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Quantifies mitochondrial damage in human airway smooth muscle cells, suggesting a new method for assessing mitochondrial health.
Mitochondrial quality control is essential for maintaining cellular homeostasis by balancing the removal of damaged mitochondria (mitophagy) with the generation of new mitochondria (mitochondrial biogenesis). A key feature of mitochondrial damage is loss of mitochondrial membrane potential (ΔΨm), which initiates mitophagy, enabling effective mitochondrial clearance. Although an array of tools exists to assess mitochondrial damage (depolarization), many rely on acute, non-physiological depolarization or provide semiquantitative measures of mitochondrial damage, limiting their ability to resolve intact versus damaged mitochondria within heterogeneous mitochondrial networks. Therefore, in the present study we developed and validated an imaging-based assay to quantify intact mitochondria in human airway smooth muscle (hASM) cells using dual-fluorescence labeling. This approach combines a ΔΨm-dependent (MitoTracker Red FM) dye with a ΔΨm-independent label (CellLight Mitochondria-GFP). Dual-labeled mitochondria in untreated hASM cells exhibited ~10% non-overlap between the two fluorescence signals, indicating presence of damaged (depolarized) mitochondria in homeostatic conditions. Dose- and time-dependent treatment with the mitochondrial uncoupler FCCP induced loss of membrane potential, confirmed by TMRM, and resulted in a marked reduction in fluorescence overlap, volume of intact mitochondria and increased mitochondrial fragmentation. Complementary analysis using the redox-sensitive reporter pMitoTimer was performed, where a shift in fluorescence signal from green to red is indicative of increased mitochondrial oxidative stress and rate of mitochondrial turnover. Together, these findings validate the dual-labeling strategy as a quantitative method to distinguish intact from damaged mitochondria in situ and as a useful tool for studying mitochondrial quality control, potentially translatable to various cell and disease models.
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Bhat et al. (2026) studied this question.
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