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LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell
Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perfo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5353544/ https://www.ncbi.nlm.nih.gov/pubmed/28300209 http://dx.doi.org/10.1038/srep44598 |
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author | Sperschneider, Jana Catanzariti, Ann-Maree DeBoer, Kathleen Petre, Benjamin Gardiner, Donald M. Singh, Karam B. Dodds, Peter N. Taylor, Jennifer M. |
author_facet | Sperschneider, Jana Catanzariti, Ann-Maree DeBoer, Kathleen Petre, Benjamin Gardiner, Donald M. Singh, Karam B. Dodds, Peter N. Taylor, Jennifer M. |
author_sort | Sperschneider, Jana |
collection | PubMed |
description | Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/. |
format | Online Article Text |
id | pubmed-5353544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53535442017-03-20 LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell Sperschneider, Jana Catanzariti, Ann-Maree DeBoer, Kathleen Petre, Benjamin Gardiner, Donald M. Singh, Karam B. Dodds, Peter N. Taylor, Jennifer M. Sci Rep Article Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/. Nature Publishing Group 2017-03-16 /pmc/articles/PMC5353544/ /pubmed/28300209 http://dx.doi.org/10.1038/srep44598 Text en Copyright © 2017, 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 Sperschneider, Jana Catanzariti, Ann-Maree DeBoer, Kathleen Petre, Benjamin Gardiner, Donald M. Singh, Karam B. Dodds, Peter N. Taylor, Jennifer M. LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell |
title | LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell |
title_full | LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell |
title_fullStr | LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell |
title_full_unstemmed | LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell |
title_short | LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell |
title_sort | localizer: subcellular localization prediction of both plant and effector proteins in the plant cell |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5353544/ https://www.ncbi.nlm.nih.gov/pubmed/28300209 http://dx.doi.org/10.1038/srep44598 |
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