Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) was recognized in Europe and worldwide in the late 1990s. Within a decade, several genetically and geographically distinct CA-MRSA lineages carrying the small SCCmec type IV and V genetic elements and the Panton-Valentine leukocidin (PVL) emerged around the world. In Europe, the predominant CA-MRSA strain belongs to clonal complex 80 (CC80) and is resistant to kanamycin/amikacin and fusidic acid. CC80 was first reported in 1993 but was relatively rare until the late 1990s. It has since been identified throughout North Africa, the Middle East, and Europe, with recent sporadic reports in sub-Saharan Africa. While strongly associated with skin and soft tissue infections, it is rarely found among asymptomatic carriers. Methicillin-sensitive S. aureus (MSSA) CC80 strains are extremely rare except in sub-Saharan Africa. In the current study, we applied whole-genome sequencing to a global collection of both MSSA and MRSA CC80 isolates. Phylogenetic analyses strongly suggest that the European epidemic CA-MRSA lineage is derived from a PVL-positive MSSA ancestor from sub-Saharan Africa. Moreover, the tree topology suggests a single acquisition of both the SCCmec element and a plasmid encoding the fusidic acid resistance determinant. Four canonical SNPs distinguish the derived CA-MRSA lineage and include a nonsynonymous mutation in accessory gene regulator C (agrC). These changes were associated with a star-like expansion into Europe, the Middle East, and North Africa in the early 1990s, including multiple cases of cross-continent imports likely driven by human migrations.

This report presents the results of the project "Closing gaps for performing a risk assessment on Listeria monocytogenes in ready-to-eat (RTE) foods: activity 3, the comparison of isolates from different compartments along the food chain, and from humans using whole genome sequencing (WGS) analysis". The main objective was to compare L. monocytogenes isolates collected in the EU from ready-to-eat (RTE) foods, compartments along the food chain and from human cases by the use of WGS. A total of 1,143 L. monocytogenes isolates were selected for the study, including 333 human clinical isolates and 810 isolates from the food chain. The isolates were whole genome sequenced. The phylogeny showed a clear delineation between L. monocytogenes lineages and between clonal complexes within lineages. A range of typing methods were applied to the sequence data, providing the framework to answer questions on genetic diversity and epidemiological relationships. Retrospective analysis of nine outbreaks showed that WGS is a powerful tool in national and international outbreak investigations as WGS can accurately rule isolates in or out of outbreaks. Source attribution models showed bovine reservoir to be the main source of human disease although other sources also contributed and generally confidence intervals were high. Numerous consistent genetic linkages between a priori unlinked strains were identified, some of which involved isolates from multiple countries. The presence of putative markers conferring the potential to survive/multiply in the food chain and/or cause disease in humans was explored by detecting the presence of putative virulence genes, AMR genes and factors conferring the ability to persist in the food processing chain. This study has demonstrated one of the major benefits of WGS, which is the ability to address a wide range of questions including those on virulence, antimicrobial resistance, source attribution, surveillance and outbreak detection and investigation, in a single experiment.

We present the LiSEQ (Listeria SEQuencing) project, funded by the European Food Safety Agency (EFSA) to compare Listeria monocytogenes isolates collected in the European Union from ready-to-eat foods, compartments along the food chain (e.g. food-producing animals, food-processing environments) and humans. In this article, we report the molecular characterization of a selection of this data set employing whole-genome sequencing analysis. We present an overview of the strain diversity observed in different sampled sources, and characterize the isolates based on their virulence and resistance profile. We integrate into our analysis the global L. monocytogenes genome collection described by Moura and colleagues in 2016 to assess the representativeness of the LiSEQ collection in the context of known L. monocytogenes strain diversity.

It has been hypothesized that, in aggregate, rare variants in coding regions of genes explain a substantial fraction of the heritability of common diseases. We sequenced the exomes of 1,000 Danish cases with common forms of type 2 diabetes (including body mass index > 27.5 kg/m(2) and hypertension) and 1,000 healthy controls to an average depth of 56×. Our simulations suggest that our study had the statistical power to detect at least one causal gene (a gene containing causal mutations) if the heritability of these common diseases was explained by rare variants in the coding regions of a limited number of genes. We applied a series of gene-based tests to detect such susceptibility genes. However, no gene showed a significant association with disease risk after we corrected for the number of genes analyzed. Thus, we could reject a model for the genetic architecture of type 2 diabetes where rare nonsynonymous variants clustered in a modest number of genes (fewer than 20) are responsible for the majority of disease risk.

This report describes one Salmonella isolate harbouring both mcr-1 and mcr-3. We also found nine other Salmonella isolates positive for the plasmid-borne colistin resistance gene, mcr-3. The strains were isolated from patients in Denmark between 2009 and 2017 and five of the patients had travelled to Asia. In addition to mcr-3, all strains were found positive for blaTEM-1, strA, strB, sul2 and tet(A) or tet(B), and most strains were positive for blaCTX-M-55 and qnrS.

In the original Supplemental Data available for download on November 27, 2013, the graphs in Figures S14-S16 and S18-S20 were unfortunately missing data because of a technical error during file conversion. The Supplemental Data file has been corrected online and is currently available for download. The authors regret the error.

Ready-to-eat spiced meat roll from a single production facility caused this outbreak. The product, served sliced and cold, is popular among the elderly; serving it at hospitals probably contributed to the high case-fatality rate. WGS used for patient isolates and isolates from food control inspections, coupled with routine epidemiological follow-up, was instrumental in swiftly locating the source of infections, preventing further illnesses and deaths.

The genus Burkholderia consists of a number of very diverse species, both in terms of lifestyle (which varies from category B pathogens to apathogenic soil bacteria and plant colonizers) and their genetic contents. We have used 56 publicly available genomes to explore the genomic diversity within this genus, including genome sequences that are not completely finished, but are available from the NCBI database. Defining the pan- and core genomes of species results in insights in the conserved and variable fraction of genomes, and can verify (or question) historic, taxonomic groupings. We find only several hundred genes that are conserved across all Burkholderia genomes, whilst there are more than 40,000 gene families in the Burkholderia pan-genome. A BLAST matrix visualizes the fraction of conserved genes in pairwise comparisons. A BLAST atlas shows which genes are actually conserved in a number of genomes, located and visualized with reference to a chosen genome. Genomic islands are common in many Burkholderia genomes, and most of these can be readily visualized by DNA structural properties of the chromosome. Trees that are based on relatedness of gene family content yield different results depending on what genes are analyzed. Some of the differences can be explained by errors in incomplete genome sequences, but, as our data illustrate, the outcome of phylogenetic trees depends on the type of genes that are analyzed.