Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation Article Swipe
Shawn M. Sternisha
,
Abraham D. Wilson
,
Emilie Bouda
,
Akash Bhattacharya
,
Ross VerHeul
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1007/s00249-023-01654-z
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1007/s00249-023-01654-z
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.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s00249-023-01654-z
- https://link.springer.com/content/pdf/10.1007/s00249-023-01654-z.pdf
- OA Status
- hybrid
- Cited By
- 11
- References
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1007/s00249-023-01654-zDigital Object Identifier
- Title
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Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-05-02Full publication date if available
- Authors
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Shawn M. Sternisha, Abraham D. Wilson, Emilie Bouda, Akash Bhattacharya, Ross VerHeulList of authors in order
- Landing page
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https://doi.org/10.1007/s00249-023-01654-zPublisher landing page
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https://link.springer.com/content/pdf/10.1007/s00249-023-01654-z.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s00249-023-01654-z.pdfDirect OA link when available
- Concepts
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Analytical Ultracentrifugation, Capsid, Characterization (materials science), Chromatography, Ultracentrifuge, Chemistry, Materials science, Virology, Nanotechnology, Biology, VirusTop concepts (fields/topics) attached by OpenAlex
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11Total citation count in OpenAlex
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2025: 6, 2024: 3, 2023: 2Per-year citation counts (last 5 years)
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14Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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