Department of Synthetic Organic Chemistry, Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470, Muelheim, Germany.
Department of Chemistry, Philipps-Universität Marburg, 35032, Marburg, Germany.
Chembiochem. 2018 Feb 2;19(3):221-228. doi: 10.1002/cbic.201700540. Epub 2017 Dec 29.
Saturation mutagenesis (SM) constitutes a widely used technique in the directed evolution of selective enzymes as catalysts in organic chemistry and in the manipulation of metabolic paths and genomes, but the quality of the libraries is far from optimal due to the inherent amino acid bias. Herein, it is shown how this fundamental problem can be solved by applying high-fidelity solid-phase chemical gene synthesis on silicon chips followed by efficient gene assembly. Limonene epoxide hydrolase was chosen as the catalyst in the model desymmetrization of cyclohexene oxide with the stereoselective formation of (R,R)- and (S,S)-cyclohexane-1,2-diol. A traditional combinatorial PCR-based SM library, produced by simultaneous randomization at several residues by using a reduced amino acid alphabet, and the respective synthetic library were constructed and compared. Statistical analysis at the DNA level with massive sequencing demonstrates that, in the synthetic approach, 97 % of the theoretically possible DNA mutants are formed, whereas the traditional SM library contained only about 50 %. Screening at the protein level also showed the superiority of the synthetic library; many highly (R,R)- and (S,S)-selective variants being discovered are not found in the traditional SM library. With the prices of synthetic genes decreasing, this approach may point the way to future directed evolution.
饱和突变(SM)是一种广泛应用于定向进化选择性酶的技术,这些酶作为有机化学中的催化剂,以及代谢途径和基因组的操作工具。但由于氨基酸固有的偏倚,文库的质量远非理想。本文展示了如何通过在硅片上应用高保真固相化学基因合成,然后进行高效的基因组装,来解决这个基本问题。在环己烯氧化物的不对称拆分模型中,选择了表没食子儿茶素没食子酸酯水解酶作为催化剂,立体选择性地形成(R,R)-和(S,S)-环己烷-1,2-二醇。构建并比较了传统的基于组合 PCR 的 SM 文库,该文库通过使用简化的氨基酸字母同时在几个残基上进行随机化,以及各自的合成文库。通过大规模测序的 DNA 水平的统计分析表明,在合成方法中,形成了 97%的理论上可能的 DNA 突变体,而传统的 SM 文库仅包含约 50%。在蛋白质水平的筛选也显示了合成文库的优越性;发现了许多高度(R,R)-和(S,S)-选择性的变体,而这些变体在传统的 SM 文库中没有发现。随着合成基因价格的降低,这种方法可能为未来的定向进化指明了方向。