Coherent beat to beat variability of self-similar Ca2+ and surface membrane's signaling mechanisms determines the spontaneous action potential firing rate and rhythm of cardiac pacemaker cells
National Institute On Aging
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Abstract
The heart rate and rhythm are regulated by rate and rhythm of spontaneous action potential (AP) firing of pacemaker cells that reside within sinoatrial node tissue. Early reductionist studies of mechanisms that underlie pacemaker automaticity had focused upon behaviors of individual surface membrane ion channels. We put forth the idea that spontaneous action potentials generated by single, isolated sinoatrial nodal cells (SANC) are generated by a coupled-clock system: An ensemble of surface membrane electrogenic molecules that directly controls the membrane potential and trans-membrane ion flux, and indirectly regulates intracellular Ca2+ cycling; and a Ca2+ clock, the sarcoplasmic reticulum (SR) and its decorator proteins, that directly control intracellular Ca2+ cycling and indirectly regulate transmembrane ion flux. The two clocks operate as a coupled system in which the coupling fidelity is controlled by voltage, time, Ca2+, intrinsic cAMP signaling, and cAMP-PKA and Ca2+-calmodulin-associated, PKA and CaMKII-dependent clock protein phosphorylation. Although by convention we refer to an average AP cycle length that characterizes a given steady state, AP cycle lengths vary from cycle to cycle indicating that a true steady state AP cycle length is never achieved. Prior to the elucidation of the coupled-clock system it had been discovered that AP cycle to cycle length variability could be linked to beat to beat homogeneity of activation states of SANC M clock ion channel molecules leading to beat to beat variability in channel availability. More recently, cycle to cycle variability in the rhythm of of local Ca2+ releases of the Ca2+ clock of SANC has also been demonstrated to be linked to action potential cycle length variability and to cycle to cycle variability of clock coupling. We hypothesized that concordant beat to beat variability of order (or disorder) among intrinsic mechanisms that regulate SANC M and Ca clock functions and their coupling determines the average AP firing rate and rhythm (cycle to cycle variability) that emerge in a given apparent steady state. We employed two external perturbations of the clock functions known to markedly effect steady state AP firing rate: (1) adrenergic receptor stimulation (bARs) and (2) an in vitro cell culture environment, in which mean APCL of cultured SANC cSANC) becomes about twice that of freshly isolated SANC (fSANC) and remains stable for several days ( ). bARs acutely restores APCL cSANC to that of fSANC. In response to bARs in single SANC, (f-SANC). In addition to recording average AP cycle lengths and AP cycle to cycle variability, we measured prior to and during bARs mean of M clock kinetic functional parameters (time to 90% AP repolarization (AP90) and time from maximum diastolic potential (MDP) to onset of non-linear diastolic depolarization (DD), and their cycle to cycle variability: and Ca2+ clock kinetic parameter the time to 90% decay of the AP-induced global cytosolic Ca2+ transient (CaT90) and diastolic LCR periods, measured as the time elapse between the prior preceding of AP induced Ca2+ transient to an LCR onset). We assessed cycle to cycle parameter variability under each condition in c and f SANC and their cycle to cycle variabilities as coefficient of variation (CV) about the mean, ie standard deviation divided by the mean. We employed linear correlation analyses, followed by principal component analyses (to determine the relationship of cycle to cycle variability of each function to its mean. To assess the degree of concordance among the means and CVs of measured M and Ca2+ clock parameters in c- and f-SANC and the concordance of these parameters to mean APCL and its CV. We used multiple regression analyses to determine whether the concordance among mean functions and concordance variability of each function) could predict the mean APCL and its cycle to cycle variability of the entire data set, ie, in C and f-SANC in control in response bARs. Finally, we employed power-law analyses to determine whether concordant degrees of order (variability) of M and Ca2+ clock kinetic functions prior to and during bARs in both c- and f-SANC are self-similar. In addition to measuring and analyzing mean and variability of AP characteristics, we explored the variability of the simulated ion currents (predicted by numerical modelling) that underlie APs in order to derive mechanistic insights into cycle variability of in currents that generates cycle variability of AP waveforms and the APFIV. And we found that the cycle to cycle variabilities of ion currents differ from each other and also differ to the experimentally measured APFIV both in control and in response to autonomic receptor stimulation. Variability of Vm and Ca2+ parameters measured experimentally in cells within and across autonomic states is linked to the respective variabilities of clock molecular availability to respond to Vm and Ca2+ cues that cannot be directly measured experimentally during AP firing. To gain further insight into the variability of these biophysical mechanisms, we performed numerical simulations using a modified Maltsev-Lakatta model that features the coupled-clock mechanism (Maltsev & Lakatta, Am J Physiol. Heart Circ Physiol. 2009). We investigated the variability of peak amplitudes and amplitudes at -40 mV during DD of 6 major currents (If, INCX, IKr, ICaL, ICaT and IKACh) and Ca under cell membrane in each of the three autonomic states: basal, ISO 100nM, and CCh 100nM. Observation of model simulations applied to experimental data indicated that (as was the case for experiment data) the simulated variables are self-similar to each other across broad range of APFI within the three autonomic states. Our numerical model simulations further extended our perspectives to the molecular scale and demonstrated that many ion currents also behave self-similar across autonomic states.
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