Accounting for cardiac t-tubule increase with age and myocyte volume to improve measurements of its membrane area and ionic current densities. (November 2020)

• Record Type: Journal Article
• Authors: Christé, Georges; Bonvallet, Robert; Chouabe, Christophe
• Is Part Of: Progress in biophysics and molecular biology. Volume 157(2020)
• Page Start: 40
• Page End: 53
• Publication Date: 2020-11
• Subjects: Cardiac myocytes -- Rat -- t-tubule -- Volume -- Capacitance -- Morphology -- Weight -- Age -- Model; Biophysics -- Periodicals; Biochemistry -- Periodicals; Biophysics -- Periodicals; Molecular Biology -- Periodicals; Biophysique -- Périodiques; Biochimie -- Périodiques; 571.4
• DOI: 10.1016/j.pbiomolbio.2020.06.005
• Languages: English
• ISSNs: 0079-6107

Abstract

Abstract: In-silico models of cardiac myocytes allow simulating experiments in numbers on series of myocytes as well as on large populations of myocytes assembled in 3D structures. The simulated myocyte populations should have realistic values and statistical dispersions of biophysical parameters such as myocyte dimensions and volume and areas of the peripheral membrane and transverse-axial tubular system (TATS). Dependencies among these variables also have to be taken into account. In this work, we propose a quantitative representation of the changes in the fraction of membrane area in the TATS that integrates published dependencies with body weight (age) and size of rat ventricular cardiac myocytes while respecting the above constraints. Imposing a constant total membrane area-to-volume ratio appears to account for the increase of this fraction with myocyte size (i.e.: volume) within a given age group. The agreement of our results with published data was discussed and reasons for discrepancies were analysed. On the basis of our framework, strategies are proposed for minimizing the influence of non-random dispersion related to myocyte volume on measurements of the area of TATS and surface membrane compartments and of ionic current densities. The next step will be to quantitatively compare these strategies by evaluating the impact of myocyte morphological parameters and their dependencies, sample size, biases and errors, on the output of experiments.