A Targeted and an Untargeted Metabolomics Approach to Study the Phytochemicals of Tomato Cultivars Grown Under Different Salinity Conditions.

J Agric Food Chem

Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville, Maryland 20705, United States.

Published: April 2024

AI Article Synopsis

  • The study assessed how different salt levels in irrigation water affect the metabolic profiles of two tomato cultivars, 'Jaune Flamme' and 'Red Pear', using advanced metabolomics techniques.
  • Key findings revealed that increasing salinity enhances specific compounds like chlorogenic acid, rutin, and free amino acids, particularly glutamine and GABA, in both tomato types.
  • The researchers employed statistical methods to analyze metabolite data and identified significant differences in how salinity impacts phytochemical accumulation, providing insights for future tomato breeding programs.

Article Abstract

In this study, we evaluated the effect of increasing the salinity of irrigation water on the metabolic content and profiles of two tomato cultivars ('Jaune Flamme' (JF) and 'Red Pear' (RP)) using targeted and untargeted metabolomics approaches. Irrigation of tomato plants was performed with four different salt concentrations provided by chloride (treatment 1) and sulfate (treatment 2) salts. Targeted analysis of the methanolic extract resulted in the identification of nine major polyphenols. Among them, chlorogenic acid, rutin, and naringenin were the prominent compounds in both cultivars. In addition, the quantification of 18 free amino acids from both tomato cultivars showed that different salinity treatments significantly enhanced the levels of glutamine, glutamic acid, and γ-aminobutyric acid (GABA). Using the untargeted metabolomic approach, we identified 129 putative metabolites encompassing a diverse array of phytochemicals including polyphenols, organic acids, lipids, sugars, and amino acids. Principal component analysis (PCA) of mass spectral data acquired under positive and negative ionization modes showed a clear separation between the two cultivars. However, only positive ionization showed separation among different salinity treatments. Unsupervised and supervised learning algorithms were applied to mine the generated data and to pinpoint metabolites different from the two cultivars. These findings suggest that different salinity conditions significantly influenced the accumulation of phytochemicals in tomato cultivars. This study will help tomato breeding programs to develop value-added tomato cultivars under varying environmental conditions.

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Source
http://dx.doi.org/10.1021/acs.jafc.3c08498DOI Listing

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