well as a storage study to evaluate the survivability of Salmonella on inoculated inshell pistachios to further understand the genetics and microbiological dynamics of this commodity-pathogen pair. The retrospective data analysis on isolates associated with pistachios was performed utilizing short-read and long-read sequencing technologies. The sequence data were analyzed using two methods: the FDA's Center for Food Safety and Applied Nutrition Single Nucleotide Polymorphism (SNP) analysis and Whole Genome Multilocus Sequence Typing (wgMLST). The year-long storage study evaluated the survival of five strains of Salmonella on pistachios stored at 25 °C at 35% and 54% relative humidity (RH). Our results demonstrate: i) evidence of persistent Salmonella Senftenberg and Salmonella Montevideo strains in pistachio environments, some of which may be due to clonal resident strains and some of which may be due to preharvest contamination; ii) presence of the Copper Homeostasis and Silver Resistance Island (CHASRI) in Salmonella Senftenberg and Montevideo strains in the pistachio supply chain; and iii) the use of metagenomic analysis is a novel tool for determining the composition of serovar survival in a cocktail inoculated storage study.

Molecular Epidemiological Analysis of ST11-K64 Extensively Drug-Resistant Klebsiella pneumoniae Infections Outbreak in Intensive Care and Neurosurgery Units Based on Whole-Genome Sequencing

Klebsiella pneumoniae (Kp) is the primary causative bacteria for nosocomial infections and hospital outbreaks. In particular, extensively drug-resistant K. pneumoniae (XDRKp) causes severe clinical infections in hospitalized patients. Here, we used pulsed-field gel electrophoresis (PFGE), drug susceptibility tests, and the whole-genome sequencing (WGS) technology to examine genetic relatedness and phenotypic traits of the strains isolated during an outbreak period. Based on PFGE, a distinct clones cluster comprised of eight XDRKp was observed. These strains were confirmed as ST11-K64 via multiple-locus sequence typing database of Kp. The strains also had genes related to the regulation of biofilm biosynthesis (type 1 & 3 fimbriae, type IV pili biosynthesis, RcsAB, and type VI secretion system) and multiple drug resistance (β-lactamase and aminoglycoside antibiotic resistance). WGS data based on core-single nucleotide polymorphisms and epidemiological investigation showed that the neurosurgery unit was likely the source of the outbreak, the strain was likely to have been transmitted to the ICU through patients. In addition, the two highly probable transmission routes were in the ICU (exposure through shared hospital beds) and the neurosurgery units (all cases were treated by the same rehabilitation physician and were most likely infected during the physical therapy). Notably, the bed mattress had played a crucial transmission role of this outbreak, served as a pathogen reservoir.

An implementation science approach to evaluating pathogen whole genome sequencing in public health

BACKGROUND

Pathogen whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide and has the potential to make significant contributions to infectious disease surveillance, outbreak investigation and infection prevention and control. However, to date, there are limited data regarding (i) the optimal models for integration of genomic data into epidemiological investigations and (ii) how to quantify and evaluate public health impacts resulting from genomic epidemiological investigations.

METHODS

We developed the Pathogen Genomics in Public HeAlth Surveillance Evaluation (PG-PHASE) Framework to guide examination of the use of WGS in public health surveillance and disease control. We illustrate the use of this framework with three pathogens as case studies: Listeria monocytogenes, Mycobacterium tuberculosis and SARS-CoV-2.

RESULTS

The framework utilises an adaptable whole-of-system approach towards understanding how interconnected elements in the public health application of pathogen genomics contribute to public health processes and outcomes. The three phases of the PG-PHASE Framework are designed to support understanding of WGS laboratory processes, analysis, reporting and data sharing, and how genomic data are utilised in public health practice across all stages, from the decision to send an isolate or sample for sequencing to the use of sequence data in public health surveillance, investigation and decision-making. Importantly, the phases can be used separately or in conjunction, depending on the need of the evaluator. Subsequent to conducting evaluation underpinned by the framework, avenues may be developed for strategic investment or interventions to improve utilisation of whole genome sequencing.

CONCLUSIONS

Comprehensive evaluation is critical to support health departments, public health laboratories and other stakeholders to successfully incorporate microbial genomics into public health practice. The PG-PHASE Framework aims to assist public health laboratories, health departments and authorities who are either considering transitioning to whole genome sequencing or intending to assess the integration of WGS in public health practice, including the capacity to detect and respond to outbreaks and associated costs, challenges and facilitators in the utilisation of microbial genomics and public health impacts.

Harmonization of whole-genome sequencing for outbreak surveillance of Enterobacteriaceae and Enterococci

Whole-genome sequencing (WGS) is becoming the de facto standard for bacterial typing and outbreak surveillance of resistant bacterial pathogens. However, interoperability for WGS of bacterial outbreaks is poorly understood. We hypothesized that harmonization of WGS for outbreak surveillance is achievable through the use of identical protocols for both data generation and data analysis. A set of 30 bacterial isolates, comprising of various species belonging to the Enterobacteriaceae family and Enterococcus genera, were selected and sequenced using the same protocol on the Illumina MiSeq platform in each individual centre. All generated sequencing data were analysed by one centre using BioNumerics (6.7.3) for (i) genotyping origin of replications and antimicrobial resistance genes, (ii) core-genome multi-locus sequence typing (cgMLST) for Escherichia coli and Klebsiella pneumoniae and whole-genome multi-locus sequencing typing (wgMLST) for all species. Additionally, a split k-mer analysis was performed to determine the number of SNPs between samples. A precision of 99.0% and an accuracy of 99.2% was achieved for genotyping. Based on cgMLST, a discrepant allele was called only in 2/27 and 3/15 comparisons between two genomes, for E. coli and K. pneumoniae, respectively. Based on wgMLST, the number of discrepant alleles ranged from 0 to 7 (average 1.6). For SNPs, this ranged from 0 to 11 SNPs (average 3.4). Furthermore, we demonstrate that using different de novo assemblers to analyse the same dataset introduces up to 150 SNPs, which surpasses most thresholds for bacterial outbreaks. This shows the importance of harmonization of data-processing surveillance of bacterial outbreaks. In summary, multi-centre WGS for bacterial surveillance is achievable, but only if protocols are harmonized.

Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds

Salmonella enterica serovar Typhimurium is the leading cause of salmonellosis in Australia, and the ability to identify outbreaks and their sources is vital to public health. Here, we examined the utility of whole-genome sequencing (WGS), including complete genome sequencing with Oxford Nanopore technologies, in examining 105 isolates from an endemic multi-locus variable number tandem repeat analysis (MLVA) type over 5 years. The MLVA type was very homogeneous, with 90 % of the isolates falling into groups with a five SNP cut-off. We developed a new two-step approach for outbreak detection using WGS. The first clustering at a zero single nucleotide polymorphism (SNP) cut-off was used to detect outbreak clusters that each occurred within a 4 week window and then a second clustering with dynamically increased SNP cut-offs were used to generate outbreak investigation clusters capable of identifying all outbreak cases. This approach offered optimal specificity and sensitivity for outbreak detection and investigation, in particular of those caused by endemic MLVA types or clones with low genetic diversity. We further showed that inclusion of complete genome sequences detected no additional mutational events for genomic outbreak surveillance. Phylogenetic analysis found that the MLVA type was likely to have been derived recently from a single source that persisted over 5 years, and seeded numerous sporadic infections and outbreaks. Our findings suggest that SNP cut-offs for outbreak cluster detection and public-health surveillance should be based on the local diversity of the relevant strains over time. These findings have general applicability to outbreak detection of bacterial pathogens.

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.

Population structure, case clusters, and genetic lesions associated with Canadian Salmonella 4,[5],12:i:- isolates

Monophasic Salmonella 4,[5]:12:i:- are a major public health problem because they are one of the top five Salmonella serotypes isolated from clinical cases globally and because they can carry resistance to multiple antibiotics. A total of 811 Salmonella 4,[5]:12:i:- and S. Typhimurium whole genome sequences (WGS) were generated. The various genetic lesions causing the Salmonella 4,[5]:12:i:- genotype were identified and assessed with regards to their distribution in the population of 811 Salmonella 4,[5]:12:i:- and S. Typhimurium isolates, their geographical and temporal distribution, and their association with non-human sources. Several clades were identified in the population structure, and the largest two were associated almost exclusively with a short prophage insertion and insertion of a mobile element carrying loci encoding antibiotic and mercury resistance. IS26-mediated deletions and fljB point mutants appeared to spread clonally. 'Inconsistent' Salmonella 4,[5]:12:i:- isolates associated with specific, single amino acid changes in fljA and hin were found in a single clade composed of water, shellfish, and avian isolates. Inclusion of isolates from different case clusters identified previously by PFGE validated some of the clusters and invalidated others. Some wgMLST clusters of clinical isolates composed of very closely related isolates contained an isolate(s) with a different genetic lesion, suggesting continuing mobility of the implicated element responsible. Such cases may need to be left out of epidemiological investigations until sufficient numbers of isolates are included that statistical significance of association with sources is not impaired. Non-human sources were frequently found in or near clinical case clusters. Prospective surveillance and WGS of non-human sources and retrospective analysis by WGS of isolates from existing culture collections provides data critical for epidemiological investigations of food- and waterborne outbreaks.

Establishment and Evaluation of a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Pseudomonas aeruginosa

The environmental bacterium Pseudomonas aeruginosa, particularly multidrug-resistant clones, is often associated with nosocomial infections and outbreaks. Today, core genome multilocus sequence typing (cgMLST) is frequently applied to delineate sporadic cases from nosocomial transmissions. However, until recently, no cgMLST scheme for a standardized typing of P. aeruginosa was available. To establish a novel cgMLST scheme for P. aeruginosa, we initially determined the breadth of the P. aeruginosa population based on MLST data with a Bayesian approach (BAPS). Using genomic data of representative isolates for the whole population and all 12 serogroups, we extracted target genes and further refined them using a random data set of 1,000 P. aeruginosa genomes. Subsequently, we investigated reproducibility and discriminatory ability with repeatedly sequenced isolates and isolates from well-defined outbreak scenarios, respectively, and compared clustering applying two recently published cgMLST schemes. BAPS generated seven P. aeruginosa groups. To cover these and all serogroups, 15 reference strains were used to determine genes common in all strains. After refinement with the data set of 1,000 genomes, the cgMLST scheme consisted of 3,867 target genes, which are representative of the P. aeruginosa population and highly reproducible using biological replicates. We finally evaluated the scheme by reanalyzing two published outbreaks where the authors used single-nucleotide polymorphism (SNP) typing. In both cases, cgMLST was concordant with the previous SNP results and the results of the two other cgMLST schemes. In conclusion, the highly reproducible novel P. aeruginosa cgMLST scheme facilitates outbreak investigations due to the publicly available cgMLST nomenclature.

Identification of Galtox, a new protein toxin from Photorhabdus bacterial symbionts of Heterorhabditis nematodes

The Gram-negative bacteria Photorhabdus lives in a symbiotic relationship with the insect-pathogenic Heterorhabditis nematodes and produces numerous hydrolytic enzymes, secondary metabolites and protein toxins. Seven Photorhabdus strains were previously isolated from the Heterorhabditis nematodes collected from different geographical regions of India. The strains IARI-SGMG3, IARI-SGHR2, IARI-SGHR4, IARI-SGMS1 and IARI-SGGJ2 were identified as P. akhurstii, whereas IARI-SGLDK1 and IARI-SGHP1 were identified as P. laumondii subsp. laumondii and P. laumondii subsp. clarkeii, respectively. A new and previously unreported 35 kDa molecular weight protein toxin 'Galtox' was identified from these Photorhabdus strains. The nucleotide sequences of the toxin gene from seven Photorhabdus strains were PCR amplified, sequenced, cloned into pET protein expression vector, and the protein toxin was expressed and purified. The Galtox sequence from various strains showed variations in sequence and toxicity against Galleria mellonella. The injection of purified Galtox protein into the 4th instar larvae showed median lethal dose (LD₅₀) values of 2.39-26.08 ng toxin/g G. mellonella bodyweight after 48 h. The protein injection killed the insects quickly and exhibited a median lethal time (LT₅₀) of 12-60 h when injected at the rate of 3.1-31.2 ng toxin/g G. mellonella bodyweight. Galtox protein sequence analysis indicated similarity to several bacterial toxin-related protein domains, such as 6rgnA domain of Bordetella membrane targeting toxin BteA, 6gy6 domain of Xenorhabdus α-Xenorhabdolysins, 4mu6A and 4xa9a domains similar to effector protein LegC3 from Legionella pneumophila and 1cv8.1 domain of staphylococcal cysteine proteinase staphopain B. The mode of action of Galtox needs to be understood to enable its use for the management of agricultural insect-pests.

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003-2010. Nine isolates were identified as S. Typhimurium sequence type 313 while the other two were S. Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S. Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

One is not enough: On the effects of reference genome for the mapping and subsequent analyses of short-reads

Mapping of high-throughput sequencing (HTS) reads to a single arbitrary reference genome is a frequently used approach in microbial genomics. However, the choice of a reference may represent a source of errors that may affect subsequent analyses such as the detection of single nucleotide polymorphisms (SNPs) and phylogenetic inference. In this work, we evaluated the effect of reference choice on short-read sequence data from five clinically and epidemiologically relevant bacteria (Klebsiella pneumoniae, Legionella pneumophila, Neisseria gonorrhoeae, Pseudomonas aeruginosa and Serratia marcescens). Publicly available whole-genome assemblies encompassing the genomic diversity of these species were selected as reference sequences, and read alignment statistics, SNP calling, recombination rates, dN/dS ratios, and phylogenetic trees were evaluated depending on the mapping reference. The choice of different reference genomes proved to have an impact on almost all the parameters considered in the five species. In addition, these biases had potential epidemiological implications such as including/excluding isolates of particular clades and the estimation of genetic distances. These findings suggest that the single reference approach might introduce systematic errors during mapping that affect subsequent analyses, particularly for data sets with isolates from genetically diverse backgrounds. In any case, exploring the effects of different references on the final conclusions is highly recommended.

Mapping consists in the alignment of reads (i.e., DNA fragments) obtained through high-throughput genome sequencing to a previously assembled reference sequence. It is a common practice in genomic studies to use a single reference for mapping, usually the ‘reference genome’ of a species—a high-quality assembly. However, the selection of an optimal reference is hindered by intrinsic intra-species genetic variability, particularly in bacteria. It is known that genetic differences between the reference genome and the read sequences may produce incorrect alignments during mapping. Eventually, these errors could lead to misidentification of variants and biased reconstruction of phylogenetic trees (which reflect ancestry between different bacterial lineages). To our knowledge, this is the first work to systematically examine the effect of different references for mapping on the inference of tree topology as well as the impact on recombination and natural selection inferences. Furthermore, the novelty of this work relies on a procedure that guarantees that we are evaluating only the effect of the reference. This effect has proved to be pervasive in the five bacterial species that we have studied and, in some cases, alterations in phylogenetic trees could lead to incorrect epidemiological inferences. Hence, the use of different reference genomes may be prescriptive to assess the potential biases of mapping.

Antibiotic Resistance and Phylogeny of Pseudomonas spp. Isolated over Three Decades from Chicken Meat in the Norwegian Food Chain

Pseudomonas is ubiquitous in nature and a predominant genus in many foods and food processing environments, where it primarily represents major food spoilage organisms. The food chain has also been reported to be a potential reservoir of antibiotic-resistant Pseudomonas. The purpose of the current study was to determine the occurrence of antibiotic resistance in psychrotrophic Pseudomonas spp. collected over a time span of 26 years from retail chicken in Norway and characterize their genetic diversity, phylogenetic distribution and resistance genes through whole-genome sequence analyses. Among the 325 confirmed Pseudomonas spp. isolates by 16S rRNA gene sequencing, antibiotic susceptibility profiles of 175 isolates to 12 antibiotics were determined. A subset of 31 isolates being resistant to ≥3 antibiotics were whole-genome sequenced. The isolates were dominated by species of the P. fluorescens lineage. Isolates susceptible to all antibiotics or resistant to ≥3 antibiotics comprised 20.6% and 24.1%, respectively. The most common resistance was to aztreonam (72.6%), colistin (30.2%), imipenem (25.6%) and meropenem (12.6%). Resistance properties appeared relatively stable over the 26-year study period but with taxa-specific differences. Whole-genome sequencing showed high genome variability, where isolates resistant to ≥3 antibiotics belonged to seven species. A single metallo-betalactmase gene (cphA) was detected, though intrinsic resistance determinants dominated, including resistance–nodulation (RND), ATP-binding cassette (ABC) and small multidrug resistance (Smr) efflux pumps. This study provides further knowledge on the distribution of psychrotrophic Pseudomonas spp. in chicken meat and their antibiotic resistance properties. Further monitoring should be encouraged to determine food as a source of antibiotic resistance and maintain the overall favorable situation with regard to antibiotic resistance in the Norwegian food chain.

Development of a Genoserotyping Method for Salmonella Infantis Detection on the Basis of Pangenome Analysis

In recent years, Salmonella Infantis has become a predominant serovariant in clinical and poultry isolates, thereby imposing a substantial economic burden on both public health and the livestock industry. With the aim of coping with the steep increase in serovar Infantis prevalence, a polymerase chain reaction (PCR)-based rapid and accurate diagnostic assay was developed in this study through pangenome profiling of 60 Salmonella serovars. A gene marker, SIN_02055, was identified, which is present in the S. Infantis genome but not in the pangenome of the other serovars. Primers specific to SIN_02055 were used to accurately detect serovar Infantis, and to successfully differentiate Infantis from the other 59 serovars in real-time PCR with a R² of 0.999 and an efficiency of 95.76%. The developed method was applied to 54 Salmonella strains belonging to eight dominant serovars, and distinguished Infantis from the other seven serovars with an accuracy of 100%. The diagnostic primer set also did not show false positive amplification with 32 strains from eight non-Salmonella bacterial species. This cost-effective and rapid method can be considered an alternative to the classic serotyping using antisera.

Nonsynonymous Polymorphism Counts in Bacterial Genomes: a Comparative Examination

Genomic data reveal single-nucleotide polymorphisms (SNPs) that may carry information about the evolutionary history of bacteria. However, it remains unclear what inferences about selection can be made from genomic SNP data. Bacterial species are often sampled during epidemic outbreaks or within hosts during the course of chronic infections. SNPs obtained from genomic analysis of these data are not necessarily fixed. Treating them as fixed during analysis by using measures such as the ratio of nonsynonymous to synonymous evolutionary changes (dN/dS) may lead to incorrect inferences about the strength and direction of selection. In this study, we consider data from a range of whole-genome sequencing studies of bacterial pathogens and explore patterns of nonsynonymous variation to assess whether evidence of selection can be identified by investigating SNP counts alone across multiple WGS studies. We visualize these SNP data in ways that highlight their relationship to neutral baseline expectations. These neutral expectations are based on a simple model of mutation, from which we simulate SNP accumulation to investigate how SNP counts are distributed under alternative assumptions about positive and negative selection. We compare these patterns with empirical SNP data and illustrate the general difficulty of detecting positive selection from SNP data. Finally, we consider whether SNP counts observed at the between-host population level differ from those observed at the within-host level and find some evidence that suggests that dynamics across these two scales are driven by different underlying processes.IMPORTANCE Identifying selection from SNP data obtained from whole-genome sequencing studies is challenging. Some current measures used to identify and quantify selection acting on genomes rely on fixed differences; thus, these are inappropriate for SNP data where variants are not fixed. With the increase in whole-genome sequencing studies, it is important to consider SNP data in the context of evolutionary processes. How SNPs are counted and analyzed can help in understanding mutation accumulation and trajectories of strains. We developed a tool for identifying possible evidence of selection and for comparative analysis with other SNP data. We propose a model that provides a rule-of-thumb guideline and two new visualization techniques that can be used to interpret and compare SNP data. We quantify the expected proportion of nonsynonymous SNPs in coding regions under neutrality and demonstrate its use in identifying evidence of positive and negative selection from simulations and empirical data.

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.

Diverse lineages of multidrug resistant clinical Salmonella enterica and a cryptic outbreak in New Hampshire, USA revealed from a year-long genomic surveillance

Salmonella enterica, the causative agent of gastrointestinal diseases and typhoid fever, is a human and animal pathogen that causes significant mortality and morbidity worldwide. In this study, we examine the genomic diversity and phylogenetic relationships of 63 S. enterica isolates from human-derived clinical specimens submitted to the Department of Health and Human Services (DHHS) in the state of New Hampshire, USA in 2017. We found a remarkably large genomic, phylogenetic and serotype variation among the S. enterica isolates, dominated by serotypes Enteritidis (sequence type [ST] 11), Heidelberg (ST 15) and Typhimurium (ST 19). Analysis of the distribution of single nucleotide polymorphisms in the core genome suggests that the ST 15 cluster is likely a previously undetected or cryptic outbreak event that occurred in the south/southeastern part of New Hampshire in August-September. We found that nearly all of the clinical S. enterica isolates carried horizontally acquired genes that confer resistance to multiple classes of antimicrobials, most notably aminoglycosides, fluoroquinolones and macrolides. Majority of the isolates (76.2%) carry at least four resistance determinants per genome. We also detected the genes mdtK and mdsABC that encode multidrug efflux pumps and the gene sdiA that encodes a regulator for a third multidrug resistance pump. Our results indicate rapid microevolution and geographical dissemination of multidrug resistant lineages over a short time span. These findings are critical to aid the DHHS and similar public health laboratories in the development of effective disease control measures, epidemiological studies and treatment options for serious Salmonella infections.

A Vibrio cholerae Core Genome Multilocus Sequence Typing Scheme To Facilitate the Epidemiological Study of Cholera

Core genome multilocus sequence typing (cgMLST) has gained popularity in recent years in epidemiological research and subspecies-level classification. cgMLST retains the intuitive nature of traditional MLST but offers much greater resolution by utilizing significantly larger portions of the genome. Here, we introduce a cgMLST scheme for Vibrio cholerae, a bacterium abundant in marine and freshwater environments and the etiologic agent of cholera. A set of 2,443 core genes ubiquitous in V. cholerae were used to analyze a comprehensive data set of 1,262 clinical and environmental strains collected from 52 countries, including 65 newly sequenced genomes in this study. We established a sublineage threshold based on 133 allelic differences that creates clusters nearly identical to traditional MLST types, providing backwards compatibility to new cgMLST classifications. We also defined an outbreak threshold based on seven allelic differences that is capable of identifying strains from the same outbreak and closely related isolates that could give clues on outbreak origin. Using cgMLST, we confirmed the South Asian origin of modern epidemics and identified clustering affinity among sublineages of environmental isolates from the same geographic origin. Advantages of this method are highlighted by direct comparison with existing classification methods, such as MLST and single-nucleotide polymorphism-based methods. cgMLST outperforms all existing methods in terms of resolution, standardization, and ease of use. We anticipate this scheme will serve as a basis for a universally applicable and standardized classification system for V. cholerae research and epidemiological surveillance in the future. This cgMLST scheme is publicly available on PubMLST (https://pubmlst.org/vcholerae/).IMPORTANCE Toxigenic Vibrio cholerae isolates of the O1 and O139 serogroups are the causative agents of cholera, an acute diarrheal disease that plagued the world for centuries, if not millennia. Here, we introduce a core genome multilocus sequence typing scheme for V. cholerae Using this scheme, we have standardized the definition for subspecies-level classification, facilitating global collaboration in the surveillance of V. cholerae In addition, this typing scheme allows for quick identification of outbreak-related isolates that can guide subsequent analyses, serving as an important first step in epidemiological research. This scheme is also easily scalable to analyze thousands of isolates at various levels of resolution, making it an invaluable tool for large-scale ecological and evolutionary analyses.

Comparative Genomics of Plasmid-Bearing Staphylococcus aureus Strains Isolated From Various Retail Meats

Food poisoning due to the consumption of Staphylococcus aureus contaminated food is a major health problem worldwide. In this study, we sequenced the genomes of ten plasmid-bearing S. aureus strains isolated from retail beef, chicken, turkey, and pork. The chromosomes of the strains varied in size from 2,654,842 to 2,807,514 bp, and a total of 25 plasmids were identified ranging from 1.4 to 118 kb. Comparative genomic analysis revealed similarities between strains isolated from the same retail meat source, indicating an origin-specific genomic composition. Genes known to modulate attachment, invasion, and toxin production were identified in the 10 genomes. Strains from retail chicken resembled human clinical isolates with respect to virulence factors and genomic islands, and retail turkey and pork isolates shared similarity with S. aureus from livestock. Most chromosomes contained antimicrobial resistance, heavy metal resistance, and stress response genes, and several plasmids contained genes involved in antimicrobial resistance and virulence. In conclusion, the genomes of S. aureus strains isolated from retail meats showed an origin-specific composition and contained virulence and antimicrobial resistance genes similar to those present in human clinical isolates.

Whole genome sequence of first Candida auris strain, isolated in Russia

Candida auris is an emergent yeast pathogen, easily transmissible between patients and with high percent of multidrug resistant strains. Here we present a draft genome sequence of the first known Russian strain of C. auris, isolated from a case of candidemia. The strain clustered within South Asian C. auris clade and seemingly represented an independent event of dissemination from the original species range. Observed fluconazole resistance was probably due to F105L and K143R mutations in ERG11.

Comparison of conventional molecular and whole-genome sequencing methods for subtyping Salmonella enterica serovar Enteritidis strains from Tunisia

We sought to determine the relative value of conventional molecular methods and whole-genome sequencing (WGS) for subtyping Salmonella enterica serovar Enteritidis recovered from 2000 to 2015 in Tunisia and to investigate the genetic diversity of this serotype. A total of 175 Salmonella Enteritidis isolates were recovered from human, animal, and foodborne outbreak samples. Pulsed-field gel electrophoresis (PFGE), multiple locus variable-number tandem repeat analysis (MLVA), and whole-genome sequencing were performed. Eight pulsotypes were detected for all isolates with PFGE (DI = 0.518). Forty-five Salmonella Enteritidis isolates were selected for the MLVA and WGS techniques. Eighteen MLVA profiles were identified and classified into two major clusters (DI = 0.889). Core genome multilocus typing (cgMLST) analysis revealed 16 profiles (DI = 0.785). Whole-genome analysis indicated 660 single-nucleotide polymorphism (SNP) divergences dividing these isolates into 43 haplotypes (DI = 0.997). The phylogenetic tree supported the classification of Salmonella Enteritidis isolates into two distinct lineages subdivided into five clades and seven subclades. Pairwise SNP differences between the isolates ranged between 302 and 350. We observed about 311 SNP differences between the two foodborne outbreaks, while only less or equal to 4 SNP differences within each outbreak. SNP-based WGS typing showed an excellent discriminatory power comparing with the conventional methods such as PFGE and MLVA. Besides, we demonstrate the added value of WGS as a complementary subtyping method to discriminate outbreak from non-outbreak isolates belonging to common subtypes. It is important to continue the survey of Salmonella Enteritidis lineages in Tunisia using WGS.

Phylogenomic analysis of Mycoplasma bovis from Belgian veal, dairy and beef herds

M. bovis is one of the leading causes of respiratory disease and antimicrobial use in cattle. The pathogen is widespread in different cattle industries worldwide, but highest prevalence is found in the veal industry. Knowledge on M. bovis strain distribution over the dairy, beef and veal industries is crucial for the design of effective control and prevention programs, but currently undocumented. Therefore, the present study evaluated the molecular epidemiology and genetic relatedness of M. bovis isolates obtained from Belgian beef, dairy and veal farms, and how these relate to M. bovis strains obtained worldwide. Full genomes of one hundred Belgian M. bovis isolates collected over a 5-year period (2014–2019), obtained from 27 dairy, 38 beef and 29 veal farms, were sequenced by long-read nanopore sequencing. Consensus sequences were used to generate a phylogenetic tree in order to associate genetic clusters with cattle sector, geographical area and year of isolation. The phylogenetic analysis of the Belgian M. bovis isolates resulted in 5 major clusters and 1 outlier. No sector-specific M. bovis clustering was identified. On a world scale, Belgian isolates clustered with Israeli, European and American strains. Different M. bovis clusters circulated for at least 1.5 consecutive years throughout the country, affecting all observed industries. Therefore, the high prevalence in the veal industry is more likely the consequence of frequent purchase from the dairy and beef industry, than that a reservoir of veal specific strains on farm would exist. These results emphasize the importance of biosecurity in M. bovis control and prevention.

Population structure of Salmonella enterica serotype Mbandaka reveals similar virulence potential irrespective of source and phylogenomic stratification

Background: Salmonella enterica serotype Mbandaka ( Salmonella ser. Mbandaka) is a multi-host adapted Non-typhoidal Salmonella (NTS) that can cause foodborne illnesses in human. Outbreaks of Salmonella ser. Mbandaka contributed to the economic stress caused by NTS due to hospitalizations. Whole genome sequencing (WGS)-based phylogenomic analysis facilitates better understanding of the genomic features that may expedite the foodborne spread of Salmonella ser. Mbandaka. Methods: In the present study, we define the population structure, antimicrobial resistance (AMR), and virulence profile of Salmonella ser. Mbandaka using WGS data of more than 400 isolates collected from different parts of the world. We validated the genotypic prediction of AMR and virulence phenotypically using an available set of representative isolates. Results: Phylogenetic analysis of Salmonella ser. Mbandaka using Bayesian approaches revealed clustering of the population into two major groups; however, clustering of these groups and their subgroups showed no pattern based on the host or geographical origin. Instead, we found a uniform virulence gene repertoire in all isolates. Phenotypic analysis on a representative set of isolates showed a similar trend in cell invasion behavior and adaptation to a low pH environment. Both genotypic and phenotypic analysis revealed the carriage of multidrug resistance (MDR) genes in Salmonella ser. Mbandaka. Conclusions: Overall, our results show that the presence of multidrug resistance along with adaptation to broad range of hosts and uniformity in the virulence potential, isolates of Salmonella ser. Mbandaka from any source could have the potential to cause foodborne outbreaks as well as AMR dissemination.

Frequency of Antimicrobial Resistance Genes in Salmonella From Brazil by in silico Whole-Genome Sequencing Analysis: An Overview of the Last Four Decades

Salmonella is a leading human pathogen and a significant public health concern worldwide. Massive food production and distribution have contributed to this pathogen dissemination, which, combined with antimicrobial resistance (AMR), creates new control challenges in food safety. The development of AMR is a natural phenomenon and can occur in the bacterial evolutionary process. However, the overuse and the misuse of antimicrobial drugs in humans and in animals have increased AMR selective pressure. In Brazil, there is an accuracy lack in AMR frequency in Salmonella because too many isolates are under-investigated for genetic and phenotypic AMR by the Brazilian health authorities and the research community. This underreporting situation makes the comprehension of the real level of Salmonella AMR in the country difficult. The present study aimed to use bioinformatics tools for a rapid in silico screening of the genetic antimicrobial resistance profile of Salmonella through whole-genome sequences (WGS). A total of 930 whole-genome sequences of Salmonella were retrieved from the public database of the National Biotechnology Information Center (NCBI). A total of 65 distinct resistance genes were detected, and the most frequent ones were tet(A), sul2, and fosA7. Nine point mutations were detected in total, and parC at the 57 position (threonine → serine) was the highest frequent substitution (26.7%, 249/930), followed by gyrA at the 83 position (serine → phenylalanine) (20.0%, 186/930) and at the 87 position (aspartic acid → asparagine) (15.7%, 146/930). The in silico prediction of resistance phenotype showed that 58.0% (540/930) of the strains can display a multidrug resistance (MDR) profile. Ciprofloxacin and nalidixic acid were the antimicrobial drugs with the highest frequency rates of the predicted phenotype resistance among the strains. The temporal analysis through the last four decades showed increased frequency rates of antimicrobial resistance genes and predicted resistance phenotypes in the 2000s and the 2010s when compared with the 1980s and 1990s. The results presented herein contributed significantly to the understanding of the strategic use of WGS associated with in silico analysis and the predictions for the determination of AMR in Salmonella from Brazil.

Comprehensive integrated NGS-based surveillance and contact-network modeling unravels transmission dynamics of vancomycin-resistant enterococci in a high-risk population within a tertiary care hospital

Vancomycin-resistant E. faecium (VRE) are an important cause of nosocomial infections, which are rapidly transmitted in hospitals. To identify possible transmission routes, we applied combined genomics and contact-network modeling to retrospectively evaluate routine VRE screening data generated by the infection control program of a hemato-oncology unit. Over 1 year, a total of 111 VRE isolates from 111 patients were collected by anal swabs in a tertiary care hospital in Southern Germany. All isolated VRE were whole-genome sequenced, followed by different in-depth bioinformatics analyses including genotyping and determination of phylogenetic relations, aiming to evaluate a standardized workflow. Patient movement data were used to overlay sequencing data to infer transmission events and strain dynamics over time. A predominant clone harboring vanB and exhibiting genotype ST117/CT469 (n = 67) was identified. Our comprehensive combined analyses suggested intra-hospital spread, especially of clone ST117/CT469, despite of extensive screening, single room placement, and contact isolation. A new interactive tool to visualize these complex data was designed. Furthermore, a patient-contact network-modeling approach was developed, which indicates both the periodic import of the clone into the hospital and its spread within the hospital due to patient movements. The analyzed spread of VRE was most likely due to placement of patients in the same room prior to positivity of screening. We successfully demonstrated the added value for this combined strategy to extract well-founded knowledge from interdisciplinary data sources. The combination of patient-contact modeling and high-resolution typing unraveled the transmission dynamics within the hospital department and, additionally, a constant VRE influx over time.

Genetic diversity of clinical Salmonella enterica serovar Typhimurium in a university hospital of south Tunisia, 2000-2013

Typhimurium is one of the main Salmonella serovar responsible for non-typhoidal gastro-enteritis in Tunisia. Here, we aimed to assess the genetic diversity of 88 clinical Salmonella Typhimurium strains recovered during 14 years from 2000 to 2013. Phage typing, CRISPR polymorphisms (CRISPOL), pulsed-field gel electrophoresis (PFGE), multi-locus variable-number tandem repeat analysis (MLVA) and Whole genome sequencing (WGS) were used to study the relatedness and spatio-temporal evolution of Salmonella Typhimurium populations (Typhimurium (n = 81), monophasic (n = 3) and nonmotile (n = 4) variants). Seven-locus MLST from whole genome assemblies showed that all isolates, except one, belonged to ST19. The isolates were divided into 10 definitive phage (DT) types, dominated by DT104-L (39.8%), DT41 (14.8%), DT116 (11.4%) and DT120 (5.7%). Fifty-seven MLVA patterns (DI, 0.978) were obtained compared to 11 different CRISPOL types and 15 PFGE types (DI,0.845). For cgMLST analysis, 20 profiles were found. A total of 3056 SNPs were identified from the whole genome of the 88 Salmonella Typhimurium isolates. These SNPs resolved these isolates into 86 SNP haplotypes. The phylogeny result allocated most Salmonella Typhimurium isolates into four distinct clades and seven subclades. Genetic diversity between the four clades ranged in the order of 249 to 720 nucleotide changes. The prevalent phage type DT104L formed a major clade on the phylogenetic tree. Pairwise SNP differences between the strains of this clade ranged between 0 and 59. SNP-based WGS typing seems to be the most valuable molecular markers for studying the evolutionary relationships of homogeneous serovar Typhimurium isolates.

Prospective Salmonella Enteritidis surveillance and outbreak detection using whole genome sequencing, Minnesota 2015-2017

Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health using both pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism analysis from 1 January 2015 through 31 December 2017. The median turnaround time for obtaining WGS results was 11 days longer than for PFGE (12 vs. 1 day). WGS analysis more than doubled the number of clusters compared to PFGE analysis, but reduced the total number of cases included in clusters by 34%. The median cluster size was two cases for WGS compared to four for PFGE, and the median duration of WGS clusters was 27 days shorter than PFGE clusters. While the percentage of PFGE clusters with a confirmed source (46%) was higher than WGS clusters (32%), a higher percentage of cases in clusters that were confirmed as outbreaks reported the vehicle or exposure of interest for WGS (78%) than PFGE (46%). WGS cluster size was a significant predictor of an outbreak source being confirmed. WGS data have enhanced S. Enteritidis cluster investigations in Minnesota by improving the specificity of cluster case definitions and has become an integral part of the S. Enteritidis surveillance process.

Whole genome sequencing (WGS) fails to detect antimicrobial resistance (AMR) from heteroresistant subpopulation of Salmonella enterica

Due to rapidly falling costs, whole genome sequencing (WGS) is becoming an essential tool in the surveillance of antimicrobial resistance (AMR) in Salmonella enterica. Although there have been many recent works evaluating the accuracy of WGS in predicting AMR from a large number of Salmonella isolates, little attention has been devoted to deciphering the underlying causes of disagreement between the WGS genotype and experimentally determined AMR phenotype. This study analyzed the genomes of six S. enterica isolates previously obtained from raw chicken which exhibited disagreements between WGS genotype and AMR phenotype. A total of five WGS false negative predictions toward ampicillin, amoxicillin/clavulanate, colistin, and fosfomycin resistance were presented in conjunction with their corresponding empirical phenotypic and/or genetic evidence of heteroresistance. A further case study highlighting the inherent limitations of WGS to detect the underlying genetic mechanisms of colistin heteroresistance was presented. These findings implicate heteroresistance as an underlying cause for false negative WGS-based AMR predictions in S. enterica and suggest that widespread use of WGS in the surveillance of AMR in food isolates might severely underestimate true resistance rates.