Abstract
To date, various strategies have been developed to construct biomimetic and functional in vitro cardiac tissue models utilizing human induced pluripotent stem cells (hiPSCs). Among these approaches, microfluidic-based Heart-on-a-chip (HOC) models are promising, as they enable the engineering of miniaturized, physiologically relevant in vitro cardiac tissues with precise control over cellular constituents and tissue architecture. Despite significant advancements, previously reported HOC models often lack the electroconductivity features of the native human myocardium. In this study, we developed a 3D electroconductive HOC (referred to as eHOC) model through the co-culture of isogenic hiPSC-derived cardiomyocytes (hiCMs) and cardiac fibroblasts (hiCFs), embedded within an electroconductive hydrogel scaffold in a microfluidic-based chip system. Functional and gene expression analyses demonstrated that, compared to non-conductive HOC, the eHOC model exhibited enhanced contractile functionality, improved calcium transients, and increased expression of structural and calcium handling genes. The eHOC model was further leveraged to investigate the underlying electroconduction-induced pathway(s) associated with cardiac tissue development through single-cell RNA sequencing (scRNA-seq). Notably, scRNA-seq analyses revealed a significant downregulation of a set of cardiac genes, associated with the fetal stage of heart development, as well as upregulation of sarcomere- and conduction-related genes within the eHOC model. Additionally, upregulation of the cardiac muscle contraction and motor protein pathways were observed in the eHOC model, consistent with enhanced contractile functionality of the engineered cardiac tissues. Comparison of scRNA-seq data from the 3D eHOC model with published datasets of adult human hearts demonstrated a similar expression pattern of fetal- and adult-like cardiac genes. Overall, this study provides a unique eHOC model with improved biomimcry and organotypic features, which could be potentially used for drug testing and discovery, as well as disease modeling applications.