Skip to content
#protein folding Open access

A Novel Reporter Mouse for Astrocyte-Derived Extracellular Vesicles Reveals Enrichment of Cargo at Neuronal Mitochondria.

Sep 2026 · The FASEB Journal · Vol 40 18, pp. e72260 · 0 citations · 71 references
Medicine

Abstract

Extracellular vesicles (EVs) mediate intercellular transfer of lipids, proteins, and nucleic acids between cell types. We previously showed that astrocyte-derived EVs modulate neuronal mitochondria in vitro. Whether endogenous astrocytic EVs associate with neuronal mitochondria in vivo remained unknown. To address this, we generated an EV reporter mouse, Aldh1l1-Cre; CD9-tGFPfl/fl, which resulted in fluorescent labeling of astrocyte-derived CD9-positive EVs. Astrocyte-specific expression of CD9-tGFP was verified in brain tissue, where CD9-tGFP-positive particles comprised 13.2% ± 1.6% of total isolated EVs. In primary glial cultures, CD9-tGFP was restricted to astrocytes, localizing to vesicular compartments and cell protrusions (filopodia and cilia); 89.3% ± 2.2% of astrocyte-derived EVs were CD9-tGFP positive. In cortex, hippocampus, and cerebellum, CD9-tGFP was predominantly detected in astrocytic processes co-labeled with glutamate aspartate transporter 1 (GLAST1) and glial fibrillary acidic protein (GFAP), forming contacts with laminin-positive capillaries and parvalbumin-positive neurons. CD9-tGFP-labeled EVs were detected at capillaries and inside neurons, and STED microscopy revealed partial co-localization with neuronal mitochondria. Live-cell spinning disk confocal imaging and AI-assisted proximity analysis confirmed uptake of CD9-tGFP EVs by neuronal cells and cargo enrichment at mitochondria in vitro. Immunoblotting and imaging of isolated mitochondria established physical association with EV-derived CD9-tGFP in vivo, with 3-fold higher CD9-tGFP puncta density on synaptic mitochondria. Together, these findings validate the Aldh1l1-Cre; CD9-tGFPfl/fl reporter mouse as a tool for tracking astrocyte-derived EVs in vivo and provide evidence of preferential cargo enrichment at synaptic mitochondria.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.