Zhang, Zhengrong

Abstract Brain-derived extracellular vesicles (BDEVs) carry tau filaments and promote tau transmission in Alzheimer’s disease (AD). However, how APOE ε4 allele, a key genetic risk factor for AD, may change BDEV molecular structures thereby facilitate disease progression is poorly understood. Here we report comprehensive analyses of BDEVs isolated from human E3/3 and E4/4 AD brains with a biological multi-omics approach. E4/4 BDEVs significantly enhanced tau propagation in aged human MAPT (Tau) knock-in and APPNL-G-F: Tau double knock-in mouse brains in vivo and increased neuronal uptake and excitability in induced pluripotent stem cell-derived neurons (iNeurons) compared to E3/3 BDEVs in vitro. Notably, correlation analysis of BDEV-lipidome and proteome exhibited synergistic enrichment in unsaturated free fatty acid (FFA)18:2, a precursor of inflammatory w6 FFA, and neural cell adhesion molecule 1 (NCAM1). Treatment of iNeurons with FFA 18:2 induces NCAM1 expression, recruits tau into EVs and enhance their tau seeding activity, which is blocked by NCAM1 antibody in vitro . Finally, intracerebroventricular injection of NCAM1 antibody significantly alleviated pathological tau accumulation and glial inflammation in PS19 tauopathy mouse brains, which had previously been reported to exhibit increased level of 18:2 FFA. This highlights novel pathological mechanism in tau transfer mediated by E4/4 BDEVs and emphasizes strong therapeutic potential of targeting EV molecules in AD progression.

AbstractBackgroundNeuron‐derived extracellular vesicles (NDEVs) are a valuable resource for understanding brain conditions and discovering neurodegenerative diseases biomarkers, notably Alzheimer’s disease (AD). Recent interest focuses on capturing neuron‐specific EVs from patient‐derived samples, characterizing their contents as a pathological reflection of the central nervous system (CNS). Our recent study identified ATPase Na+/K+ Transporting Subunit Alpha 3 (ATP1A3) as a prevalent neuron‐specific EV marker specifically expressed in brains. This study systematically analyzes neuronal EVs to assess the specificity of ATP1A3 to NDEVs and its potential as a target for NDEV pulldown from accessible biofluids for disease monitoring. Additionally, ATP1A3 is compared with other proposed NDEV markers.MethodWe applied immunoelectron microscopy to detect ATP1A3, L1 cell adhesion molecule (L1CAM) and neural cell adhesion molecule 1 (NCAM1) in EVs isolated from iPSC‐derived excitatory neurons, brain tissue, cerebrospinal fluid (CSF) and plasma. Neuronal EV enrichment was achieved through immunoaffinity isolation, utilizing anti‐ATP1A3, L1CAM and NCAM1 antibodies separately. Evaluation involved quantitative mass‐spectrometry, immunoblotting and ELISA. To compare the enrichment of neuronal markers, EVs isolated from CSF and plasma samples were analyzed using ExoView and Nanoimager. Additionally, we investigated the potential of ATP1A3+ plasma EVs as AD biomarker by comparing the value of amyloid‐beta peptide (Aβ) in ATP1A3+ plasma EVs measured by Nanoimager and other plasma AD biomarkers as determined by SIMOA.ResultATP1A3, identified as a neuron‐specific protein, exhibits substantial enrichment in NDEVs isolated from induced human neurons, brain tissue, CSF, and plasma samples, surpassing NCAM1 or L1CAM. Both single‐ and bulk‐EV analysis consistently demonstrate a higher enrichment of ATP1A3 associated EVs in human samples. Immunoprecipitation of ATP1A3+ EVs from human brain tissues reveals superior neuronal cell‐type specificity over NCAM1+ and L1CAM+ EVs by label‐free mass spectrometry. Increased Aβ levels are observed in ATP1A3+ EVs derived from CSF and plasma of AD cases by SIMOA. Moreover, Aβ+ populations in ATP1A3+ EVs from plasma can distinguish AD from mild cognitive impairment and control cases via Nanoimager compared to the conventional quantification of AD markers.ConclusionOur findings demonstrate that ATP1A3 as a promising target for isolating NDEVs from biofluids, offering potential diagnostic advancements in neurological research.

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.

Neuron-derived extracellular vesicles (NDEVs) are potential biomarkers of neurological diseases although their reliable molecular target is not well established. Here, we demonstrate that ATPase Na + /K + transporting subunit alpha 3 (ATP1A3) is abundantly expressed in extracellular vesicles (EVs) isolated from induced human neuron, brain, cerebrospinal fluid, and plasma in comparison with the presumed NDEV markers NCAM1 and L1CAM by using super-resolution microscopy and biochemical assessments. Proteomic analysis of immunoprecipitated ATP1A3 + brain-derived EVs shows higher enrichment of synaptic markers and cargo proteins relevant to Alzheimer’s disease (AD) compared to NCAM1 + or LICAM + EVs. Single particle analysis shows the elevated amyloid-β positivity in ATP1A3 + EVs from AD plasma, providing better diagnostic prediction of AD over other plasma biomarkers. Thus, ATP1A3 is a reliable target to isolate NDEV from biofluids for diagnostic research.

Abstract Extracellular vesicles (EVs) have emerged as critical mediators of intercellular communication and promising biomarkers and therapeutics in the central nervous system (CNS). Human brain‐derived EVs (BDEVs) provide a comprehensive snapshot of physiological changes in the brain's environment, however, the isolation of BDEVs and the comparison of different methods for this purpose have not been fully investigated. In this study, we compared the yield, morphology, subtypes and protein cargo composition of EVs isolated from the temporal cortex of aged human brains using three established separation methods: size‐exclusion chromatography (SEC), phosphatidylserine affinity capture (MagE) and sucrose gradient ultracentrifugation (SG‐UC). Our results showed that SG‐UC method provided the highest yield and collected larger EVs compared to SEC and MagE methods as assessed by transmission electron microscopy and nanoparticle tracking analysis (NTA). Quantitative tandem mass‐tag (TMT) mass spectrometry analysis of EV samples from three different isolation methods identified a total of 1158 proteins, with SG‐UC showing the best enrichment of common EV proteins with less contamination of non‐EV proteins. In addition, SG‐UC samples were enriched in proteins associated with ATP activity and CNS maintenance, and were abundant in neuronal and oligodendrocytic molecules. In contrast, MagE samples were more enriched in molecules related to lipoproteins, cell‐substrate junction and microglia, whereas SEC samples were highly enriched in molecules related to extracellular matrix, Alzheimer's disease and astrocytes. Finally, we validated the proteomic results by performing single‐particle analysis using the super‐resolution microscopy and flow cytometry. Overall, our findings demonstrate the differences in yield, size, enrichment of EV cargo molecules and single EV assay by different isolation methods, suggesting that the choice of isolation method will have significant impact on the downstream analysis and protein discovery.