Comparison of whole genome sequencing typing results and epidemiological contact information from outbreaks of Salmonella Dublin in Swedish cattle herds

Using SNP addresses for Salmonella Typhimurium DT104 in routine veterinary outbreak detection

SNP addresses are a pathogen typing method based on whole-genome sequences (WGSs), assigning groups at seven different levels of genetic similarity. Public health surveillance uses it for several gastro-intestinal infections; this work trialled its use in veterinary surveillance for salmonella outbreak detection. Comparisons were made between temporal and spatio-temporal cluster detection models that either defined cases by their SNP address or by phage type, using historical data sets. Clusters of SNP incidents were effectively detected by both methods, but spatio-temporal models consistently detected these clusters earlier than the corresponding temporal models. Unlike phage type, SNP addresses appeared spatially and temporally limited, which facilitated the differentiation of novel, stable, or expanding clusters in spatio-temporal models. Furthermore, these models flagged spatio-temporal clusters containing only two to three cases at first detection, compared with a median of seven cases in phage-type models. The large number of SNP addresses will require automated methods to implement these detection models routinely. Further work is required to explore how temporal changes and different host species may impact the sensitivity and specificity of cluster detection. In conclusion, given validation with more sequencing data, SNP addresses are likely to be a valuable addition to early warning systems in veterinary surveillance.

Clonal relation between Salmonella enterica subspecies enterica serovar Dublin strains of bovine and food origin in Germany

Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) is a host-adapted serovar causing enteritis and/or systemic diseases in cattle. As the serovar is not host-restricted, it may cause infections in other animals, including humans with severe illness and higher mortality rates than other non-typhoidal serovars. As human infections are mainly caused by contaminated milk, milk products and beef, information on the genetic relationship of S. Dublin strains from cattle and food should be evaluated. Whole-genome sequencing (WGS) of 144 S. Dublin strains from cattle and 30 strains from food origin was performed. Multilocus sequence typing (MLST) revealed mostly sequence type ST-10 from both, cattle and food isolates. In total, 14 of 30 strains from food origin were clonally related to at least one strain from cattle, as detected by core-genome single nucleotide polymorphisms typing as well as core-genome MLST. The remaining 16 foodborne strains fit into the genome structure of S. Dublin in Germany without outliers. WGS proved to be a powerful tool not only to gain information on the epidemiology of Salmonella strains but also to detect clonal relations between organisms isolated from different stages of production. This study has shown a high genetic correlation between S. Dublin strains from cattle and food and, therefore, the potential to cause human infections. S. Dublin strains of both origins share an almost identical set of virulence factors, emphasizing their potential to cause severe clinical manifestations in animals, but also in humans and thus the need for effective control of S. Dublin in a farm-to-fork strategy.

Whole-Genome Investigation of Salmonella Dublin Considering Mountain Pastures as Reservoirs in Southern Bavaria, Germany

Worldwide, Salmonella Dublin (S. Dublin) is responsible for clinical disease in cattle and also in humans. In Southern Bavaria, Germany, the serovar was identified as a causative agent for 54 animal disease outbreaks in herds between 2017 and 2021. Most of these emerged from cattle herds (n = 50). Two occurred in pig farms and two in bovine herds other than cattle. Genomic analysis of 88 S. Dublin strains isolated during these animal disease outbreaks revealed 7 clusters with 3 different MLST-based sequence types and 16 subordinate cgMLST-based complex types. Antimicrobial susceptibility investigation revealed one resistant and three intermediate strains. Furthermore, only a few genes coding for bacterial virulence were found among the isolates. Genome analysis enables pathogen identification and antimicrobial susceptibility, serotyping, phylogeny, and follow-up traceback analysis. Mountain pastures turned out to be the most likely locations for transmission between cattle of different herd origins, as indicated by epidemiological data and genomic traceback analyses. In this context, S. Dublin shedding was also detected in asymptomatic herding dogs. Due to the high prevalence of S. Dublin in Upper Bavaria over the years, we suggest referring to this administrative region as "endemic". Consequently, cattle should be screened for salmonellosis before and after mountain pasturing.

Epidemiological Analysis of Salmonella enterica subsp. enterica Serovar Dublin in German Cattle Herds Using Whole-Genome Sequencing

Salmonella enterica subsp. enterica serovar Dublin is a cattle-adapted serovar that causes enteritis and systemic diseases in animals. In Germany, S. Dublin is not detected or is very rarely detected in some federal states but is endemic in certain regions. Information on detailed genetic characteristics of S. Dublin is not available. An understanding of the paths and spreading of S. Dublin within and between regions and over time is essential to establish effective control strategies. Whole-genome sequencing (WGS) and bioinformatic analysis were used to explore the genetic traits of S. Dublin and to determine their epidemiological context. Seventy-four S. Dublin strains collected in 2005 to 2018 from 10 federal states were studied. The phylogeny was analyzed using core-genome single-nucleotide polymorphisms (cgSNPs) and core-genome multilocus sequence typing. Genomic clusters at 100 cgSNPs, 40 cgSNPs, and 15 cgSNPs were selected for molecular epidemiology. WGS-based genoserotyping confirmed serotyping. Important specific virulence determinants were detected in all strains, but multidrug resistance in German S. Dublin organisms is uncommon. Use of different thresholds for cgSNP analysis enabled a broad view and also a detailed view of the occurrence of S. Dublin in Germany. Genomic clusters could be allocated nationwide, to a limited number of federal states, or to special regions only. Results indicate both persistence and spread of S. Dublin within and between federal states in short and longer time periods. However, to detect possible routes of infection or persistence of S. Dublin indicated by genomic analysis, information on the management of the cattle farms and contacts with corresponding farms are essential.

IMPORTANCESalmonella enterica subsp. enterica serovar Dublin is a bovine host-adapted serovar that causes up to 50% of all registered outbreaks of salmonellosis in cattle in Germany. S. Dublin is not detected or is only rarely detected in some federal states but has been endemic in certain regions of the country for a long time. Information on genetic traits of the causative strains is essential to determine routes of infection. WGS and bioinformatic analysis should be used to explore the genetic characteristics of S. Dublin. Combining the genomic features of S. Dublin strains with information on the management of the cattle farms concerned should enable the detection of possible routes of infection or persistence of S. Dublin. This approach is regarded as a prerequisite to developing effective intervention strategies.

Monitoring the Microevolution of Salmonella enterica in Healthy Dairy Cattle Populations at the Individual Farm Level Using Whole-Genome Sequencing

Livestock represent a possible reservoir for facilitating the transmission of the zoonotic foodborne pathogen Salmonella enterica to humans; there is also concern that strains can acquire resistance to antimicrobials in the farm environment. Here, whole-genome sequencing (WGS) was used to characterize Salmonella strains (n = 128) isolated from healthy dairy cattle and their associated environments on 13 New York State farms to assess the diversity and microevolution of this important pathogen at the level of the individual herd. Additionally, the accuracy and concordance of multiple in silico tools are assessed, including: (i) two in silico serotyping tools, (ii) combinations of five antimicrobial resistance (AMR) determinant detection tools and one to five AMR determinant databases, and (iii) one antimicrobial minimum inhibitory concentration (MIC) prediction tool. For the isolates sequenced here, in silico serotyping methods outperformed traditional serotyping and resolved all un-typable and/or ambiguous serotype assignments. Serotypes assigned in silico showed greater congruency with the Salmonella whole-genome phylogeny than traditional serotype assignments, and in silico methods showed high concordance (99% agreement). In silico AMR determinant detection methods additionally showed a high degree of concordance, regardless of the pipeline or database used (≥98% agreement among susceptible/resistant assignments for all pipeline/database combinations). For AMR detection methods that relied exclusively on nucleotide BLAST, accuracy could be maximized by using a range of minimum nucleotide identity and coverage thresholds, with thresholds of 75% nucleotide identity and 50-60% coverage adequate for most pipeline/database combinations. In silico characterization of the microevolution and AMR dynamics of each of six serotype groups (S. Anatum, Cerro, Kentucky, Meleagridis, Newport, Typhimurium/Typhimurium variant Copenhagen) revealed that some lineages were strongly associated with individual farms, while others were distributed across multiple farms. Numerous AMR determinant acquisition and loss events were identified, including the recent acquisition of cephalosporin resistance-conferring bla CMY- and bla CTX-M-type beta-lactamases. The results presented here provide high-resolution insight into the temporal dynamics of AMR Salmonella at the scale of the individual farm and highlight both the strengths and limitations of WGS in tracking zoonotic pathogens and their associated AMR determinants at the livestock-human interface.

Disentangling a complex nationwide Salmonella Dublin outbreak associated with raw-milk cheese consumption, France, 2015 to 2016

On 18 January 2016, the French National Reference Centre for Salmonella reported to Santé publique France an excess of Salmonella enterica serotype Dublin (S. Dublin) infections. We investigated to identify the source of infection and implement control measures. Whole genome sequencing (WGS) and multilocus variable-number tandem repeat analysis (MLVA) were performed to identify microbiological clusters and links among cases, animal and food sources. Clusters were defined as isolates with less than 15 single nucleotide polymorphisms determined by WGS and/or with identical MLVA pattern. We compared different clusters of cases with other cases (case–case study) and controls recruited from a web-based cohort (case–control study) in terms of food consumption. We interviewed 63/83 (76%) cases; 2,914 controls completed a questionnaire. Both studies’ findings indicated that successive S. Dublin outbreaks from different sources had occurred between November 2015 and March 2016. In the case–control study, cases of distinct WGS clusters were more likely to have consumed Morbier (adjusted odds ratio (aOR): 14; 95% confidence interval (CI): 4.8–42) or Vacherin Mont d’Or (aOR: 27; 95% CI: 6.8–105), two bovine raw-milk cheeses. Based on these results, the Ministry of Agriculture launched a reinforced control plan for processing plants of raw-milk cheeses in the production region, to prevent future outbreaks.

Epidemiology of Salmonella enterica Serovar Dublin in Cattle and Humans in Denmark, 1996 to 2016: a Retrospective Whole-Genome-Based Study

Salmonella enterica serovar Dublin is a cattle-adapted S. enterica serovar causing both intestinal and systemic infection in its bovine host, and it is also a serious threat to human health. The present study aimed to determine the population structure of S Dublin isolates obtained from Danish cattle herds and to investigate how cattle isolates relate to Danish human isolates, as well as to non-Danish human and bovine isolates. Phylogenetic analysis of 197 Danish cattle isolates from 1996 to 2016 identified three major clades corresponding to distinct geographical regions of cattle herds. Persistence of closely related isolates within the same herd and their circulation between epidemiologically linked herds for a period of more than 20 years were demonstrated. These findings suggest that a lack of internal biosecurity and, to some extent, also a lack of external biosecurity in the herds have played an important role in the long-term persistence of S Dublin in Danish cattle herds in the period investigated. Global population analysis revealed that Danish cattle isolates clustered separately from bovine isolates from other countries, whereas human isolates were geographically spread. Resistance genes were not commonly demonstrated in Danish bovine isolates; only the isolates within one Danish clade were found to often harbor two plasmids of IncFII/IncFIB and IncN types, the latter plasmid carrying bla _TEM-1, tetA, strA, and strB antibiotic resistance genes.IMPORTANCE S Dublin causes economic losses in cattle production, and the bacterium is a public health concern. A surveillance and control program has been in place in Denmark since 2002 with the ultimate goal to eradicate S Dublin from Danish cattle herds; however, a small proportion of herds have remained positive for many years. In this study, we demonstrate that herds with persistent infection often were infected with the same strain for many years, indicating that internal biosecurity has to be improved to curb the infection. Further, domestic cases of S Dublin infection in humans were found to be caused both by Danish cattle isolates and by isolates acquired abroad. This study shows the strength of whole-genome sequencing to obtain detailed information on epidemiology of S Dublin and allows us to suggest internal biosecurity as a main way to control this bacterium in Danish cattle herds.

Prevalence and genomic characteristics of zoonotic gastro-intestinal pathogens and ESBL/pAmpC producing Enterobacteriaceae among Swedish corvid birds

Introduction: Wild birds pose a potential threat to animal and human health by spreading infectious diseases. In the present study, we studied the occurrence of bacterial zoonotic pathogens as well as enterobacteria with transferrable antimicrobial resistance genes among Swedish corvids. Materials and methods: Intestines from 66 jackdaws, crows, rooks and magpies from the vicinity of livestock farms at 14 locations in 7 counties were analysed by direct culture or PCR screening followed by culture. Isolates were investigated by whole-genome sequencing. Results and discussion: Campylobacter jejuni were detected in 82% and Yersinia in 3% of the birds. ESBL-producing E. coli were found in one sample (2%) and carried bla CTX-M-55. No Enterobacteriaceae with transferable carbapenem resistance were identified. No Salmonella or E. coli O157:H7 were found, but PCR analysis for enterohaemorrhagic E. coli virulence genes revealed 35% positive samples for intimin, 9% for verotoxin 1 and 17% for verotoxin 2. C. jejuni isolates from corvids were compared to previously published isolates from Swedish sources by multi-locus sequence typing based on genome sequences. All corvid C. jejuni isolates formed a cluster, intermingled with human and chicken isolates. Our results indicate that C. jejuni is ubiquitous among Swedish corvid birds, with sporadic transmission to poultry and humans.

Genomic Investigation of the Emergence of Invasive Multidrug-Resistant Salmonella enterica Serovar Dublin in Humans and Animals in Canada

Salmonella enterica subsp. enterica serovar Dublin is a zoonotic pathogen that often leads to invasive bloodstream infections in humans that are multidrug resistant. Described here are the results of Canadian national surveillance of S Dublin from 2003 to 2015 in humans and bovines, principally collected through the Canadian Integrated Program for Antibiotic Resistance Surveillance (CIPARS). An increase in human infections due to multidrug-resistant (MDR) S Dublin was observed in 2010, many of which were bloodstream infections. Phylogenomic analysis of human and bovine isolates revealed a closely related network that differed by only 0 to 17 single nucleotide variants (SNVs), suggesting some potential transmission between humans and bovines. Phylogenomic comparison of global publicly available sequences of S Dublin showed that Canadian isolates clustered closely with those from the United States. A high correlation between phenotypic and genotypic antimicrobial susceptibility was observed in Canadian isolates. IS26 replication was widespread among U.S. and Canadian isolates and caused the truncation and inactivation of the resistance genes strA and blaTEM-1B A hybrid virulence and MDR plasmid (pN13-01125) isolated from a Canadian S Dublin isolate was searched against NCBI SRA data of bacteria. The pN13-01125 coding sequences were found in 13 Salmonella serovars, but S Dublin appears to be a specific reservoir. In summary, we have observed the rise of invasive MDR S Dublin in humans in Canada and found that they are closely related to bovine isolates and to American isolates in their mobile and chromosomal contents.

Investigation of a Carbapenemase-producing Acinetobacter baumannii outbreak using whole genome sequencing versus a standard epidemiologic investigation

Background

The standard epidemiologic investigation of outbreaks typically relies on spatiotemporal data and pulsed-field gel electrophoresis (PFGE), but whole genome sequencing (WGS) is becoming increasingly used. This investigation aimed to characterize a carbapenemase-producing Acinetobacter baumannii (CPAb) nosocomial outbreak using WGS compared to a standard outbreak investigation.

Methods

The CPAb outbreak occurred in a single center between 2012 and 2014. The standard investigation used spatiotemporal data and PFGE to generate a chain of transmission. A separate WGS investigation generated a chain of transmission based solely on WGS and date of sampling and was blinded to all other spatiotemporal data and PFGE. Core single nucleotide variant (SNV) phylogenetic analysis was performed on WGS data generated using the Illumina MiSeq platform. The chains of transmission were compared quantitatively and qualitatively to assess the concordance between both methods.

Results

28 colonized and infected cases were included. Of the 27 transmission events identified using the standard investigation, 12 (44%) were identical to the transmission events using WGS. WGS identified several transmission events that had not been detected by traditional method, and numerous transmission events that had occurred on different hospital wards than suspected by standard methods. The average number (standard deviation [SD]) of SNVs per transmission events was 1.63 (SD, 1.31) by traditional method and 0.63 (SD, 0.79) by WGS (p = 0.001) All isolates harbored the rare carbapenemase bla_OXA-237.

Conclusions

The traditional and WGS investigations had moderate concordance. When used alongside epidemiologic data and clinical information, WGS could help improve the mapping of transmission events.

Transforming bacterial disease surveillance and investigation using whole-genome sequence to probe the trace

Two decades have passed since the first bacterial whole-genome sequencing, which provides new opportunity for microbial genome. Consequently, considerable genetic diversity encoded by bacterial genomes and among the strains in the same species has been revealed. In recent years, genome sequencing techniques and bioinformatics have developed rapidly, which has resulted in transformation and expedited the application of strategy and methodology for bacterial genome comparison used in dissection of infectious disease epidemics. Bacterial whole-genome sequencing and bioinformatic computing allow genotyping to satisfy the requirements of epidemiological study in disease control. In this review, we outline the significance and summarize the roles of bacterial genome sequencing in the context of bacterial disease control and prevention.We discuss the applications of bacterial genome sequencing in outbreak detection, source tracing, transmission mode discovery, and new epidemic clone identification. Wide applications of genome sequencing and data sharing in infectious disease surveillance networks will considerably promote outbreak detection and early warning to prevent the dissemination of bacterial diseases.