Next-generation AAV vectors for clinical use: an ever-accelerating race

Abstract

During the past five decades, it has become evident that Adeno-associated virus (AAV) represents one of the most potent, most versatile, and thus most auspicious platforms available for gene delivery into cells, animals and, ultimately, humans. Particularly attractive is the ease with which the viral capsid—the major determinant of virus–host interaction including cell specificity and antibody recognition—can be modified and optimized at will. This has motivated countless researchers to develop high-throughput technologies in which genetically engineered AAV capsid libraries are subjected to a vastly hastened emulation of natural evolution, with the aim to enrich novel synthetic AAV capsids displaying superior features for clinical application. While the power and potential of these forward genetics approaches is undisputed, they are also inherently challenging as success depends on a combination of library quality, fidelity, and complexity. Here, we will describe and discuss two original, very exciting strategies that have emerged over the last three years and that promise to alleviate at least some of these concerns, namely, (i) a reverse genetics approach termed “ancestral AAV sequence reconstruction,” and (ii) AAV genome barcoding as a technology that can advance both, forward and reverse genetics stratagems. Notably, despite the conceptual differences of these two technologies, they pursue the same goal which is tailored acceleration of AAV evolution and thus winning the race for the next-generation AAV vectors for clinical use.

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Correspondence to Dirk Grimm.

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Edited by Anja Ehrhardt and Florian Kreppel.

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Weinmann, J., Grimm, D. Next-generation AAV vectors for clinical use: an ever-accelerating race. Virus Genes 53, 707–713 (2017). https://doi.org/10.1007/s11262-017-1502-7

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Keywords

  • AAV, Adeno-associated virus(es)
  • Gene therapy
  • Viral vector(s)
  • Molecular evolution
  • Ancestral sequence reconstruction
  • DNA barcoding
  • High-throughput
  • Capsid selection