4.8 Article

Major proteome variations associated with cherry tomato pericarp development and ripening

Journal

PLANT PHYSIOLOGY
Volume 143, Issue 3, Pages 1327-1346

Publisher

AMER SOC PLANT BIOLOGISTS
DOI: 10.1104/pp.106.092817

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Tomato (Solanum lycopersicum) is a model plant for studying fleshy fruit development. Several genetic and molecular approaches have been developed to increase our knowledge about the physiological basis of fruit growth, but very few data are yet available at the proteomic level. The main stages of fruit development were first determined through the dynamics of fruit diameter and pericarp cell number. Then, total proteins were extracted from pericarp tissue at six relevant developmental stages and separated by two-dimensional gel electrophoresis. Protein patterns were markedly different between stages. Proteins showing major variations were monitored. We identified 90 of 1,791 well-resolved spots either by matrix-assisted laser-desorption ionization time-of-flight peptide mass fingerprinting or liquid chromatography-mass spectrometry sequencing and expressed sequence tag database searching. Clustered correlation analysis results pointed out groups of proteins with similar expression profiles during fruit development. In young fruit, spots linked to amino acid metabolism or protein synthesis were mainly expressed during the cell division stage and down-regulated later. Some spots linked to cell division processes could be identified. During the cell expansion phase, spots linked to photosynthesis and proteins linked to cell wall formation transiently increased. In contrast, the major part of the spots related to C compounds and carbohydrate metabolism or oxidative processes were up-regulated during fruit development, showing an increase in spot intensity during development and maximal abundance in mature fruit. This was also the case for spots linked to stress responses and fruit senescence. We discuss protein variations, taking into account their potential role during fruit growth and comparing our results with already known variations at mRNA and metabolite-profiling levels.

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