MitoWave: Spatiotemporal analysis of mitochondrial membrane potential fluctuations during I/R

Abstract

Mitochondria exhibit unstable inner membrane potentials (ΔΨ_m) when subjected to stress, such as during ischemia/reperfusion (I/R). Understanding the mechanism of ΔΨ_m instability involves characterizing and quantifying this phenomenon in an unbiased and reproducible manner. Here, we describe a simple analytical workflow called "MitoWave" that combines wavelet transform methods and image segmentation to unravel dynamic ΔΨ_m changes in the cardiac mitochondrial network during I/R. In vitro ischemia was affected by placing a glass coverslip on a monolayer of neonatal mouse ventricular myocytes for 1 h and removing the coverslip to allow for reperfusion, revealing complex oscillatory ΔΨ_m. MitoWave analysis was then used to identify individual mitochondrial clusters within the cells and track their intrinsic oscillation frequencies over the course of reperfusion. Responses segregated into five typical behaviors were quantified by MitoWave that were corroborated by visual inspection of the time series. Statistical analysis of the distribution of oscillating mitochondrial clusters during reperfusion showed significant differences between the five different outcomes. Features such as the time point of ΔΨ_m depolarization during I/R, area of mitochondrial clusters, and time-resolved frequency components during reperfusion were determined per cell and per mitochondrial cluster. Mitochondria from neonatal mouse ventricular myocytes subjected to I/R oscillate in the frequency range of 8.6-45 mHz, with a mean of 8.73 ± 4.35 mHz. Oscillating clusters had smaller areas ranging from 49.8 ± 1.2 μm², whereas nonoscillating clusters had larger areas 66 ± 1.5 μm². A negative correlation between frequency and mitochondrial cluster area was observed. We also observed that late ΔΨ_m loss during ischemia correlated with early ΔΨ_m stabilization after oscillation on reperfusion. Thus, MitoWave analysis provides a semiautomated method to quantify complex time-resolved mitochondrial behavior in an easy-to-follow workflow, enabling unbiased, reproducible quantitation of complex nonstationary cellular phenomena.