AAV-p40 Bioengineering Platform for Variant Selection Based on Transgene Expression

Adrian Westhaus, Marti Cabanes-Creus, Timo Jonker, Erwan Sallard, Renina Gale Navarro, Erhua Zhu, Grober Baltazar Torres, Scott Lee, Patrick Wilmott, Anai Gonzalez-Cordero, Giorgia Santilli, Adrian J. Thrasher, Ian E. Alexander, Leszek Lisowski

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The power of adeno-associated viral (AAV)-directed evolution for identifying novel vector variants with improved properties is well established, as evidenced by numerous publications reporting novel AAV variants. However, most capsid variants reported to date have been identified using either replication-competent (RC) selection platforms or polymerase chain reaction-based capsid DNA recovery methods, which can bias the selection toward efficient replication or unproductive intracellular trafficking, respectively. A central objective of this study was to validate a functional transduction (FT)-based method for rapid identification of novel AAV variants based on AAV capsid mRNA expression in target cells. We performed a comparison of the FT platform with existing RC strategies. Based on the selection kinetics and function of novel capsids identified in an in vivo screen in a xenograft model of human hepatocytes, we identified the mRNA-based FT selection as the most optimal AAV selection method. Lastly, to gain insight into the mRNA-based selection mechanism driven by the native AAV-p40 promoter, we studied its activity in a range of in vitro and in vivo targets. We found AAV-p40 to be a ubiquitously active promoter that can be modified for cell-type-specific expression by incorporating binding sites for silencing transcription factors, allowing for cell-type-specific library selection.
Original languageEnglish
Pages (from-to)664-682
Number of pages19
JournalHuman Gene Therapy
Volume33
Issue number11-12
DOIs
Publication statusPublished - 1 Jun 2022

Keywords

  • AAV
  • Adeno-associated viral vectors
  • Capsid bioengineering
  • Directed evolution
  • Novel vectors
  • Vector development

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