1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Multilocus sequence typing reveals clonality in Saprolegnia parasitica outbreaks

      1 , 1 , 2
      Journal of Fish Diseases
      Wiley

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references21

          • Record: found
          • Abstract: found
          • Article: not found

          eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

          The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            OligoCalc: an online oligonucleotide properties calculator

            We developed OligoCalc as a web-accessible, client-based computational engine for reporting DNA and RNA single-stranded and double-stranded properties, including molecular weight, solution concentration, melting temperature, estimated absorbance coefficients, inter-molecular self-complementarity estimation and intra-molecular hairpin loop formation. OligoCalc has a familiar ‘calculator’ look and feel, making it readily understandable and usable. OligoCalc incorporates three common methods for calculating oligonucleotide-melting temperatures, including a nearest-neighbor thermodynamic model for melting temperature. Since it first came online in 1997, there have been more than 900 000 accesses of OligoCalc from nearly 200 000 distinct hosts, excluding search engines. OligoCalc is available at http://basic.northwestern.edu/biotools/OligoCalc.html, with links to the full source code, usage patterns and statistics at that link as well.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Multilocus sequence typing of bacteria.

              Multilocus sequence typing (MLST) was proposed in 1998 as a portable, universal, and definitive method for characterizing bacteria, using the human pathogen Neisseria meningitidis as an example. In addition to providing a standardized approach to data collection, by examining the nucleotide sequences of multiple loci encoding housekeeping genes, or fragments of them, MLST data are made freely available over the Internet to ensure that a uniform nomenclature is readily available to all those interested in categorizing bacteria. At the time of writing, over thirty MLST schemes have been published and made available on the Internet, mostly for pathogenic bacteria, although there are schemes for pathogenic fungi and some nonpathogenic bacteria. MLST data have been employed in epidemiological investigations of various scales and in studies of the population biology, pathogenicity, and evolution of bacteria. The increasing speed and reduced cost of nucleotide sequence determination, together with improved web-based databases and analysis tools, present the prospect of increasingly wide application of MLST.
                Bookmark

                Author and article information

                Journal
                Journal of Fish Diseases
                J Fish Dis
                Wiley
                01407775
                November 2018
                November 2018
                July 27 2018
                : 41
                : 11
                : 1653-1665
                Affiliations
                [1 ]Laboratory of applied microbiology; University of Applied Sciences and Arts of Southern Switzerland; Bellinzona Switzerland
                [2 ]Centre for Fish and Wildlife Health; Institute of Animal Pathology; University of Bern; Bern Switzerland
                Article
                10.1111/jfd.12869
                30051543
                bcb7de01-a04d-459c-9493-aa28cb4a872c
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                History

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content3,943

                Cited by5

                Most referenced authors478