Research

Research Project

  • In Vitro Cardiac Disease Modeling Using Engineered Heart Tissues

    To investigate the mechanisms of atrial fibrillation and related cardiac diseases, we are developing an in vitro co-culture model using stem cell-derived engineered heart tissue (EHT). By differentiating patient-derived induced pluripotent stem cells (iPSCs) into cardiomyocytes and cardiac fibroblasts, we generate 3D tissues that more closely replicate the native cardiac microenvironment. This platform enables personalized disease modeling and drug screening. Our next goal is to apply this co-culture model to study peripartum cardiomyopathy, with the aim of uncovering disease-specific responses and therapeutic targets.

    Related publications:

Optimizing hiPSC Differentiation

This project focuses on optimizing the differentiation of human induced pluripotent stem cells (hiPSCs) into cardiomyocytes using a scalable 2D monolayer protocol. The goal is to improve consistency and efficiency across different iPSC lines for use in in vitro disease modeling. In parallel, the work involves preparing 3D suspension cultures using a bioreactor system and maintaining hiPSC lines. Pluripotency and differentiation outcomes are assessed through PCR, cell viability assays, and other molecular techniques in both 2D and 3D systems.

3D Bioprint Engineered Heart Tissues

This project focuses on integrating 3D bioprinting technologies to enable the scalable fabrication of robust and mature EHTs. Current investigations involve biomaterials such as alginate-gelatin and collagen-fibrin bioinks. The objectives of the project are to use bioprinting strategies to improve the structural and functional maturation of EHTs, including enhanced sarcomere alignment, more synchronous contractile activity, and upregulation of cardiac-specific gene expression.

Developing a High-Throughput System for EHTs

This project focuses on optimizing the design and fabrication of micropillar post platforms for quantifying contractile force in EHTs and enhancing their structural alignment. By providing anchoring points, these micropillars facilitate better tissue organization and functional maturation. The platform is being scaled for high-throughput applications and is designed to integrate seamlessly with a custom 3D bioprinter to enable rapid and scalable biomanufacturing of EHTs. This system supports the development of physiologically relevant cardiac models for drug testing and disease modeling. To further promote tissue maturation, an in-house electrical stimulator was developed to deliver controlled stimulation to the constructs as part of a comprehensive functional assessment workflow.

High-Throughput Optical Mapping with Robotic KIC

This research project focuses on the application and optimization of the Kinetic Image Cytometer (KIC) developed by Vala Sciences—an advanced high-throughput optical mapping platform. Fewer than ten KIC systems currently exist worldwide, and the unit used in this project is uniquely engineered to interface with a fully automated high-throughput robotic system at SFU. The initial phase of the project involved optimizing the KIC’s performance to meet the specific demands of cardiac tissue research. The system is employed to conduct calcium and voltage imaging on cardiomyocytes derived from patient-specific iPSCs carrying titin-truncating mutations, as well as their CRISPR-corrected isogenic controls. Future work will leverage the KIC’s high-throughput capabilities to investigate drug-induced cardiotoxicities and other electrophysiological abnormalities. The KIC’s integrated optical mapping and automated liquid handling functions make it a versatile tool for addressing a wide range of research questions in cardiovascular medicine.

Multimodal and Molecular Profiling of Hypertrophic Cardiomyopathy

Hypertrophic Cardiomyopathy (HCM) is a prevalent inherited cardiac disorder marked by abnormal thickening of the left ventricular myocardium. This project integrates clinical, imaging, genetic, and molecular data to improve the diagnosis and management of HCM. Cardiac magnetic resonance imaging (cMRI) is used to assess myocardial tissue characteristics and fibrosis, while an ensemble machine learning framework applies penalized logistic regression to predict clinical outcomes from multimodal datasets. In parallel, molecular profiling using multiomics approaches is being employed to uncover the molecular signatures underlying HCM, offering deeper insight into disease mechanisms and potential biomarkers. Together, these approaches aim to enhance risk stratification, treatment prioritization, and personalized care for patients with HCM.

Titin Variants and Risk of Cardiac Rhythm Disorders

Atrial fibrillation, a common heart rhythm disorder that prevents the heart from pumping blood effectively, is linked to an increased risk of life-threatening diseases like stroke and heart failure. Genetic variants in the titin protein were recently identified as a potential cause of atrial fibrillation and ventricular rhythm disorders. However, how titin variants lead to rhythm disorders in individuals with healthy hearts is unclear. This project focuses on understanding the risks of having titin variants at a population level as well as its rhythm perturbing effects in atrial and ventricular patient stem cell-derived heart cells. We found that titin variants increase the likelihood of having atrial fibrillation, especially in individuals with pre-existing conditions like high blood pressure. In heart cells, titin variants can affect electrical signalling or force generation and could lead to rhythm disorders differently for each patient. These results improve our understanding of titin and its role in the development of abnormal heart rhythms.