Related Experiment Video
Updated: Jun 4, 2026
07:25
Combining Histochemical Staining and Image Analysis to Quantify Starch in the Ovary Primordia of Sweet Cherry during Winter Dormancy
Published on: March 20, 2019
Microarray data can predict diurnal changes of starch content in the picoalga Ostreococcus
Oksana Sorokina1, Florence Corellou, David Dauvillée
1School of Biological Sciences, The University of Edinburgh King's Buildings, Mayfield Road, Edinburgh EH9 3JH, UK. oksana.sorokina@ed.ac.uk
BMC Systems Biology
|March 1, 2011
Summary
This study models starch dynamics in the alga Ostreococcus tauri, revealing how gene expression influences carbohydrate metabolism. The findings highlight a new method for predicting metabolic changes from genetic data.
Area of Science:
- * Biochemistry and Molecular Biology
- * Systems Biology
- * Phycology
Background:
- * Starch storage in plants is regulated transcriptionally and post-translationally, with daily gene expression patterns not fully predicting metabolite dynamics.
- * Unicellular phytoplankton, like *Ostreococcus tauri*, exhibit complex carbohydrate metabolism, with transcriptomic data suggesting significant transcriptional regulation.
- * Discrepancies between RNA profiles and enzyme activity highlight the need for dynamic modeling in understanding metabolic regulation.
Purpose of the Study:
- * To infer the dynamics of starch content in *Ostreococcus tauri* during a 12h light/12h dark cycle using a constraint-based modeling approach.
- * To integrate transcriptomic data with a detailed stoichiometric model of starch metabolism.
- * To predict optimal flux distribution and starch content dynamics, and identify key genetic regulatory targets.
Main Methods:
- * Utilized a quasi-steady-state, constraint-based modeling approach.
- * Integrated microarray-derived RNA expression datasets with a stoichiometric reconstruction of starch metabolism.
- * Performed in silico analysis to predict genetic regulatory targets within the starch metabolic pathway.
Main Results:
- * Developed a detailed reaction model for starch metabolism in *Ostreococcus tauri*, preserving mass balance.
- * Predicted starch content dynamics over a 24-hour light/dark cycle, validated by experimental data.
- * Identified key genetic regulatory targets influencing starch metabolism dynamics.
Conclusions:
- * A simplified, single-reaction model is insufficient for explaining diurnal variations in starch-related enzyme activity.
- * The developed detailed reaction model is the first to describe polysaccharide polymerization while maintaining mass balance.
- * The quasi-steady-state modeling approach effectively infers dynamic metabolic information from time-series gene expression data in *Ostreococcus tauri*.
