We would like to present to you the abstract of our keynote speaker Petri-Jaan Lahtvee, who is working as a senior scientist and group leader at centre for synthetic biology at the University of Tartu Institute of Technology (TUIT).
Quantitative Multi-Layer Stress Regulation Analysis in Yeast.
Institute of Technology, University of Tartu, Tartu, Estonia
Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Yeast is extensively used in various biotechnological processes with the global market reaching yearly into billions of dollars. However, to make bioprocesses more cost efficient and more generally applied, well performing cell factory with increased production of precursor molecules and robustness towards stress factors must be addressed. In the current study, gradual increase of three different stress conditions (ethanol, osmolarity and temperature) were studied in the yeast Saccharomyces cerevisiae at constant dilution rate to understand the regulation of induced stress conditions without the effect caused by decreasing specific growth rate. More than thirty chemostats were performed at constant dilution rate but due to varying stress conditions and levels, significant variations in specific glucose uptake rate were detected.
The major common specific glucose uptake rate dependent change took place in mitochondria where mainly oxidative phosphorylation related genes and proteins showed strong specific glucose consumption rate dependence. Latter was also the biggest group of genes that showed significant transcriptional regulation. Rather surprisingly, only relatively small overlap was determined at mRNA and protein levels between different stress conditions. As a common effect, elevated stress caused a decrease in biomass yield which was directly related to increased maintenance energy demand of the cells.
However, effects for increased maintenance seemed to vary from one stress condition to another. General underlying energy dependent curve was discovered which also allows one to predict the on-set of overflow metabolism. Various integrative data analysis, including transcription factor analysis, indicated more similar response towards temperature and ethanol stress conditions, where protein turnover and membrane fluidity were mainly influenced. Osmotic stress showed more distinct patterns as oxidative stress pathways were activated. Gathered quantitative multi-layer datasets together with integrated data analysis sheds light on the regulatory patterns and energy metabolism for each stress conditions separately and defines a general stress response in yeast. Additionally, it gave suggestions for metabolic engineering purposes to produce more robust cell factories.