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      Genome analysis provides insights into the epidemiology of infection with Flavobacterium psychrophilum among farmed salmonid fish in Sweden

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          Abstract

          The pathogen Flavobacterium psychrophilum is a major problem for the expanding salmonid fish farming industry in Sweden as well as worldwide. A better understanding of the phylogeography and infection routes of F. psychrophilum outbreaks could help to improve aquaculture profitability and the welfare of farmed fish while reducing the need for antibiotics. In the present study, high-throughput genome sequencing was applied to a collection of F. psychrophilum isolates ( n=38) from outbreaks on fish farms in different regions of Sweden between 1988 and 2016. Antibiotic susceptibility tests were applied to a subset of the isolates and the results correlated to the presence of genetic resistance markers. We show that F. psychrophilum clones are not regionally biased and that new clones with a higher degree of antibiotic resistance have emerged nationwide during the study period. This supports previous theories of the importance of live fish and egg trade as a route of infection. Continuous monitoring of recovered isolates by high-throughput sequencing techniques in the future could facilitate tracing of clones within and between countries, as well as the detection of emergent virulent or antibiotic-resistant clones. This article contains data hosted by Microreact.

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          Most cited references 19

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data

            (2013)
          Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.
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            Benchmarking of methods for genomic taxonomy.

            One of the first issues that emerges when a prokaryotic organism of interest is encountered is the question of what it is--that is, which species it is. The 16S rRNA gene formed the basis of the first method for sequence-based taxonomy and has had a tremendous impact on the field of microbiology. Nevertheless, the method has been found to have a number of shortcomings. In the current study, we trained and benchmarked five methods for whole-genome sequence-based prokaryotic species identification on a common data set of complete genomes: (i) SpeciesFinder, which is based on the complete 16S rRNA gene; (ii) Reads2Type that searches for species-specific 50-mers in either the 16S rRNA gene or the gyrB gene (for the Enterobacteraceae family); (iii) the ribosomal multilocus sequence typing (rMLST) method that samples up to 53 ribosomal genes; (iv) TaxonomyFinder, which is based on species-specific functional protein domain profiles; and finally (v) KmerFinder, which examines the number of cooccurring k-mers (substrings of k nucleotides in DNA sequence data). The performances of the methods were subsequently evaluated on three data sets of short sequence reads or draft genomes from public databases. In total, the evaluation sets constituted sequence data from more than 11,000 isolates covering 159 genera and 243 species. Our results indicate that methods that sample only chromosomal, core genes have difficulties in distinguishing closely related species which only recently diverged. The KmerFinder method had the overall highest accuracy and correctly identified from 93% to 97% of the isolates in the evaluations sets.
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              Complete genome sequence of the fish pathogen Flavobacterium psychrophilum.

              We report here the complete genome sequence of the virulent strain JIP02/86 (ATCC 49511) of Flavobacterium psychrophilum, a widely distributed pathogen of wild and cultured salmonid fish. The genome consists of a 2,861,988-base pair (bp) circular chromosome with 2,432 predicted protein-coding genes. Among these predicted proteins, stress response mediators, gliding motility proteins, adhesins and many putative secreted proteases are probably involved in colonization, invasion and destruction of the host tissues. The genome sequence provides the basis for explaining the relationships of the pathogen to the host and opens new perspectives for the development of more efficient disease control strategies. It also allows for a better understanding of the physiology and evolution of a significant representative of the family Flavobacteriaceae, whose members are associated with an interesting diversity of lifestyles and habitats.
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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                mgen
                mgen
                Microbial Genomics
                Microbiology Society
                2057-5858
                December 2018
                13 December 2018
                13 December 2018
                : 4
                : 12
                Affiliations
                [ 1]Department of Microbiology, National Veterinary Institute (SVA) , 75189, Uppsala, Sweden
                [ 2]Department of Animal Health and Antimicrobial Strategies, National Veterinary Institute (SVA) , Uppsala, Sweden
                Author notes
                *Correspondence: Robert Söderlund, robert.soderlund@ 123456sva.se
                Article
                mgen000241
                10.1099/mgen.0.000241
                6412038
                30543323
                © 2018 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Product
                Funding
                Funded by: Swedish Board of Agriculture
                Categories
                Short Communication
                Microbial Evolution and Epidemiology: Phylogeography
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