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Leuconostoc carnosum is a known colonizer of meat-related food matrices. It reaches remarkably high loads during the shelf life in packaged meat products and plays a role in spoilage, although preservative effects have been proposed for some strains. In this study, the draft genomes of 17 strains of L. carnosum (i.e., all the strains that have been sequenced so far) were compared to decipher their metabolic and functional potential and to determine their role in food transformations. Genome comparison and pathway reconstruction indicated that L. carnosum is a compact group of closely related heterofermentative bacteria sharing most of the metabolic features. Adaptation to a nitrogen-rich environment, such as meat, is evidenced by 23 peptidase genes identified in the core genome and by the autotrophy for nitrogen compounds including several amino acids, vitamins, and cofactors. Genes encoding the decarboxylases yielding biogenic amines were not present. All the strains harbored 1-4 of 32 different plasmids, bearing functions associated to proteins hydrolysis, transport of amino acids and oligopeptides, exopolysaccharides, and various resistances (e.g., to environmental stresses, bacteriophages, and heavy metals). Functions associated to bacteriocin synthesis, secretion, and immunity were also found in plasmids. While genes for lactococcin were found in most plasmids, only three harbored the genes for leucocin B, a class IIa antilisterial bacteriocin. Determinants of antibiotic resistances were absent in both plasmids and chromosomes. Published version

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An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample. Published version

Metagenomics-based high-throughput sequencing (HTS) enables comprehensive detection of all species comprised in a sample with a single assay and is becoming a standard method for outbreak investigation. However, unlike real-time PCR or serological assays, HTS datasets generated for pathogen detection do not easily provide yes/no answers. Rather, results of the taxonomic read assignment need to be assessed by trained personnel to gain information thereof. Proficiency tests are important instruments of validation, harmonization, and standardization. Within the European Union funded project COMPARE [COllaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks in Europe], we conducted a proficiency test to scrutinize the ability to assess diagnostic metagenomics data. An artificial dataset resembling shotgun sequencing of RNA from a sample of contaminated trout was provided to 12 participants with the request to provide a table with per-read taxonomic assignments at species level and a report with a summary and assessment of their findings, considering different categories like pathogen, background, or contaminations. Analysis of the read assignment tables showed that the software used reliably classified the reads taxonomically overall. However, usage of incomplete reference databases or inappropriate data pre-processing caused difficulties. From the combination of the participants' reports with their read assignments, we conclude that, although most species were detected, a number of important taxa were not or not correctly categorized. This implies that knowledge of and awareness for potentially dangerous species and contaminations need to be improved, hence, capacity building for the interpretation of diagnostic metagenomics datasets is necessary. This research was supported by the EU funded project COMPARE (Grant Agreement No. 643476). JG was supported bya grant of the within theframework of the project Ess-B.A.R. (FKZ 13N13982). Sí