ATP13A2-mediated endo-lysosomal polyamine export counters mitochondrial oxidative stress.

Recessive loss-of-function mutations in ATP13A2 (PARK9) are associated with a spectrum of neurodegenerative disorders, including Parkinson's disease (PD). We recently revealed that the late endo-lysosomal transporter ATP13A2 pumps polyamines like spermine into the cytosol, whereas ATP13A2 dysfunction causes lysosomal polyamine accumulation and rupture. Here, we investigate how ATP13A2 provides protection against mitochondrial toxins such as rotenone, an environmental PD risk factor. Rotenone promoted mitochondrial-generated superoxide (MitoROS), which was exacerbated by ATP13A2 deficiency in SH-SY5Y cells and patient-derived fibroblasts, disturbing mitochondrial functionality and inducing toxicity and cell death. Moreover, ATP13A2 knockdown induced an ATF4-CHOP-dependent stress response following rotenone exposure. MitoROS and ATF4-CHOP were blocked by MitoTEMPO, a mitochondrial antioxidant, suggesting that the impact of ATP13A2 on MitoROS may relate to the antioxidant properties of spermine. Pharmacological inhibition of intracellular polyamine synthesis with α-difluoromethylornithine (DFMO) also increased MitoROS and ATF4 when ATP13A2 was deficient. The polyamine transport activity of ATP13A2 was required for lowering rotenone/DFMO-induced MitoROS, whereas exogenous spermine quenched rotenone-induced MitoROS via ATP13A2. Interestingly, fluorescently labeled spermine uptake in the mitochondria dropped as a consequence of ATP13A2 transport deficiency. Our cellular observations were recapitulated in vivo, in a Caenorhabditis elegans strain deficient in the ATP13A2 ortholog catp-6 These animals exhibited a basal elevated MitoROS level, mitochondrial dysfunction, and enhanced stress response regulated by atfs-1, the C. elegans ortholog of ATF4, causing hypersensitivity to rotenone, which was reversible with MitoTEMPO. Together, our study reveals a conserved cell protective pathway that counters mitochondrial oxidative stress via ATP13A2-mediated lysosomal spermine export.

MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology.

While the analysis of mitochondrial morphology has emerged as a key tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a challenging task and bottleneck for statistically robust conclusions. Here, we present Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6 ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet in a toolbox for Windows and Linux operating systems that combines segmentation with morphological analysis.