Cardiac Harmony: Modelling Heart Beats with Stem Cells and Code

Description

Despite significant advancements in cardiac research, heart disease remains a leading cause of mortality globally. Unexpected cardiac events can occur even in young, fit individuals engaged in routine activities. One promising avenue of research involves the use of induced pluripotent stem cells (iPSCs) to produce differentiated cardiac cells to replace damaged heart tissue. However, there are still many unknowns regarding the behaviour and connectivity of these cells in vitro.
This project aims to culture cardiac myocytes from iPSCs and develop computer models to simulate their activity and interconnections. The ultimate goal is to use the in silico model to elucidate the limitations of the in vitro stem cell model and identify specific pathways to improvement.

The project will be divided into three phases:

Phase I

• Culturing and Characterizing Cardiac iPSCs The student will grow and characterise iPSC-derived cardiac cells, potentially producing different types and combining them in a co-culture system, that includes atrial, myocyte and nodal tissue. Concurrently, the student will learn to code simulations of cardiac activity, primarily using Python and pyNEURON, although other options may be explored.

Phase II

• Quantifying Functional Activity and Model Validation The student will quantify the functional activity of the cardiac cultures and compare this to the computer model. The model parameters will be adjusted to fit the cultures, and the latter part of this phase will involve formal validation and sensitivity analysis of the models.

Phase III

• Pharmacological Interrogation of Models The in silico and in vitro models will be interrogated with pharmacological interventions. Blocking certain ion channel proteins in silico will generate predicted changes of function, which can then be tested experimentally on the multi-electrode array. Our group’s expertise in machine learning, including deep learning, will be utilized to identify deviations between the two models.

We are seeking a student with some scripting experience (Python preferred) to conduct these studies. A background in cellular physiology, biochemistry, molecular biology, or pharmacology would be advantageous. This project offers a unique opportunity to contribute to our understanding of cardiac stem cell networks and their potential therapeutic applications.