Characterization of the metabolic profile of olive tissues (roots, stems and leaves): relationship with cultivars' resistance/susceptibility to the soil fungus Verticillium dahliae.

Serrano García, Irene, Olmo García, Lucía, Monago Maraña, Olga, Muñoz Cabello de Alba, Iván, León, Lorenzo, Rosa, Raúl de la, Serrano, Alicia, GómezCaravaca, Ana María y Carrasco Pancorbo, Alegría . (2023) Characterization of the metabolic profile of olive tissues (roots, stems and leaves): relationship with cultivars' resistance/susceptibility to the soil fungus Verticillium dahliae.. Antioxidants (2023), 12, 2120 - 2143

Ficheros (Some files may be inaccessible until you login with your e-spacio credentials)
Nombre Descripción Tipo MIME Size
Monago_Marana__Olga_Antioxidants.pdf Monago Marana, Olga_Antioxidants.pdf Click to show the corresponding preview/stream application/pdf; 1.25MB

Título Characterization of the metabolic profile of olive tissues (roots, stems and leaves): relationship with cultivars' resistance/susceptibility to the soil fungus Verticillium dahliae.
Autor(es) Serrano García, Irene
Olmo García, Lucía
Monago Maraña, Olga
Muñoz Cabello de Alba, Iván
León, Lorenzo
Rosa, Raúl de la
Serrano, Alicia
GómezCaravaca, Ana María
Carrasco Pancorbo, Alegría
Materia(s) Ciencias
Abstract Verticillium wilt of olive (VWO) is one of the most widespread and devastating olive diseases in the world. Harnessing host resistance to the causative agent is considered one of the most important measures within an integrated control strategy of the disease. Aiming to understand the mechanisms underlying olive resistance to VWO, the metabolic profiles of olive leaves, stems and roots from 10 different cultivars with varying levels of susceptibility to this disease were investigated by liquid chromatography coupled to mass spectrometry (LC-MS). The distribution of 56 metabolites among the three olive tissues was quantitatively assessed and the possible relationship between the tissues’ metabolic profiles and resistance to VWO was evaluated by applying unsupervised and supervised multivariate analysis. Principal component analysis (PCA) was used to explore the data, and separate clustering of highly resistant and extremely susceptible cultivars was observed. Moreover, partial least squares discriminant analysis (PLS-DA) models were built to differentiate samples of highly resistant, intermediate susceptible/resistant, and extremely susceptible cultivars. Root models showed the lowest classification capability, but metabolites from leaf and stem were able to satisfactorily discriminate samples according to the level of susceptibility. Some typical compositional patterns of highly resistant and extremely susceptible cultivars were described, and some potential resistance/susceptibility metabolic markers were pointed out.
Palabras clave Olea europaea L
verticillium wilt
plant metabolomics
LC-MS profiling
secondary metabolites
phenolic compounds
triterpenic compounds
Editor(es) MDPI
Fecha 2023-12-15
Formato application/pdf
Identificador bibliuned:DptoCA-FCIE-Articulos-Omonago-0001
http://e-spacio.uned.es/fez/view/bibliuned:DptoCA-FCIE-Articulos-Omonago-0001
DOI - identifier https://doi.org/10.3390/antiox12122120
ISSN - identifier eISSN 2076-3921
Nombre de la revista Antioxidants
Número de Volumen 12
Página inicial 2120
Página final 2143
Publicado en la Revista Antioxidants (2023), 12, 2120 - 2143
Idioma eng
Versión de la publicación publishedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto
Notas adicionales The registered version of this article, first published in Antioxidants, is available online at the publisher's website: MDPI, https://doi.org/10.3390/antiox12122120
Notas adicionales La versión registrada de este artículo, publicado por primera vez en Antioxidants, está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/antiox12122120

Tipo de documento: Artículo de revista
Collections: Departamento de Ciencias Analiticas. Artículos
Set de artículo
Set de openaire
 
Versiones
Versión Tipo de filtro
Contador de citas: Google Scholar Search Google Scholar
Estadísticas de acceso: 37 Visitas, 6 Descargas  -  Estadísticas en detalle
Creado: Tue, 13 Feb 2024, 05:29:05 CET