Dataset Information

Protein profiling of CAST.APP/PS1 mouse brain-derived Extracellular vesicles

ABSTRACT: Extracellular vesicles (EVs) are secreted by any neuronal cells in the central nervous system (CNS) for molecular clearance, cellular communications and disease spread in multiple neurodegenerative diseases, including Alzheimer’s disease (AD), although their exact molecular mechanism is poorly understood. We hypothesize that high-resolution proteomic profiling of EVs separated from animal models of AD would determine the composition of EV contents and their cellular origin.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Brain

SUBMITTER: Satoshi Muraoka

LAB HEAD: Tsuneya Ikezu

PROVIDER: PXD022349 | Pride | 2021-09-09

REPOSITORIES: Pride

ACCESS DATA

Publications

Enrichment of Neurodegenerative Microglia Signature in Brain-Derived Extracellular Vesicles Isolated from Alzheimer's Disease Mouse Models.

Muraoka Satoshi S Jedrychowski Mark P MP Iwahara Naotoshi N Abdullah Mohammad M Onos Kristen D KD Keezer Kelly J KJ Hu Jianqiao J Ikezu Seiko S Howell Gareth R GR Gygi Steven P SP Ikezu Tsuneya T

Journal of proteome research 20210203 3

Extracellular vesicles (EVs) are secreted by any neural cells in the central nervous system for molecular clearance, cellular communications, and disease spread in multiple neurodegenerative diseases, including Alzheimer's disease (AD), although their exact molecular mechanism is poorly understood. We hypothesize that high-resolution proteomic profiling of EVs separated from animal models of AD would determine the composition of EV contents and their cellular origin. Here, we examined recently d ...[more]

PMID: 33534581

Similar Datasets

Project description:Removal of damaged organelles via the process of selective autophagy constitutes a major form of cellular quality control. Damaged organelles are recognized by a dedicated surveillance machinery, leading to the assembly of an autophagosome around the damaged organelle, prior to fusion with the degradative lysosomal compartment. Lysosomes themselves are also prone to damage and are degraded through the process of lysophagy. While early steps involve recognition of ruptured lysosomal membranes by glycan-binding Galectins and ubiquitylation of transmembrane lysosomal proteins, many steps in the process, and their inter-relationships, remain poorly understood, including the role and identity of cargo receptors required for completion of lysophagy. Here, we employ quantitative organelle capture and proximity biotinylation proteomics of autophagy adaptors, cargo receptors, and Galectins in response to acute lysosomal damage, thereby revealing the landscape of lysosomal proteome remodeling during lysophagy. Among proteins dynamically recruited to damaged lysosomes were ubiquitin-binding autophagic cargo receptors. Using newly developed lysophagic flux reporters including Lyso-Keima, we demonstrate that TAX1BP1, together with its associated kinase TBK1, are both necessary and sufficient to promote lysophagic flux in both Hela cells and induced neurons (iNeurons). While the related receptor OPTN can drive damage-dependent lysophagy when overexpressed, cells lacking either OPTN or CALCOCO2 still maintain significant lysophagic flux in HeLa cells. Mechanistically, TAX1BP1-driven lysophagy requires its N-terminal SKICH domain, which binds both TBK1 and the autophagy regulatory factor RB1CC1, and requires upstream ubiquitylation events for efficient recruitment and lysophagic flux. These results identify TAX1BP1 as a central component in the lysophagy pathway and provide a proteomic resource for future studies of the lysophagy process.

Project description:Objective: The loss of insulin-secreting β-cells, ultimately characterizing most diabetes forms, demands the development of cell replacement therapies. The common endpoint for all ex vivo strategies is transplantation into diabetic patients. However, the effects of hyperglycemia environment on the transplanted cells were not yet properly assessed. Thus, the main goal of this study was to characterize global effect of brief and prolonged in vivo hyperglycemia exposure on the cell fate acquisition and maintenance of transplanted human pancreatic progenitors. Methods: To rigorously study the effect of hyperglycemia, in vitro differentiated human induced pluripotent stem cells (hiPSC)-derived pancreatic progenitors were xenotransplanted in normoglycemic and diabetic NSG RIP-DTR mice. The transplants were retrieved after one-week or one-month exposure to overt hyperglycemia and analyzed by large-scale microscopy or global proteomics. For this study we pioneer the use of the NSG RIP-DTR system in the transplantation of hiPSC, making use of its highly reproducible specific and absolute β-cell ablation property in the absence of inflammation or other organ toxicity. Results: Here we show for the first time that besides the presence of an induced oxidative stress signature, the cell fate and proteome landscape response to hyperglycemia was different, involving largely different mechanisms, according to the period spent in the hyperglycemic environment. Surprisingly, brief hyperglycemia exposure increased the bihormonal cell number by impeding the activity of specific islet lineage determinants. Moreover it activated antioxidant and inflammation protection mechanisms signatures in the transplanted cells. In contrast, the prolonged exposure was characterized by decreased numbers of hormone+ cells, low/absent detoxification signature, augmented production of oxygen reactive species and increased apoptosis. Conclusion: Hyperglycemia exposure induced distinct, period-dependent, negative effects on xenotransplanted human pancreatic progenitor, affecting their energy homeostasis, cell fate acquisition and survival.

Dataset Information

Protein profiling of CAST.APP/PS1 mouse brain-derived Extracellular vesicles

Publications

Enrichment of Neurodegenerative Microglia Signature in Brain-Derived Extracellular Vesicles Isolated from Alzheimer's Disease Mouse Models.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure