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酵母合成生物学的创新:用于免疫治疗的工程化发现系统

Innovations in Yeast Synthetic Biology: Engineered Discovery Systems for Immunotherapy.

作者信息

Slaton Ethan W, Clay Natalie, Phan Nathan, Kimmel Blaise R

机构信息

Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio 43210, United States.

Center for Cancer Engineering, Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, United States.

出版信息

ACS Synth Biol. 2025 Sep 19;14(9):3293-3305. doi: 10.1021/acssynbio.5c00321. Epub 2025 Aug 13.

Abstract

Yeast-based platforms are emerging as innovative synthetic biology tools for the discovery of immunotherapeutic proteins. Through the integration of (i) high-throughput surface display technologies, (ii) automated evolution systems (such as OrthoRep), and (iii) computational design strategies, the field of synthetic biology can make a direct impact toward rapidly identifying and engineering novel protein-based therapeutics. In this review, we will highlight the latest innovations regarding using engineered yeast to display proteins (e.g., nanobodies) and screen for potential antigens for immune receptors (e.g., GPCRs, TCRs). We will also discuss emerging areas in which the field has recently progressed and how the innovative technologies from these efforts help bridge the gap between synthetic biology and immunology such as identifying therapeutic binding events for engineered proteins of interest with the potential to actuate downstream immune responses. These innovations illustrate how yeast enables new design, build, test, and learn (DBTL) workflows in immunoengineering and offers a scalable, programmable chassis for developing tools and technologies for the construction of next-generation biotherapeutics.

摘要

基于酵母的平台正成为用于发现免疫治疗蛋白的创新合成生物学工具。通过整合(i)高通量表面展示技术、(ii)自动化进化系统(如OrthoRep)和(iii)计算设计策略,合成生物学领域能够对快速识别和工程化新型蛋白质疗法产生直接影响。在本综述中,我们将重点介绍利用工程酵母展示蛋白质(如纳米抗体)以及筛选免疫受体(如GPCR、TCR)潜在抗原的最新创新成果。我们还将讨论该领域最近取得进展的新兴领域,以及这些努力中的创新技术如何有助于弥合合成生物学与免疫学之间的差距,例如识别感兴趣的工程蛋白的治疗性结合事件,这些事件有可能引发下游免疫反应。这些创新展示了酵母如何在免疫工程中实现新的设计、构建、测试和学习(DBTL)工作流程,并为开发用于构建下一代生物疗法的工具和技术提供了一个可扩展的、可编程的底盘。

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