Self-organization of conducting pathways explains electrical wave propagation in cardiac tissues with high fraction of non-conducting cells

Nina Kudryashova, Aygul Nizamieva, Valeriya Tsvelaya, Alexander V Panfilov, Konstantin I Agladze

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Cardiac fibrosis occurs in many forms of heart disease and is considered to be one of the main arrhythmogenic factors. Regions with a high density of fibroblasts are likely to cause blocks of wave propagation that give rise to dangerous cardiac arrhythmias. Therefore, studies of the wave propagation through these regions are very important, yet the precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Particularly, it is not clear how wave propagation is organized at the cellular level, as experiments show that the regions with a high percentage of fibroblasts (65-75%) are still conducting electrical signals, whereas geometric analysis of randomly distributed conducting and non-conducting cells predicts connectivity loss at 40% at the most (percolation threshold). To address this question, we used a joint in vitro-in silico approach, which combined experiments in neonatal rat cardiac monolayers with morphological and electrophysiological computer simulations. We have shown that the main reason for sustainable wave propagation in highly fibrotic samples is the formation of a branching network of cardiomyocytes. We have successfully reproduced the morphology of conductive pathways in computer modelling, assuming that cardiomyocytes align their cytoskeletons to fuse into cardiac syncytium. The electrophysiological properties of the monolayers, such as conduction velocity, conduction blocks and wave fractionation, were reproduced as well. In a virtual cardiac tissue, we have also examined the wave propagation at the subcellular level, detected wavebreaks formation and its relation to the structure of fibrosis and, thus, analysed the processes leading to the onset of arrhythmias.

Original languageEnglish
Pages (from-to)e1006597
Number of pages21
JournalPLoS Computational Biology
Volume15
Issue number3
DOIs
Publication statusPublished - 18 Mar 2019
Externally publishedYes

Keywords / Materials (for Non-textual outputs)

  • Animals
  • Animals, Newborn
  • Arrhythmias, Cardiac/physiopathology
  • Computer Simulation
  • Heart/physiology
  • Heart Conduction System/physiology
  • Models, Cardiovascular
  • Rats

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