Plant cell cultures represent important model systems to understand metabolism and its modulation by regulatory factors. Even in controlled conditions, cell metabolism is highly dynamic and can be fully characterized only by time course experiments. Here, we show that statistical analysis of this type of data gains power if it moves to approaches able to compare the ‘trends’ of the different metabolites. In particular, we show how generalized additive models can be used to model the time-dependent profile of anthocyanin synthesis in grapevine cell suspension cultures (Vitis vinifera cv. Gamay), following treatment with 100 μm methyl jasmonate. The sampling was performed daily for 20 days of culturing following elicitation at day 5. All samples were analyzed by UPLC-MS/MS for the identification and quantification of fifteen anthocyanin compounds. The models confirmed the separation in the anthocyanin biosynthetic pathway between delphinidin-based and cyanidin-based compounds, showing that methyl jasmonate modulates the anthocyanin concentration profiles. Our results clearly indicate that the combination of high-throughput metabolomics and state of the art statistical modeling is a powerful approach to study plant metabolism. This approach is expected to gain popularity due to the growing availability of low-cost high-throughput ‘omic’ assays.

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