An integrated molecular cell biology and agent-based simulation approach to dissecting microRNA regulatory networks

Discoveries in the world of non-coding RNAs made during the turn of the last century challenge the flow of information described by Francis Crick in his description of the central dogma of molecular biology – the information encoded by the DNA no longer solely requires a protein intermediate to control the fate of a living cell. Dozens of mechanisms involving RNA-protein, protein-protein and RNA-RNA interactions have been described that govern regulation of information controlled at the level of replication, transcription and translation. The networks that emerge from these interactions support unique, context dependent regulation of gene expression, are dynamic in nature, and provide multiple layers of complexity underlying the biological system. Advancements in molecular biology allow researchers to dissect complex interactions between components of gene regulatory networks, interpretation of which is only feasible using automated computer-aided approaches.
Inevitably, uncovering novel mechanisms involved in biological systems benefits from an integrated approach between experimental biology and computational modelling. This thesis investigates the function of a group of non coding RNAs, microRNAs, that regulate gene expression at a post-transcriptional level. Firstly, Argonaute-2, the crucial effector of microRNA function, is revealed as a novel direct target of microRNA-132. The functional role of this regulation is explored in primary lymphatic endothelial cells during cell activation. Secondly, the regulation of two microRNA-132 targets – Argonaute-2, required for microRNA-mediated gene regulation, and E1A associated Protein p300, necessary for microRNA-132 transcription – are incorporated into an agent-based model. Following the CoSMoS process, a rigorous methodology for model development, the documented regulatory network is captured in a model that is able to simulate the expected behaviour of the real-world problem domain. Finally, using the gathered data on microRNA-132 regulation and cell activation, the model is used to evaluate the domain knowledge of microRNA mediated gene silencing in silico, proposing testable hypothesis for in vitro experimentation.