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PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data

Although the majority of bacteria are harmless or even beneficial to their host, others are highly virulent and can cause serious diseases, and even death. Due to the constantly decreasing cost of high-throughput sequencing there are now many completely sequenced genomes available from both human pa...

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Autores principales: Cosentino, Salvatore, Voldby Larsen, Mette, Møller Aarestrup, Frank, Lund, Ole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3810466/
https://www.ncbi.nlm.nih.gov/pubmed/24204795
http://dx.doi.org/10.1371/journal.pone.0077302
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author Cosentino, Salvatore
Voldby Larsen, Mette
Møller Aarestrup, Frank
Lund, Ole
author_facet Cosentino, Salvatore
Voldby Larsen, Mette
Møller Aarestrup, Frank
Lund, Ole
author_sort Cosentino, Salvatore
collection PubMed
description Although the majority of bacteria are harmless or even beneficial to their host, others are highly virulent and can cause serious diseases, and even death. Due to the constantly decreasing cost of high-throughput sequencing there are now many completely sequenced genomes available from both human pathogenic and innocuous strains. The data can be used to identify gene families that correlate with pathogenicity and to develop tools to predict the pathogenicity of newly sequenced strains, investigations that previously were mainly done by means of more expensive and time consuming experimental approaches. We describe PathogenFinder (http://cge.cbs.dtu.dk/services/PathogenFinder/), a web-server for the prediction of bacterial pathogenicity by analysing the input proteome, genome, or raw reads provided by the user. The method relies on groups of proteins, created without regard to their annotated function or known involvement in pathogenicity. The method has been built to work with all taxonomic groups of bacteria and using the entire training-set, achieved an accuracy of 88.6% on an independent test-set, by correctly classifying 398 out of 449 completely sequenced bacteria. The approach here proposed is not biased on sets of genes known to be associated with pathogenicity, thus the approach could aid the discovery of novel pathogenicity factors. Furthermore the pathogenicity prediction web-server could be used to isolate the potential pathogenic features of both known and unknown strains.
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spelling pubmed-38104662013-11-07 PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data Cosentino, Salvatore Voldby Larsen, Mette Møller Aarestrup, Frank Lund, Ole PLoS One Research Article Although the majority of bacteria are harmless or even beneficial to their host, others are highly virulent and can cause serious diseases, and even death. Due to the constantly decreasing cost of high-throughput sequencing there are now many completely sequenced genomes available from both human pathogenic and innocuous strains. The data can be used to identify gene families that correlate with pathogenicity and to develop tools to predict the pathogenicity of newly sequenced strains, investigations that previously were mainly done by means of more expensive and time consuming experimental approaches. We describe PathogenFinder (http://cge.cbs.dtu.dk/services/PathogenFinder/), a web-server for the prediction of bacterial pathogenicity by analysing the input proteome, genome, or raw reads provided by the user. The method relies on groups of proteins, created without regard to their annotated function or known involvement in pathogenicity. The method has been built to work with all taxonomic groups of bacteria and using the entire training-set, achieved an accuracy of 88.6% on an independent test-set, by correctly classifying 398 out of 449 completely sequenced bacteria. The approach here proposed is not biased on sets of genes known to be associated with pathogenicity, thus the approach could aid the discovery of novel pathogenicity factors. Furthermore the pathogenicity prediction web-server could be used to isolate the potential pathogenic features of both known and unknown strains. Public Library of Science 2013-10-28 /pmc/articles/PMC3810466/ /pubmed/24204795 http://dx.doi.org/10.1371/journal.pone.0077302 Text en © 2013 Cosentino et al http://creativecommons.org/licenses/by/4.0/ 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 properly credited.
spellingShingle Research Article
Cosentino, Salvatore
Voldby Larsen, Mette
Møller Aarestrup, Frank
Lund, Ole
PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data
title PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data
title_full PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data
title_fullStr PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data
title_full_unstemmed PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data
title_short PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data
title_sort pathogenfinder - distinguishing friend from foe using bacterial whole genome sequence data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3810466/
https://www.ncbi.nlm.nih.gov/pubmed/24204795
http://dx.doi.org/10.1371/journal.pone.0077302
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