Cabanes-Creus Marti, Ginn Samantha L, Amaya Anais K, Liao Sophia H Y, Westhaus Adrian, Hallwirth Claus V, Wilmott Patrick, Ward Jason, Dilworth Kimberley L, Santilli Giorgia, Rybicki Arkadiusz, Nakai Hiroyuki, Thrasher Adrian J, Filip Adrian C, Alexander Ian E, Lisowski Leszek
Translational Vectorology Group, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia.
Great Ormond Street Institute of Child Health, University College London, London, UK.
Mol Ther Methods Clin Dev. 2018 Nov 1;12:71-84. doi: 10.1016/j.omtm.2018.10.016. eCollection 2019 Mar 15.
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.
腺相关病毒(AAV)载体已成为人类基因治疗中使用最广泛的基因转移工具之一。目前,大量的工作集中在AAV衣壳工程策略上,目的是开发出对特定人类细胞类型具有增强嗜性、降低人类血清反应性且提高可制造性的新型变体。基于定向进化的筛选策略依赖于使用诸如DNA家族改组等方法生成高度可变的AAV衣壳文库,该技术依赖于输入亲本衣壳序列之间的高DNA序列同一性片段。改组衣壳重新组装对这种同一性的依赖本质上是有局限性的,并且随着亲本AAV衣壳之间的系统发育距离增加,改组效率会降低。为了克服这一局限性,我们开发了一种新型密码子优化算法,该算法利用亲本序列中每个氨基酸残基进化定义的密码子使用情况。这种方法增加了衣壳之间的平均序列同一性,同时提高了保留衣壳功能的概率,并有助于将系统发育距离较远的血清型纳入DNA改组文库。这项技术将有助于加速发现越来越强大的AAV衣壳变体库,用于细胞类型和疾病特异性应用。