DPhil the Future: CalTrack a new way to understand calcium flow in the heart
Posted: 18th June 2021
Doctoral Student Francesca Margara has helped develop new software to accurately and automatically analyse large quantities of calcium data – key to detecting potential cardiac abnormalities.
Calcium is an important signalling molecule in the human heart. Calcium transients within cardiac cells control how the heart contracts and relaxes and can trigger life-threatening abnormal cardiac rhythms. Furthermore, calcium signalling is often altered in cardiac diseases. Thus, being able to track the dynamic changes of calcium can advance our understanding of cardiac physiology, pathology, and response to pharmacological therapies.
Nowadays, researchers can use advanced imaging techniques to acquire large amount of calcium data from many different cell types. However, the possibility of performing an accurate and automated analysis of this large quantity of data is limited.
In collaboration with Cardiovascular Medicine at Oxford, we developed CalTrack to address this need and we have made the software freely available to other researchers. CalTrack is an easy to use, adaptable, and automated analysis pipeline. It can provide several key measurements that characterise calcium transients’ morphology and how it changes in different scenarios.
Importantly, CalTrack enables computational investigations into the mechanisms through which calcium affects the heart function in heath, disease, and under drug action, by generating large amount of high-quality data. DPhil student Francesca MargaraIn my DPhil thesis I have additionally integrated and augmented calcium data analysed by CalTrack with modelling and simulation of human cardiac cells, to better understand how genetic mutations cause a disease called hypertrophic cardiomyopathy. This is a common inherited cardiac disorder that affects 1 in 500 people and can lead to sudden death.
I constructed models of human cardiac cells under different genetic mutations and conducted simulation studies to identify and explain the mechanisms through which specific mutations underlie the changes in calcium transient as quantified by CalTrack, and how these would affect other cellular properties such as the cell’s ability to contract. Based on this, I also assessed whether specific pharmacological interventions would be beneficial to restore cellular function altered by the mutation.
Such combined approach of experimental and computational research can advance our understanding on the response to drug action in specific scenarios.
When CalTrack analysis is applied to cardiac cells derived from patients, analysed data and computer models can then predict and explain drug action in the individual subject. Thus, these findings can improve the development and administration of novel effective pharmacological interventions that are patient specific.