Assessment of pre-clinical liver models based on their ability to predict the liver-tropism of AAV vectors

The liver is a prime target for in vivo gene therapies using recombinant adeno-associated viral vectors (rAAV). Multiple clinical trials have been undertaken for this target in the past 15 years, however we are still to see market approval of the first liver-targeted AAV-based gene therapy. Inefficient expression of the therapeutic transgene, vector-induced liver toxicity and capsid, and/or transgene-mediated immune responses reported at high vector doses are the main challenges to date. One of the contributing factors to the insufficient clinical outcomes, despite highly encouraging preclinical data, is the lack of robust, biologically- and clinically-predictive preclinical models. To this end, this study reports findings of a functional evaluation of six AAV vectors in twelve preclinical models of the human liver, with the aim to uncover which combination of models is the most relevant for the identification of AAV capsid variant for safe and efficient transgene delivery to primary human hepatocytes. The results, generated by studies in models ranging from immortalized cells, iPSC-derived and primary hepatocytes, and primary human hepatic organoids to in vivo models, increased our understanding of the strengths and weaknesses of each system. This should allow the development of novel gene therapies targeting the human liver

Codon-Optimization of Wild-Type Adeno-Associated Virus Capsid Sequences Enhances DNA Family Shuffling while Conserving Functionality

Adeno-associated virus (AAV) vectors have become one of the most widely used gene transfer tools in human gene therapy. Considerable effort is currently being focused on AAV capsid engineering strategies with the aim of developing novel variants with enhanced tropism for specific human cell types, decreased human seroreactivity, and increased manufacturability. Selection strategies based on directed evolution rely on the generation of highly variable AAV capsid libraries using methods such as DNA-family shuffling, a technique reliant on stretches of high DNA sequence identity between input parental capsid sequences. This identity dependence for reassembly of shuffled capsids is inherently limiting and results in decreased shuffling efficiency as the phylogenetic distance between parental AAV capsids increases. To overcome this limitation, we have developed a novel codon-optimization algorithm that exploits evolutionarily defined codon usage at each amino acid residue in the parental sequences. This method increases average sequence identity between capsids, while enhancing the probability of retaining capsid functionality, and facilitates incorporation of phylogenetically distant serotypes into the DNA-shuffled libraries. This technology will help accelerate the discovery of an increasingly powerful repertoire of AAV capsid variants for cell-type and disease-specific applications. Keywords: AAV, library, directed evolution, codon optimization, DNA shuffling, capsi