Bottom-Up Design: A Modular Golden Gate Assembly Platform of Yeast Plasmids for Simultaneous Secretion and Surface Display of Distinct FAP Fusion Proteins.
Bottom-Up Design: A Modular Golden Gate Assembly Platform of Yeast Plasmids for Simultaneous Secretion and Surface Display of Distinct FAP Fusion Proteins.
复制标题
自下而上的设计：酵母质粒的模块化金门组装平台，用于同时分泌和表面展示不同的 FAP 融合蛋白。
DOI：
10.1021/acssynbio.2c00283
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发表时间：
2022
影响因子：
4.7
通讯作者：
vandeWeerd,Robert
中科院分区：
文献类型：
--
作者：
Szent-Gyorgyi,Christopher;Perkins,LydiaA;Schmidt,BrigitteF;Liu,Zhen;Bruchez,MarcelP;vandeWeerd,Robert
合成生物学中的一个需要是能够精确和高效地制造灵活的、完全设计的载体，以解决具有挑战性的单质粒克隆策略，这些策略依赖于在文库筛选等项目中有用的大量靶标和诱饵融合记者的组合共表达。对于这些策略，调控元件和功能元件需要与项目特定的序列元件完美对应，以促进这些元件的容易交换。这需要系统地实施和建立在金门(GG)最近改进的基础上，以确保这种复杂载体的高克隆效率。目前，在合成生物学中的各种分子GG克隆技术中没有解决这一问题。在这里，我们介绍了自下而上的设计和质粒合成，以制备10kb的功能性酵母分泌和展示载体，该载体使用优化的GG版本并结合荧光素激活蛋白报告技术。这使得我们能够在单个细胞中展示纳米体/靶蛋白的相互作用，通过同源纳米体对分泌的靶蛋白的细胞表面保留来检测到这一点。这验证了GG构造方法，并提出了一种发现蛋白质相互作用的新方法。我们的GG组装平台为基于载体的文库筛选铺平了道路，并可用于其他重组GG平台。
A need in synthetic biology is the ability to precisely and efficiently make flexible fully designed vectors that addresses challenging cloning strategies of single plasmids that rely on combinatorial co-expression of a multitude of target and bait fusion reporters useful in projects like library screens. For these strategies, the regulatory elements and functional components need to correspond perfectly to project specific sequence elements that facilitate easy exchange of these elements. This requires systematic implementation and building on recent improvements in Golden Gate (GG) that ensures high cloning efficiency for such complex vectors. Currently, this is not addressed in the variety of molecular GG cloning techniques in synthetic biology. Here, we present the bottom-up design and plasmid synthesis to prepare 10 kb functional yeast secrete and display plasmids that uses an optimized version of GG in combination with fluorogen-activating protein reporter technology. This allowed us to demonstrate nanobody/target protein interactions in a single cell, as detected by cell surface retention of secreted target proteins by cognate nanobodies. This validates the GG constructional approach and suggests a new approach for discovering protein interactions. Our GG assembly platform paves the way for vector-based library screening and can be used for other recombinant GG platforms.