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Boosters for adeno-associated virus (AAV) vector (r)evolution
Institution:1. Department of Infectious Diseases/Virology, Section Viral Vector Technologies, Medical Faculty, University of Heidelberg, Heidelberg, Germany;2. BioQuant Center and Center for Integrative Infectious Diseases Research (CIID), University of Heidelberg, Heidelberg, Germany;3. German Center for Infection Research (Deutsches Zentrum für Infektionsforschung, DZIF) and German Center for Cardiovascular Research (Deutsches Zentrum für Herz-Kreislauf-Erkrankungen, DZHK), partner site Heidelberg, Heidelberg, Germany;1. School of Chemistry, College of Science and Engineering, University of Leicester, Leicester LE1 7RH, UK;2. Genethon, 91000 Evry, France;3. Université Paris-Saclay, Univ. Evry, Inserm, Genethon, Integrare Research Unit UMR_S951, 91000 Evry, France
Abstract: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 occurring 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 exceptional 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 stratification of focused AAV capsid libraries on the single-cell level. Together with other emerging AAV engineering stratagems, such as rational design or machine learning, these pioneering techniques promise to provide an urgently needed booster for AAV (r)evolution.
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