Jorge Candido Rodrigues-Neto1,2, Mauro Vicentini Correia1,3, Augusto Lopes Souto1, José Antônio de Aquino Ribeiro1, Letícia Rios Vieira1,4, Manoel Teixeira Souza1,4, Clenilson Martins Rodrigues1, Patrícia Verardi Abdelnur5,6. 1. Brazilian Agricultural Research Corporation, Embrapa Agroenergy, W3 Norte, PqEB, Brasília, DF, 70770-901, Brazil. 2. Institute of Chemistry, Federal University of Goiás, Campus Samambaia, Goiânia, GO, 74690-900, Brazil. 3. Institute of Chemistry, University of Brasília, Campus Universitário Darcy Ribeiro, Brasília, DF, 70910-900, Brazil. 4. Graduate Program in Plant Biotechnology, Federal University of Lavras, CP 3037, Lavras, MG, 37200-000, Brazil. 5. Brazilian Agricultural Research Corporation, Embrapa Agroenergy, W3 Norte, PqEB, Brasília, DF, 70770-901, Brazil. patricia.abdelnur@embrapa.br. 6. Institute of Chemistry, Federal University of Goiás, Campus Samambaia, Goiânia, GO, 74690-900, Brazil. patricia.abdelnur@embrapa.br.
Abstract
INTRODUCTION: Oil palm (E. guineensis), the most consumed vegetable oil in the world, is affected by fatal yellowing (FY), a condition that can lead to the plant's death. Although studies have been performed since the 1980s, including investigations of biotic and abiotic factors, FY's cause remains unknown and efforts in researches are still necessary. OBJECTIVES: This work aims to investigate the metabolic expression in plants affected by FY using an untargeted metabolomics approach. METHOD: Metabolic fingerprinting analysis of oil palm leaves was performed using ultra high liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS). Chemometric analysis, using principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), was applied to data analysis. Metabolites identification was performed by high resolution mass spectrometry (HRMS), MS/MS experiments and comparison with databases and literature. RESULTS: Metabolomics analysis based on MS detected more than 50 metabolites in oil palm leaf samples. PCA and PLS-DS analysis provided group segregation and classification of symptomatic and non-symptomatic FY samples, with a great external validation of the results. Nine differentially expressed metabolites were identified as glycerophosphorylcholine, arginine, asparagine, apigenin 6,8-di-C-hexose, tyramine, chlorophyllide, 1,2-dihexanoyl-sn-glycero-3-phosphoethanolamine, proline and malvidin 3-glucoside-5-(6″-malonylglucoside). Metabolic pathways and biological importance of those metabolites were assigned. CONCLUSION: Nine metabolites were detected in a higher concentration in non-symptomatic FY plants. Seven are related to stress factors i.e. plant defense and nutrient absorption, which can be affected by the metabolic depression of these compounds. Two of those metabolites (glycerophosphorylcholine and 1,2-dihexanoyl-sn-glycero-3-phosphoethanolamine) are presented as potential biomarkers, since they have no known direct relation to plant stress.
INTRODUCTION:Oil palm (E. guineensis), the most consumed vegetable oil in the world, is affected by fatal yellowing (FY), a condition that can lead to the plant's death. Although studies have been performed since the 1980s, including investigations of biotic and abiotic factors, FY's cause remains unknown and efforts in researches are still necessary. OBJECTIVES: This work aims to investigate the metabolic expression in plants affected by FY using an untargeted metabolomics approach. METHOD: Metabolic fingerprinting analysis of oil palm leaves was performed using ultra high liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS). Chemometric analysis, using principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), was applied to data analysis. Metabolites identification was performed by high resolution mass spectrometry (HRMS), MS/MS experiments and comparison with databases and literature. RESULTS: Metabolomics analysis based on MS detected more than 50 metabolites in oil palm leaf samples. PCA and PLS-DS analysis provided group segregation and classification of symptomatic and non-symptomatic FY samples, with a great external validation of the results. Nine differentially expressed metabolites were identified as glycerophosphorylcholine, arginine, asparagine, apigenin 6,8-di-C-hexose, tyramine, chlorophyllide, 1,2-dihexanoyl-sn-glycero-3-phosphoethanolamine, proline and malvidin 3-glucoside-5-(6″-malonylglucoside). Metabolic pathways and biological importance of those metabolites were assigned. CONCLUSION: Nine metabolites were detected in a higher concentration in non-symptomatic FY plants. Seven are related to stress factors i.e. plant defense and nutrient absorption, which can be affected by the metabolic depression of these compounds. Two of those metabolites (glycerophosphorylcholine and 1,2-dihexanoyl-sn-glycero-3-phosphoethanolamine) are presented as potential biomarkers, since they have no known direct relation to plant stress.
Entities:
Keywords:
Biomarkers; Chemometrics; Fatal yellowing; High resolution mass spectrometry; Metabolomics; Oil palm
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