Successful completion of fruit developmental programs depends on the interplay between multiple phytohormones. However, besides ethylene, the impact of other hormones on fruit quality traits remains elusive. A previous study has shown that downregulation of SlARF4, a member of the tomato (Solanum lycopersicum) auxin response factor (ARF) gene family, results in a darkgreen fruit phenotype with increased chloroplasts (Jones et al., 2002). This study further examines the role of this auxin transcriptional regulator during tomato fruit development at the level of transcripts, enzyme activities, and metabolites. It is noteworthy that the dark-green phenotype of antisense SlARF4-suppressed lines is restricted to fruit, suggesting that SlARF4 controls chlorophyll accumulation specifically in this organ. The SlARF4 underexpressing lines accumulate more starch at early stages of fruit development and display enhanced chlorophyll content and photochemical efficiency, which is consistent with the idea that fruit photosynthetic activity accounts for the elevated starch levels. SlARF4 expression is high in pericarp tissues of immature fruit and then undergoes a dramatic decline at the onset of ripening concomitant with the increase in sugar content. The higher starch content in developing fruits of SlARF4 down-regulated lines correlates with the up-regulation of genes and enzyme activities involved in starch biosynthesis, suggesting their negative regulation by SlARF4. Altogether, the data uncover the involvement of ARFs in the control of sugar content, an essential feature of fruit quality, and provide insight into the link between auxin signaling, chloroplastic activity, and sugar metabolism in developing fruit.

To assess the influence of the environment on fruit metabolism, tomato (Solanum lycopersicum 'Moneymaker') plants were grown under contrasting conditions (optimal for commercial, water limited, or shaded production) and locations. Samples were harvested at nine stages of development, and 36 enzyme activities of central metabolism were measured as well as protein, starch, and major metabolites, such as hexoses, sucrose, organic acids, and amino acids. The most remarkable result was the high reproducibility of enzyme activities throughout development, irrespective of conditions or location. Hierarchical clustering of enzyme activities also revealed tight relationships between metabolic pathways and phases of development. Thus, cell division was characterized by high activities of fructokinase, glucokinase, pyruvate kinase, and tricarboxylic acid cycle enzymes, indicating ATP production as a priority, whereas cell expansion was characterized by enzymes involved in the lower part of glycolysis, suggesting a metabolic reprogramming to anaplerosis. As expected, enzymes involved in the accumulation of sugars, citrate, and glutamate were strongly increased during ripening. However, a group of enzymes involved in ATP production, which is probably fueled by starch degradation, was also increased. Metabolites levels seemed more sensitive than enzymes to the environment, although such differences tended to decrease at ripening. The integration of enzyme and metabolite data obtained under contrasting growth conditions using principal component analysis suggests that, with the exceptions of alanine amino transferase and glutamate and malate dehydrogenase and malate, there are no links between single enzyme activities and metabolite time courses or levels.

A metabolomics approach combining (1)H NMR and gas chromatography-electrospray ionization time-of-flight mass spectrometry (GC-EI-TOFMS) profiling was employed to characterize melon (Cucumis melo L.) fruit. In a first step, quantitative (1)H NMR of polar extracts and principal component analyses (PCA) of the corresponding data highlighted the major metabolites in fruit flesh, including sugars, organic acids, and amino acids. In a second step, the spatial localization of metabolites was investigated using both analytical techniques. Direct (1)H NMR profiling of juice or GC-EI-TOFMS profiling of tissue extracts collected from different locations in the fruit flesh provided information on advantages and drawbacks of each technique for the analysis of a sugar-rich matrix such as fruit. (1)H NMR and GC-EI-TOFMS data sets were compared using independently performed PCA and multiblock hierarchical PCA (HPCA), respectively. In addition a correlation-based multiblock HPCA was used for direct comparison of both analytical data sets. These data analyses revealed several gradients of metabolites in fruit flesh which can be related with differences in metabolism and indicated the suitability of multiblock HPCA for correlation of data from two (or potentially more) metabolomics platforms.