Plasmon-Enhanced\nFluorescence of Single Extracellular\nVesicles Captured in Arrayed Aluminum Nanoholes
Extracellular vesicles (EVs) are nanoparticles encapsulated\nwith\na lipid bilayer, and they constitute an excellent source of biomarkers\nfor multiple diseases. However, the heterogeneity in their molecular\ncompositions constitutes a major challenge for their recognition and\nprofiling, thereby limiting their application as an effective biomarker.\nA single-EV analysis technique is crucial to both the discovery and\nthe detection of EV subpopulations that carry disease-specific signatures.\nHerein, a plasmonic nanohole array is designed for capturing single\nEVs and subsequently performing fluorescence detection of their membrane\nproteins by exploiting plasmonic amplification of the fluorescence\nsignal. Unlike other reported methods, our design relies on an exclusive\ndetection of single EVs captured inside nanoholes, thus allowing us\nto study only plasmonic effects and avoid other metal-induced phenomena\nwhile leveraging on the proximity of emitters to the plasmonic hotspots.\nThe method is optimized through numerical simulations and verified\nby a combination of atomic force, scanning electron microscopy, and\nfluorescence microscopy. Fluorescence enhancement is then estimated\nby measuring the CD9 expression of small EVs derived from the human\nembryonic kidney (HEK293) cell line and carefully considering the\nspatial distribution of emission and excitation intensities. Fluorescence\nintensities of immunostained EVs show a moderate overall enhancement\nof intensity and follow the intensity trend predicted by simulation\nfor nanohole arrays with different nanohole periods. Moreover, the\nnumber of observed EVs in the best-performing nanohole array increases\nby more than 12 times compared with EVs immobilized on a reference\nsubstrate, uncovering a vast amount of weakly fluorescent EVs that\nwould remain undetected with the regular fluorescent method. Our nanohole\narray provides a basis for a future platform of single-EV analyses,\nalso promising to capture the signature arising from low-expressing\nproteins.
Publication Details
- Journal
- Figshare
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1021/acsomega.4c05492.s001
- Primary Topic
- Educational Robotics and Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00