A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles

Abstract

To take full advantage of the power of functional genomics technologies and in particular those for metabolomics, both the analytical approach and the strategy chosen for data analysis need to be as unbiased and comprehensive as possible. Existing approaches to analyze metabolomic data still do not allow a fast and unbiased comparative analysis of the metabolic composition of the hundreds of genotypes that are often the target of modern investigations. We have now developed a novel strategy to analyze such metabolomic data. This approach consists of (1) full mass spectral alignment of gas chromatography (GC)-mass spectrometry (MS) metabolic profiles using the MetAlign software package, (2) followed by multivariate comparative analysis of metabolic phenotypes at the level of individual molecular fragments, and (3) multivariate mass spectral reconstruction, a method allowing metabolite discrimination, recognition, and identification. This approach has allowed a fast and unbiased comparative multivariate analysis of the volatile metabolite composition of ripe fruits of 94 tomato (Lycopersicon esculentum Mill.) genotypes, based on intensity patterns of .20,000 individual molecular fragments throughout 198 GC-MS datasets. Variation in metabolite composition, both between-and within-fruit types, was found and the discriminative metabolites were revealed. In the entire genotype set, a total of 322 different compounds could be distinguished using multivariate mass spectral reconstruction. A hierarchical cluster analysis of these metabolites resulted in clustering of structurally related metabolites derived from the same biochemical precursors. The approach chosen will further enhance the comprehensiveness of GC-MS-based metabolomics approaches and will therefore prove a useful addition to nontargeted functional genomics research.

RNA Interference Silencing of Chalcone Synthase, the First Step in the Flavonoid Biosynthesis Pathway, Leads to Parthenocarpic Tomato Fruits

“…To address whether or not the parthenocarpic phenotype dramatically affects fruit taste, we measured the levels of the most important taste-and flavor-related tomato metabolites (sugars, organic acids, and 16 volatiles; Yilmaz, 2001;Ruiz et al, 2005) in Chs RNAi and wild-type tomatoes. For both wild-type and Chs RNAi fruits, the levels of flavor-related volatile compounds fell well within the variation observed in a collection of 94 commercially available tomato cultivars (Tikunov et al, 2005). Similar results were obtained for sugars (Suc, Fru, and Glc) and organic acids (citric acid and malic acid; results not shown), suggesting that these parthenocarpic tomatoes potentially have a normal tomato-like taste.…”

Multi-matrix, dual polarity, tandem mass spectrometry imaging strategy applied to a germinated maize seed: toward mass spectrometry imaging of an untargeted metabolome

“…In typical untargeted GC-MS profiling of a plant metabolome, one-half to two-thirds of the metabolites cannot be confidently identified. [11][12][13] Unknown compound identification in LC-MS/MS is even more difficult, as its database is much smaller.…”

A Correlation between Antioxidant Activity and Metabolite Release during the Blanching ofChrysanthemum coronariumL.

“…19,24,25) The final alignment data (208 variables in negative mode mass spectra and 250 variables in positive mode mass spectra) were used to compare the phenotypic differences resulting from the blanching process via PCA and PLS-DA. R 2 X, R 2 Y, and Q2 (cum) are usually used to evaluate the quality of PCA, PLS, and the PLS-DA model.…”