Digital Droplet PCR Method for the Quantification of AAV Transduction Efficiency in Murine Retina.


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
25 12 2021
Historique:
entrez: 10 1 2022
pubmed: 11 1 2022
medline: 6 4 2022
Statut: epublish

Résumé

Many retinal cell biology laboratories now routinely use Adeno-associated viruses (AAVs) for gene editing and regulatory applications. The efficiency of AAV transduction is usually critical, which affects the overall experimental outcomes. One of the main determinants for transduction efficiency is the serotype or variant of the AAV vector. Currently, various artificial AAV serotypes and variants are available with different affinities to host cell surface receptors. For retinal gene therapy, this results in varying degrees of transduction efficiencies for different retinal cell types. In addition, the injection route and the quality of AAV production may also affect the retinal AAV transduction efficiencies. Therefore, it is essential to compare the efficiency of different variants, batches, and methodologies. The digital droplet PCR (dd-PCR) method quantifies the nucleic acids with high precision and allows performing absolute quantification of a given target without any standard or a reference. Using dd-PCR, it is also feasible to assess the transduction efficiencies of AAVs by absolute quantification of AAV genome copy numbers within an injected retina. Here, we provide a straightforward method to quantify the transduction rate of AAVs in retinal cells using dd-PCR. With minor modifications, this methodology can also be the basis for the copy number quantification of mitochondrial DNA as well as assessing the efficiency of base editing, critical for several retinal diseases and gene therapy applications.

Identifiants

pubmed: 35001911
doi: 10.3791/63038
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Video-Audio Media

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Iskalen Cansu Topcu Okan (ICT)

Molecular Biology, Genetics and Bioengineering Program, Sabanci University; Nanotechnology Research and Application Center (SUNUM), Sabanci University.

Mehri Ahmadian (M)

Molecular Biology, Genetics and Bioengineering Program, Sabanci University; Nanotechnology Research and Application Center (SUNUM), Sabanci University.

Yesim Tutuncu (Y)

Molecular Biology, Genetics and Bioengineering Program, Sabanci University; Nanotechnology Research and Application Center (SUNUM), Sabanci University.

Halit Yusuf Altay (HY)

Molecular Biology, Genetics and Bioengineering Program, Sabanci University; Nanotechnology Research and Application Center (SUNUM), Sabanci University.

Cavit Agca (C)

Molecular Biology, Genetics and Bioengineering Program, Sabanci University; Nanotechnology Research and Application Center (SUNUM), Sabanci University; cavit.agca@sabanciuniv.edu.

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Classifications MeSH