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Computational prediction shines light on type III secretion origins
Type III secretion system is a key bacterial symbiosis and pathogenicity mechanism responsible for a variety of infectious diseases, ranging from food-borne illnesses to the bubonic plague. In many Gram-negative bacteria, the type III secretion system transports effector proteins into host cells, co...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054392/ https://www.ncbi.nlm.nih.gov/pubmed/27713481 http://dx.doi.org/10.1038/srep34516 |
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author | Goldberg, Tatyana Rost, Burkhard Bromberg, Yana |
author_facet | Goldberg, Tatyana Rost, Burkhard Bromberg, Yana |
author_sort | Goldberg, Tatyana |
collection | PubMed |
description | Type III secretion system is a key bacterial symbiosis and pathogenicity mechanism responsible for a variety of infectious diseases, ranging from food-borne illnesses to the bubonic plague. In many Gram-negative bacteria, the type III secretion system transports effector proteins into host cells, converting resources to bacterial advantage. Here we introduce a computational method that identifies type III effectors by combining homology-based inference with de novo predictions, reaching up to 3-fold higher performance than existing tools. Our work reveals that signals for recognition and transport of effectors are distributed over the entire protein sequence instead of being confined to the N-terminus, as was previously thought. Our scan of hundreds of prokaryotic genomes identified previously unknown effectors, suggesting that type III secretion may have evolved prior to the archaea/bacteria split. Crucially, our method performs well for short sequence fragments, facilitating evaluation of microbial communities and rapid identification of bacterial pathogenicity – no genome assembly required. pEffect and its data sets are available at http://services.bromberglab.org/peffect. |
format | Online Article Text |
id | pubmed-5054392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50543922016-10-19 Computational prediction shines light on type III secretion origins Goldberg, Tatyana Rost, Burkhard Bromberg, Yana Sci Rep Article Type III secretion system is a key bacterial symbiosis and pathogenicity mechanism responsible for a variety of infectious diseases, ranging from food-borne illnesses to the bubonic plague. In many Gram-negative bacteria, the type III secretion system transports effector proteins into host cells, converting resources to bacterial advantage. Here we introduce a computational method that identifies type III effectors by combining homology-based inference with de novo predictions, reaching up to 3-fold higher performance than existing tools. Our work reveals that signals for recognition and transport of effectors are distributed over the entire protein sequence instead of being confined to the N-terminus, as was previously thought. Our scan of hundreds of prokaryotic genomes identified previously unknown effectors, suggesting that type III secretion may have evolved prior to the archaea/bacteria split. Crucially, our method performs well for short sequence fragments, facilitating evaluation of microbial communities and rapid identification of bacterial pathogenicity – no genome assembly required. pEffect and its data sets are available at http://services.bromberglab.org/peffect. Nature Publishing Group 2016-10-07 /pmc/articles/PMC5054392/ /pubmed/27713481 http://dx.doi.org/10.1038/srep34516 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Goldberg, Tatyana Rost, Burkhard Bromberg, Yana Computational prediction shines light on type III secretion origins |
title | Computational prediction shines light on type III secretion origins |
title_full | Computational prediction shines light on type III secretion origins |
title_fullStr | Computational prediction shines light on type III secretion origins |
title_full_unstemmed | Computational prediction shines light on type III secretion origins |
title_short | Computational prediction shines light on type III secretion origins |
title_sort | computational prediction shines light on type iii secretion origins |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054392/ https://www.ncbi.nlm.nih.gov/pubmed/27713481 http://dx.doi.org/10.1038/srep34516 |
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