Okan, İskalen Cansu and Ahmadiangollajeh, Mehri and Tütüncü, Yeşim and Altay, Halit Yusuf and Ağca, Cavit (2021) Digital droplet PCR method for the quantification of AAV transduction efficiency in murine retina. Journal of visualized experiments : JoVE (178). ISSN 1940-087X
Full text not available from this repository. (Request a copy)
Official URL: https://dx.doi.org/10.3791/63038
Abstract
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.
Item Type: | Article |
---|---|
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Biological Sciences & Bio Eng. Faculty of Engineering and Natural Sciences Sabancı University Nanotechnology Research and Application Center |
Depositing User: | Cavit Ağca |
Date Deposited: | 25 Aug 2022 17:58 |
Last Modified: | 25 Aug 2022 17:58 |
URI: | https://research.sabanciuniv.edu/id/eprint/43978 |