Abstract:

Genetic evolution is a defining feature of all biological systems, whereby lives are able to adapt to the rapidly changing environments. Quantitative synthetic biology, an emerging field in life science, mainly studies how to apply synthetic biosystems to reveal quantitative biological rules, which in turn guides the rational design of synthetic life. Although such artificial biosystems are created in the laboratory, they are also governed by the rules of evolution, such as mutation, genetic drift, Darwinian selection, etc. However, the evolutionary potential of a synthetic biosystem might have been underrated, which often leads to the circuit failures or the emergence of undesigned function. Therefore, overcoming evolutionary perturbations is one of grand challenges in robust circuit design, and harnessing the rules of evolution would be important for more robust design of artificial biosystems. On the other hand, bottom-up synthetic systems provide favorable biological models to test and explore the evolutionary principles that are hard to study based on natural biosystems. In this review, we first summarize the current progress in screening functional proteins through continuous directed-evolution guided by the evolutionary principles. We assess advantages and disadvantages for different architectures in continuous directed-evolution through evolutionary perspective. We also review the evolutionary strategies that are used to improve the stability of synthetic circuits in host cells, including reducing mutation rate, the coupling of host cell fitness with target gene expression, synthetic addiction, compartmentalization, feedback control, orthogonal system, etc. Furthermore, we discuss how to use the synthetic biology approaches to address some basic theories in evolutionary biology, such as the origin of life, the development of multicellularity, genetic constraint and epistasis, and the evolutionary tradeoff of complex life system, etc. We believe that a real-time precise control of the evolutionary process would enhance the quantitative features and predictability in the field of synthetic biology, and greatly advance the applications of robust synthetic biosystems for human sustainable goals.

Key words: biological evolution, quantitative biology, synthetic biology, artificial life, community evolution

摘要：

遗传进化是生物系统的一个基本特征，生物系统的结构与功能都是动态变化的，生物通过进化更好地适应环境。定量合成生物学作为一门新兴交叉学科，主要研究如何利用合成系统定量刻画生物学规律，以及基于理性设计和改造人工生命系统来解答生命科学前沿问题。然而，目前掌握的知识还不足以满足理性设计和定量可控的要求。尽管人工生命系统产生于实验室，但其同样受到进化法则的支配，比如突变、遗传漂变、达尔文自然选择等，因此需要利用进化规律帮助设计和构建更加稳定的人工生命系统；反过来，简单、周期短且可控的定量合成生物系统也可帮助研究生物进化原理提供更佳的生物模型，两者相互促进，为更好地探索生命法则提供了理论支撑和技术手段。本文主要综述了目前应用进化原理筛选目标蛋白的连续定向进化方法，总结了利用进化原理提高合成线路稳定性的策略；同时，介绍了用定量合成生物学的手段研究生物进化原理的进展，并提出了基于进化原理的人工生命设计的研究方向。未来合成生物学与进化生物学的融合发展将为精确控制生命系统提供思路和方法，增进合成生物学改善人类可持续发展的应用。

关键词: 遗传进化, 定量生物学, 合成生物学, 人工生命系统, 群落进化