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Published October 21, 2021 | Supplemental Material + Submitted + Published
Journal Article Open

Deep Parallel Characterization of AAV Tropism and AAV-Mediated Transcriptional Changes via Single-Cell RNA Sequencing

Abstract

Engineered variants of recombinant adeno-associated viruses (rAAVs) are being developed rapidly to meet the need for gene-therapy delivery vehicles with particular cell-type and tissue tropisms. While high-throughput AAV engineering and selection methods have generated numerous variants, subsequent tropism and response characterization have remained low throughput and lack resolution across the many relevant cell and tissue types. To fully leverage the output of these large screening paradigms across multiple targets, we have developed an experimental and computational single-cell RNA sequencing (scRNA-seq) pipeline for in vivo characterization of barcoded rAAV pools at high resolution. Using this platform, we have both corroborated previously reported viral tropisms and discovered unidentified AAV capsid targeting biases. As expected, we observed that the tropism profile of AAV.CAP-B10 in mice was shifted toward neurons and away from astrocytes when compared with AAV-PHP.eB. Transcriptomic analysis revealed that this neuronal bias is due mainly to increased targeting efficiency for glutamatergic neurons, which we confirmed by RNA fluorescence in situ hybridization. We further uncovered cell subtype tropisms of AAV variants in vascular and glial cells, such as low transduction of pericytes and Myoc+ astrocytes. Additionally, we have observed cell-type-specific transitory responses to systemic AAV-PHP.eB administration, such as upregulation of genes involved in p53 signaling in endothelial cells three days post-injection, which return to control levels by day twenty-five. The presented experimental and computational approaches for parallel characterization of AAV tropism will facilitate the advancement of safe and precise gene delivery vehicles, and showcase the power of understanding responses to gene therapies at the single-cell level.

Additional Information

© 2021 Brown, Altermatt, Dobreva, Chen, Wang, Thomson and Gradinaru. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Received: 25 June 2021; Accepted: 17 September 2021; Published: 21 October 2021. We thank the Gradinaru and Thomson labs for helpful discussions, Allan-Hermann Pool for advice on the mouse brain tissue dissociation procedure, Jeff Park for advice on 10X Genomics Chromium single-cell library preparation, Min Jee Jang for help in designing probes and troubleshooting FISH-HCR, and Ben Deverman and Ken Chan for early discussions on strategy. We also thank the software packages employed for visualization. Figures 1, 2, and Supplemental Figures 1, 2, and 4 were partially created with Biorender.com. Bar graphs, scatter plots, and box plots were generated with the help of the Plotly Python graphing library. This work was supported by the NIH Pioneer DP1OD025535, NIH BRAIN R01MH117069, Beckman Institute for CLARITY, Optogenetics and Vector Engineering Research (CLOVER) at Caltech, the Single-Cell Profiling and Engineering Center (SPEC) in the Beckman Institute at Caltech, the Curci Foundation, the CZI Neurodegeneration Challenge Network (VG), and the Vallee Foundation (VG). VG and MT are Heritage Principal Investigators supported by the Heritage Medical Research Institute. DB was supported by PHS Grant Number 5T32NS105595-02. Data Availability Statement: All raw FASTQ files are available under the SRA BioProject PRJNA758711 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA758711/). Processed gene count matrices for droplets identified as cells, as well as the demultiplexed virus cargo counts, are available at CaltechData, doi: 22002/D1.2090 (http://dx.doi.org/10.22002/D1.2090). Ethics Statement: Animal husbandry and all experimental procedures involving animals were performed in accordance with the California Institute of Technology Institutional Animal Care and Use Committee (IACUC) guidelines and reviewed and approved by the Office of Laboratory Animal Resources at the California Institute of Technology (animal protocol no. 1650). Author Contributions: DB, MA, TD, and VG conceived the project and designed the experiments. SC and MT provided critical single-cell RNA sequencing expertise. TD, MA, and DB prepared the DNA constructs and produced virus. MA performed the injections, tissue dissociation, histology, imaging and image quantification. DB and TD performed the single-cell library preparation and prepared samples for sequencing. DB and MA built the data processing pipeline. DB, MA, TD, and AW performed the analysis. All authors contributed to the MS as drafted by DB, MA, and VG. MT supervised single-cell RNA sequencing computational pipelines while VG supervised the overall project. All authors contributed to the article and approved the submitted version. Conflict of Interest: VG is a Co-founder and BoD member for Capsida Biotherapeutics, a Fully Integrated AAV Engineering and Gene Therapy Company in Southern California. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Published - fimmu-12-730825.pdf

Submitted - 2021.06.25.449955v2.full.pdf

Supplemental Material - 5672098.zip

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Additional details

Created:
August 20, 2023
Modified:
March 5, 2024