Ray, Nibedita Basu

Abstract P2x purinoreceptor 7 (P2RX7), an ATP-gated ion channel, is known to play pivotal roles in the progression of Alzheimer’s disease (AD), although its cell type-specific pathological mechanisms have yet to be elucidated. Here, we show that genetic deletion of P2rx7 mitigates brain atrophy, tau accumulation and cognitive impairment in PS19 tauopathy mice. Specific deletion of P2rx7 in microglia, but not astrocytes, significantly suppresses tau propagation from the entorhinal cortex to CA1 in the hippocampus, an early event in AD pathology. Single-cell (sc)-RNA sequencing of mouse brains revealed specific P2rx7 expression in microglia, inducing inflammatory changes accompanied by elevated extracellular vesicles (EVs) secretion in PS19 mice. Brain-derived EVs (BDEVs) proteome demonstrated that P2RX7 increases EV cargo loading of tau and mitochondrial molecules in BDEVs from PS19 mice, which was further validated by single-molecule super-resolution. Notably, following the injection of BDEVs isolated from PS19 mice with or without P2rx7 deficiency, the microglial transcriptome of recipient mice revealed enriched DNA-sensing and type II interferon signaling in response to BDEVs from PS19 mice, which was diminished in the group injected with P2rx7-deficient BDEVs. Thus, our results indicate that P2RX7 regulates EV-mediated tau and mitochondrial transfer and inflammatory activation in microglia with increased EV secretion, thereby contributing to tauopathy and neurodegeneration, highlighting the therapeutic potential of targeting the P2RX7-EV axis in AD.

AbstractThe characterization of single extracellular vesicle (EV) has been an emerging tool for the early detection of various diseases despite there being challenges regarding how to interpret data with different protocols or instruments. In this work, standard EV particles were characterized for single CD9+, single CD81+ or double CD9+/CD81+ tetraspanin molecule positivity with two single EV analytic technologies in order to optimize their EV sample preparation after antibody labelling and analysis methods: NanoImager for direct stochastic optical reconstruction microscopy (dSTORM)‐based EV imaging and characterization, and Flow NanoAnalyzer for flow‐based EV quantification and characterization. False positives from antibody aggregates were found during dSTORM‐based NanoImager imaging. Analysis of particle radius with lognormal fittings of probability density histogram enabled the removal of antibody aggregates and corrected EV quantification. Furthermore, different machine learning models were trained to differentiate antibody aggregates from EV particles and correct EV quantification with increased double CD9+/CD81+ population. With Flow NanoAnalyzer, EV samples were prepared with different dilution or fractionation methods, which increased the detection rate of CD9+/CD81+ EV population. Comparing the EV phenotype percentages measured by two instruments, differences in double positive and single positive particles existed after percentage correction, which might be due to the different detection limit of each instrument. Our study reveals that the characterization of individual EVs for tetraspanin positivity varies between two platforms—the NanoImager and the Flow NanoAnalyzer—depending on the EV sample preparation methods used after antibody labelling. Additionally, we applied machine learning models to correct for false positive particles identified in imaging‐based results by fitting size distribution data.