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Bimodal optical-electrical data generated when a 20 nm diameter silica (SiO2) nanoparticle was trapped by a plasmonic nanopore sensor were simulated using Multiphysics COMSOL and compared with sensor measurements for closely matching experimental parameters. The nanosensor, employed self-induced back action (SIBA) to optically trap nanoparticles in the center of a double nanohole (DNH) structure on top a solid-state nanopores (ssNP). This SIBA actuated nanopore electrophoresis (SANE) sensor enables simultaneous capture of optical and electrical data generated by several underlying forces acting on the trapped SiO2 nanoparticle: plasmonic optical trapping, electroosmosis, electrophoresis, viscous drag, and heat conduction forces. The Multiphysics simulations enabled dissecting the relative contributions of those forces acting on the nanoparticle as a function of its location above and through the sensor’s ssNP. Comparisons between simulations and experiments demonstrated qualitative similarities in the optical and electrical time-series data generated as the nanoparticle entered and exited from the SANE sensor. These experimental parameter-matched simulations indicated that the competition between optical and electrical forces shifted the trapping equilibrium position close to the top opening of the ssNP, relative to the optical trapping force maximum that was located several nm above. The experimentally estimated minimum for the optical force needed to trap a SiO2 nanoparticle was consistent with corresponding simulation predictions of optical-electrical force balance. The comparison of Multiphysics simulations with experiments improves our understanding of the interplay between optical and electrical forces as a function of nanoparticle position across this plasmonic nanopore sensor.
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This content will become publicly available on December 1, 2026
Plasmonic Nanopore Sensing to Probe the DNA Loading Status of Adeno-Associated Viruses
Adeno-associated viruses (AAVs) are a leading vector for gene therapy, yet their clinical utility is limited by the lack of robust quality control methods to distinguish between empty (AAVempty), partially loaded (AAVpartial), and fully DNA loaded (AAVfull) capsids. Current analytical techniques provide partial insights but remain limited in sensitivity, throughput, or resolution. Here we present a multimodal plasmonic nanopore sensor that integrates optical trapping with electrical resistive-pulse sensing to characterize AAV9 capsids at the single-particle level in tens of μL sample volumes and fM range concentrations. As a model system, we employed AAV9 capsids not loaded with DNA, capsids loaded with a self-complementary 4.7 kbp DNA (AAVscDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAVssDNA). Ground-truth validation was performed with analytical ultracentrifugation (AUC). Nanosensor data were acquired concurrently for optical step changes (occurring at AAV trapping and un-trapping) both in transmittance and reflectance geometries, and electrical nanopore resistive pulse signatures, making for a total of five data dimensions. The acquired data was then filtered and clustered by Gaussian mixture models (GMMs), accompanied by spectral clustering stability analysis, to successfully separate between AAV species based on their DNA load status (AAVempty, AAVpartial, AAVfull) and DNA load type (AAVscDNA versus AAVssDNA). The motivation for quantifying the AAVempty and AAVpartial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAVscDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAVscDNA and AAVssDNA despite their identical masses. In contrast, AUC could not differentiate between AAVscDNA and AAVssDNA. An equimolar mixture of AAVscDNA, AAVssDNA and AAVempty was also measured with the sensor, and the results showed the expected population fractions, supporting the capacity of the method to differentiate AAV load status in heterogeneous solutions. In addition, less common optical and electrical signal signatures were identified in the acquired data, which were attributed to debris, rapid entry re-entry to the optical trap, or weak optical trap exits, representing critical artifacts to recognize for correct interpretation of the data. Together, these findings establish plasmonic nanopore sensing as a promising platform for quantifying AAV DNA loading status and genome type with the potential to extend ultra-sensitive single-particle characterization beyond the capabilities of existing methods.
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- Award ID(s):
- 2415309
- PAR ID:
- 10651837
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Chemosensors
- Volume:
- 13
- Issue:
- 12
- ISSN:
- 2227-9040
- Page Range / eLocation ID:
- 418
- Subject(s) / Keyword(s):
- plasmonic nanopore adeno-associated virus single-particle sensing GFP optical–electrical detection AAVs gene therapy quality control
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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