Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation.

Autor: Sternisha SM; Beckman Coulter Life Sciences, Indianapolis, IN, USA. ssternisha@beckman.com., Wilson AD; Beckman Coulter Life Sciences, Indianapolis, IN, USA., Bouda E; Beckman Coulter Life Sciences, Indianapolis, IN, USA., Bhattacharya A; Beckman Coulter Life Sciences, Indianapolis, IN, USA., VerHeul R; Beckman Coulter Life Sciences, Indianapolis, IN, USA.
Jazyk: angličtina
Zdroj: European biophysics journal : EBJ [Eur Biophys J] 2023 Jul; Vol. 52 (4-5), pp. 387-392. Date of Electronic Publication: 2023 May 02.
DOI: 10.1007/s00249-023-01654-z
Abstrakt: Viral vector-based gene therapies and vaccines require accurate characterization of capsid species. The current gold standard for assessing capsid loading of adeno-associated virus (AAV) is sedimentation velocity analytical ultracentrifugation (SV-AUC). However, routine SV-AUC analysis is often size-limited, especially without the use of advanced techniques (e.g., gravitational-sweep) or when acquiring the multiwavelength data needed for assessing the loading fraction of viral vectors, and requires analysis by specialized software packages. Density gradient equilibrium AUC (DGE-AUC) is a highly simplified analytical method that provides high-resolution separation of biologics of different densities (e.g., empty and full viral capsids). The analysis required is significantly simpler than SV-AUC, and larger viral particles such as adenovirus (AdV) are amenable to characterization by DGE-AUC using cesium chloride gradients. This method provides high-resolution data with significantly less sample (estimated 56-fold improvement in sensitivity compared to SV-AUC). Multiwavelength analysis can also be used without compromising data quality. Finally, DGE-AUC is serotype-agnostic and amenable to intuitive interpretation and analysis (not requiring specialized AUC software). Here, we present suggestions for optimizing DGE-AUC methods and demonstrate a high-throughput AdV packaging analysis with the AUC, running as many as 21 samples in 80 min.
(© 2023. The Author(s).)
Databáze: MEDLINE
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