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Center for Nonlinear Studies |
Single-‐molecule, single-‐cell studies of genetic expression have provided key insights into how cells respond to external stimuli [1-‐5]. By directly measuring copy numbers of individual biomolecules in cells, such as the number of individual messenger RNA transcripts, it is now possible to obtain statistical measures of the spatio-‐temporal distributions of key signaling and regulatory molecules. Such comprehensive datasets can be used to infer system-‐level models that yield quantitative insight into cellular regulation, predict cellular responses in new experimental conditions, and suggest more revealing experiments to uncover regulatory dynamics. The integration of single-‐molecule spectroscopy, biochemistry,and numerical modeling is a powerful multi-‐disciplinary approach to investigating cellular response at the genetic level. In this talk I will provide a walk-‐through of our single-‐molecule experiments, data analysis, and numerical modeling for one specific example, the Interleukin-‐1 alpha pathway [6]. I will specifically focus on how the large amount of information in these datasets allows one to probe what types of fluctuations are most informative about the underlying gene regulatory process. REFERENCES [1] Munsky, B., et al., Science, 336(6078), 183–187 (2012). [2] Femino A.M., et al., Science, 280(5363), 585-‐590 (1998). [3] Choi H.M.T, et al, Nat Biotechnol, 28(11), 1208-‐1212(2010). [4] Raj A., et al., Nat Meth, 5(10), 877-‐879 (2008). [5] Katranidis A, et al., Angew Chem Int Edit 48(10), 1578-‐1761 (2009). [6] Shepherd D.P., et al, Proc. SPIE 8228, 8228-‐08 (2012).
Host: Kipton Barros, T-4 and CNLS