A systems genetics analysis of Rho-family GTPase signalling
Supervisor(s): Dr Chris Bakal
Team: Dynamical Cell Systems
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Summary
We use high-throughput functional genomic approaches in tandem with integrative computational technologies to describe the complex systems that control cell shape and migration during development and organism homeostasis. Understanding the regulation of morphogenesis and motility on a systems level is an important first step in developing network-based therapeutics for the treatment of metastatic cancers.
In all eukaryotic cells, migration is dependent on the activity of Rho-family GTPases, but it is unclear how activation of these proteins by different stimuli results in the distinct morphological changes that are required for motility, such as the formation of lamellipodia and focal adhesions at leading edge of cells, and the retraction of the tailing edge. We employ systems-level approaches to study the regulation of Rho-family GTPases by Rho GTP Exchange Factors (RhoGEFs) and Rho GTPase Activating Proteins (RhoGAPs). Whereas the Rho-family GTPases are “generic” molecules that are involved in regulating a variety of different cellular behaviors including motility, RhoGEFs and RhoGAPs are thought to act to specify the output of RhoGTPase activity in response to highly specific stimuli. Activated RhoGEFs have been extensively implicated in the progression of numerous cancers, and may in fact represent the largest family of oncogenes in the genome. Similarly, a number of RhoGAPs appear to be potent tumor suppressors.
To understand how diverse signals activate different RhoGEFs and RhoGAPs to control migration we perform high-throughput RNAi screens where cell shape [1] and FRET- based reporters [2] are used as readouts of signaling events across a variety of genetic and environmental conditions. These screens identify both specific and general regulators of individual Rho components and thus provide novel insight as to how Rho-family GTPase activity is tailored. We also seek to develop and implement novel computational methods [2] in order to integrate the results of high-throughput screens with orthogonal datasets – such as those derived from mass spectrometry approaches – to describe network architecture and information flow mediated by RhoGEFs and RhoGAPs.
References
- Bakal, C. et al (2007) Quantitative Morphological Signatures Define Local Signaling Networks Regulating Cell Morphology. Science Vol 316(5832) p1753-6
- Bakal, C. et al (2008) Phosphorylation Networks Regulating JNK Activity in Diverse Genetic Backgrounds. Science Vol 322(5900) p453-456
