scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution.

ABSTRACT

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. Funding: This work was supported by funding from the Ford Foundation, NEI/NIH, Research to Prevent Blindness, Foundation Fighting Blindness, UPMC Immune Transplant and Therapy Center, and the Van Sloun fund for canine genetic research.

Gene therapy is an experimental approach to treating disease that involves altering faulty genes or replacing them with new, working copies. Most often, the new genetic material is delivered into cells using a modified virus that no longer causes disease, called a viral vector. Virus-mediated gene therapies are currently being explored for degenerative eye diseases, such as retinitis pigmentosa, and neurological disorders, like Alzheimer's and Parkinson's disease. A number of gene therapies have also been approved for treating some rare cancers, blood disorders and a childhood form of motor neuron disease. Despite the promise of virus-mediated gene therapy, there are significant hurdles to its widespread success. Viral vectors need to deliver enough genetic material to the right cells without triggering an immune response or causing serious side effects. Selecting an optimal vector is key to achieving this. A type of viruses called adeno-associated viruses (AAV) are prime candidates, partly because they can be easily engineered. However, accurately comparing the safety and efficacy of newly engineered AAVs is difficult, due to variation between test subjects and the labor and cost involved in careful testing. Öztürk et al. addressed this issue by developing an experimental pipeline called scAAVengr for comparing gene therapy vectors head-to-head. The process involves tagging potential AAV vectors with unique genetic barcodes, which can then be detected and quantified in individual cells using a technique called single-cell RNA sequencing. This means that when several vectors are used to infect lab-grown cells or a test animal at the same time, they can be tracked. The vectors can then be ranked on their ability to infect specific cell types and deliver useful genetic material. Using scAAVengr, Öztürk et al. compared viral vectors designed to target the light-sensitive cells of the retina, which allow animals to see. First, a set of promising viral vectors were evaluated using the scAAVengr pipeline in the eyes of marmosets and macaques, two small primates. Precise levels and locations of gene delivery were quantified. The top-performing vector was then identified and used to deliver Cas9, a genome editing tool, to primate retinas. Öztürk et al. also used scAAVengr to compare viral vectors in mice, analysing the vectors' ability to deliver their genetic cargo to the brain, heart, and liver. These experiments demonstrated that scAAVengr can be used to evaluate vectors in multiple tissues and in different organisms. In summary, this work outlines a method for identifying and precisely quantifying the performance of top-performing viral vectors for gene therapy. By aiding the selection of optimal viral vectors, the scAAVengr pipeline could help to improve the success of preclinical studies and early clinical trials testing gene therapies.