NF-kB is a family of transcription factors that coordinately control hundreds of genes involved in many steps of inflammatory processes, from microbial killing to cancer. When inflammatory stimuli hit the cell surface, NF-kB undergoes several cycles of nucleus-to-cytoplasm translocations, resulting in oscillations of nuclear NF-kB concentrations and activity.
At single cell level, live imaging and mathematical modeling suggest that NF-kB oscillations are selected over other non-oscillatory dynamics.
At population level there is significant heterogeneity, mainly due to cell asynchrony. Mathematical models reproducing population heterogeneity indicate absence of coupling between dynamics of individual cells. This behaviour is thought to be adaptive by enabling a wider multiplicity of responses, but this has not been tested. Moreover, due to collective heterogeneity, the link of NF-kB dynamics to gene expression in a tissue as a whole is far from being clear.
Analyses of mathematical models of the NF-kB system using my expertise on Nonlinear Dynamics and Chaos Theory showed that complex oscillatory population dynamics are possible. Furthermore, regimes for coherent collective behaviours (synchrony) can be found. These regimes entail the use of periodic stimulations with different intensities and/or periods, suggestive of acute and chronic inflammatory conditions.
My project proposes to mathematically explore and experimentally validate complex population dynamics. In vivo quantitative imaging of NF-kB dynamics in GFP-p65 knock-in cells upon repetitive stimulations will provide data to build models on NF-kB collective behaviours. Transcription profiles of synchronized cells will be incorporated into the model. By increasing our understanding on NF-kB collective dynamics, we expect to contribute to strategies for the control of diseases with a huge social impact, like septic shock, autoimmune diseases and cancer, in which the deregulation of NF-kB plays a pivotal role
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