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Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection

Phakopsora pachyrhizi is a biotrophic fungus, causer of the disease Asian Soybean Rust, a severe crop disease of soybean and one that demands greater investment from producers. Thus, research efforts to control this disease are still needed. We investigated the expression of metabolites in soybean p...

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Autores principales: Silva, Evandro, Perez da Graça, José, Porto, Carla, Martin do Prado, Rodolpho, Nunes, Estela, Corrêa Marcelino-Guimarães, Francismar, Conrado Meyer, Mauricio, Jorge Pilau, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003322/
https://www.ncbi.nlm.nih.gov/pubmed/33808519
http://dx.doi.org/10.3390/metabo11030179
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author Silva, Evandro
Perez da Graça, José
Porto, Carla
Martin do Prado, Rodolpho
Nunes, Estela
Corrêa Marcelino-Guimarães, Francismar
Conrado Meyer, Mauricio
Jorge Pilau, Eduardo
author_facet Silva, Evandro
Perez da Graça, José
Porto, Carla
Martin do Prado, Rodolpho
Nunes, Estela
Corrêa Marcelino-Guimarães, Francismar
Conrado Meyer, Mauricio
Jorge Pilau, Eduardo
author_sort Silva, Evandro
collection PubMed
description Phakopsora pachyrhizi is a biotrophic fungus, causer of the disease Asian Soybean Rust, a severe crop disease of soybean and one that demands greater investment from producers. Thus, research efforts to control this disease are still needed. We investigated the expression of metabolites in soybean plants presenting a resistant genotype inoculated with P. pachyrhizi through the untargeted metabolomics approach. The analysis was performed in control and inoculated plants with P. pachyrhizi using UHPLC-MS/MS. Principal component analysis (PCA) and the partial least squares discriminant analysis (PLS-DA), was applied to the data analysis. PCA and PLS-DA resulted in a clear separation and classification of groups between control and inoculated plants. The metabolites were putative classified and identified using the Global Natural Products Social Molecular Networking platform in flavonoids, isoflavonoids, lipids, fatty acyls, terpenes, and carboxylic acids. Flavonoids and isoflavonoids were up-regulation, while terpenes were down-regulated in response to the soybean–P. pachyrhizi interaction. Our data provide insights into the potential role of some metabolites as flavonoids and isoflavonoids in the plant resistance to ASR. This information could result in the development of resistant genotypes of soybean to P. pachyrhizi, and effective and specific products against the pathogen.
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spelling pubmed-80033222021-03-28 Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection Silva, Evandro Perez da Graça, José Porto, Carla Martin do Prado, Rodolpho Nunes, Estela Corrêa Marcelino-Guimarães, Francismar Conrado Meyer, Mauricio Jorge Pilau, Eduardo Metabolites Article Phakopsora pachyrhizi is a biotrophic fungus, causer of the disease Asian Soybean Rust, a severe crop disease of soybean and one that demands greater investment from producers. Thus, research efforts to control this disease are still needed. We investigated the expression of metabolites in soybean plants presenting a resistant genotype inoculated with P. pachyrhizi through the untargeted metabolomics approach. The analysis was performed in control and inoculated plants with P. pachyrhizi using UHPLC-MS/MS. Principal component analysis (PCA) and the partial least squares discriminant analysis (PLS-DA), was applied to the data analysis. PCA and PLS-DA resulted in a clear separation and classification of groups between control and inoculated plants. The metabolites were putative classified and identified using the Global Natural Products Social Molecular Networking platform in flavonoids, isoflavonoids, lipids, fatty acyls, terpenes, and carboxylic acids. Flavonoids and isoflavonoids were up-regulation, while terpenes were down-regulated in response to the soybean–P. pachyrhizi interaction. Our data provide insights into the potential role of some metabolites as flavonoids and isoflavonoids in the plant resistance to ASR. This information could result in the development of resistant genotypes of soybean to P. pachyrhizi, and effective and specific products against the pathogen. MDPI 2021-03-19 /pmc/articles/PMC8003322/ /pubmed/33808519 http://dx.doi.org/10.3390/metabo11030179 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Silva, Evandro
Perez da Graça, José
Porto, Carla
Martin do Prado, Rodolpho
Nunes, Estela
Corrêa Marcelino-Guimarães, Francismar
Conrado Meyer, Mauricio
Jorge Pilau, Eduardo
Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection
title Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection
title_full Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection
title_fullStr Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection
title_full_unstemmed Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection
title_short Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection
title_sort untargeted metabolomics analysis by uhplc-ms/ms of soybean plant in a compatible response to phakopsora pachyrhizi infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003322/
https://www.ncbi.nlm.nih.gov/pubmed/33808519
http://dx.doi.org/10.3390/metabo11030179
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