Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly
Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly
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DOI：
10.1016/j.ymben.2020.12.001
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发表时间：
2021-01-18
影响因子：
8.4
通讯作者：
Freemont，Paul S.
中科院分区：
文献类型：
--
作者：
Young，Rosanna;Haines，Matthew;Freemont，Paul S.
合成生物学是一个快速发展的跨学科领域，主要建立在分子生物学的基础进步与模块化和互操作性等工程设计原理的基础上。该领域认为生命系统在基因水平上是可编程的，并通过新平台技术的发展和方法论的进步进行了定义。推动该领域的一个关键概念是设计-构建-测试-学习循环，它为构建新的生物系统提供了系统框架。合成生物学的主要应用领域之一是生物合成途径工程，需要不同遗传调控元件和生物合成酶的模块化组装。在这篇综述中，我们概述了模块化 DNA 组装，并描述和比较了用于组合途径工程的多种体外和体内组装方法。还提出了零件设计和酶平衡方法的考虑因素，并简要讨论了细胞内途径组装的替代方案，包括微生物群落和用于生物合成的无细胞系统。最后，我们描述了通路设计和组装的计算工具和自动化，并认为对遗传设计、通路调控和细胞代谢的许多不同变量的更深入了解将允许更具预测性的通路设计和工程。
Synthetic Biology is a rapidly growing interdisciplinary field that is primarily built upon foundational advances in molecular biology combined with engineering design principles such as modularity and interoperability. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies and methodological advances. A key concept driving the field is the Design-Build-Test-Learn cycle which provides a systematic framework for building new biological systems. One major application area for synthetic biology is biosynthetic pathway engineering that requires the modular assembly of different genetic regulatory elements and biosynthetic enzymes. In this review we provide an overview of modular DNA assembly and describe and compare the plethora of in vitro and in vivo assembly methods for combinatorial pathway engineering. Considerations for part design and methods for enzyme balancing are also presented, and we briefly discuss alternatives to intracellular pathway assembly including microbial consortia and cell-free systems for biosynthesis. Finally, we describe computational tools and automation for pathway design and assembly and argue that a deeper understanding of the many different variables of genetic design, pathway regulation and cellular metabolism will allow more predictive pathway design and engineering.