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.

Gene therapy is a rapidly developing approach for the treatment of inherited disease, and AAV is a leading viral vector candidate for safe and efficient delivery. A growing number of clinical trials are using AAV to treat diseases such as retinal degeneration, neurological disorders, and hemophilia, through gene replacement, genome editing, and optogenetics (High and Roncarolo, 2019; Sahel and Dalkara, 2019). And, with the recent FDA approval for treatment of Leber congenital amaurosis and spinal muscular atrophy, gene therapies are rapidly becoming a clinical reality. However, significant hurdles prevent the successful, widespread implementation of AAV-mediated gene therapies, including efficient gene delivery and immune response to viral vectors and gene products. Recent efforts to reengineer viral vectors have shown promise for addressing these issues, resulting in AAVs with improved abilities (Li and Samulski, 2020). The enhanced viral vectors produced by these high-throughput methods still require quantitative validation and comparison, however, currently a challenging and burdensome process.

The selection of an optimal vector is essential to the success of the therapy. Sufficient gene expression is critical, while enhanced tropism and greater efficiency of gene delivery reduces the titer of vector required and decreases the likelihood of immune response. Quantitative comparisons of newly engineered vectors, including evaluation of transgene expression levels and cell-type tropism, have in the past required large numbers of animals, and therefore involved significant ethical and financial burden. Additionally, in primates, the large variability between animals, due to differences in anatomy and immune responses, has made comparisons between animals inaccurate. Here, we have developed a single cell RNA-seq AAV engineering (scAAVengr) pipeline for rapid, quantitative in vivo comparison of transgene expression from newly engineered AAV capsid variants across all different cell types in a tissue in parallel, and in the same animals.

In this work, the scAAVengr pipeline was applied to primates, which are the most physiologically similar animal to humans, and are thus a critical preclinical model. Successful clinical translation of gene therapies depends on highly efficient vectors for human tissue, and vector performance in small animals often does not accurately predict efficiency in primates. For retinal gene therapy in particular, primates are essential, as existing AAV vectors infect the primate retina significantly less efficiently than in rodent retina (Dalkara et al., 2013). Furthermore, primates are the only animal model that has a macula and foveal pit (the region of the retina responsible for high acuity vision in humans), making them the most relevant translational model. Notably, the pattern of AAV expression also differs in foveal and in peripheral retina (Dalkara et al., 2013), with highest expression in the foveola and in a perifoveal ring of retinal ganglion cells, and punctate expression near blood vessels in the periphery. The scAAVengr single-cell RNA-Seq pipeline allowed us to quantitatively evaluate the clinical potential of multiple lead candidates across all retinal cell types, in the foveal and peripheral retina, in a large animal model with eyes similar to humans. The scAAVengr pipeline can be applied to any species or tissue for which marker genes can be identified, however, as demonstrated here through screening performed in mouse brain, heart, and liver following systemic injections of pooled AAV library.

Together these results validate the scAAVengr pipeline as a platform for simultaneous quantitative evaluation and ranking of new AAV serotypes with cell-type resolution. Quantitative comparisons of newly engineered vectors, including evaluation of transgene expression levels and cell-type tropism, have, in the past, required large numbers of animals. In primates, such studies have been impractical, due to the associated ethical and financial burden. Additionally, in primates, the large variability between animals has made comparisons between animals inaccurate, and evaluation of multiple AAVs in the same animal was not possible. In order to address these problems, we developed a single-cell RNA-seq AAV engineering (scAAVengr) pipeline for quantitative head-to-head in vivo comparison of transgene expression from newly engineered AAV capsid variants. By simultaneously quantifying cellular and viral RNA at the single-cell level, this method allows for efficient, direct, and head-to-head comparison of multiple vectors across all cell types in the same animals. Pan-tissue efficiency of transgene expression can be determined, as well as specificity for any cell-type of interest that can be identified by its transcriptome profile. The number and identity of unique AAV serotypes infecting a single cell can be observed, and the efficiency and specificity of a potential gene therapy can be accurately estimated.

Here, we have evaluated the AAV tropism of newly engineered AAV capsid variants, created in the context of dog retina, with increased ability to infect all major retinal cell types. These variants were directly compared to variants created through DE in primate eyes, as well as naturally occurring variants and tyrosine modified versions. The overall top-performing AAV, K912, was identified through screening performed in the context of the canine retina. Canines, which have an even thicker vitreous than primates, may represent a more difficult model, with a higher barrier for transduction, resulting in better performing viruses. Further work will need to be done to determine whether vectors from canine screens consistently out-perform variants screened in other animal models.

The overall rate of infection achieved by K912, around 2% of total retinal cells, suggests that significant improvements in AAV transduction must be achieved for maximal therapeutic benefit to be achieved via intravitreal injections. Additional improvements to AAV screening protocols or library construction may be required in order to find even better performing vectors. Here, the best performing variants were determined by using the cloned AAV DE library (plasmid used for packaging) as the denominator for evaluation. Additional work will be required to determine whether the packaged AAV DE library (Round 0) may be a better common denominator to follow DE enrichment. It remains to be seen whether barriers to retinal penetration by AAV vectors from intravitreal injection can be overcome by modification of the AAV capsid alone, or whether alternative methods for vector delivery are required. The scAAVengr pipeline may also be useful in determining absolute rates of infection and direct comparison with other routes of administration or methods for transgene expression.

The 17-member scAAVengr library of AAV variants was also analyzed in brain, heart and liver following systemic injection in neonatal mice. Variants including K912 and NHP9, which performed well in primate retina, did not infect mouse brain, liver and heart, which indicates that the mutations which confer increased ability to cross structural barriers in the retina are not sufficient for infection from systemic injection in neonatal mice. Further analysis could be performed, using the same dataset, to quantify infectivity in specific subtypes of retinal cell types, as subtype marker genes are validated. Additional work is required to determine the maximum number of pooled AAV variants that can be screened simultaneously, though our results indicate that libraries containing at least E + 5 variants can be evaluated from a single sample containing 8000 cells. Quantification revealed that multiple AAV serotypes do infect individual cells, suggesting that competition between variants does not inhibit infection. Analysis of in vitro infection of AAV variants in HEK293 cells also suggests that competition between variants infecting the same cells does not significantly affect the number of infected cells or the level of transgene expression in infected cells, validating infectivity data from pooled AAV variants. However, in vivo confirmation of this finding is warranted, as the barriers affecting the dynamics of infection may differ in a more complex environment, such as the retina.

Marmoset eyes, which are significantly smaller than human and macaque eyes, were more easily infected than cynomolgus macaques, with greater percentages of cells infected and more infection events per cell. Marmoset eyes may represent a less challenging target for AAV transduction than cynomolgus macaques due to more efficient diffusion of viral particles in smaller eyes, a less rigid vitreous consistency, or immunological factors. This suggests that large primates may be of more use for accurate prediction of performance of gene delivery efficiencies in humans, particularly in the retina, but potentially in other targets as well, such as infection of organs from systemic injections, where diffusion rates and structural barriers may differ between marmosets and macaques. The rate of Cas9 editing in macaques was similar to the total percent of cells infected by K912, indicating that editing was efficient in infected cells. Importantly, similar rates of infection and genome editing indicate that scRNA-seq can accurately estimate the efficiency of viral gene delivery.

Data from primate retina and mouse brain, heart, and liver validate that the scAAVengr workflow is applicable to any tissue for which cell type marker genes are available, and provides a rapid, quantitative method by which AAV vectors can be rapidly evaluated for their clinical potential. This method enables the definitive ranking of AAV’s, in terms of transgene expression efficiency, and in future studies will enable the identification of vectors with greater cell-type specificity. The quantitative nature and single-cell resolution provided by the scAAVengr pipeline therefore enables identification and development of optimal AAV vectors for clinical translation.

Data, including count matrix files, raw fastq files as well as AAV/cell barcode tables generated from read quantification, have been uploaded to GEO under accession code GSE161645.

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Author details

1. Bilge E Öztürk

   Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5117-077X

2. Molly E Johnson

   Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9575-3192

3. Michael Kleyman

   Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, United States

   Contribution

   Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

4. Serhan Turunç

   Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

5. Jing He

   Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9034-8390

6. Sara Jabalameli

   Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

7. Zhouhuan Xi

   1. Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States
   2. Eye Center of Xiangya Hospital, Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, China

   Contribution

   Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

8. Meike Visel

   Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States

   Contribution

   Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   is an inventor on AAV capsid variants (US patent IDs: 10,214,785, 10,745,453). MV has also received royalty payments from UC Berkeley. The author has no other competing interests to declare

   "This ORCID iD identifies the author of this article:" 0000-0002-5033-3730

9. Valérie L Dufour

   Division of Experimental Retinal Therapies, Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States

   Contribution

   Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

10. Simone Iwabe

    Division of Experimental Retinal Therapies, Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States

    Contribution

    Investigation, Writing – original draft, Writing – review and editing

    Competing interests

    No competing interests declared

11. Luis Felipe L Pompeo Marinho

    Division of Experimental Retinal Therapies, Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States

    Contribution

    Investigation, Writing – original draft, Writing – review and editing

    Competing interests

    No competing interests declared

12. Gustavo D Aguirre

    Division of Experimental Retinal Therapies, Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States

    Contribution

    Funding acquisition, Investigation, Resources, Supervision, Writing – original draft, Writing – review and editing

    Competing interests

    No competing interests declared

13. José-Alain Sahel

    Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States

    Contribution

    Funding acquisition, Supervision, Writing – original draft, Writing – review and editing

    Competing interests

    has served as a consultant (with no consulting fee) for Pixium Vision, GenSight Biologics and SparingVision. Personal financial interests: Pixium Vision, GenSight Biologics, Prophesee and Chronolife, SparingVision, SHARPEYE, Vegavect, Newsight Therapeutics. The author has no other competing interests to declare

14. David V Schaffer

    1. Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
    2. Chemical Engineering, University of California, Berkeley, Berkeley, United States

    Contribution

    Conceptualization, Funding acquisition, Resources, Supervision, Writing – original draft, Writing – review and editing

    Competing interests

    is named as an inventor on patent applications on AAV capsid variants (U.S. Patent Applications No. 16/315,032, 16/486,681). DS is also a co-founder of 4D Molecular Therapeutics, and DS performs consultancy and owns stock options in this company. The author has no other competing interests to declare

15. Andreas R Pfenning

    Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, United States

    Contribution

    Formal analysis, Funding acquisition, Supervision, Writing – original draft, Writing – review and editing

    Competing interests

    has received an honorarium from the University of Rhode Island, and has applied for patents on specific Nuclear-Anchored Independent Labeling System (PCT/US2020/038520 and PCT/US2020/038528). The author has no other competing interests to declare

16. John G Flannery

    1. Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
    2. Vision Science, Herbert Wertheim School of Optometry, University of California Berkeley, Berkeley, United States

    Contribution

    Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review and editing

    Competing interests

    is an inventor on patent application on AAV capsid variants (U.S. Patent Application No. 16/315,032, 16/486,681). The author has no other competing interests to declare

    "This ORCID iD identifies the author of this article:" 0000-0002-0720-8897

17. William A Beltran

    Division of Experimental Retinal Therapies, Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States

    Contribution

    Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review and editing

    Competing interests

    is an inventor on patent application on AAV capsid variants(16/315,032). The author has no other competing interests to declare

18. William R Stauffer

    Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States

    Contribution

    Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Supervision, Writing – original draft, Writing – review and editing

    Competing interests

    is an inventor on a patent application for methods of AAV capsid development (PCT/US2019/068489). The author has no other competing interests to declare

    "This ORCID iD identifies the author of this article:" 0000-0003-1031-8824

19. Leah C Byrne

    1. Department of Ophthalmology, University of Pittsburgh, Pittsburgh, United States
    2. Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States
    3. Division of Experimental Retinal Therapies, Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States
    4. Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States

    Contribution

    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing

    For correspondence

    lbyrne@pitt.edu

    Competing interests

    is named as an inventor on patent applications on AAV capsid variants and AAV screening methods (U.S. Patent Applications No. 16/315,032, 16/486,681, PCT/US2019/068489). LB has consulted on AAV-mediated gene therapy for Vedere Therapeutics, and is a named founder of Vegavect and Newsight Therapeutics. The author has no other competing interests to declare

    "This ORCID iD identifies the author of this article:" 0000-0002-3229-4993

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