Scott Renkes

Cytochrome c oxidase (CCO) is widely regarded as the primary photoacceptor underlying photobiomodulation (PBM), in which light absorption stimulates mitochondrial respiration by promoting electron transfer through CCO. Single-molecule plasmonic nanopore measurements were used to examine cytochrome c (CC)–CCO interactions across three excitation wavelengths spanning the near-infrared range, which is preferred for PBM studies in vivo due to increased tissue penetration. Wavelength-dependent measurements of CC–CCO interactions were performed under normoxic, hypoxic, and allosterically inhibited conditions, revealing distinct interaction populations that are obscured in ensemble measurements. CC–CCO interactions were resolved into short-duration, long-duration, and heterogeneous populations for all wavelengths and oxygenation conditions. The short-duration population was selectively and substantially depleted by both hypoxia and ADDA5-mediated allosteric inhibition, supporting its assignment as a distinct, putative electron-transfer-associated interaction state. Allosteric inhibition strongly favored the long-duration population, whereas hypoxia predominantly increased heterogeneous duration interactions, consistent with non-specific binding. Under normoxia, 820 nm and 905 nm produced statistically comparable population fractions of the putative electron-transfer-active population, whereas the corresponding population fraction at 1064 nm was significantly lower but remained substantial. The short-duration binding population kinetics remained largely unchanged across wavelength and oxygenation states, indicating that these conditions primarily altered access to the CCO binding site rather than affecting its binding lifetime. These findings reveal the previously unresolved heterogeneity in CC–CCO interactions and provide a single-molecule framework for understanding how the excitation wavelength and oxygenation state may influence molecular interactions relevant to PBM efficiency.

Reliable quality control of adeno-associated virus (AAV) vectors remains a major bottleneck in gene therapy manufacturing, particularly for resolving subtle differences in genome loading and conformation at the single-particle level. Existing approaches often struggle to distinguish AAV populations with similar mass and charge, such as capsids carrying self-complementary versus single-stranded DNA. Here, we introduce an AC plasmonic nanopore sensing framework for AAV9 characterization. Individual AAV capsids were optically trapped within a plasmonic double-nanohole nanopore and interrogated using multi-frequency AC pulse trains spanning 500 Hz to 100 kHz. To enhance sensitivity to localized particle–field interactions, a nanofabricated Ag/AgCl ring electrode was integrated concentrically with the plasmonic nanopore. Relative to a conventional wire electrode, the ring electrode produced broader and more robust analyte-dependent differences across multiple frequency-dependent parameters, enabling reliable discrimination of empty capsids (AAV_empty) and genome-loaded capsids carrying either self-complementary (AAV_scDNA) or single-stranded DNA (AAV_ssDNA), despite their near-identical genome mass. Concentration titration experiments further demonstrated that the extracted multivariate AC features remained largely concentration-independent over the tested range. Together, these results demonstrate that ring-electrode-enabled AC plasmonic nanopore sensing provides a multidimensional framework for resolving closely related AAV populations and advances plasmonic nanopores toward practical single-particle quality control of gene therapy vectors.

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 (AAV_empty), partially loaded (AAV_partial), and fully DNA loaded (AAV_full) 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 (AAV_scDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAV_ssDNA). 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 (AAV_empty, AAV_partial, AAV_full) and DNA load type (AAV_scDNA versus AAV_ssDNA). The motivation for quantifying the AAV_empty and AAV_partial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAV_scDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAV_scDNA and AAV_ssDNA despite their identical masses. In contrast, AUC could not differentiate between AAV_scDNA and AAV_ssDNA. An equimolar mixture of AAV_scDNA, AAV_ssDNA and AAV_empty 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.

Active targeting nanoparticles are a new generation of drug and gene delivery systems with the potential for greatly improved therapeutics delivery compared to conventional nanomedicine approaches. Despite their potential, the translation of active targeting nanoparticles faces challenges in production scale-up and batch consistency. Accurate quality control methods for nanoparticle therapeutic payload and coating characterization are critical for attaining the desired levels of batch repeatability, drug/gene loading efficiency, targeting molecule coating effectiveness, and safety profiles. Current limitations in nanoparticle characterization technologies, such as relying on ensemble-average analysis, pose challenges in assessing the drug/gene content and surface modification heterogeneity, which can greatly affect therapeutic outcomes. Single-molecule analysis technologies have emerged as a promising alternative, offering rich information on heterogeneity and stochastic variations between nanoparticle batches. This review first evaluates and identifies the challenges of traditional nanoparticle characterization tools that rely on indirect, bulk solution quantification methods. Subsequently, newly emerging characterization technologies are introduced for the quantification of therapeutic loading and targeted moiety coating efficiencies with single-nanoparticle resolution, to help guide researchers towards advancing the translation of active targeting nanoparticles into the clinical setting.

The use of plasmonic nanopores for single molecule detection has attracted considerable attention due to their high sensitivity and selectivity. In this study, we present a phase analysis approach for characterizing the trapping of single molecules in an AC-driven plasmonic nanopore. By analyzing the phase response of the plasmonic nanopore at select frequencies, we can differentiate between a test ligand, the antibody targeting this ligand, and the complexes that these ligands form, as well as observe their dynamics while inside the optical trap of the plasmonic nanopore. This pilot work shows the feasibility of a new approach for rapid and accurate identification of single molecules in complex mixtures.