Advances in data analysis in Metabolomics: towards a dynamic view of responses in plant cell cultures

Metabolite profiling of plant cell cultures under stress is an important approach towards the understanding of the biology of stress responses in plants by identifying by-products of the stress metabolism, either stress signal transduction molecules or molecules that are involved in adaptive respons...

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Bibliographic Details
Main Author: Saw, Nay Min Min Thaw
Contributors: Martens, Stefan ( Dr. habil. ) (Thesis advisor)
Format: Dissertation
Language:English
Published: Philipps-Universität Marburg 2019
Pharmazie
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Summary:Metabolite profiling of plant cell cultures under stress is an important approach towards the understanding of the biology of stress responses in plants by identifying by-products of the stress metabolism, either stress signal transduction molecules or molecules that are involved in adaptive responses. To model in a comprehensive way such complex biological phenomena, it is important to analyse the time-dependent behaviour of the cell metabolism in response to external stimuli. A single point measurement indeed gives only a snapshot of the cellular state in which all the dynamical information is not captured. In this respect, high resolution time-course experiments are expected to provide more information in the phase of data analysis than a series of measurements collected only at a few time-points. The main objective of this thesis is to study the metabolic response of grapevine cell cultures subjected to an external stimulus, designed to mimic the interaction of the plant with environment factors. The PhD thesis firstly describes the optimization of the sample preparation method, extraction protocol and targeted metabolomics analysis of compounds isolated from the grape cells. This optimized metabolomics protocol was then applied to study the long-term dynamic response of elicited grapevine (Vitis vinifera cv. Gamay) cell suspension cultures treated by methyl jasmonate or sodium nitroprusside. Generalized additive models were applied to study the time dependent profile of secondary metabolites in grapevine cell suspension cultures. The results suggested that this class of non-parametric statistical models in combination with metabolomics could be an effective tool to explore the complete time-dependent changes of secondary metabolites and their responses to external stimuli in plant cells and foundation for further integrative omics studies.
Physical Description:159 Pages
DOI:https://doi.org/10.17192/z2019.0522