Azithromycin resistance in Escherichia coli and Salmonella from food-producing animals and meat in Europe.

OBJECTIVES: To characterize the genetic basis of azithromycin resistance in Escherichia coli and Salmonella collected within the EU harmonized antimicrobial resistance (AMR) surveillance programme in 2014-18 and the Danish AMR surveillance programme in 2016-19. METHODS: WGS data of 1007 E. coli [165 azithromycin resistant (MIC > 16 mg/L)] and 269 Salmonella [29 azithromycin resistant (MIC > 16 mg/L)] were screened for acquired macrolide resistance genes and mutations in rplDV, 23S rRNA and acrB genes using ResFinder v4.0, AMRFinder Plus and custom scripts. Genotype-phenotype concordance was determined for all isolates. Transferability of mef(C)-mph(G)-carrying plasmids was assessed by conjugation experiments. RESULTS: mph(A), mph(B), mef(B), erm(B) and mef(C)-mph(G) were detected in E. coli and Salmonella, whereas erm(C), erm(42), ere(A) and mph(E)-msr(E) were detected in E. coli only. The presence of macrolide resistance genes, alone or in combination, was concordant with the azithromycin-resistant phenotype in 69% of isolates. Distinct mph(A) operon structures were observed in azithromycin-susceptible (n = 50) and -resistant (n = 136) isolates. mef(C)-mph(G) were detected in porcine and bovine E. coli and in porcine Salmonella enterica serovar Derby and Salmonella enterica 1,4, [5],12:i:-, flanked downstream by ISCR2 or TnAs1 and associated with IncIγ and IncFII plasmids. CONCLUSIONS: Diverse azithromycin resistance genes were detected in E. coli and Salmonella from food-producing animals and meat in Europe. Azithromycin resistance genes mef(C)-mph(G) and erm(42) appear to be emerging primarily in porcine E. coli isolates. The identification of distinct mph(A) operon structures in susceptible and resistant isolates increases the predictive power of WGS-based methods for in silico detection of azithromycin resistance in Enterobacterales.

Various arrangements of mobile genetic elements among CC147 subpopulations of Klebsiella pneumoniae harboring blaNDM-1: a comparative genomic analysis of carbapenem resistant strains.

BACKGROUND: Certain clonal complexes (CCs) of Klebsiella pneumoniae such as CC147 (ST147 and ST392) are major drivers of blaNDM dissemination across the world. ST147 has repeatedly reported from our geographical region, but its population dynamics and evolutionary trajectories need to be further studied. METHODS: Comparative genomic analysis of 51 carbapenem-nonsusceptible strains as well as three hypervirulent K. pneumoniae (hvKp) recovered during 16-months of surveillance was performed using various bioinformatics tools. We investigated the genetic proximity of our ST147 strains with publicly available corresponding genomes deposited globally and from neighbor countries in our geographic region. RESULTS: While IncL/M plasmid harboring blaOXA-48 was distributed among divergent clones, blaNDM-1 was circulated by twenty of the 25 CC147 dominant clone and were mostly recovered from the ICU. The NDM-1 core structure was bracketed by a single isoform of mobile genetic elements (MGEs) [ΔISKpn26-NDM-TnAs3-ΔIS3000-Tn5403] and was located on Col440I plasmid in 68.7% of ST392. However, various arrangements of MGEs including MITESen1/MITESen1 composite transposon or combination of MITESen1/ISSen4/IS903B/IS5/ISEhe3 on IncFIb (pB171) were identified in ST147. It seems that ST392 circulated blaNDM-1 in 2018 before being gradually replaced by ST147 from the middle to the end of sample collection in 2019. ST147 strains possessed the highest number of resistance markers and showed high genetic similarity with four public genomes that harbored blaNDM-1 on the same replicon type. Mainly, there was a convergence between clusters and isolated neighboring countries in the minimum-spanning tree. A conserved arrangement of resistance markers/MGEs was linked to methyltransferase armA which was embedded in class 1 integron in 8 isolates of ST147/ST48 high-risk clones. CONCLUSION: Our findings highlight the dynamic nature of blaNDM-1 transmission among K. pneumoniae in Iran that occurs both clonally and horizontally via various combinations of MGEs. This is the first analysis of Iranian ST147/NDM + clone in the global context.

An Overview of Antimicrobial Resistance Profiles of Publicly Available Salmonella Genomes with Sufficient Quality and Metadata.

Salmonella enterica (S. enterica) is a commensal organism or pathogen causing diseases in animals and humans, as well as widespread in the environment. Antimicrobial resistance (AMR) has increasingly affected both animal and human health and continues to raise public health concerns. A decade ago, it was estimated that the increased use of whole genome sequencing (WGS) combined with sharing of public data would drastically change and improve the surveillance and understanding of Salmonella epidemiology and AMR. This study aimed to evaluate the current usefulness of public WGS data for Salmonella surveillance and to investigate the associations between serovars, antibiotic resistance genes (ARGs), and metadata. Out of 191,306 Salmonella genomes deposited in European Nucleotide Archive and NCBI databases, 47,452 WGS with sufficient minimum metadata (country, year, and source) of S. enterica were retrieved from 116 countries and isolated between 1905 and 2020. For in silico analysis of the WGS data, KmerFinder, SISTR, and ResFinder were used for species, serovars, and AMR identification, respectively. The results showed that the five common isolation sources of S. enterica are human (29.10%), avian (22.50%), environment (11.89%), water (9.33%), and swine (6.62%). The most common ARG profiles for each class of antimicrobials are ß-lactam (blaTEM-1B; 6.78%), fluoroquinolone [(parC[T57S], qnrB19); 0.87%], folate pathway antagonist (sul2; 8.35%), macrolide [mph(A); 0.39%], phenicol (floR; 5.94%), polymyxin B (mcr-1.1; 0.09%), and tetracycline [tet(A); 12.95%]. Our study reports the first overview of ARG profiles in publicly available Salmonella genomes from online databases. All data sets from this study can be searched at Microreact.

Prevalence and genomic analysis of ESBL-producing Escherichia coli in retail raw meats in Singapore.

OBJECTIVES: To determine the prevalence and genetic characteristics of ESBL-producing Escherichia coli in retail raw meats from Singapore markets. METHODS: A total of 634 raw meat (chicken, pork and beef) samples were collected from markets in Singapore during June 2017-October 2018. The samples were enriched overnight and then incubated on Brilliance™ ESBL Agar. Presumptive ESBL isolates were confirmed using the double-disc synergy test. Confirmed ESBL-producing E. coli were sent for WGS and bioinformatic analysis was performed. RESULTS: The prevalence of ESBL-producing E. coli in chicken, pork and beef meats was 51.2% (109/213), 26.9% (58/216) and 7.3% (15/205), respectively. A total of 225 ESBL-producing E. coli were isolated from 184 samples. ß-Lactam resistance genes were detected in all isolates. After ß-lactam resistance genes, the most common antimicrobial resistance genes detected were aminoglycoside resistance genes (92.4%). One hundred and seventy-two (76.4%), 102 (45.3%) and 52 (23.1%) isolates carried blaCTX-M genes, blaTEM genes and blaSHV genes, respectively. blaCTX-M-55 (57/225, 25.3%) and blaCTX-M-65 (40/225, 17.8%) were the most frequent ESBL genes. Colistin resistance genes (including mcr-1, mcr-3 and mcr-5) were found in 15.6% of all isolates. CONCLUSIONS: This study indicates that ESBL-producing E. coli are widely found in retail raw meats, especially chicken, in Singapore. Occurrence of MDR (resistance to at least three classes of antimicrobial) and colistin resistance genes in retail raw meat suggests potential food safety and public health risks.

Salmonella enterica serovar Typhi H58 clone has been endemic in Zimbabwe from 2012 to 2019.

BACKGROUND: Typhoid fever, caused by S. enterica ser. Typhi, continues to be a substantial health burden in developing countries. Little is known of the genotypic diversity of S. enterica ser. Typhi in Zimbabwe, but this is key for understanding the emergence and spread of this pathogen and devising interventions for its control. OBJECTIVES: To report the molecular epidemiology of S. enterica ser. Typhi outbreak strains circulating from 2012 to 2019 in Zimbabwe, using comparative genomics. METHODS: A review of typhoid cases records from 2012 to 2019 in Zimbabwe was performed. The phylogenetic relationship of outbreak isolates from 2012 to 2019 and emergence of antibiotic resistance was investigated by whole-genome sequence analysis. RESULTS: A total 22 479 suspected typhoid cases, 760 confirmed cases were reported from 2012 to 2019 and 29 isolates were sequenced. The majority of the sequenced isolates were predicted to confer resistance to aminoglycosides, ß-lactams, phenicols, sulphonamides, tetracycline and fluoroquinolones (including qnrS detection). The qnrS1 gene was associated with an IncN (subtype PST3) plasmid in 79% of the isolates. Whole-genome SNP analysis, SNP-based haplotyping and resistance determinant analysis showed that 93% of the isolates belonged to a single clade represented by multidrug-resistant H58 lineage I (4.3.1.1), with a maximum pair-wise distance of 22 SNPs. CONCLUSIONS: This study has provided detailed genotypic characterization of the outbreak strain, identified as S. Typhi 4.3.1.1 (H58). The strain has reduced susceptibility to ciprofloxacin due to qnrS carried by an IncN (subtype PST3) plasmid resulting from ongoing evolution to full resistance.

Extended-spectrum beta-lactamase-producing Escherichia coli and antimicrobial resistance in municipal and hospital wastewaters in Czech Republic: Culture-based and metagenomic approaches.

Wastewaters serve as important hot spots for antimicrobial resistance and monitoring can be used to analyse the abundance and diversity of antimicrobial resistance genes at the level of large bacterial and human populations. In this study, whole genome sequencing of beta-lactamase-producing Escherichia coli and metagenomic analysis of whole-community DNA were used to characterize the occurrence of antimicrobial resistance in hospital, municipal and river waters in the city of Brno (Czech Republic). Cefotaxime-resistant E. coli were mainly extended-spectrum beta-lactamase (ESBL) producers (95.6%, n = 158), of which the majority carried blaCTX-M (98.7%; n = 151) and were detected in all water samples except the outflow from hospital wastewater treatment plant. A wide phylogenetic diversity was observed among the sequenced E. coli (n = 78) based on the detection of 40 sequence types and single nucleotide polymorphisms (average number 34,666 ± 15,710) between strains. The metagenomic analysis revealed a high occurrence of bacterial genera with potentially pathogenic members, including Pseudomonas, Escherichia, Klebsiella, Aeromonas, Enterobacter and Arcobacter (relative abundance >50%) in untreated hospital and municipal wastewaters and predominance of environmental bacteria in treated and river waters. Genes encoding resistance to aminoglycosides, beta-lactams, quinolones and macrolides were frequently detected, however blaCTX-M was not found in this dataset which may be affected by insufficient sequencing depth of the samples. The study pointed out municipal treated wastewater as a possible source of multi-drug resistant E. coli and antimicrobial resistance genes for surface waters. Moreover, the combination of two different approaches provided a more holistic view on antimicrobial resistance in water environments. The culture-based approach facilitated insight into the dynamics of ESBL-producing E. coli and the metagenomics shows abundance and diversity of bacteria and antimicrobial resistance genes vary across water sites.

New Brucella variant isolated from Croatian cattle.

BACKGROUND: A novel Brucella strain closely related to Brucella (B.) melitensis biovar (bv) 3 was found in Croatian cattle during testing within a brucellosis eradication programme. CASE PRESENTATION: Standardised serological, brucellin skin test, bacteriological and molecular diagnostic screening for Brucella infection led to positive detection in one dairy cattle herd. Three isolates from that herd were identified to species level using the Bruce ladder method. Initially, two strains were typed as B. melitensis and one as B. abortus, but multiplex PCR based on IS711 and the Suis ladder showed that all of them to belong to B. melitensis, and the combination of whole-genome and multi-locus sequencing as well as Multi-Locus Variable numbers of tandem repeats Analysis (MLVA) highlighted a strong proximity within the phylogenetic branch of B. melitensis strains previously isolated from Croatia, Albania, Kosovo and Bosnia and Herzegovina. Two isolates were determined to be B. melitensis bv. 3, while the third showed a unique phylogenetic profile, growth profile on dyes and bacteriophage typing results. This isolate contained the 609-bp omp31 sequence, but not the 723-bp omp31 sequence present in the two isolates of B. melitensis bv. 3. CONCLUSIONS: Identification of a novel Brucella variant in this geographic region is predictable given the historic endemicity of brucellosis. The emergence of a new variant may reflect a combination of high prevalence among domestic ruminants and humans as well as weak eradication strategies. The zoonotic potential, reservoirs and transmission pathways of this and other Brucella variants should be explored.

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium.

Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the next generation sequencing technology, it is possible to develop novel source attribution models. We investigated the potential of machine learning to predict the animal reservoir from which a bacterial strain isolated from a human salmonellosis case originated based on whole-genome sequencing. Machine learning methods recognize patterns in large and complex data sets and use this knowledge to build models. The model learns patterns associated with genetic variations in bacteria isolated from the different animal reservoirs. We selected different machine learning algorithms to predict sources of human salmonellosis cases and trained the model with Danish Salmonella Typhimurium isolates sampled from broilers (n = 34), cattle (n = 2), ducks (n = 11), layers (n = 4), and pigs (n = 159). Using cgMLST as input features, the model yielded an average accuracy of 0.783 (95% CI: 0.77-0.80) in the source prediction for the random forest and 0.933 (95% CI: 0.92-0.94) for the logit boost algorithm. Logit boost algorithm was most accurate (valid accuracy: 92%, CI: 0.8706-0.9579) and predicted the origin of 81% of the domestic sporadic human salmonellosis cases. The most important source was Danish produced pigs (53%) followed by imported pigs (16%), imported broilers (6%), imported ducks (2%), Danish produced layers (2%), Danish produced cattle and imported cattle (<1%) while 18% was not predicted. Machine learning has potential for improving source attribution modeling based on sequence data. Results of such models can inform risk managers to identify and prioritize food safety interventions.

Using WGS to identify antibiotic resistance genes and predict antimicrobial resistance phenotypes in MDR Acinetobacter baumannii in Tanzania.

BACKGROUND: Reliable phenotypic antimicrobial susceptibility testing can be a challenge in clinical settings in low- and middle-income countries. WGS is a promising approach to enhance current capabilities. AIM: To study diversity and resistance determinants and to predict and compare resistance patterns from WGS data of Acinetobacter baumannii with phenotypic results from classical microbiological testing at a tertiary care hospital in Tanzania. METHODS AND RESULTS: MLST using Pasteur/Oxford schemes yielded eight different STs from each scheme. Of the eight, two STs were identified to be global clones 1 (n = 4) and 2 (n = 1) as per the Pasteur scheme. Resistance testing using classical microbiology determined between 50% and 92.9% resistance across all drugs. Percentage agreement between phenotypic and genotypic prediction of resistance ranged between 57.1% and 100%, with coefficient of agreement (κ) between 0.05 and 1. Seven isolates harboured mutations at significant loci (S81L in gyrA and S84L in parC). A number of novel plasmids were detected, including pKCRI-309C-1 (219000 bp) carrying 10 resistance genes, pKCRI-43-1 (34935 bp) carrying two resistance genes and pKCRI-49-1 (11681 bp) and pKCRI-28-1 (29606 bp), each carrying three resistance genes. New ampC alleles detected included ampC-69, ampC-70 and ampC-71. Global clone 1 and 2 isolates were found to harbour ISAba1 directly upstream of the ampC gene. Finally, SNP-based phylogenetic analysis of the A. baumannii isolates revealed closely related isolates in three clusters. CONCLUSIONS: The validity of the use of WGS in the prediction of phenotypic resistance can be appreciated, but at this stage is not sufficient for it to replace conventional antimicrobial susceptibility testing in our setting.

IncI1 ST3 and IncI1 ST7 plasmids from CTX-M-1-producing Escherichia coli obtained from patients with bloodstream infections are closely related to plasmids from E. coli of animal origin.

OBJECTIVES: Fully sequenced IncI1 plasmids obtained from CTX-M-1-producing Escherichia coli of human and animal origin were compared. METHODS: Twelve E. coli isolates sharing identical ESBL genes and plasmid multilocus STs sequenced on Illumina and MinION platforms were obtained from the Danish antimicrobial resistance surveillance programme, DANMAP. After de novo assembly, the sequences of plasmids harbouring blaCTX-M-1 were manually curated and ORFs annotated. Within-group comparisons were performed separately for the IncI1 ST3 plasmid type and the IncI1 ST7 plasmid type. The IncI1 ST3 plasmid group was obtained from 10 E. coli isolates (2 from patients with bloodstream infections, 6 from food and 2 from animals). The IncI1 ST7 plasmids originated from E. coli isolates obtained from a patient with bloodstream infection and from a pig. Sequences of IncI1 ST3 and IncI1 ST7 plasmids harbouring blaCTX-M-1 with determined origin were retrieved from GenBank and used for comparison within the respective group. RESULTS: The 10 IncI1 ST3 blaCTX-M-1 plasmids were highly similar in structure and organization with only minor plasmid rearrangements and differences in the variable region. The IncI1 ST7 blaCTX-M-1 plasmids also showed high similarity in structure and organization. The high level of similarity was also observed when including plasmids from E. coli of animal origin from Australia, Switzerland, the Netherlands and France. CONCLUSIONS: This study shows broad spread of a very successful CTX-M-1-producing IncI1 type plasmid among E. coli of both human and animal origin.

ST131 fimH22 Escherichia coli isolate with a blaCMY-2/IncI1/ST12 plasmid obtained from a patient with bloodstream infection: highly similar to E. coli isolates of broiler origin.

OBJECTIVES: This study compares the genome of an ST131 CMY-2-producing Escherichia coli isolate from a Danish patient with other ST131 CMY-2-producing E. coli isolates of both human and animal origin. METHODS: In 2016, an ST131 CMY-2-producing E. coli isolate (ESBL20160056) was obtained from a patient with a bloodstream infection. The genome of the ESBL20160056 isolate was compared with genomes from six ST131 CMY-2-producing E. coli isolates obtained from broiler meat imported to Denmark, 15 ST131 CMY-2-producing E. coli isolates obtained from Enterobase (http://enterobase.warwick.ac.uk) and two ST131 CMY-2-producing E. coli from European collaborators. The plasmid from ESBL20160056 was sequenced using a MinION Mk1B (Oxford Nanopore Technologies). RESULTS: The E. coli isolate from the Danish patient clustered together with 13 other fimH22 ST131 CMY-2-producing E. coli isolates in a distinct clade. The clade consisted of genomes from six E. coli isolates from humans collected in Denmark, Spain, Cambodia and the USA, six E. coli isolates obtained from broiler meat samples imported to Denmark from France, the Netherlands and Germany, and two E. coli isolates obtained from broilers in Belgium and Luxembourg. The 101.5 kb plasmid with blaCMY-2 from ESBL20160056 had an IncI1 replicon and belonged to ST12 using the plasmid MLST scheme. In total, 10 of the 14 ST131 E. coli isolates belonging to the fimH22 clade carried an IncI1 ST12 plasmid with blaCMY-2. CONCLUSIONS: From our data, it seems plausible that the ST131 fimH22 CMY-2-producing E. coli isolate obtained from the Danish patient could have a zoonotic broiler origin.

Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.

Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and virulence among strains. The potential of machine learning algorithms for predicting the risk/health burden at the population level while inputting large and complex NGS data was explored with Listeria monocytogenes as a case study. Listeria data consisted of a percentage similarity matrix from genome assemblies of 38 and 207 strains of clinical and food origin, respectively. Basic Local Alignment (BLAST) was used to align the assemblies against a database of 136 virulence and stress resistance genes. The outcome variable was frequency of illness, which is the percentage of reported cases associated with each strain. These frequency data were discretized into seven ordinal outcome categories and used for supervised machine learning and model selection from five ensemble algorithms. There was no significant difference in accuracy between the models, and support vector machine with linear kernel was chosen for further inference (accuracy of 89% [95% CI: 68%, 97%]). The virulence genes FAM002725, FAM002728, FAM002729, InlF, InlJ, Inlk, IisY, IisD, IisX, IisH, IisB, lmo2026, and FAM003296 were important predictors of higher frequency of illness. InlF was uniquely truncated in the sequence type 121 strains. Most important risk predictor genes occurred at highest prevalence among strains from ready-to-eat, dairy, and composite foods. We foresee that the findings and approaches described offer the potential for rethinking the current approaches in MRA.

Investing in Food Safety for Developing Countries: Opportunities and Challenges in Applying Whole-Genome Sequencing for Food Safety Management.

Whole-genome sequencing (WGS) has become a significant tool in investigating foodborne disease outbreaks and some countries have incorporated WGS into national food control systems. However, WGS poses technical challenges that deter developing countries from incorporating it into their food safety management system. A rapid scoping review was conducted, followed by a focus group session, to understand the current situation regarding the use of WGS for foodborne disease surveillance and food monitoring at the global level and identify key limiting factors for developing countries in adopting WGS for their food control systems. The results showed that some developed nations routinely use WGS in their food surveillance systems resulting in more precise understanding of the causes of outbreaks. In developing nations, knowledge of WGS exists in the academic/research sectors; however, there is limited understanding at the government level regarding the usefulness of WGS for food safety regulatory activities. Thus, incorporation of WGS is extremely limited in most developing nations. While some countries lack the capacity to collect and analyze the data generated from WGS, the most significant technical gap in most developing countries is in data interpretation using bioinformatics. The gaps in knowledge and capacities between developed and developing nations regarding use of WGS likely introduce an inequality in international food trade, and thus, relevant international organizations, as well as the countries that are already proficient in the use of WGS, have significant roles in assisting developing nations to be able to fully benefit from the technology and its applications in food safety management.

Multiplex PCR for detection of plasmid-mediated colistin resistance determinants, mcr-1, mcr-2, mcr-3, mcr-4 and mcr-5 for surveillance purposes.

Background and aimPlasmid-mediated colistin resistance mechanisms have been identified worldwide in the past years. A multiplex polymerase chain reaction (PCR) protocol for detection of all currently known transferable colistin resistance genes (mcr-1 to mcr-5, and variants) in Enterobacteriaceae was developed for surveillance or research purposes. Methods: We designed four new primer pairs to amplify mcr-1, mcr-2, mcr-3 and mcr-4 gene products and used the originally described primers for mcr-5 to obtain a stepwise separation of ca 200 bp between amplicons. The primer pairs and amplification conditions allow for single or multiple detection of all currently described mcr genes and their variants present in Enterobacteriaceae. The protocol was validated testing 49 European Escherichia coli and Salmonella isolates of animal origin. Results: Multiplex PCR results in bovine and porcine isolates from Spain, Germany, France and Italy showed full concordance with whole genome sequence data. The method was able to detect mcr-1, mcr-3 and mcr-4 as singletons or in different combinations as they were present in the test isolates. One new mcr-4 variant, mcr-4.3, was also identified. Conclusions: This method allows rapid identification of mcr-positive bacteria and overcomes the challenges of phenotypic detection of colistin resistance. The multiplex PCR should be particularly interesting in settings or laboratories with limited resources for performing genetic analysis as it provides information on the mechanism of colistin resistance without requiring genome sequencing.

The invasome of Salmonella Dublin as revealed by whole genome sequencing.

BACKGROUND: Salmonella enterica serovar Dublin is a zoonotic infection that can be transmitted from cattle to humans through consumption of contaminated milk and milk products. Outbreaks of human infections by S. Dublin have been reported in several countries including high-income countries. A high proportion of S. Dublin cases in humans are associated with invasive disease and systemic illness. The genetic basis of virulence in S. Dublin is not well characterized. METHODS: Whole genome sequencing was applied to a set of clinical invasive and non-invasive S. Dublin isolates from different countries in order to characterize the putative genetic determinants involved in the virulence and invasiveness of S. Dublin in humans. RESULTS: We identified several virulence factors that form the bacterial invasome and may contribute to increasing bacterial virulence and pathogenicity including mainly Gifsy-2 prophage, two different type 6 secretion systems (T6SSs) harbored by Salmonella pathogenicity islands; SPI-6 and SPI-19 respectively and virulence genes; ggt and PagN. Although Vi antigen and the virulence plasmid have been reported previously to contribute to the virulence of S. Dublin we did not detect them in all invasive isolates indicating that they are not the main virulence determinants in S. Dublin. CONCLUSION: Several virulence factors within the genome of S. Dublin might contribute to the ability of S. Dublin to invade humans' blood but there were no genomic markers that differentiate invasive from non-invasive isolates suggesting that host immune response play a crucial role in the clinical outcome of S. Dublin infection.

Population Genetic Structure of Listeria monocytogenes Strains as Determined by Pulsed-Field Gel Electrophoresis and Multilocus Sequence Typing.

UNLABELLED: Listeria monocytogenes is a ubiquitous bacterium that may cause the foodborne illness listeriosis. Only a small amount of data about the population genetic structure of strains isolated from food is available. This study aimed to provide an accurate view of the L. monocytogenes food strain population in France. From 1999 to 2014, 1,894 L. monocytogenes strains were isolated from food at the French National Reference Laboratory for L. monocytogenes and classified according to the five risk food matrices defined by the European Food Safety Authority (EFSA). A total of 396 strains were selected on the basis of different pulsed-field gel electrophoresis (PFGE) clusters, serotypes, and strain origins and typed by multilocus sequence typing (MLST), and the MLST results were supplemented with MLST data available from Institut Pasteur, representing human and additional food strains from France. The distribution of sequence types (STs) was compared between food and clinical strains on a panel of 675 strains. High congruence between PFGE and MLST was found. Out of 73 PFGE clusters, the two most prevalent corresponded to ST9 and ST121. Using original statistical analysis, we demonstrated that (i) there was not a clear association between ST9 and ST121 and the food matrices, (ii) serotype IIc, ST8, and ST4 were associated with meat products, and (iii) ST13 was associated with dairy products. Of the two major STs, ST121 was the ST that included the fewest clinical strains, which might indicate lower virulence. This observation may be directly relevant for refining risk analysis models for the better management of food safety. IMPORTANCE: This study showed a very useful backward compatibility between PFGE and MLST for surveillance. The results enabled better understanding of the population structure of L. monocytogenes strains isolated from food and management of the health risks associated with L. monocytogenes food strains. Moreover, this work provided an accurate view of L. monocytogenes strain populations associated with specific food matrices. We clearly showed that some STs were associated with food matrices, such as meat, meat products, and dairy products. We opened the way to source attribution modeling in order to quantify the relative importance of the main food matrices.

Global Genomic Epidemiology of Salmonella enterica Serovar Typhimurium DT104.

It has been 30 years since the initial emergence and subsequent rapid global spread of multidrug-resistant Salmonella entericaserovar Typhimurium DT104 (MDR DT104). Nonetheless, its origin and transmission route have never been revealed. We used whole-genome sequencing (WGS) and temporally structured sequence analysis within a Bayesian framework to reconstruct temporal and spatial phylogenetic trees and estimate the rates of mutation and divergence times of 315S Typhimurium DT104 isolates sampled from 1969 to 2012 from 21 countries on six continents. DT104 was estimated to have emerged initially as antimicrobial susceptible in ∼1948 (95% credible interval [CI], 1934 to 1962) and later became MDR DT104 in ∼1972 (95% CI, 1972 to 1988) through horizontal transfer of the 13-kb Salmonella genomic island 1 (SGI1) MDR region into susceptible strains already containing SGI1. This was followed by multiple transmission events, initially from central Europe and later between several European countries. An independent transmission to the United States and another to Japan occurred, and from there MDR DT104 was probably transmitted to Taiwan and Canada. An independent acquisition of resistance genes took place in Thailand in ∼1975 (95% CI, 1975 to 1990). In Denmark, WGS analysis provided evidence for transmission of the organism between herds of animals. Interestingly, the demographic history of Danish MDR DT104 provided evidence for the success of the program to eradicate Salmonellafrom pig herds in Denmark from 1996 to 2000. The results from this study refute several hypotheses on the evolution of DT104 and suggest that WGS may be useful in monitoring emerging clones and devising strategies for prevention of Salmonella infections.

Construction and application of a protein interaction map for white spot syndrome virus (WSSV).

White spot syndrome virus (WSSV) is currently the most serious global threat for cultured shrimp production. Although its large, double-stranded DNA genome has been completely characterized, most putative protein functions remain obscure. To provide more informative knowledge about this virus, a proteomic-scale network of WSSV-WSSV protein interactions was carried out using a comprehensive yeast two-hybrid analysis. An array of yeast transformants containing each WSSV open reading frame fused with GAL4 DNA binding domain and GAL4 activation domain was constructed yielding 187 bait and 182 prey constructs, respectively. On screening of ∼28,000 pairwise combinations, 710 interactions were obtained from 143 baits. An independent coimmunoprecipitation assay (co-IP) was performed to validate the selected protein interaction pairs identified from the yeast two-hybrid approach. The program Cytoscape was employed to create a WSSV protein-protein interaction (PPI) network. The topology of the WSSV PPI network was based on the Barabási-Albert model and consisted of a scale-free network that resembled other established viral protein interaction networks. Using the RNA interference approach, knocking down either of two candidate hub proteins gave shrimp more protection against WSSV than knocking down a nonhub gene. The WSSV protein interaction map established in this study provides novel guidance for further studies on shrimp viral pathogenesis, host-viral protein interaction and potential targets for therapeutic and preventative antiviral strategies in shrimp aquaculture.