Research at the MBI applies a range of experimental approaches to study these complex behaviors of cells in response to different mechanical stimuli. These efforts are greatly supported by theoretical studies and modeling of the possible mechanisms involved. Working alongside experimental methods, modeling allows us to incorporate and readily control various parameters that may influence the application and detection of the mechanical forces in question.
The MBI combines a bioinformatics and systems approach with experimental techniques in order to better understand mechanobiology at the molecular level . These experimental techniques primarily focus on purified molecular systems of proteins and RNA, as well as biophysical techniques like mass spectrometry, intrinsic fluorescence and FRET. The output of these studies, such as potential conformational changes in proteins, can be sampled and the mechanical transitions in protein domains further studied.
How the epithelial cells maintain correct positioning, how they migrate in a directed and collective fashion and the role of cytoskeletal machinery in these processes are key points of interest. The mechanical factors that control cell movement and motility are currently being characterized experimentally. We are developing computational models to further elucidate these processes, the results of which feed back into experiments. This dynamic feedback loop ensures our theoretical models and predictions are constantly evolving in line with experimental data.
Wong, S.Y., Chiam K.H.,Lim C.T. and P. Matsudaira. Computational Model of Cell Positioning, Directed and Collective Migration in the Intestinal Crypt Epithelium. J. R. Soc Interface. 7:S351-63(2010)
A Ananthanarayanan et al., Systems Biology in Biomaterials and Tissue Engineering Chapter in Book: Comprehensive Biomaterials (accepted).
Venkatraman L, Yu H, Bhowmick SS, Dewey F, Tucker-Kellogg L. The steady States and dynamics of urokinase-mediated plasmin activation. Pacific Symposium on Biocomputing) p.190-200(2010)
Betel D, Breitkreuz KE, Isserlin R, Dewar-Darch D, Tyers M, and Hogue CWV. Structure-templated predictions of novel protein interactions from sequence information. PLOS Computational Biology 2007 3:1783-9.