Boosters for adeno-associated virus (AAV) vector (r)evolution

Adeno-associated virus (AAV) is one of the most exciting and most versatile templates for engineering of gene-delivery vectors for use in human gene therapy, owing to the existence of numerous naturally occur-ring capsid variants and their amenability to directed molecular evolution. As a result, the field has witnessed an explosion of novel designer AAV capsids and ensuing vectors over the last two decades, which have been isolated from comprehensive capsid libraries generated through technologies such as DNA shuffling or peptide display, and stratified under stringent positive and/or negative selection pressures. Here, we briefly highlight a panel of recent, innovative and transformative methodologies that we consider to have excep-tional potential to advance directed AAV capsid evolution and to thereby accelerate AAV vector revolution. These avenues comprise original technologies for (i) barcoding and high-throughput screening of individual AAV variants or entire capsid libraries, (ii) selection of transduction-competent AAV vectors on the DNA level, (iii) enrichment of expression-competent AAV variants on the RNA level, as well as (iv) high-resolution strat-ification of focused AAV capsid libraries on the single-cell level. Together with other emerging AAV engineer-ing stratagems, such as rational design or machine learning, these pioneering techniques promise to provide an urgently needed booster for AAV (r)evolution.(c) 2022 International Society for Cell & Gene Therapy. Published by Elsevier Inc. All rights reserved.

Automated summary

Adeno-associated virus (AAV) has become a versatile and exciting tool for gene therapy due to its naturally occurring capsid variants and amenability to molecular evolution. Recent advancements in technologies such as barcoding and high-throughput screening, transduction-competent AAV vector selection, expression-competent AAV variant enrichment, and high-resolution stratification of AAV capsid libraries hold exceptional potential for advancing directed AAV capsid evolution, ultimately accelerating the AAV vector revolution. These innovative techniques, along with other emerging strategies like rational design and machine learning, can greatly contribute to the advancement of AAV research and development.