High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts

The Janus face of mitophagy in myocardial ischemia/reperfusion injury and recovery

In myocardial ischemia/reperfusion injury (MIRI), moderate mitophagy is a protective or adaptive mechanism because of clearing defective mitochondria accumulates during MIRI. However, excessive mitophagy lead to an increase in defective mitochondria and ultimately exacerbate MIRI by causing overproduction or uncontrolled production of mitochondria. Phosphatase and tensin homolog (PTEN)-induced kinase 1 (Pink1), Parkin, FUN14 domain containing 1 (FUNDC1) and B-cell leukemia/lymphoma 2 (BCL-2)/adenovirus E1B19KD interaction protein 3 (BNIP3) are the main mechanistic regulators of mitophagy in MIRI. Pink1 and Parkin are mitochondrial surface proteins involved in the ubiquitin-dependent pathway, while BNIP3 and FUNDC1 are mitochondrial receptor proteins involved in the non-ubiquitin-dependent pathway, which play a crucial role in maintaining mitochondrial homeostasis and mitochondrial quality. These proteins can induce moderate mitophagy or inhibit excessive mitophagy to protect against MIRI but may also trigger excessive mitophagy or insufficient mitophagy, thereby worsening the condition. Understanding the actions of these mitophagy mechanistic proteins may provide valuable insights into the pathological mechanisms underlying MIRI development. Based on the above background, this article reviews the mechanism of mitophagy involved in MIRI through Pink1/Parkin pathway and the receptor mediated pathway led by FUNDC1 and BNIP3, as well as the related drug treatment, aim to provide effective strategies for the prevention and treatment of MIRI.

Fluorescence microscopy and correlative brightfield videos of mitochondria and vesicles in H9c2 cardiomyoblasts

This paper presents data acquired to study the dynamics and interactions of mitochondria and subcellular vesicles in living cardiomyoblasts. The study was motivated by the importance of mitochondrial quality control and turnover in cardiovascular health. Although fluorescence microscopy is an invaluable tool, it presents several limitations. Correlative fluorescence and brightfield images (label-free) were therefore acquired with the purpose of achieving virtual labelling via machine learning. In comparison with the fluorescence images of mitochondria, the brightfield images show vesicles and subcellular components, providing additional insights about sub-cellular components. A large part of the data contains correlative fluorescence images of lysosomes and/or endosomes over a duration of up to 400 timepoints (>30 min). The data can be reused for biological inferences about mitochondrial and vesicular morphology, dynamics, and interactions. Furthermore, virtual labelling of mitochondria or subcellular vesicles can be achieved using these datasets. Finally, the data can inspire new imaging experiments for cellular investigations or computational developments. The data is available through two large, open datasets on DataverseNO.