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      Using whole genome sequencing to study American foulbrood epidemiology in honeybees

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      1 , 2 , 3 , *
      PLoS ONE
      Public Library of Science

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          Abstract

          American foulbrood (AFB), caused by Paenibacillus larvae, is a devastating disease in honeybees. In most countries, the disease is controlled through compulsory burning of symptomatic colonies causing major economic losses in apiculture. The pathogen is endemic to honeybees world-wide and is readily transmitted via the movement of hive equipment or bees. Molecular epidemiology of AFB currently largely relies on placing isolates in one of four ERIC-genotypes. However, a more powerful alternative is multi-locus sequence typing (MLST) using whole-genome sequencing (WGS), which allows for high-resolution studies of disease outbreaks. To evaluate WGS as a tool for AFB-epidemiology, we applied core genome MLST (cgMLST) on isolates from a recent outbreak of AFB in Sweden. The high resolution of the cgMLST allowed different bacterial clones involved in the disease outbreak to be identified and to trace the source of infection. The source was found to be a beekeeper who had sold bees to two other beekeepers, proving the epidemiological link between them. No such conclusion could have been made using conventional MLST or ERIC-typing. This is the first time that WGS has been used to study the epidemiology of AFB. The results show that the technique is very powerful for high-resolution tracing of AFB-outbreaks.

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          Most cited references21

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          MLST revisited: the gene-by-gene approach to bacterial genomics.

          Multilocus sequence typing (MLST) was proposed in 1998 as a portable sequence-based method for identifying clonal relationships among bacteria. Today, in the whole-genome era of microbiology, the need for systematic, standardized descriptions of bacterial genotypic variation remains a priority. Here, to meet this need, we draw on the successes of MLST and 16S rRNA gene sequencing to propose a hierarchical gene-by-gene approach that reflects functional and evolutionary relationships and catalogues bacteria 'from domain to strain'. Our gene-based typing approach using online platforms such as the Bacterial Isolate Genome Sequence Database (BIGSdb) allows the scalable organization and analysis of whole-genome sequence data.
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            Rapid whole-genome sequencing for investigation of a neonatal MRSA outbreak.

            Isolates of methicillin-resistant Staphylococcus aureus (MRSA) belonging to a single lineage are often indistinguishable by means of current typing techniques. Whole-genome sequencing may provide improved resolution to define transmission pathways and characterize outbreaks. We investigated a putative MRSA outbreak in a neonatal intensive care unit. By using rapid high-throughput sequencing technology with a clinically relevant turnaround time, we retrospectively sequenced the DNA from seven isolates associated with the outbreak and another seven MRSA isolates associated with carriage of MRSA or bacteremia in the same hospital. We constructed a phylogenetic tree by comparing single-nucleotide polymorphisms (SNPs) in the core genome to a reference genome (an epidemic MRSA clone, EMRSA-15 [sequence type 22]). This revealed a distinct cluster of outbreak isolates and clear separation between these and the nonoutbreak isolates. A previously missed transmission event was detected between two patients with bacteremia who were not part of the outbreak. We created an artificial "resistome" of antibiotic-resistance genes and demonstrated concordance between it and the results of phenotypic susceptibility testing; we also created a "toxome" consisting of toxin genes. One outbreak isolate had a hypermutator phenotype with a higher number of SNPs than the other outbreak isolates, highlighting the difficulty of imposing a simple threshold for the number of SNPs between isolates to decide whether they are part of a recent transmission chain. Whole-genome sequencing can provide clinically relevant data within a time frame that can influence patient care. The need for automated data interpretation and the provision of clinically meaningful reports represent hurdles to clinical implementation. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.).
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              American Foulbrood in honeybees and its causative agent, Paenibacillus larvae.

              After more than a century of American Foulbrood (AFB) research, this fatal brood infection is still among the most deleterious bee diseases. Its etiological agent is the Gram-positive, spore-forming bacterium Paenibacillus larvae. Huge progress has been made, especially in the last 20 years, in the understanding of the disease and of the underlying host-pathogen interactions. This review will place these recent developments in the study of American Foulbrood and of P. larvae into the general context of AFB research. Copyright 2009 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Role: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 November 2017
                2017
                : 12
                : 11
                : e0187924
                Affiliations
                [1 ] Department of Microbiology, National Veterinary Institute, Uppsala, Sweden
                [2 ] Federal Research Institute for Animal Health, Friedrich-Loeffler-Institut, Greifswald, Insel Riems, Germany
                [3 ] Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden
                Philipps-Universitat Marburg Fachbereich Biologie, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-8244-7265
                Article
                PONE-D-17-25635
                10.1371/journal.pone.0187924
                5687730
                29140998
                7aaa607e-282f-4cda-af4a-b9dbade47232
                © 2017 Ågren et al

                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 author and source are credited.

                History
                : 7 July 2017
                : 27 October 2017
                Page count
                Figures: 2, Tables: 1, Pages: 13
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Developmental Biology
                Life Cycles
                Larvae
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Invertebrate Genomics
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Hymenoptera
                Bees
                Honey Bees
                Medicine and Health Sciences
                Epidemiology
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Hymenoptera
                Bees
                Medicine and Health Sciences
                Epidemiology
                Infectious Disease Epidemiology
                Medicine and Health Sciences
                Infectious Diseases
                Infectious Disease Epidemiology
                Medicine and Health Sciences
                Infectious Diseases
                Infectious Disease Control
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genomic Libraries
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genomic Libraries
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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                Uncategorized

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