Mechanisms of Adeno-Associated Virus Serotype 9 Vector Characterization and Quality Control through Solid-State Nanopores
Year: 2025
Type: article
Abstract: Adeno-associated virus (AAV) vectors are excellent gene-delivery carriers in gene therapy; however, improperly packaged capsids produced during manufacturing can reduce potency and raise safety concerns. We introduce a machine-learning-assisted, low-cost, label-free nanopore sensing platform with single-particle resolution to enhance AAV quality control. Using solid-state nanopore (SSN) devices on Si x N y membranes, we optimized in vitro conditions for AAV9 detection and classification. We observed pH-dependent capsid denaturation under strong alkaline conditions. Buffer-specific, selective translocation of emptyAAV9 capsids from cargo-loaded samples enabled clear discrimination and revealed potential avenues for in situ filtration. We also observed distinct translocation behaviors between vectors encapsulating single-stranded DNA and those encapsulating self-complementary DNA. In addition, unsupervised clustering algorithms demonstrated high accuracy in distinguishing capsids with truncated genomes from those with full genomes, further facilitating AAV production quality. These findings support practical avenues for AAV filtration and analysis, providing a basis for label-free, high-throughput, precise, and scalable quality control in AAV vector manufacturing.
Source: ACS Nano
Authors: Navod Thyashan, Janeesha Manawasinghe, Chaoming Gu, Santosh Khatri, Christopher Nelson, Merve Emecen Sanli, Steven J. Gray, Sangyoup Lee, Prashanta Dutta, George Alexandrakis, Min Jun Kim
Institutions: Southern Methodist University, Oak Ridge National Laboratory, Center for Nanophase Materials Sciences, Istanbul University, The University of Texas Southwestern Medical Center, Korean Association Of Science and Technology Studies, Korea Institute of Science and Technology, Washington State University, The University of Texas at Arlington
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4417247625
