Spatio-temporal oscillations of individual mitochondria in cardiac myocytes reveal modulation of synchronized mitochondrial clusters

Abstract

Mitochondrial networks in cardiac myocytes under oxidative stress show collective (cluster) behavior through synchronization of their inner membrane potentials (ΔΨ m ). However, it is unclear whether the oscillation frequency and coupling strength between individual mitochondria affect the size of the cluster and vice versa. We used the wavelet transform and developed advanced signal processing tools that allowed us to capture individual mitochondrial ΔΨ m oscillations in cardiac myocytes and examine their dynamic spatio-temporal properties. Heterogeneous frequency behavior prompted us to sort mitochondria according to their frequencies. Signal analysis of the mitochondrial network showed an inverse relationship between cluster size and cluster frequency as well as between cluster amplitude and cluster size. High cross-correlation coefficients between neighboring mitochondria clustered longitudinally along the myocyte striations, indicated anisotropic communication between mitochondria. Isochronal mapping of the onset of myocyte-wide ΔΨ m depolarization further exemplified heterogeneous ΔΨ m among mitochondria. Taken together, the results suggest that frequency and amplitude modulation of clusters of synchronized mitochondria arises by means of strong changes in local coupling between neighboring mitochondria.wavelets | frequency | amplitude | mitochondrial oscillator | mitochondrial coupling M itochondria in cardiac myocytes under the influence of substrate deprivation or oxidative stress have a fundamental role as determinants of cell life or death, with implications that scale to affect the function of the whole heart (1, 2). Cardiac mitochondria are organized in a highly ordered network consisting of intermyofibrillar, subcarcolemmal, and perinuclear (3) mitochondria whose coordinated function controls the energy metabolism of the myocyte (4).In cardiac myocytes, the localized perturbation of a few mitochondria within the overall mitochondrial network can trigger the transition from the physiological to the pathophysiological state by producing synchronized whole-myocyte oscillations of ΔΨ m that can be monitored with the fluorescent dye tetramethylrhodamine ethyl ester (TMRE) (5). The imbalance between reactive oxygen species (ROS) generation and ROS scavenging capacity in a significant proportion of the network (∼60%) (5) is thought to destabilize ΔΨ m beyond a critical point into a state of ROS-induced ROS release. Increased ROS overflow exceeding a threshold level results in the appearance of a spanning cluster of mitochondria oscillating in apparent synchrony throughout the cell as the mitochondrial network locks into a low-frequency, high-amplitude oscillatory mode (6, 7).In many disparate examples of physically and chemically coupled oscillators, synchronization of the system generally arises from an initial nucleus of (spontaneously) synchronized oscillators that integrate neighboring oscillators, thereby increasing the size and signal amplitude of the initial oscillatory nucleus (8-11).When the clus...

Extramitochondrial domain rich in carbonic anhydrase activity improves myocardial energetics

“…Locally, at the level of individual mitochondria, CO 2 production fluctuates as a result of oscillating mitochondrial activity (8) regulated by Ca 2+ transients (9)(10)(11) and redox state (12,13). CO 2 vents out of the mitochondrial matrix, across the cytoplasm, and into the extracellular space, crossing at least three membranes (including two mitochondrial membranes plus the sarcolemma) and a distance of several microns which varies as a result of heterogeneous (14) and time-dependent capillary perfusion (15).…”

Chaos in Biochemistry and Physiology

“…10). These m fluctuations developed into actively propagating waves of mitochondrial depolarization/ collapse (velocity ¾20 µm s 1 , similar to those described in cells) [98,102] across the epicardial surface (4 mm 2 area with cellular spatial resolution) [109]. Complex spatiotemporal gradients of m during metabolic stress produced by ischemic injury could be also visualized in hearts exhibiting left ventricular hypertrophy (LVH) [110].…”

“…The other two evident oscillation periods are ¾40 min (circahoralian bursts) and ¾4 min; (b) Depicted is the corresponding logarithmic absolute squared wavelet transform over logarithmic frequency and time. As a form of time-frequency representation, the wavelet transform expands signals in terms of wavelets by breaking the signal down into different scale components [102]. At any time, the wavelet transform uncovers the predominant frequencies: there are periodically recurring frequency contents at about 3.1-10 mHz ( 2.5 to 2.0 on the logarithmic frequency scale, light blue: corresponding to the few min period range) and at about 0.1-1 mHz ( 4 to 3 on the logarithmic frequency scale, yellow: corresponding to the circahoralian range).…”

“…The boxes and arrows show the correspondence between the time series and the wavelet plot. Wavelet analysis was carried out using the Morlet wavelet with wavelet software in Matlab v7.1.0.246 (R14), as described previously [102]. The figure and wavelet analysis were provided courtesy of Dr F. T. Kurz, affiliated with Charité Universitätsmedizin, Berlin, Germany, and Massachusetts General Hospital, Charlestown, USA.…”

Systems Biology of the Fluxome

“…The top-down approach involves the integrated study of different sort of networks, and their simulation with computational models [7,8]. Bottom-up approaches include the study of selected processes in cells, organs, or organisms, at high spatio-temporal resolution, which can also be simulated through computational modeling [9][10][11][12][13][14][15][16]. From improving the production of a high-value metabolite or polymer in unicellular eukaryotes or prokaryotes, to the understanding of the pathophysiology of a disease, the focus can be placed on single mechanistic pathways such as amino acids or sympathetic signaling in cardiovascular disease, or a global study of a large number of molecules and then dissecting the individual pathways involved [3].…”