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Center for Nonlinear Studies |
Genetic regulation in eukaryotic organisms enables cells to process environmental information for generating rapid and functional responses needed for confronting the harmful external conditions, DNA damage or lack of food. Experiments have shown that this efficient information processing largely owes to the ability of cells to rapidly and often simultaneously up- or down-regulating the expression of hundreds of genes. The detailed mechanisms for rapid information flow in eukaryotic cells are currently not well understood and are often rationalized in terms of thermodynamic equilibrium models which are paradigmatic for bacterial gene regulation and may not always apply to more complex information processing that takes places in eukaryotic cells. In this talk I use a classic example of eukaryotic gene regulatory network of N F−κB to illustrate the existence of an interesting kinetic paradox that is not resolvable within the classic thermodynamic paradigm of gene regulation. In the second half of the talk, I will provide a resolution of the paradox by uncovering a detailed molecular level mechanism for kinetic control of genetic switching which we have come to call “Molecular stripping”. Details simulations and comparisons with experiment will be shown that confirm the existence of molecular stripping and its role in broadcasting signals to multiple genes. Towards the end I will present theoretical arguments and stochastic simulations of gene network of N F−κB to show that any mechanism based on passive dissociation runs into time-scale crisis where large number of genomic site make the networks too slow and inefficient. Molecular stripping on the other hand resolves the time scale crisis and leads to robust responses and ultra sensitive oscillations in the N F−κB network. The theory also shows that mammalian genomes must have evolved active non-equilibrium mechanisms like molecular stripping in order to broadcast externally received cellular signals to many genetic targets.
Host: Yen Ting Lin