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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...

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Autores principales: Sperschneider, Jana, Catanzariti, Ann-Maree, DeBoer, Kathleen, Petre, Benjamin, Gardiner, Donald M., Singh, Karam B., Dodds, Peter N., Taylor, Jennifer M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
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/.
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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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