Towards an integrated platform for gene network inference and validation

The prevalent pathology leading to high mortality from cardiovascular disease is atherosclerosis. Despite strong evidence for the association of shear stress and the site-specificity of atherosclerosis initiation, there is a lack of treatment focusing on modulating shear stress-induced phenotypes in endothelial cells. The overarching theme of the thesis is to uncover the causal molecular networks that are activated by mechanical forces in endothelial cells. We present an integrated platform for gene network inference and validation, which integrates network inference from gene expression data with functional genomics within a single framework to set up an iterative cycle of measurement and network refinement. In order to achieve this, a number of technological innovations were necessary and developed. We present an approach, named ARNI, to logically model and construct through abductive reasoning, regulatory gene networks from gene expression profiles and background prior knowledge on gene functions and interactions. We demonstrate the improved predictive power and complexity of our inferred network topologies compared with those generated by other non-symbolic inference approaches. A bioinformatics workflow for the integration of gene expression profiles across platforms and species is presented and applied for generating an integrated endothelial cell mechanoresponsive gene expression profile. The integrated dataset identified >1600 genes to be shear responsive, more than any other study, and in this gene set all known mechanosensitive genes and pathways were present. We also present the first high-throughput RNAi platform to demonstrate successful reverse electroporation of mammalian primacy cell lines and which couples RNAi screening with mechanotransduction studies. Each step of the assemblage is evaluated and effective loss-of-function is demonstrated for multiple gene targets. The tools presented in this thesis provide the basis for developing qualitative models and targeted therapies, in order to further our pursuit for shear-mediated atherosclerosis prevention.