Bilal, R; (2013) Dynamics of Gene Regulatory Networks in the Immune System. Doctoral thesis (PhD), UCL (University College London).

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Abstract

The aim of this project is to study the dynamics of Gene Regulatory Networks (GRN) in the immune system. For this purpose two principles of regulation were discussed. First principle is to study the effect of the speed with which the system crosses the critical region on choosing the final attractor in bistable system and in the immune system genetic switch that governs the differentiation of progenitor cell in the presence of small asymmetries and fluctuations. Second is to study the constructive role played by high-frequency force driving vibrational resonance (VR), and the effect of interaction between vibrational resonance and stochastic resonance in signal detection. Understanding the integrated behaviour of gene regulatory networks, RNA, proteins and other molecules that mutually interact to control the dynamical behaviour of the network within and between cells, has come out as a fundamental problem in system biology. To study the effect of external signalling speed, we specifically analyzed the role of parameter sweeping, external asymmetry, and noise in the canonical supercritical pitch- fork bifurcation model, both by numerical simulations and analytical solutions. As genetic switch exhibits bistable behaviour in its dynamics, we will apply these results to genetic switch by using model of immune system genetic switch that governs differentiation of progenitor cell into two different fates. Since cell phenotype in stem cell differentiation, cell cycle progression, or apoptosis has been successfully identified as attractors of a whole network. So in the presence of small asymmetries and fluctuations, slow passage through the critical region increases considerably specific attractor selection, which has strong implication for the cell fate decision process. Excitable system do not respond to stimulus that is below its excitation threshold. We studied in detail two phenomena vibrational resonance and stochastic resonance to enhance the response of an excitable system to a low-frequency sub-threshold, by first considering mathematical model of excitable neurons the Fitz-Hugh Nagumo (FHN model), and then applying same phenomena on two different models of excitable genetic circuits. When optimal amplitude of high-frequency signal enhance the response of an excitable system to low-frequency sub-threshold is called vibrational resonance, while when appropriate noise intensities enhance the system detection of sub-threshold signals then this phenomenon is called stochastic resonance. We found for two different biological systems that adding a high-frequency force of an appropriate amplitude to the system enhance the neural or genetic response to a sub-threshold low-frequency signal. Also appropriate Gaussian white noise intensities reduces the optimal response that can be reached by vibrational resonance alone but it also reduce high-frequency amplitude that gives best response.

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