功能拓扑的理性设计及其在合成生物学中的应用

孙智; 杨宁; 娄春波; 汤超; 杨晓静

doi:10.12211/2096-8280.2023-003

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功能拓扑的理性设计及其在合成生物学中的应用

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- 功能拓扑的理性设计及其在合成生物学中的应用
- Rational design for functional topology and its applications in synthetic biology
- 合成生物学 2023年4卷第3期页码：444-463
- 作者机构：
  
  1.北京大学定量生物学中心，北京大学-清华大学生命科学联合中心，北京大学前沿学科交叉研究院，北京大学，北京 100871
  2.中国科学院深圳先进技术研究院，细胞与基因线路设计中心，广东深圳 518000
- 作者简介：
  
  [ "孙智（1994—），男，博士后。研究方向为定量合成生物学，人工生命系统的理性设计。 E-mail：sunz@pku.edu.cn" ]
  [ "杨宁（1995—），男，博士研究生。研究方向为复杂系统、定量生物学。 E-mail：yn_biophy@pku.edu.cn" ]
  [ "汤超（1958—），男，中国科学院院士，讲席教授，博士生导师。研究方向为物理生物学，系统生物学，统计物理和复杂系统。 E-mail：tangc@pku.edu.cn" ]
  [ "杨晓静（1978—），女，副研究员。研究方向为系统生物学，定量生物学，合成生物学。 E-mail：xiaojing_yang@pku.edu.cn" ]
- 基金信息：
  
  国家重点研发计划(2018YFA0900700;2021YFF1200501);北京大学-清华大学生命科学联合中心博士后基金
- DOI：10.12211/2096-8280.2023-003
  中图分类号： Q81
- 收稿：2023-01-02，
  
  修回：2023-02-09，
  
  纸质出版：2023-06-30
- 稿件说明：
移动端阅览
孙智，杨宁，娄春波，汤超，杨晓静. 功能拓扑的理性设计及其在合成生物学中的应用［J］. 合成生物学， 2023， 4（3）： 444-463

SUN Zhi， YANG Ning， LOU Chunbo， TANG Chao， YANG Xiaojing. Rational design for functional topology and its applications in synthetic biology［J］. Synthetic Biology Journal， 2023， 4（3）： 444-463
孙智，杨宁，娄春波，汤超，杨晓静. 功能拓扑的理性设计及其在合成生物学中的应用［J］. 合成生物学， 2023， 4（3）： 444-463 DOI： 10.12211/2096-8280.2023-003.

SUN Zhi， YANG Ning， LOU Chunbo， TANG Chao， YANG Xiaojing. Rational design for functional topology and its applications in synthetic biology［J］. Synthetic Biology Journal， 2023， 4（3）： 444-463 DOI： 10.12211/2096-8280.2023-003.

摘要

生物网络以超乎寻常的精度、可靠性和鲁棒性执行着各种各样复杂的功能。网络的拓扑结构、动力学性质与功能之间密切相关。如何定量刻画这种关系，找到复杂多样的生物网络的底层设计规律是系统生物学和合成生物学的巨大挑战。本文对功能拓扑的理性设计及其在合成生物学中的应用进行了综述。生物网络在统计性质上不同于随机网络，其结构呈现出模块化的趋势，本文首先总结了自然生物系统中出现的高频模块及其功能，回顾了最近系统生物学对于功能拓扑设计原理的探索，包括目前搜索功能拓扑的两种常用计算方法，同时对理论获得的典型功能拓扑进行了总结。继而总结了近年来实际合成生物学系统中功能拓扑的设计和构建，以基于转录调控的基因回路为主，按照其内部调控节点的数目，系统地介绍了不同拓扑结构被用来实现的具体功能及其典型实例。最后，介绍了近期自动化设计集成基因线路的发展、非转录多层次调控机制以及网络鲁棒性的设计原理，并简单探讨了对于复杂功能拓扑设计的机遇和挑战。

Abstract

Biological networks are capable of performing complex functions with accuracy

reliability

and robustness. In topology

the dynamic property and function of a network are closely related. How to depict this relationship quantitatively and discover design principles for complex and diverse biological networks are great challenges. In this review

we comment progress in this regard and its applications in synthetic biology. Biological networks are different statistically from random ones

which show a characteristic of modularization. There are recurrent network motifs linked to particular functions

such as temporally programed expression

reliable cell decisions

and robust biological oscillations

suggesting that despite the apparent complexity of cellular networks

there may only be a limited number of topological networks for executing particular biological functions robustly. Indeed

by enumerating all possible topological networks with two or three nodes

systems biology studies have shown that only a handful of topological network

s can perform a given function. Here

we first summarize the high-frequency modules and their functions in natural biological systems

review progress in systems biology to find design principles for functional topology

including two current methods (

enumeration and optimization) to search functional topology computationally

and highlight the typical functional topological networks that have been developed theoretically so far. Then

we focus on the functional topology that has been constructed and used in synthetic biology

such as genetic circuits developed based on transcriptional regulation. Organized by the number of nodes

we show typical examples and applications of different functional topological networks

including single-node positive/negative feedback loops

two-node positive/negative feedback loops

multi-node negative feedback/feedforward loops

and the combinational logic gates etc. Finally

we address frontiers in functional topology

including automated design of integrated gene circuits

other regulatory mechanisms beyond transcription

design of network robustness. We end by briefly discussing opportunities and challenges for designing complex functional topological networks.

关键词

Keywords

references

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