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      Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food‐borne microorganisms

      research-article
      EFSA Panel on Biological Hazards (EFSA BIOHAZ Panel), , , , , , , , , , , , , , , , , , , , , , , ,
      EFSA Journal
      John Wiley and Sons Inc.
      whole genome sequencing, metagenomics, microbial risk assessment, source attribution, antimicrobial resistance, typing of food‐borne pathogens, food‐borne outbreak investigation

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          Abstract

          This Opinion considers the application of whole genome sequencing ( WGS) and metagenomics for outbreak investigation, source attribution and risk assessment of food‐borne pathogens. WGS offers the highest level of bacterial strain discrimination for food‐borne outbreak investigation and source‐attribution as well as potential for more precise hazard identification, thereby facilitating more targeted risk assessment and risk management. WGS improves linking of sporadic cases associated with different food products and geographical regions to a point source outbreak and can facilitate epidemiological investigations, allowing also the use of previously sequenced genomes. Source attribution may be favoured by improved identification of transmission pathways, through the integration of spatial‐temporal factors and the detection of multidirectional transmission and pathogen–host interactions. Metagenomics has potential, especially in relation to the detection and characterisation of non‐culturable, difficult‐to‐culture or slow‐growing microorganisms, for tracking of hazard‐related genetic determinants and the dynamic evaluation of the composition and functionality of complex microbial communities. A SWOT analysis is provided on the use of WGS and metagenomics for Salmonella and Shigatoxin‐producing Escherichia coli ( STEC) serotyping and the identification of antimicrobial resistance determinants in bacteria. Close agreement between phenotypic and WGS‐based genotyping data has been observed. WGS provides additional information on the nature and localisation of antimicrobial resistance determinants and on their dissemination potential by horizontal gene transfer, as well as on genes relating to virulence and biological fitness. Interoperable data will play a major role in the future use of WGS and metagenomic data. Capacity building based on harmonised, quality controlled operational systems within European laboratories and worldwide is essential for the investigation of cross‐border outbreaks and for the development of international standardised risk assessments of food‐borne microorganisms.

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          Mobile Genetic Elements Associated with Antimicrobial Resistance

          SUMMARY Strains of bacteria resistant to antibiotics, particularly those that are multiresistant, are an increasing major health care problem around the world. It is now abundantly clear that both Gram-negative and Gram-positive bacteria are able to meet the evolutionary challenge of combating antimicrobial chemotherapy, often by acquiring preexisting resistance determinants from the bacterial gene pool. This is achieved through the concerted activities of mobile genetic elements able to move within or between DNA molecules, which include insertion sequences, transposons, and gene cassettes/integrons, and those that are able to transfer between bacterial cells, such as plasmids and integrative conjugative elements. Together these elements play a central role in facilitating horizontal genetic exchange and therefore promote the acquisition and spread of resistance genes. This review aims to outline the characteristics of the major types of mobile genetic elements involved in acquisition and spread of antibiotic resistance in both Gram-negative and Gram-positive bacteria, focusing on the so-called ESKAPEE group of organisms ( Enterococcus faecium , Staphylococcus aureus , Klebsiella pneumoniae , Acinetobacter baumannii , Pseudomonas aeruginosa , Enterobacter spp., and Escherichia coli ), which have become the most problematic hospital pathogens.
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            Community structure and metabolism through reconstruction of microbial genomes from the environment.

            Microbial communities are vital in the functioning of all ecosystems; however, most microorganisms are uncultivated, and their roles in natural systems are unclear. Here, using random shotgun sequencing of DNA from a natural acidophilic biofilm, we report reconstruction of near-complete genomes of Leptospirillum group II and Ferroplasma type II, and partial recovery of three other genomes. This was possible because the biofilm was dominated by a small number of species populations and the frequency of genomic rearrangements and gene insertions or deletions was relatively low. Because each sequence read came from a different individual, we could determine that single-nucleotide polymorphisms are the predominant form of heterogeneity at the strain level. The Leptospirillum group II genome had remarkably few nucleotide polymorphisms, despite the existence of low-abundance variants. The Ferroplasma type II genome seems to be a composite from three ancestral strains that have undergone homologous recombination to form a large population of mosaic genomes. Analysis of the gene complement for each organism revealed the pathways for carbon and nitrogen fixation and energy generation, and provided insights into survival strategies in an extreme environment.
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              Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

              Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at .
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                Author and article information

                Journal
                EFSA J
                EFSA J
                10.1002/(ISSN)1831-4732
                EFS2
                EFSA Journal
                John Wiley and Sons Inc. (Hoboken )
                1831-4732
                03 December 2019
                December 2019
                : 17
                : 12 ( doiID: 10.1002/efs2.v17.12 )
                : e05898
                Author notes
                [*] Correspondence: biohaz@ 123456efsa.europa.eu
                Article
                EFS25898
                10.2903/j.efsa.2019.5898
                7008917
                32626197
                c32a57dd-557e-40bb-969e-f5497901d271
                © 2019 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited and no modifications or adaptations are made.

                History
                Page count
                Figures: 2, Tables: 6, Pages: 78, Words: 45282
                Categories
                Scientific Opinion
                Scientific Opinion
                Custom metadata
                2.0
                December 2019
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.5 mode:remove_FC converted:21.01.2020

                whole genome sequencing,metagenomics,microbial risk assessment,source attribution,antimicrobial resistance,typing of food‐borne pathogens,food‐borne outbreak investigation

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