酵母合成生物学的创新:免疫治疗的工程发现系统。

IF 3.9 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Ethan W. Slaton, Natalie Clay, Nathan Phan and Blaise R. Kimmel*, 
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引用次数: 0

摘要

基于酵母的平台正在成为发现免疫治疗蛋白的创新合成生物学工具。通过整合(i)高通量表面显示技术,(ii)自动进化系统(如OrthoRep)和(iii)计算设计策略,合成生物学领域可以对快速识别和设计新的基于蛋白质的治疗方法产生直接影响。在这篇综述中,我们将重点介绍利用工程酵母展示蛋白质(如纳米体)和筛选免疫受体潜在抗原(如gpcr, TCRs)的最新创新。我们还将讨论该领域最近取得进展的新兴领域,以及这些努力的创新技术如何帮助弥合合成生物学和免疫学之间的差距,例如识别感兴趣的工程蛋白的治疗结合事件,并有可能启动下游免疫反应。这些创新说明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可扩展的、可编程的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Innovations in Yeast Synthetic Biology: Engineered Discovery Systems for Immunotherapy

Innovations in Yeast Synthetic Biology: Engineered Discovery Systems for Immunotherapy

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.

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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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