Literature DB >> 19866456

Metabolic response of tomato leaves upon different plant-pathogen interactions.

M Pilar López-Gresa1, Federica Maltese, José María Bellés, Vicente Conejero, Hye Kyong Kim, Young Hae Choi, Robert Verpoorte.   

Abstract

INTRODUCTION: Plants utilise various defence mechanisms against their potential biotic stressing agents such as viroids, viruses, bacteria or fungi and abiotic environmental challenges. Among them metabolic alteration is a common response in both compatible and incompatible plant-pathogen interactions. However, the identification of metabolic changes associated with defence response is not an easy task due to the complexity of the metabolome and the plant response. To address the problem of metabolic complexity, a metabolomics approach was employed in this study.
OBJECTIVE: To identify a wide range of pathogen (citrus exocortis viroid, CEVd, or Pseudomonas syringae pv. tomato)-induced metabolites of tomato using metabolomics.
METHODOLOGY: Nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate data analysis were performed to analyse the metabolic changes implicated in plant-pathogen interaction.
RESULTS: NMR-based metabolomics of crude extracts allowed the identification of different metabolites implicated in the systemic (viroid) and hypersensitive response (bacteria) in plant-pathogen interactions. While glycosylated gentisic acid was the most important induced metabolite in the viroid infection, phenylpropanoids and a flavonoid (rutin) were found to be associated with bacterial infection.
CONCLUSIONS: NMR metabolomics is a potent platform to analyse the compounds involved in different plant infections. A broad response to different pathogenic infections was revealed at metabolomic levels in the plant. Also, metabolic specificity against each pathogen was observed. (c) 2009 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 19866456     DOI: 10.1002/pca.1179

Source DB:  PubMed          Journal:  Phytochem Anal        ISSN: 0958-0344            Impact factor:   3.373


  26 in total

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Review 3.  Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value.

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4.  Molecular cloning and characterization of a novel tomato xylosyltransferase specific for gentisic acid.

Authors:  Susana Tárraga; Purificación Lisón; María Pilar López-Gresa; Cristina Torres; Ismael Rodrigo; José María Bellés; Vicente Conejero
Journal:  J Exp Bot       Date:  2010-08-20       Impact factor: 6.992

5.  Metabolic and miRNA profiling of TMV infected plants reveals biphasic temporal changes.

Authors:  Ariel A Bazzini; Carlos A Manacorda; Takayuki Tohge; Gabriela Conti; Maria C Rodriguez; Adriano Nunes-Nesi; Sofía Villanueva; Alisdair R Fernie; Fernando Carrari; Sebastian Asurmendi
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Review 6.  Genetic and genomic approaches for R-gene mediated disease resistance in tomato: retrospects and prospects.

Authors:  M R Ercolano; W Sanseverino; P Carli; F Ferriello; L Frusciante
Journal:  Plant Cell Rep       Date:  2012-02-18       Impact factor: 4.570

7.  Metabolomic Response of Tomatoes (Solanum lycopersicum L.) against Bacterial Wilt (Ralstonia solanacearum) Using 1H-NMR Spectroscopy.

Authors:  Rudi Hari Murti; Enik Nurlaili Afifah; Tri Rini Nuringtyas
Journal:  Plants (Basel)       Date:  2021-06-03

8.  FT-ICR/MS and GC-EI/MS metabolomics networking unravels global potato sprout's responses to Rhizoctonia solani infection.

Authors:  Konstantinos A Aliferis; Suha Jabaji
Journal:  PLoS One       Date:  2012-08-03       Impact factor: 3.240

9.  Tomato transcriptome and mutant analyses suggest a role for plant stress hormones in the interaction between fruit and Botrytis cinerea.

Authors:  Barbara Blanco-Ulate; Estefania Vincenti; Ann L T Powell; Dario Cantu
Journal:  Front Plant Sci       Date:  2013-05-14       Impact factor: 5.753

10.  Similar metabolic changes induced by HIPVs exposure as herbivore in Ammopiptanthus mongolicus.

Authors:  Jingru Sun; Xiao Zhang; Chuanjian Cao; Xindi Mei; Ningning Wang; Suli Yan; Shixiang Zong; Youqing Luo; Haijun Yang; Yingbai Shen
Journal:  PLoS One       Date:  2014-04-18       Impact factor: 3.240

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