Fantastic AAV gene therapy cectors and how to find them

• Verfasst von: Becker, Jonas [VerfasserIn]
• Verfasst von: Fakhiri, Julia [VerfasserIn]
• Verfasst von: Grimm, Dirk [VerfasserIn]
• Titel: Fantastic AAV gene therapy cectors and how to find them
• Titelzusatz: random diversification, rational design and machine learning
• Verf.angabe: Jonas Becker, Julia Fakhiri and Dirk Grimm
• E-Jahr: 2022
• Jahr: 3 July 2022
• Umfang: 30 S.
• Fussnoten: Gesehen am 19.08.2022
• Titel Quelle: Enthalten in: Pathogens
• Ort Quelle: Basel : MDPI, 2012
• Jahr Quelle: 2022
• Band/Heft Quelle: 11(2022), 7, Artikel-ID 756, Seite 1-30
• ISSN Quelle: 2076-0817
• DOI: doi:10.3390/pathogens11070756
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: AAV
• Sach-SW: adeno-associated virus
• Sach-SW: capsid engineering
• Sach-SW: gene therapy
• Sach-SW: molecular evolution
• K10plus-PPN: 1814730427

Abstract

Parvoviruses are a diverse family of small, non-enveloped DNA viruses that infect a wide variety of species, tissues and cell types. For over half a century, their intriguing biology and pathophysiology has fueled intensive research aimed at dissecting the underlying viral and cellular mechanisms. Concurrently, their broad host specificity (tropism) has motivated efforts to develop parvoviruses as gene delivery vectors for human cancer or gene therapy applications. While the sum of preclinical and clinical data consistently demonstrates the great potential of these vectors, these findings also illustrate the importance of enhancing and restricting in vivo transgene expression in desired cell types. To this end, major progress has been made especially with vectors based on Adeno-associated virus (AAV), whose capsid is highly amenable to bioengineering, repurposing and expansion of its natural tropism. Here, we provide an overview of the state-of-the-art approaches to create new AAV variants with higher specificity and efficiency of gene transfer in on-target cells. We first review traditional and novel directed evolution approaches, including high-throughput screening of AAV capsid libraries. Next, we discuss programmable receptor-mediated targeting with a focus on two recent technologies that utilize high-affinity binders. Finally, we highlight one of the latest stratagems for rational AAV vector characterization and optimization, namely, machine learning, which promises to facilitate and accelerate the identification of next-generation, safe and precise gene delivery vehicles.