Addressing evolutionary questions with synthetic biology

F. Baier, Y. Schaerli
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引用次数: 2

Abstract

Synthetic biology emerged as an engineering discipline to design and construct artificial biological systems. Synthetic biological designs aim to achieve specific biological behavior, which can be exploited for biotechnological, medical and industrial purposes. In addition, mimicking natural systems using well-characterized biological parts also provides powerful experimental systems to study evolution at the molecular and systems level. A strength of synthetic biology is to go beyond nature’s toolkit, to test alternative versions and to study a particular biological system and its phenotype in isolation and in a quantitative manner. Here, we review recent work that implemented synthetic systems, ranging from simple regulatory circuits, rewired cellular networks to artificial genomes and viruses, to study fundamental evolutionary concepts. In particular, engineering, perturbing or subjecting these synthetic systems to experimental laboratory evolution provides a mechanistic understanding on important evolutionary questions, such as: Why did particular regulatory networks topologies evolve and not others? What happens if we rewire regulatory networks? Could an expanded genetic code provide an evolutionary advantage? How important is the structure of genome and number of chromosomes? Although the field of evolutionary synthetic biology is still in its teens, further advances in synthetic biology provide exciting technologies and novel systems that promise to yield fundamental insights into evolutionary principles in the near future.
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用合成生物学解决进化问题
合成生物学是一门设计和构建人工生物系统的工程学科。合成生物学设计旨在实现特定的生物行为,可用于生物技术、医学和工业目的。此外,利用具有良好特征的生物部件模拟自然系统也为在分子和系统水平上研究进化提供了强大的实验系统。合成生物学的一个优势是超越自然的工具包,测试替代版本,并以隔离和定量的方式研究特定的生物系统及其表型。在这里,我们回顾了最近实现合成系统的工作,从简单的调节电路,重新连接的细胞网络到人工基因组和病毒,以研究基本的进化概念。特别是,工程、干扰或使这些合成系统服从于实验实验室的进化,提供了对重要进化问题的机制理解,例如:为什么特定的调节网络拓扑进化而不是其他的?如果我们重新连接监管网络会发生什么?扩展的遗传密码能提供进化优势吗?基因组的结构和染色体的数量有多重要?虽然进化合成生物学领域仍处于青少年时期,但合成生物学的进一步发展提供了令人兴奋的技术和新系统,有望在不久的将来产生对进化原理的基本见解。
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