Cardiac mitochondria exhibit dynamic functional clustering

Abstract

Multi-oscillatory behavior of mitochondrial inner membrane potential ΔΨm in self-organized cardiac mitochondrial networks can be triggered by metabolic or oxidative stress. Spatio-temporal analyses of cardiac mitochondrial networks have shown that mitochondria are heterogeneously organized in synchronously oscillating clusters in which the mean cluster frequency and size are inversely correlated, thus suggesting a modulation of cluster frequency through local inter-mitochondrial coupling. In this study, we propose a method to examine the mitochondrial network's topology through quantification of its dynamic local clustering coefficients. Individual mitochondrial ΔΨm oscillation signals were identified for each cardiac myocyte and cross-correlated with all network mitochondria using previously described methods (Kurz et al., 2010a). Time-varying inter-mitochondrial connectivity, defined for mitochondria in the whole network whose signals are at least 90% correlated at any given time point, allowed considering functional local clustering coefficients. It is shown that mitochondrial clustering in isolated cardiac myocytes changes dynamically and is significantly higher than for random mitochondrial networks that are constructed using the Erdös–Rényi model based on the same sets of vertices. The network's time-averaged clustering coefficient for cardiac myocytes was found to be 0.500 ± 0.051 (N = 9) vs. 0.061 ± 0.020 for random networks, respectively. Our results demonstrate that cardiac mitochondria constitute a network with dynamically connected constituents whose topological organization is prone to clustering. Cluster partitioning in networks of coupled oscillators has been observed in scale-free and chaotic systems and is therefore in good agreement with previous models of cardiac mitochondrial networks.

Mitochondrial health, the epigenome and healthspan

“…A diverse array of mechanisms underlie the dynamic function of mitochondrial networks such as chemical communication [15–19], physical contact via partial or complete fusion enabling complementation [20–23], intermitochondrial junctions [24], and nanotunneling [25]. Functional organization within localized mitochondrial clusters also represents an additional important organizational principle of mitochondria in cells and organs [17, 26–28]. Examples of the functional importance of localized clusters are given by subsarcolemmal and interfibrillar mitochondrial subpopulations in human and rodent cardiac cells [29–31] and in skeletal muscle [20].…”

“…1). The contribution of mitochondria to cell function results from their collective cluster dynamics in different cellular locations (perinuclear, subsarcolemmal, intermyofibrillar) connected via local signaling events [17, 19, 26, 27]. Mitochondria drive catabolic and anabolic reactions supplying energy (e.g.…”

The Shape of Mitochondrial Dysfunction in Down Syndrome

“…Structurally, mitochondria are organized as a network with fragments of all sizes, ranging from 1 to several μm of length. Mitochondrial networks exhibit a variety of behaviors, including cell‐wide oscillations in the metabolic state (Aon et al , ), dynamic functional clustering (Kurz et al , ), as well as phase transitions in response to OS (Aon et al , ; Park et al , ) and fractal topology (Aon et al , ; Sukhorukov et al , ). Interestingly, there is a strong dependency of mitochondrial function on network organization, since global architecture determines ROS propagation (Park et al , ), mitochondrial recycling (Rambold et al , ), and mtDNA maintenance.…”

Network dynamics: quantitative analysis of complex behavior in metabolism, organelles, and cells, from experiments to models and back

“…The major frequency component (dark red) varies between 15 and 20 mHz corresponding to the wavelet frequency with maximum power of the absolute squared wavelet transform at each time‐point. (Reprinted with permission from Ref . Copyright 2014 Frontiers Open Access Academic Publisher)…”