Project Details
Description
Brassica vegetables are rich in various phytochemicals that support immune function and prevent chronic diseases in human. Protective effects are mainly accredited to the specific hydrolysis products of glucosinolates, a group of secondary metabolites. Glucosinolate hydrolysis is influenced by the activity of several plant enzymes, resulting in the formation of nitriles, epithionitriles, or amines. In order to increase the understanding of glucosinolate-related compound accumulation in Brassica vegetables as a prerequisite to optimize crop quality, investigating hydrolysis patterns and identifying modifier proteins is essential. In a 2023field trial, we have grown 318 accessions of different B. oleracea vegetables (kohlrabi, white cabbage, red cabbage, savoy cabbage, cauliflower, Chinese broccoli, kale) at IGZ, and quantified their glucosinolates (10 metabolites on average per accession) and glucosinolate hydrolysis products (20 metabolites on average per accession). The initial results show a high metabolite profile diversity among vegetable types and among accessions within vegetable types. In this proposed project, we want to apply multivariate data analysis methods across a large number of accessions for the exploration and integration of the analytical datasets. Following initial data inspection by PCA and hierarchical cluster analysis, the complex correlation structure of the bipartite relationship between the glucosinolate contents and the associated hydrolysis products will be analyzed by approaches such as PLS2 regression, (Regularized) Canonical Correlation Analysis, and through a relevance network. The analysis will support the identification of accession-specific patterns of secondary metabolite formation with respect to the phylogenetic relationships, and subsequently guide sample and target selection for future molecular analysis, e.g. to characterize yet unknown modifier proteins. The project outcomes will be made available upon publication as an interactive web application within the Food Systems Biology Database (https://fsbi-db.de/) to foster future research projects. With this project, we want to establish a cooperation between IGZ and LSB, and lay ground for follow-up proposals with respect to the computational analysis of multi-omics datasets and application of the complimentary analytical platforms.
Layman's description
Brassica vegetables are rich in various secondary plant substances that support immune function and prevent chronic diseases in humans. A large proportion of these protective effects are attributed to certain breakdown products of mustard oil glycosides, the glucosinolates. These secondary metabolites are modified by specific plant enzymes. In order to better understand their accumulation in cabbage vegetables and thus also improve plant quality, the different hydrolysis patterns are to be investigated and the modifying proteins identified.
The aim of the project is therefore to use multivariate data analysis methods to identify variety-specific patterns in the formation of secondary metabolites in cabbage vegetables (Brassica oleracea) with regard to their evolutionary relationships. In addition, they will serve as clues for the characterization of previously unknown modifying enzymes.
Metabolite profiles of 317 varieties of cabbage serve as the data basis: kohlrabi, white cabbage, red cabbage, savoy cabbage, cauliflower, Chinese broccoli and kale. The profiles originate from a field trial at the IGZ in summer 2023. The results will be made available as an interactive web application within the Food Systems Biology Database.
The project, which is funded by the Leibniz Association, lays the foundation for in-depth joint collaboration between IGZ and LSB for the computer-aided analysis of multi-omics data sets and the application of the two institutes' complementary analytical platforms.
The aim of the project is therefore to use multivariate data analysis methods to identify variety-specific patterns in the formation of secondary metabolites in cabbage vegetables (Brassica oleracea) with regard to their evolutionary relationships. In addition, they will serve as clues for the characterization of previously unknown modifying enzymes.
Metabolite profiles of 317 varieties of cabbage serve as the data basis: kohlrabi, white cabbage, red cabbage, savoy cabbage, cauliflower, Chinese broccoli and kale. The profiles originate from a field trial at the IGZ in summer 2023. The results will be made available as an interactive web application within the Food Systems Biology Database.
The project, which is funded by the Leibniz Association, lays the foundation for in-depth joint collaboration between IGZ and LSB for the computer-aided analysis of multi-omics data sets and the application of the two institutes' complementary analytical platforms.
Funder
Leibniz Association
Funding programme
Leibniz Research Network Bioactive Compounds Seed Money
| Title | Computational analysis of the natural variation of glucosinolate-related compounds in Brassica oleracea |
|---|---|
| Status | Finished |
| Effective start/end date | 1/01/24 → 30/06/24 |
Collaborative partners
- IGZ - Leibniz Institute of Vegetable and Ornamental Crops (lead)
- Leibniz Institute for Food Systems Biology at the Technical University of Munich
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