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<p>Naturally occurring adeno-associated viruses (AAVs) are an integral part of gene therapy, yet engineering novel AAV variants is necessary to expand targetable tissues and treatable diseases. Directed evolution, particularly through DNA shuffling of the capsid genes of wild-type AAV serotypes, is a widely employed strategy to generate novel chimeric variants with desired properties. Yet, the computational analysis of such chimeric sequences presents challenges. We introduce <i>hafoe</i>, a novel computational tool designed for the exploratory analysis of chimeric AAV libraries, which does not require extensive bioinformatics expertise. <i>hafoe</i> accurately deciphers the serotype composition and enrichment patterns of chimeric AAV variants across different tissues. Validation against synthetic datasets demonstrates that <i>hafoe</i> identifies parental serotype compositions with an accuracy of 96.3% to 97.5%. Additionally, we engineered chimeric AAV capsid libraries and screened novel AAV variants for tropism to human dermal fibroblasts and dendritic cells, as well as canine muscle, and liver tissues. Using <i>hafoe</i> we identified and characterized enriched AAV variants in these tissues for potential use in gene therapy and vaccine development. <i>Overall, hafoe</i> can provide valuable insights that may further support the rational design of AAV vectors based on parental serotype and sequence preferences of the capsid genes in target tissues.</p>

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hafoe: an interactive tool for the analysis of chimeric AAV libraries after random mutagenesis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月8日

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  • Tatevik Jalatyan,
  • Erik Aznauryan,
  • Rokib Hasan,
  • Valeri Vardanyan,
  • Stepan Nersisyan,
  • David B. Thompson,
  • Noah Davidsohn,
  • Sanya Thomas,
  • Simon van Haren,
  • Jenny Tam,
  • Denitsa Milanova,
  • George M. Church,
  • Lilit Nersisyan

摘要

Naturally occurring adeno-associated viruses (AAVs) are an integral part of gene therapy, yet engineering novel AAV variants is necessary to expand targetable tissues and treatable diseases. Directed evolution, particularly through DNA shuffling of the capsid genes of wild-type AAV serotypes, is a widely employed strategy to generate novel chimeric variants with desired properties. Yet, the computational analysis of such chimeric sequences presents challenges. We introduce hafoe, a novel computational tool designed for the exploratory analysis of chimeric AAV libraries, which does not require extensive bioinformatics expertise. hafoe accurately deciphers the serotype composition and enrichment patterns of chimeric AAV variants across different tissues. Validation against synthetic datasets demonstrates that hafoe identifies parental serotype compositions with an accuracy of 96.3% to 97.5%. Additionally, we engineered chimeric AAV capsid libraries and screened novel AAV variants for tropism to human dermal fibroblasts and dendritic cells, as well as canine muscle, and liver tissues. Using hafoe we identified and characterized enriched AAV variants in these tissues for potential use in gene therapy and vaccine development. Overall, hafoe can provide valuable insights that may further support the rational design of AAV vectors based on parental serotype and sequence preferences of the capsid genes in target tissues.