Researchers at the University of Tampere have developed a computational model for analysing and classifying information on cardiomyocytes differentiated from induced pluripotent stem cells (iPS cells).
The aim of the study was to analyse in more detail the calcium transients of cardiomyocytes. Calcium released from the intracellular compartment (sarcoplasmic reticulum) of the cardiomyocytes binds to sarcomeric proteins of the cell and creates a contraction. When the cardiomyocytes relax, the calcium is released and pumped back into sarcoplasmic reticulum. Calcium cycling in cardiomyocytes is thus crucial for the beating behaviour of the cells, i.e. for the normal functionality of the heart.
Heart failure is due to abnormal calcium cycling and different drug molecules can alter the normal calcium metabolism of cardiomyocytes and lead to severe arrhythmia.
The computational model for classification of different calcium transients is based on signal analysis and machine learning methods providing a novel insight into the calcium cycling of cardiomyocytes. The new method helps to visualise the calcium transients on the basis of signal data gathered from the heart muscle cells and to classify the cells’ signals of spontaneous calcium release as either normal or abnormal.
“The cardiomyocytes we analysed are derived from patients having a genetic cardiac disease, usually arrhythmia or cardiomyopathy”, says Katriina Aalto-Setälä, professor of physiology at the University of Tampere who was in charge of the medical and cellular parts of the study.
“With the help of the computational model, we are able to conduct a more detailed analysis of calcium cycling in cardiomyocytes. A clearly deviant signal signifies arrhythmia and enables us to investigate if we could fix the calcium cycle with a drug molecule. We can also investigate if some medical compounds interfere with the normal calcium cycling.”
The computational model was developed by Martti Juhola, professor of computer science and his data analysis research group at the School of Information Sciences of the University of Tampere.
The research article Signal analysis and classification methods for the calcium transient data of stem cell-derived cardiomyocytes was published in the Computers in Biology and Medicine journal. Corresponding research has never been published before.
“We measured 280 signals in the cardiomyocytes, which had been differentiated from iPS cells”, Professor Juhola explains.
Juhola and his research group also aim to produce other new computational models, such as analysing microscopic pictures of cells and cell colonies, which can be used in stem cell research to investigate both normal and abnormal cells from patients and to analyse drug responses.
“As stem cell research expands globally, developing computer models for medical research – for drug development for example – is very important for the future”, Juhola says.
Signal analysis and classification methods for the calcium transient data of stem cell-derived cardiomyocytes. Juhola M, Penttinen K, Joutsijoki H, Varpa K, Saarikoski J, Rasku J, Siirtola H, Iltanen K, Laurikkala J, Hyyrö H, Hyttinen J, Aalto-Setälä K. Computers in Biology and Medicine 2015 Jun:61:1-7. DOI: http://dx.doi.org/10.1016/j.compbiomed.2015.03.016
A synopsis of the research was published by Global Medical Discovery, which publishes breaking news of latest medical discoveries. It has a very discerning publication policy and reissues less than 0.1 percent of published research.
For more information, please contact:
Professor Martti Juhola, tel. +358 40 190 1716
Professor Katriina Aalto-Setälä, tel. +358 40 582 9567