Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Sternisha, Shawn M., Wilson, Abraham D., Bouda, Emilie, Bhattacharya, Akash, VerHeul, Ross
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444642/
https://www.ncbi.nlm.nih.gov/pubmed/37130969
http://dx.doi.org/10.1007/s00249-023-01654-z
_version_ 1785093993575481344
author Sternisha, Shawn M.
Wilson, Abraham D.
Bouda, Emilie
Bhattacharya, Akash
VerHeul, Ross
author_facet Sternisha, Shawn M.
Wilson, Abraham D.
Bouda, Emilie
Bhattacharya, Akash
VerHeul, Ross
author_sort Sternisha, Shawn M.
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00249-023-01654-z.
format Online
Article
Text
id pubmed-10444642
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-104446422023-08-24 Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation Sternisha, Shawn M. Wilson, Abraham D. Bouda, Emilie Bhattacharya, Akash VerHeul, Ross Eur Biophys J Original Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00249-023-01654-z. Springer International Publishing 2023-05-02 2023 /pmc/articles/PMC10444642/ /pubmed/37130969 http://dx.doi.org/10.1007/s00249-023-01654-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Sternisha, Shawn M.
Wilson, Abraham D.
Bouda, Emilie
Bhattacharya, Akash
VerHeul, Ross
Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
title Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
title_full Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
title_fullStr Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
title_full_unstemmed Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
title_short Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
title_sort optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444642/
https://www.ncbi.nlm.nih.gov/pubmed/37130969
http://dx.doi.org/10.1007/s00249-023-01654-z
work_keys_str_mv AT sternishashawnm optimizinghighthroughputviralvectorcharacterizationwithdensitygradientequilibriumanalyticalultracentrifugation
AT wilsonabrahamd optimizinghighthroughputviralvectorcharacterizationwithdensitygradientequilibriumanalyticalultracentrifugation
AT boudaemilie optimizinghighthroughputviralvectorcharacterizationwithdensitygradientequilibriumanalyticalultracentrifugation
AT bhattacharyaakash optimizinghighthroughputviralvectorcharacterizationwithdensitygradientequilibriumanalyticalultracentrifugation
AT verheulross optimizinghighthroughputviralvectorcharacterizationwithdensitygradientequilibriumanalyticalultracentrifugation