Cyanobacteria-derived near-infrared autofluorescent exosomes enabling synergistic brain lesion imaging and neuroprotection
Abstract
Precision diagnosis and treatment of central nervous system (CNS) diseases are hindered by limited probe penetration, toxicity risks, and low imaging signal-to-noise ratio (SNR). The blood-brain barrier (BBB) further restricts drug delivery, especially in stroke therapy. This study proposes and validates a natural exosome (sExos) from cyanobacteria, featuring intrinsic near-infrared-I (NIR-I) autofluorescence, with strong imaging and neuroprotective functions. As a theranostic nanoplatform, sExos enable integrated diagnosis and treatment of stroke and other brain disorders. Enriched with the fluorescent phycobiliprotein ApcE, sExos support label-free, high-SNR brain imaging in the NIR-I window. In vivo , sExos cross the BBB and accumulate in ischemic lesions, enabling dynamic visualization. Mechanistically, sExos regulate lipid metabolism and inhibit NF-κB signaling, reducing oxidative stress and neuroinflammation, while promoting neural recovery. Toxicity and immunogenicity evaluations confirm excellent biocompatibility and safety. In summary, this naturally autofluorescent exosome offers a label-free, brain-penetrant, and therapeutically promising imaging-intervention strategy, opening avenues for noninvasive stroke therapy and precision CNS disease management. • A cyanobacteria-derived, naturally autofluorescent exosome is developed for BBB-penetrant CNS theranostics. • Intrinsic NIR-I autofluorescence enables label-free, high-SNR brain imaging in vivo. • The exosomes cross the BBB and selectively accumulate in ischemic brain lesions. • Neuroprotection is achieved via lipid metabolism regulation and NF-κB inhibition. • Favorable biocompatibility supports translational potential.
Fields of Study & Subjects
Extracellular vesicles in disease
Algal biology and biofuel production
Biocrusts and Microbial Ecology
Publication details
- Journal / source
- Bioactive Materials
- Publisher
- Elsevier BV
- Volume
- 63
- Pages
- 718–731
- Publication date
- 20 April 2026
- Language
- EN