γ-Secretases are a family of intramembrane-cleaving proteases involved in various signaling pathways and diseases, including Alzheimer's disease (AD). Cells co-express differing γ-secretase complexes, including two homologous presenilins (PSENs). We examined the significance of this heterogeneity and identified a unique motif in PSEN2 that directs this γ-secretase to late endosomes/lysosomes via a phosphorylation-dependent interaction with the AP-1 adaptor complex. Accordingly, PSEN2 selectively cleaves late endosomal/lysosomal localized substrates and generates the prominent pool of intracellular Aβ that contains longer Aβ; familial AD (FAD)-associated mutations in PSEN2 increased the levels of longer Aβ further. Moreover, a subset of FAD mutants in PSEN1, normally more broadly distributed in the cell, phenocopies PSEN2 and shifts its localization to late endosomes/lysosomes. Thus, localization of γ-secretases determines substrate specificity, while FAD-causing mutations strongly enhance accumulation of aggregation-prone Aβ42 in intracellular acidic compartments. The findings reveal potentially important roles for specific intracellular, localized reactions contributing to AD pathogenesis.
Manuscript 2Synapses are often far from the soma and independently cope with proteopathic stress induced by intense neuronal activity. However, how presynaptic compartments turnover proteins is poorly understood. We show that the synapse-enriched protein EndophilinA, thus far studied for its role in endocytosis, induces macroautophagy at presynaptic terminals. We find that EndophilinA executes this unexpected function at least partly independent of its role in synaptic vesicle endocytosis. EndophilinA-induced macroautophagy is activated when the kinase LRRK2 phosphorylates the EndophilinA-BAR domain and is blocked in animals where EndophilinA cannot be phosphorylated. EndophilinA INTRODUCTIONNeurons can be metabolically very active, firing at rates of more than 100 Hz.Synaptic proteins and organelles are used and re-used multiple times and accumulate damage as a result of this stress. Furthermore, synapses are often located far away from the cell body and must therefore in part operate independently. This raises the question how synapses maintain protein quality. Given that neurodegeneration is thought to start with subtle synaptic defects before evolving into blunt neuronal death (Burke and O'Malley, 2013;, the mechanisms of synaptic protein homeostasis are likely relevant for the understanding of neurodegenerative disease.Macroautophagy is well-placed to mediate protein turnover, but how the needs of synapses are served by this process has not been well-studied. Cellular signals like stress and amino acid deprivation induce macroautophagy, where cytoplasm is engulfed by double membrane structures before fusion with degradative lysosomes (Mizushima et al., 2011).Autophagosomes have been visualized using fluorescent markers in yeast, Drosophila and mammalian cells and are often observed as Atg8/LC3 positive puncta (Kabeya et al., 2000;Scott et al., 2004). At the stage of initiation, Atg9-positive vesicles fuse into elongated preautophagosomal structures with growing edges (He et al., 2006). These edges are highly curved and harbor lipid packing defects. These edges serve as protein docking sites, attracting specific autophagic factors such as Atg3, Atg14/Barkor and Atg1 that insert into such zones, recognizing specific lipids (phosphatidylinositol-3-phosphate (PI(3)P)) and lipid packing defects (Fan et al., 2011;Nath et al., 2014;Ragusa et al., 2012). The recruitment of these factors then promotes the further steps of autophagosome formation; in particular the E2-like protein Atg3 itself recruits the autophagic marker LC3/Atg8 (Nath et al., 2014). However, how these highly curved edges are formed and maintained is very poorly understood.While autophagy has been mostly analyzed in the soma of cultured cells and yeast, autophagic markers have also been observed away from the soma at neuronal synapses 4 (Hernandez et al., 2012;Maday and Holzbaur, 2014;Williamson et al., 2010) and these markers were shown to be transported along axons (Maday and Holzbaur, 2014). However, how autophagosomes are formed at synapses an...
Mutations in the genes for PINK1 and parkin cause Parkinson’s disease. PINK1 and parkin cooperate in the selective autophagic degradation of damaged mitochondria (mitophagy) in cultured cells. However, evidence for their role in mitophagy in vivo is still scarce. Here, we generated a Drosophila model expressing the mitophagy probe mt-Keima. Using live mt-Keima imaging and correlative light and electron microscopy (CLEM), we show that mitophagy occurs in muscle cells and dopaminergic neurons in vivo, even in the absence of exogenous mitochondrial toxins. Mitophagy increases with aging, and this age-dependent rise is abrogated by PINK1 or parkin deficiency. Knockdown of the Drosophila homologues of the deubiquitinases USP15 and, to a lesser extent, USP30, rescues mitophagy in the parkin-deficient flies. These data demonstrate a crucial role for parkin and PINK1 in age-dependent mitophagy in Drosophila in vivo.
Data availabilityData associated with this study have been deposited in the NCBI Gene Expression Omnibus under accession numbers GSE126231, GSE126734 and GSE146637 respectively for the microarray, ATAC-seq and single-cell RNA-seq. Data supporting the findings of this study are available within the article (and its Supplementary Information files). Source data behind Figures 1-4 and Extended Data Figures 1-12 are available within the manuscript files. Code availabilityCustom computer code and algorithm used to generate results that are reported in the paper are available within the article (and its Supplementary Information files) and from the corresponding authors on reasonable request. The code used for the modeling of the clonal data has been deposited in GitHub (available at https://github.com/BenSimonsLab/Aragona_Nature_2020). In relation with the single-cells analysis, sequencing reads were preprocessed using cutadapt (version 1.13, https://pypi.org/project/ cutadapt/), alignments were generated using STAR (version 2.5.2b
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