4.6 Article

Vector Affinity and Receptor Distribution Define Tissue-Specific Targeting in an Engineered AAV Capsid

Journal

JOURNAL OF VIROLOGY
Volume 97, Issue 6, Pages -

Publisher

AMER SOC MICROBIOLOGY
DOI: 10.1128/jvi.00174-23

Keywords

Adeno-associated virus; Blood-brain barrier; Capsid engineering

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Unbiased in vivo selections of diverse capsid libraries can yield engineered capsids that overcome gene therapy delivery challenges, but little is known about the parameters of capsid-receptor interactions that govern their improved activity. In this work, a high-throughput method for quantifying capsid-receptor affinity is developed, and it is demonstrated that efficient central nervous system transduction requires high levels of target receptor expression at the blood-brain barrier. Enhanced receptor affinity leads to reduced transduction of off-target tissues but can negatively impact on-target cellular transduction and penetration of endothelial barriers. This work provides a set of tools for defining vector-receptor affinities and demonstrates how receptor expression and affinity interact to impact the performance of engineered AAV vectors.
Unbiased in vivo selections of diverse capsid libraries can yield engineered capsids that overcome gene therapy delivery challenges like traversing the blood-brain barrier (BBB), but little is known about the parameters of capsid-receptor interactions that govern their improved activity. This hampers broader efforts in precision capsid engineering and is a practical impediment to ensuring the translatability of capsid properties between preclinical animal models and human clinical trials. In this work, we utilize the adeno-associated virus (AAV)-PHP.B-Ly6a model system to better understand the targeted delivery and BBB penetration properties of AAV vectors. This model offers a defined capsid-receptor pair that can be used to systematically define relationships between target receptor affinity and in vivo activity of engineered AAV vectors. Here, we report a high-throughput method for quantifying capsid-receptor affinity and demonstrate that direct binding assays can be used to organize a vector library into families with varied affinity for their target receptor. Our data indicate that efficient central nervous system transduction requires high levels of target receptor expression at the BBB, but it is not a requirement for receptor expression to be limited to the target tissue. We observed that enhanced receptor affinity leads to reduced transduction of off-target tissues but can negatively impact on-target cellular transduction and penetration of endothelial barriers. Together, this work provides a set of tools for defining vector-receptor affinities and demonstrates how receptor expression and affinity interact to impact the performance of engineered AAV vectors in targeting the central nervous system.IMPORTANCE Novel methods for measuring adeno-associated virus (AAV)-receptor affinities, especially in relation to vector performance in vivo, would be useful to capsid engineers as they develop AAV vectors for gene therapy applications and characterize their interactions with native or engineered receptors. Here, we use the AAV-PHP.B-Ly6a model system to assess the impact of receptor affinity on the systemic delivery and endothelial penetration properties of AAV-PHP.B vectors. We discuss how receptor affinity analysis can be used to isolate vectors with optimized properties, improve the interpretation of library selections, and ultimately translate vector activities between preclinical animal models and humans. Novel methods for measuring adeno-associated virus (AAV)-receptor affinities, especially in relation to vector performance in vivo, would be useful to capsid engineers as they develop AAV vectors for gene therapy applications and characterize their interactions with native or engineered receptors. Here, we use the AAV-PHP.B-Ly6a model system to assess the impact of receptor affinity on the systemic delivery and endothelial penetration properties of AAV-PHP.B vectors.

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