Abstract P436: Modeling Genetic Dilated Cardiomyopathy Using Induced Pluripotent Stem Cell-derived Engineered Heart Tissues For Precision Medicine

Recent advancement of human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) technologies has opened the door to next-generation modeling of human cardiac biology and disease. Not only does this alleviate the need for human primary tissue and compensate for the well documented deficiencies of rodent models for cardiovascular disease, but these technologies may lead to the identification of better candidates for clinical development. Unfortunately, most current 2D hiPSC-CM models lack the biochemical, mechanical, and electrical feedback that cardiomyocytes endure in a multi-cellular aligned tissue, which limits their translatability into clinical settings. To address this, we incorporated hiPSC-CMs modeling various genetic dilated cardiomyopathies (DCM) into 3D engineered heart tissues (EHTs). Here, we show these models develop distinguishable contractile defects recapitulating hallmarks of DCM when compared to biologically relevant controls. Moreover, this distinct phenotype is quantitative, reproducible, and demonstrates utility for drug discovery. As this innovative technology continues to develop, EHTs are on the forefront of emerging biomimetic assays that can be used to prevent drug attrition in the late stages of drug development.

Haploids adapt faster than diploids across a range of environments

Despite a great deal of theoretical attention, we have limited empirical data about how ploidy influences the rate of adaptation. We evolved isogenic haploid and diploid populations of Saccharomyces cerevisiae for 200 generations in seven different environments. We measured the competitive fitness of all ancestral and evolved lines against a common competitor and find that in all seven environments, haploid lines adapted faster than diploids, significantly so in three environments. We apply theory that relates the rates of adaptation and measured effective population sizes to the properties of beneficial mutations. We obtained rough estimates of the average selection coefficients in haploids between 2% and 10% for these first selected mutations. Results were consistent with semi-dominant to dominant mutations in four environments and recessive to additive mutations in two other environments. These results are consistent with theory that predicts haploids should evolve faster than diploids at large population sizes.