Author: Bilge E Öztürk, Molly E Johnson, Michael Kleyman, Serhan Turunç, Jing He, Sara Jabalameli, Zhouhuan Xi, Meike Visel, Valérie L Dufour, Simone Iwabe, Felipe Pompeo Marinho, Gustavo D Aguirre, José-Alain Sahel, David V Schaffer, Andreas R Pfenning, John G Flannery, William A Beltran, William R Stauffer, Leah C Byrne
Title: scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution
Summary: Background: Adeno-associated virus (AAV)-mediated gene therapies are rapidly advancing to the clinic, and AAV engineering has resulted in vectors with increased ability to deliver therapeutic genes. Although the choice of vector is critical, quantitative comparison of AAVs, especially in large animals, remains challenging.
Methods: Here, we developed an efficient single-cell AAV engineering pipeline (scAAVengr) to simultaneously quantify and rank efficiency of competing AAV vectors across all cell types in the same animal.
Results: To demonstrate proof-of-concept for the scAAVengr workflow, we quantified – with cell-type resolution – the abilities of naturally occurring and newly engineered AAVs to mediate gene expression in primate retina following intravitreal injection. A top performing variant identified using this pipeline, K912, was used to deliver SaCas9 and edit the rhodopsin gene in macaque retina, resulting in editing efficiency similar to infection rates detected by the scAAVengr workflow. scAAVengr was then used to identify top-performing AAV variants in mouse brain, heart and liver following systemic injection.
Conclusions: These results validate scAAVengr as a powerful method for development of AAV vectors.
Source: eLife 2021;10:e64175 DOI: 10.7554/eLife.64175
