Author

Amanda X. Chen

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Open access Aug 2026

Functional evaluation of a natural AAV capsid liver targeting motif in human hepatocytes

Background&Aims Adeno-associated virus (AAV) vectors are attractive delivery vehicles for therapeutic gene delivery, and a notable feature of most AAVs is their natural tropism for the liver, which leads to significant hepatic uptake following systemic administration. In previous work, we identified 266G as a conserved motif on a variable region on the capsid of many commonly used AAV variants that controls liver uptake in both mice and non-human primates. This single amino acid could be functionally leveraged to engineer AAVs to either de-target from or enhance tropism to the liver. Here, we explored whether these observations extended to the human context. Methods Two human hepatocyte models were tested: Fah−/−/Rag2−/−/Il2rg−/− (FRG) mice with humanized livers and a bioengineered human microliver platform in vitro. A barcoded AAV capsid library including standard control serotypes were used to assess the role of the 266G motif on gene transfer and transgene expression in both liver systems. Results In vivo, 266G containing AAVs indeed targeted human hepatocytes superiorly, with some noted dependency on the degree of human-hepatocyte replacement in the chimeric mouse model. Initial studies in the micropatterned primary human hepatocyte co-culture model however demonstrated enrichment of heparin-binding AAVs, and not 266G variants. Notably, incorporation of polyethylene glycol (PEG) into the system modified the AAV transduction potential of those capsids including the liver-targeting motif, recapitulating the hepatocyte transduction pattern observed in vivo. Importantly, when PEG was used, the two human models, both at the DNA and RNA level, did correlate significantly. Conclusions Our results showed the potential of a combinatorial AAV library for model validation and revealed the human microliver platform-PEG as a reliable system for the development of AAV therapeutics.

Carmen Unzu, Amanda X. Chen, Liliana Mancio-Silva et al. · 0 citations