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Updated: Dec 29, 2025

Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants

Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants

Published on: October 18, 2022

Tracking Adeno-Associated Virus Capsid Evolution by High-Throughput Sequencing.

Gustavo de Alencastro^1,2, Katja Pekrun^1,2, Paul Valdmanis^1,2

¹Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, USA.

Human Gene Therapy

|February 7, 2020

Summary

This summary is machine-generated.

Optimizing adeno-associated virus (AAV) capsid selection requires careful consideration of screening parameters. This study reveals that helper-virus inclusion, AAV competition, multiplicity of infection, and selection rounds significantly impact the isolation of effective gene therapy vectors.

Keywords:

AAV libraries capsid evolution high-throughput sequencing

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Engineering and Evolution of Synthetic Adeno-Associated Virus AAV Gene Therapy Vectors via DNA Family Shuffling

Engineering and Evolution of Synthetic Adeno-Associated Virus AAV Gene Therapy Vectors via DNA Family Shuffling

Published on: April 2, 2012

Area of Science:

Gene Therapy
Molecular Virology
Biotechnology

Background:

Recombinant adeno-associated virus (rAAV) vectors are crucial for gene therapy but face challenges like pre-existing antibodies and poor transduction.
Current AAV capsid selection methods lack clear parameters, hindering the development of more efficient vectors.
Readministration of rAAV vectors is limited by immune responses against the viral capsid.

Purpose of the Study:

To investigate how various parameters influence the screening of barcoded adeno-associated virus (AAV) capsid libraries.
To identify optimal conditions for isolating AAV variants with enhanced properties for gene therapy applications.
To provide insights into maximizing the efficiency of AAV capsid library screens using high-throughput sequencing.

Main Methods:

Utilized barcoding for AAV capsid libraries to enable high-throughput sequencing and tracking of capsid evolution.
Screened two distinct AAV libraries in two human cell types to assess the impact of different parameters.
Analyzed the effects of helper-virus inclusion, AAV competition, multiplicity of infection, and multiple selection rounds on AAV variant propagation and transduction.

Main Results:

Helper-virus inclusion favors variants with higher replication titers, not necessarily superior transduction efficiency.
AAVs with specific capsids can compete within cells co-infected with different AAVs.
Low multiplicity of infection leads to increased variability and suboptimal selection of desired AAV capsids.
Multiple rounds of selection can be counterproductive, hindering the isolation of optimal AAV variants.

Conclusions:

The parameters evaluated significantly affect the outcome of AAV library screens.
Careful optimization of helper-virus use, infection multiplicity, and selection strategies is essential for successful AAV capsid development.
Understanding these parameters is critical for improving the efficiency and success rate of gene therapy vector design.