Talk by Wolf Frommer: "Measuring Metabolic Flux with FRET-based Biosensors" : 19. maj 2011
(Auditorium A2-70.03, Thorvaldsensvej 50, Frederikberg C)
Prof. Wolf Frommer, Carnegie Institution, Stanford gives the talk "Measuring Metabolic Flux with FRET-based Biosensors"
When: May 19, 2011; 11am
Where: Auditorium A2-70.03, Thorvaldsensvej 40, Frederiksberg
Abstract: Metabolic flux must be acclimated to changing nutrient availability and different demands. This is achieved by a combination of transporters and enzymes that are controlled by signaling networks. We developed a new set of tools to measure the impedance of metabolic flux to systematically identify the control networks. We use genetically FRET-based metabolite sensors to determine the impedance of metabolic flux through a specific node in the pathway, e.g. phosphate, glucose, sucrose, maltose, trehalose, glutamate, or tryptophan (Fehr et al., 2003 JBC; Okumoto et al., 2005 PNAS; Kaper et al., 2008 PLoS Biol; Okumoto et al., 2008 New Phytol.; Takanaga et al., 2010 FASEB J.).
The sensors exploit conformational changes in binding proteins and report the ligand-induced conformational change as a change in resonance energy transfer between two attached fluorophores. The sensors are genetically encoded and can thus be deployed easily in any cell or organisms that is accessible to genetic transformation. They can be genetically targeted to subcellular compartments such as nuclei, ER, Golgi or even secreted into the intercellular space.
We have widely used these sensors in bacteria, yeast, intact plants and human cells. We have used the sensors for gene discovery to identify novel sugar transporters involved in sugar efflux (Chen et al., 2010 Nature). As a proof of concept we tested whether yeast maintains glucose flux capability even in the absence of glucose. We analyzed which hexose transporters are kept active in the absence of glucose (Bermejo et al., 2010 Biochem J.). Moreover, we screened the collection of yeast protein kinase and phosphatase mutants and identified 15 signaling components that control flux through this node. The affected genes fall into at least three networks: the Ras/Pka, the SNF1/4 and the Pho85 pathways. We use the same general approach to identify signaling networks in plant and human cells.