UC San Diego

In order to improve disease models, understanding and manipulating the factors that contribute to cellular phenotype is of utmost importance. The role of genetics in disease, while long appreciated from a clinical standpoint, has become more elucidated by modern sequencing techniques. Mechanical forces include both the environmental forces that act on cells as well as the forces exerted by cells back on their environment. While focusing individually on genetics or mechanics is important, this dissertation aims to highlight the value of utilizing both in combination to improve disease modeling.In chapter one, we first provide an overview of the tools that allow us to manipulate and study genetic risk for disease, including gene editing techniques as well as induced pluripotent stem cell (iPSC) technology, and then provide examples where they have been successfully utilized to improve our understanding of cancer and heart disease. We then describe progress in the field of material based-mechanobiology and the engineered systems for mimicking forces exerted on cells by the extracellular matrix (ECM), surrounding fluid, and neighboring cells. We conclude by highlighting studies that have successfully manipulated both genetic and mechanical factors to improve our understanding of different cancers and heart diseases. In the second chapter, we provide an example of how combining patient derived iPSCs and haplotype editing with biophysical cell sorting can unveil insight into how the non-coding gene locus, 9p21.3, incurs risk for coronary artery disease. Utilizing adhesion-based sorting with a microfluidic device, we show that iPSC-derived vascular smooth muscle cells from patients with single nucleotide polymorphisms (SNPs) at 9p21 (RR) have increased phenotypic heterogeneity compared to those lacking the SNPs and isogenic knockouts, specifically with increased presence of a synthetic, non-contractile phenotype. We identified heterogeneous expression of an alternatively spliced long-non coding RNA within a RR patient population drives a subset of cells towards the synthetic phenotype, exacerbating disease and potentially explaining the incomplete penetrance of the disease locus. The methodology highlighted here has broad applicability to a number of different diseases, highlighting the value of approaches that both manipulate and measure genetic factors and mechanics to investigate disease development.