Functional Heterogeneity of Cell Populations Increases Robustness of Pacemaker Function in a Numerical Model of the Sinoatrial Node Tissue

Abstract

Each heartbeat is initiated by specialized pacemaker cells operating within the sinoatrial node (SAN). While individual cells within SAN tissue exhibit substantial heterogeneity of their electrophysiological parameters and Ca cycling, the role of this heterogeneity for cardiac pacemaker function remains mainly unknown. Here we investigated the problem numerically in a 25 × 25 square grid of connected coupled-clock Maltsev-Lakatta cell models. The tissue models were populated by cells with different degree of heterogeneity of the two key model parameters, maximum L-type Ca current conductance (gCaL) and sarcoplasmic reticulum Ca pumping rate (Pup). Our simulations showed that in the areas of Pup-gCaL parametric space at the edge of the system stability, where action potential (AP) firing is absent or dysrhythmic in SAN tissue models populated with identical cells, rhythmic AP firing can be rescued by populating the tissues with heterogeneous cells. This robust SAN function is synergistic with respect to heterogeneity in gCaL and Pup and can be further strengthened by clustering of cells with similar properties. The effect of cell heterogeneity is not due to a simple summation of activity of intrinsically firing cells naturally present in heterogeneous SAN; rather AP firing cells locally and critically interact with non-firing/dormant cells. When firing cells prevail, they recruit many dormant cells to fire, strongly enhancing overall SAN function; and vice versa, prevailing dormant cells suppress AP firing in cells with intrinsic automaticity and halt SAN function. The transitions between firing and non-firing states of the system are sharp, resembling phase transitions in statistical physics. Furthermore, robust function of heterogeneous SAN tissue requires weak cell coupling, a known property of the central area of SAN where cardiac impulse emerges; stronger cell coupling reduces AP firing rate and ultimately halts SAN automaticity at the edge of stability.

Coupling and heterogeneity modulate pacemaking capability in healthy and diseased two-dimensional sinoatrial node tissue models

“…More recent studies, from that group and others [9,51,52], have confirmed the existence of dormant SA nodal cells in tissue under a variety of conditions. Our results, along with similar recent modeling studies [38], demonstrate that when dormant cells are coupled with a minority of spontaneous cells, the tissue can exhibit stable electrical activity even in the absence of sympathetic stimulation. Our results also suggest that relatively large percentages of dormant cells can indeed be consistent with normal pacemaker function at the tissue level due to the protective effects of heterogeneity and intercellular coupling.…”

The paradigm shift: heartbeat initiation without “the pacemaker cell”

“…APs) within SAN tissue, e.g. via a stochastic resonance (Clancy and Santana, 2020;Grainger et al, 2021;Guarina et al, 2022), or a phase transition-like process each cycle (Weiss and Qu, 2020;Maltsev et al, 2022a). Thus, following this logic, in addition to the tonic influence or simple “wake-up” function under stress, dormant cells can be in fact functionally active generating important subthreshold signals.…”

“…What are potential roles and benefits of the new pacemaker mechanism? It can keep the system alive at the edge of criticality in heterogenous SAN tissue (Campana et al, 2022;Maltsev et al, 2022a), e.g. in aging and disease.…”

“…What are potential roles and benefits of the new pacemaker mechanism? It can keep the system alive at the edge of criticality in heterogenous SAN tissue (Campana et al, 2022;Maltsev et al, 2022a), e.g.in aging and disease. Indeed, major pacemaker components (ICaL, If, and LCRs) of intrinsic automaticity deteriorate with aging (Jones et al, 2007;Larson et al, 2013;Liu et al, 2014).…”

“…One idea is that synchronized APs at the SAN exits emerge from heterogeneous subcellular subthreshold Ca signals, similar to multiscale complex processes of impulse generation within clusters of neurons in neuronal networks (Bychkov et al, 2020;Bychkov et al, 2022). Possible specific mechanisms of signal processing within the network also include stochastic resonance (Clancy and Santana, 2020;Grainger et al, 2021), or a phase transition (Weiss and Qu, 2020;Maltsev et al, 2022a), and electrotonic interactions of firing cells with non-firing cells (Fenske et al, 2020).…”