297 research outputs found

    Genealogical typing of Neisseria meningitidis

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    Despite the increasing popularity of multilocus sequence typing (MLST), the most appropriate method for characterizing bacterial variation and facilitating epidemiological investigations remains a matter of debate. Here, we propose that different typing schemes should be compared on the basis of their power to infer clonal relationships and investigate the utility of sequence data for genealogical reconstruction by exploiting new statistical tools and data from 20 housekeeping loci for 93 isolates of the bacterial pathogen Neisseria meningitidis. Our analysis demonstrated that all but one of the hyperinvasive isolates established by multilocus enzyme electrophoresis and MLST were grouped into one of six genealogical lineages, each of which contained substantial variation. Due to the confounding effect of recombination, evolutionary relationships among these lineages remained unclear, even using 20 loci. Analyses of the seven loci in the standard MLST scheme using the same methods reproduced this classification, but were unable to support finer inferences concerning the relationships between the members within each complex

    Simultaneous genome sequencing of symbionts and their hosts

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    Second-generation sequencing has made possible the sequencing of genomes of interest for even small research groups. However, obtaining separate clean cultures and clonal or inbred samples of metazoan hosts and their bacterial symbionts is often difficult. We present a computational pipeline for separating metazoan and bacterial DNA in silico rather than at the bench. The method relies on the generation of deep coverage of all the genomes in a mixed sample using Illumina short-read sequencing technology, and using aggregate properties of the different genomes to identify read sets belonging to each. This inexpensive and rapid approach has been used to sequence several nematode genomes and their bacterial endosymbionts in the last year in our laboratory and can also be used to visualize and identify unexpected contaminants (or possible symbionts) in genomic DNA samples. We hope that this method will enable researchers studying symbiotic systems to move from gene-centric to genome-centric approaches

    Whole genome sequencing to investigate the emergence of clonal complex 23 Neisseria meningitidis serogroup Y disease in the United States

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    In the United States, serogroup Y, ST-23 clonal complex Neisseria meningitidis was responsible for an increase in meningococcal disease incidence during the 1990s. This increase was accompanied by antigenic shift of three outer membrane proteins, with a decrease in the population that predominated in the early 1990s as a different population emerged later in that decade. To understand factors that may have been responsible for the emergence of serogroup Y disease, we used whole genome pyrosequencing to investigate genetic differences between isolates from early and late N. meningitidis populations, obtained from meningococcal disease cases in Maryland in the 1990s. The genomes of isolates from the early and late populations were highly similar, with 1231 of 1776 shared genes exhibiting 100% amino acid identity and an average πN = 0.0033 and average πS = 0.0216. However, differences were found in predicted proteins that affect pilin structure and antigen profile and in predicted proteins involved in iron acquisition and uptake. The observed changes are consistent with acquisition of new alleles through horizontal gene transfer. Changes in antigen profile due to the genetic differences found in this study likely allowed the late population to emerge due to escape from population immunity. These findings may predict which antigenic factors are important in the cyclic epidemiology of meningococcal disease

    Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

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    Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security

    Ergatis: a web interface and scalable software system for bioinformatics workflows

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    Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users
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