alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria
Alfalfa has emerged as one of the most important forage crops, owing to its wide adaptation and high biomass production worldwide. In the last decade, the emergence of bacterial stem blight (caused by <i>Pseudomonas syringae</i> pv. <i>syringae</i> ALF3) in alfalfa has caused...
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doaj-c1dcb6094aa3445486562ba7d009eaab2021-08-06T15:26:21ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-08-01228342834210.3390/ijms22158342alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing BacteriaRaghav Kataria0Rakesh Kaundal1Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, Logan, UT 84322, USADepartment of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, Logan, UT 84322, USAAlfalfa has emerged as one of the most important forage crops, owing to its wide adaptation and high biomass production worldwide. In the last decade, the emergence of bacterial stem blight (caused by <i>Pseudomonas syringae</i> pv. <i>syringae</i> ALF3) in alfalfa has caused around 50% yield losses in the United States. Studies are being conducted to decipher the roles of the key genes and pathways regulating the disease, but due to the sparse knowledge about the infection mechanisms of <i>Pseudomonas</i>, the development of resistant cultivars is hampered. The database alfaNET is an attempt to assist researchers by providing comprehensive <i>Pseudomonas</i> proteome annotations, as well as a host–pathogen interactome tool, which predicts the interactions between host and pathogen based on orthology. alfaNET is a user-friendly and efficient tool and includes other features such as subcellular localization annotations of pathogen proteins, gene ontology (GO) annotations, network visualization, and effector protein prediction. Users can also browse and search the database using particular keywords or proteins with a specific length. Additionally, the BLAST search tool enables the user to perform a homology sequence search against the alfalfa and <i>Pseudomonas</i> proteomes. With the successful implementation of these attributes, alfaNET will be a beneficial resource to the research community engaged in implementing molecular strategies to mitigate the disease. alfaNET is freely available for public use at http://bioinfo.usu.edu/alfanet/.https://www.mdpi.com/1422-0067/22/15/8342alfalfa<i>Pseudomonas syringae</i> ALF3bacterial stem blighteffectorsprotein–protein interactionsinterolog |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Raghav Kataria Rakesh Kaundal |
spellingShingle |
Raghav Kataria Rakesh Kaundal alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria International Journal of Molecular Sciences alfalfa <i>Pseudomonas syringae</i> ALF3 bacterial stem blight effectors protein–protein interactions interolog |
author_facet |
Raghav Kataria Rakesh Kaundal |
author_sort |
Raghav Kataria |
title |
alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria |
title_short |
alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria |
title_full |
alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria |
title_fullStr |
alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria |
title_full_unstemmed |
alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria |
title_sort |
alfanet: a database of alfalfa-bacterial stem blight protein–protein interactions revealing the molecular features of the disease-causing bacteria |
publisher |
MDPI AG |
series |
International Journal of Molecular Sciences |
issn |
1661-6596 1422-0067 |
publishDate |
2021-08-01 |
description |
Alfalfa has emerged as one of the most important forage crops, owing to its wide adaptation and high biomass production worldwide. In the last decade, the emergence of bacterial stem blight (caused by <i>Pseudomonas syringae</i> pv. <i>syringae</i> ALF3) in alfalfa has caused around 50% yield losses in the United States. Studies are being conducted to decipher the roles of the key genes and pathways regulating the disease, but due to the sparse knowledge about the infection mechanisms of <i>Pseudomonas</i>, the development of resistant cultivars is hampered. The database alfaNET is an attempt to assist researchers by providing comprehensive <i>Pseudomonas</i> proteome annotations, as well as a host–pathogen interactome tool, which predicts the interactions between host and pathogen based on orthology. alfaNET is a user-friendly and efficient tool and includes other features such as subcellular localization annotations of pathogen proteins, gene ontology (GO) annotations, network visualization, and effector protein prediction. Users can also browse and search the database using particular keywords or proteins with a specific length. Additionally, the BLAST search tool enables the user to perform a homology sequence search against the alfalfa and <i>Pseudomonas</i> proteomes. With the successful implementation of these attributes, alfaNET will be a beneficial resource to the research community engaged in implementing molecular strategies to mitigate the disease. alfaNET is freely available for public use at http://bioinfo.usu.edu/alfanet/. |
topic |
alfalfa <i>Pseudomonas syringae</i> ALF3 bacterial stem blight effectors protein–protein interactions interolog |
url |
https://www.mdpi.com/1422-0067/22/15/8342 |
work_keys_str_mv |
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