iRhythmics: Programming pacemaker cells for in vitro drug testing

iRhythmics: Programming pacemaker cells for in vitro drug testing

The project addresses the generation and establishment of programmed pacemaker cells for an in vitro drug testing possibility to perform predictive tests. This may lead to an improved treatment of cardiac arrhythmias or an accurate identification of potential drug molecules at an early stage of development. Important benefits will arise in verifying the safety of a wide variety of medicines while reducing animal testing.

 

The data is managed in FairdomHub - https://fairdomhub.org/projects/28

This project is funded by the European Social Fund (ESF) program of the European Union (ESF/14-BM-A55-0027).

Visit our official Project-Website:

https://irhythmics.med.uni-rostock.de/

Related publications

Cardiomyocyte Transplantation after Myocardial Infarction Alters the Immune Response in the Heart

Vasudevan P, Wolfien M, Lemcke H, Lang CI, Skorska A, Gaebel R, Koczan D, Lindner T, Engelmann R, Vollmar B, Krause BJ, Wolkenhauer O, Lang H, Steinhoff G, David R

Cells 2020, 9(8), 1825

Integrative cluster analysis of whole hearts reveals proliferative cardiomyocytes in adult mice

Galow AM, Wolfien M, Müller P, Bartsch M, Brunner RM, Hoeflich A, Wolkenhauer O, David R, Goldammer T

Cells 2020, 9 (5), 1144

A benchmark of hemoglobin blocking during library preparation for mRNA-Sequencing of human blood samples​

Uellendahl-Werth F, Wolfien M, Franke A, Wolkenhauer O, Ellinghaus D

Scientific Reports 2020, 10, 5630

Single Nuclei Sequencing of entire Mammalian Hearts: Strain-dependent Cell Type Composition and Velocity

Wolfien M, Galow AM, Müller P, Bartsch M, Brunner RM, Goldammer T, Wolkenhauer O, Hoeflich A, David R

RNA-Based Strategies for Cardiac Reprogramming of Human Mesenchymal Stromal Cells

Mueller P, Wolfien M, Ekat K, Lang CI, Koczan D, Wolkenhauer O, Hahn O, Peters K, Lang H, David R, Lemcke H

Cells 2020, 9 (2), 504

Single Nuclei Sequencing of an entire Mammalian Heart: Cell Type Composition and Velocity

Wolfien M, Galow AM, Müller P, Bartsch M, Brunner RM, Goldammer T, Wolkenhauer O, Hoeflich A, David R

Cells 2020, 9, 318

Tools for Understanding miRNA–mRNA Interactions for Reproducible RNA Analysis

Bagnacani A, Wolfien M, Wolkenhauer O

Springer (2019), chapter in Computational Biology of Non-Coding RNA. Methods in Molecular Biology, vol 1912.

Workflow Development for the Functional Characterization of ncRNAs

Wolfien M, Brauer DL, Bagnacani A, Wolkenhauer O

Springer (2019), chapter in Computational Biology of Non-Coding RNA. Methods in Molecular Biology, vol 1912.

Comparison of Deep Learning Approaches for Cardiomyocyte Evaluation

Maximilian Hillemanns

2020

Arrhythmias are severe cardiac diseases and lethal if untreated. To serve as an in vitro drug testing option for anti-arrhythmic agents, cardiomyocytes and especially pacemaker cells are being generated in vitro from induced pluripotent stem cells (iPSCs). These generated cardiomyocytes resemble fetal cardiac tissue rather than adult cardiomyocytes. An automated tool for evaluations of cardiomyocytes would help the establishment of new generation protocols. In this work, a novel approach for this task is presented and evaluated.
Different convolutional neural networks (CNNs) including transfer models and native 2D and 3D models were trained on fluorescence images of cardiomyocytes, which were rated based on their sarcomerisation and the orientation of sarcomeres (directionality) beforehand. The CNNs were trained to perform classifications on sarcomerisation and directionality ratings and cell source, as cardiomyocytes from five different sources were used in this work. In this thesis, it could be shown that cellular fluorescence images can be analysed with CNNs. This  classifier can be used to make trustworthy predictions on the quality of a cardiomyocyte which will hopefully benefit the generation of cardiomyocytes from iPSCs. This classifier is currently being