An optimized protocol for quality control of gene therapy vectors using nanopore direct RNA sequencing.


Journal

Genome research
ISSN: 1549-5469
Titre abrégé: Genome Res
Pays: United States
ID NLM: 9518021

Informations de publication

Date de publication:
28 Oct 2024
Historique:
received: 25 03 2024
accepted: 27 09 2024
medline: 29 10 2024
pubmed: 29 10 2024
entrez: 28 10 2024
Statut: aheadofprint

Résumé

Despite recent advances made toward improving the efficacy of lentiviral gene therapies, a sizeable proportion of produced vector contains an incomplete and thus potentially nonfunctional RNA genome. This can undermine gene delivery by the lentivirus as well as increase manufacturing costs and must be improved to facilitate the widespread clinical implementation of lentiviral gene therapies. Here, we compare three long-read sequencing technologies for their ability to detect issues in vector design and determine nanopore direct RNA sequencing to be the most powerful. We show how this approach identifies and quantifies incomplete RNA caused by cryptic splicing and polyadenylation sites, including a potential cryptic polyadenylation site in the widely used Woodchuck Hepatitis Virus Posttranscriptional Regulatory Element (WPRE). Using artificial polyadenylation of the lentiviral RNA, we also identify multiple hairpin-associated truncations in the analyzed lentiviral vectors (LVs), which account for most of the detected RNA fragments. Finally, we show that these insights can be used for the optimization of LV design. In summary, nanopore direct RNA sequencing is a powerful tool for the quality control and optimization of LVs, which may help to improve lentivirus manufacturing and thus the development of higher quality lentiviral gene therapies.

Identifiants

pubmed: 39467647
pii: gr.279405.124
doi: 10.1101/gr.279405.124
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 Zeglinski et al.; Published by Cold Spring Harbor Laboratory Press.

Auteurs

Kathleen Zeglinski (K)

Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia; zeglinski.k@wehi.edu.au.

Christian Montellese (C)

CSL Behring, Research, CH-3014 Bern, Switzerland.
Swiss Institute for Translational Medicine, sitem-insel, 3010 Bern, Switzerland.

Matthew E Ritchie (ME)

Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.

Monther Alhamdoosh (M)

Research Data Science Group, R&D, CSL, Parkville, Victoria 3000, Australia.

Cédric Vonarburg (C)

CSL Behring, Research, CH-3014 Bern, Switzerland.
Swiss Institute for Translational Medicine, sitem-insel, 3010 Bern, Switzerland.

Rory Bowden (R)

Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.

Monika Jordi (M)

CSL Behring, Research, CH-3014 Bern, Switzerland.

Quentin Gouil (Q)

Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.

Florian Aeschimann (F)

CSL Behring, Research, CH-3014 Bern, Switzerland.
Swiss Institute for Translational Medicine, sitem-insel, 3010 Bern, Switzerland.

Arthur Hsu (A)

Research Data Science Group, R&D, CSL, Parkville, Victoria 3000, Australia.

Classifications MeSH