No abstract

Ryanodine receptor channels at calcium release sites of cardiac myocytes operate on the principle of calcium-induced calcium release. In vitro experiments revealed competition of Ca2+ and Mg2+ in the activation of ryanodine receptors (RyRs) as well as inhibition of RyRs by Mg2+. The impact of RyR modulation by Mg2+ on calcium release is not well understood due to the technical limitations of in situ experiments. We turned instead to an in silico model of a calcium release site (CRS), based on a homotetrameric model of RyR gating with kinetic parameters determined from in vitro measurements. We inspected changes in the activity of the CRS model in response to a random opening of one of 20 realistically distributed RyRs, arising from Ca2+/Mg2+ interactions at RyR channels. Calcium release events (CREs) were simulated at a range of Mg2+-binding parameters at near-physiological Mg2+ and ATP concentrations. Facilitation of Mg2+ binding to the RyR activation site inhibited the formation of sparks and slowed down their activation. Impeding Mg-binding to the RyR activation site enhanced spark formation and speeded up their activation. Varying Mg2+ binding to the RyR inhibition site also dramatically affected calcium release events. Facilitation of Mg2+ binding to the RyR inhibition site reduced the amplitude, relative occurrence, and the time-to-end of sparks, and vice versa. The characteristics of CREs correlated dose-dependently with the effective coupling strength between RyRs, defined as a function of RyR vicinity, single-channel calcium current, and Mg-binding parameters of the RyR channels. These findings postulate the role of Mg2+ in calcium release as a negative modulator of the coupling strength among RyRs in a CRS, translating to damping of the positive feedback of the calcium-induced calcium-release mechanism.

Transient signals convey information on the state and function of the studied system. The estimation of characteristic parameters of transient signals is complicated by the noise in the records. The reduction of noise by filtering leads to certain signal distortion. Alternatively, the transient signal can be approximated by a mathematical function, if available. We introduce here the model-independent approximation method for general noisy transient signals based on the Gaussian process regression. The method was implemented in the software TransientAnalyzer, which detects transients in a record, finds their best approximation by the Gaussian process, constructs a surrogate spline function, and estimates specified signal parameters. The method and software were tested on a model of the calcium concentration transient, characterized by abrupt rise and slow decay, contaminated by various signal-to-noise ratios, and recorded at a low sampling frequency. Statistics of the analyzed data set revealed that the software estimates all signal parameters reliably. The error of estimation and the standard deviation of estimates were less than 10% for SNR ≥ 7. The software and its description are available on GitHub.