生物逆向工程设计在合成生物学中的应用

陈欣懋; 欧阳颀

doi:10.12211/2096-8280.2020-063

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生物逆向工程设计在合成生物学中的应用

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- 生物逆向工程设计在合成生物学中的应用
- The application of biological reverse engineering in synthetic biology
- 合成生物学 2020年1卷第1期页码：29-43
- 作者机构：
  
  北京大学物理学院，北京100871
- 作者简介：
  
  [ "陈欣懋(1994-)，女，博士研究生,研究方向为定量系统生物学和合成生物学。E-mail: xmaochen@pku.edu.cn" ]
  [ "欧阳颀(1955-)，男，博士，教授，中国科学院院士,研究方向为定量系统生物学、生物网络动力学、生物系统中的非线性问题、生物微流体技术。E-mail: qi@pku.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(11774011)
- DOI：10.12211/2096-8280.2020-063
  中图分类号： Q61
- 收稿：2020-05-06，
  
  修回：2020-05-16，
  
  纸质出版：2020-02-29
- 稿件说明：
移动端阅览
陈欣懋, 欧阳颀. 生物逆向工程设计在合成生物学中的应用[J]. 合成生物学, 2020, 1(1): 29-43

CHEN Xinmao, OUYANG Qi. The application of biological reverse engineering in synthetic biology[J]. Synthetic Biology Journal, 2020, 1(1): 29-43
陈欣懋, 欧阳颀. 生物逆向工程设计在合成生物学中的应用[J]. 合成生物学, 2020, 1(1): 29-43 DOI： 10.12211/2096-8280.2020-063.

CHEN Xinmao, OUYANG Qi. The application of biological reverse engineering in synthetic biology[J]. Synthetic Biology Journal, 2020, 1(1): 29-43 DOI： 10.12211/2096-8280.2020-063.

摘要

合成生物学是一门涉及生物学、生物工程学、系统生物学、数学、物理、化学与信息科学的新生的交叉学科。它的目的是在工程化思想的指导下有目的地、可预测地设计人造生命系统。经过近二十年的蓬勃发展，合成生物学取得了重大成就，但依旧面临复杂系统理性设计的困难。在系统生物学中，运用数学物理等知识根据网络功能来研究功能背后网络结构的方法被称为逆向工程。系统生物学逆向工程的研究思路与合成生物学设计过程的一致性，启发了我们利用逆向工程指导合成生物学的理性设计。逆向工程应用到合成生物学，将大大降低复杂功能回路的设计难度。本文从合成生物学的设计思路与问题出发，根据本文作者研究团队近十年来在逆向工程研究中的经验，归纳总结了目前逆向工程设计在合成生物学中的应用方法，包括网络穷举方法、子网络拼接方法、从离散模型到连续模型的方法，论证了逆向工程指导合成生物学理性设计的可行性与有效性，分析了目前逆向工程设计在合成生物学中的发展瓶颈。

Abstract

Aiming to purposefully and rationally design and construct predictable man-made life systems with pre-defined functions under the guidance of engineering principles

synthetic biology is an advanced interdisciplinary science by combining a broad range of methodologies from various disciplines

such as traditional biology

bioengineering

systems biology

mathematics

physics

chemistry

and information science. With the booming development for nearly two decades

great progress has been made in synthetic biology. However

there are a number of factors that should be taken into account for rationally designing complex systems

such as robustness and bifurcation. Because of the consistency between the research idea of biological reverse engineering and the design process of synthetic biology

we are enlightened to resolve these problems in rationally designing genetic circuits with compley pre-defined functions with the help of reverse engineering In this review

based on the accumulated experience of our research group in reverse engineering

we started with engineering principles and design difficulties in synthetic biology

and then summarized the current methods of applying reverse engineering in synthetic biology

including network enumeration

sub-network combinations

the method from Boolean network model to continuous model. In addition

we proved the efficiency of combining reverse engineering with synthetic biology to rationally design biological complex regulation networks. Finally

we concluded with the analysis of bottlenecks for the application of reverse engineering in synthetic biology.

关键词

Keywords

references

IDEKER T , THORSSON V , RANISH J A , et al . Integrated genomic and proteomic analyses of a systematically perturbed metabolic network [J ] . Science , 2001 , 292 ( 5518 ): 929-934.

BARABÁSI A , CRANDALL R E . Linked: the new science of networks [J ] . American Journal of Physics , 2002 , 71 ( 4 ): 243-270.

WOLKENHAUER O . Systems biology: the reincarnation of systems theory applied in biology? [J ] . Briefings in Bioinformatics , 2001 , 2 ( 3 ): 258-270.

BORNHOLDT S . Less is more in modeling large genetic networks [J ] . Science , 2005 , 310 ( 5747 ): 449-451.

FRIEDMAN N . Inferring cellular networks using probabilistic graphical models [J ] . Science , 2004 , 303 ( 5659 ): 799-805.

SAEZ‐RODRIGUEZ J , ALEXOPOULOS L G , EPPERLEIN J , et al . Discrete logic modelling as a means to link protein signaling networks with functional analysis of mammalian signal transduction [J ] . Molecular Systems Biology , 2009 , 5 ( 1 ): e331.

BASSO K , MARGOLIN A A , STOLOVITZKY G , et al . Reverse engineering of regulatory networks in human B cells [J ] . Nature Genetics , 2005 , 37 ( 4 ): 382-390.

ZOPPOLI P , MORGANELLA S , CECCARELLI M . TimeDelay-ARACNE: reverse engineering of gene networks from time-course data by an information theoretic approach [J ] . BMC Bioinformatics , 2010 , 11 ( 1 ): 154-169.

YEUNG M K S , TEGNÉR J , COLLINS J J . Reverse engineering gene networks using singular value decomposition and robust regression [J ] . PNAS , 2002 , 99 ( 9 ): 6163-6168.

TEGNER J , YEUNG M K S , HASTY J , et al . Reverse engineering gene networks: integrating genetic perturbations with dynamical modeling [J ] . PNAS , 2003 , 100 ( 10 ): 5944-5949.

BONGARD J , LIPSON H . Automated reverse engineering of nonlinear dynamical systems [J ] . PNAS , 2007 , 104 ( 24 ): 9943-9948.

D’HAESELEER P , LIANG S , SOMOGYI R . Genetic network inference: from co-expression clustering to reverse engineering [J ] . Bioinformatics , 2000 , 16 ( 8 ): 707-726.

GARDNER T S , FAITH J J . Reverse-engineering transcription control networks [J ] . Physics of Life Reviews , 2005 , 2 ( 1 ): 65-88.

VILLAVERDE A F , BANGA J R . Reverse engineering and identification in systems biology: strategies, perspectives and challenges [J ] . Journal of the Royal Society Interface , 2014 , 11 ( 91 ): 20130505.

SLUSARCZYK A L , LIN A , WEISS R . Foundations for the design and implementation of synthetic genetic circuits [J ] . Nature Reviews Genetics , 2012 , 13 ( 6 ): 406-420.

CANTON B , LABNO A , ENDY D . Refinement and standardization of synthetic biological parts and devices [J ] . Nature Biotechnology , 2008 , 26 ( 7 ): 787-793.

ENDY D . Foundations for engineering biology [J ] . Nature , 2005 , 438 ( 7067 ): 449-453.

ELOWITZ M B , LEIBLER S . A synthetic oscillatory network of transcriptional regulators [J ] . Nature , 2000 , 403 ( 6767 ): 335-338.

GARDNER T S , CANTOR C R , Collins J J . Construction of a genetic toggle switch in Escherichia coli [J ] . Nature , 2000 , 403 ( 6767 ): 339-342.

BASHOR C J , HORWITZ A A , PEISAJOVICH S G , et al . Rewiring cells: synthetic biology as a tool to interrogate the organizational principles of living systems [J ] . Annual Review of Biophysics , 2010 , 39 : 515-537.

MAYO A E , SETTY Y , SHAVIT S , et al . Plasticity of the cis-regulatory input function of a gene [J ] . PLoS Biology , 2006 , 4 ( 4 ):555-561.

ANDERSON J C , VOIGT C A , ARKIN A P . Environmental signal integration by a modular AND gate [J ] . Molecular Systems Biology , 2007 , 3 ( 1 ): e133.

TAMSIR A , TABOR J J , VOIGT C A . Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’ [J ] . Nature , 2011 , 469 ( 7329 ): 212-215.

MOON T S , LOU C , TAMSIR A , et al . Genetic programs constructed from layered logic gates in single cells [J ] . Nature , 2012 , 491 ( 7423 ): 249-253.

LOU C , LIU X , NI M , et al . Synthesizing a novel genetic sequential logic circuit: a push‐on push‐off switch [J ] . Molecular Systems Biology , 2010 , 6 ( 1 ): e350.

WANG B , KITNEY R I , JOLY N , et al . Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology [J ] . Nature Communications , 2011 , 2 ( 1 ): 1-9.

BALAGADDÉ F K , SONG H , OZAKI J , et al . A synthetic Escherichia coli predator-prey ecosystem [J ] . Molecular Systems Biology , 2008 , 4 ( 1 ): e187.

MARTIN V J J , PITERA D J , WITHERS S T , et al . Engineering a mevalonate pathway in Escherichia coli for pro duction of terpenoids [J ] . Nature Biotechnology , 2003 , 21 ( 7 ): 796-802.

RO D K , PARADISE E M , OUELLET M , et al . Production of the antimalarial drug precursor artemisinic acid in engineered yeast [J ] . Nature , 2006 , 440 ( 7086 ): 940-943.

ZHANG H , LIN M , SHI H , et al . Programming a Pavlovian-like conditioning circuit in Escherichia coli [J ] . Nature Communications , 2014 , 5 ( 1 ): 1-10.

MATSUURA S , ONO H , KAWASAKI S , et al . Synthetic RNA-based logic computation in mammalian cells [J ] . Nature Communications , 2018 , 9 ( 1 ): 1-8.

LIU W , CREMER J , LI D , et al . An evolutionarily stable strategy to colonize spatially extended habitats [J ] . Nature , 2019 , 575 ( 7784 ): 664-668.

BASHOR C J , PATEL N , CHOUBEY S , et al . Complex signal processing in synthetic gene circuits using cooperative regulatory assemblies [J ] . Science , 2019 , 364 ( 6440 ): 593-597.

SHAO Y , LU N , WU Z , et al . Creating a functional single-chromosome yeast [J ] . Nature , 2018 , 560 ( 7718 ): 331-335.

MCKAY M D , BECKMAN R J , Conover W J . A comparison of three methods for selecting values of input variables in the analysis of output from a computer code [J ] . Technometrics , 2000 , 42 ( 1 ): 55-61.

MA W , TRUSINA A , El-SAMAD H , et al . Defining network topologies that can achieve biochemical adaptation [J ] . Cell , 2009 , 138 ( 4 ): 760-773.

MA W , LAI L , OUYANG Q , et al . Robustness and modular design of the Drosophila segment polarity network [J ] . Molecular Systems Biology , 2006 , 2 ( 1 ): e70.

YAN L , OUYANG Q , WANG H . Dose-response aligned circuits in signaling systems [J ] . PLoS One , 2012 , 7 ( 4 ): e34727.

CHAU A H , WALTER J M , GERARDIN J , et al . Designing synthetic regulatory networks capable of self-organizing cell polarization [J ] . Cell , 2012 , 151 ( 2 ): 320-332.

ZHENG M M , SHAO B , OUYANG Q . Identifying network topologies that can generate turing pattern [J ] . Journal of Theoretical Biology , 2016 , 408 : 88-96.

WU L , OUYANG Q , WANG H . Robust network topologies for generating oscillations with temperature-independent periods [J ] . PLoS One , 2017 , 12 ( 2 ): e0171263.

GERARDIN J , REDDY N R , LIM W A . The design principles of biochemical timers: circuits that discriminate between transient and sustained stimulation [J ] . Cell Systems , 2019 , 9 ( 3 ): 297-308.

GUET C C , ELOWITZ M B , HSING W , et al . Combinatorial synthesis of genetic networks [J ] . Science , 2002 , 296 ( 5572 ): 1466-1470.

MANGAN S , ALON U . Structure and function of the feed-forward loop network motif [J ] . PNAS , 2003 , 100 ( 21 ): 11980-11985.

WHITAKER W R , DAVIS S A , ARKIN A P , et al . Engineering robust control of two-component system phosphotransfer using modular scaffolds [J ] . PNAS , 2012 , 109 ( 4 ): 18090-18095.

习静怡 . 生物网络逆向工程的子网络合并法以及生物系统中的量子热力学 [D ] . 北京：北京大学， 2017 .

XI J Y . Sub-network combination in biological network reverse engineering and quantum thermodynamics in biological systems [D ] . Beijing : Peking University , 2017 .

XI J Y , OUYANG Q . Using sub-network combinations to scale up an enumeration method for determining the network structures of biological functions [J ] . PLoS One , 2016 , 11 ( 12 )： e0168214.

WU L , WANG H , OUYANG Q . Constructing network topologies for multiple signal-encoding functions [J ] . BMC Systems Biology , 2019 , 13 ( 1 ): 6.

ZENG W , DU P , LOU Q , et al . Rational design of an ultrasensitive quorum-sensing switch [J ] . ACS Synthetic Biology , 2017 , 6 ( 8 ): 1445-1452.

曾维倩 . 基于逆向工程的超敏细胞密度开关的理性设计 [D ] . 北京 : 北京大学， 2017 .

ZENG W Q . Rational design of an ultrasensitive cell density switch based on reverse engineering [D ] . Beijing : Peking University , 2017 .

LI F , LONG T , LU Y , et al . The yeast cell-cycle network is robustly designed [J ] . PNAS , 2004 , 101 ( 14 ): 4781-4786.

WANG G , DU C , CHEN H , et al . Process-based network decomposition reveals backbone motif structure [J ] . PNAS , 2010 , 107 ( 23 ): 10478-10483.

张晓萌 . 布尔网络动力学研究及其反向工程 [D ] . 北京 : 北京大学 , 2011 .

ZHANG X M . Dynamics and reverse engineering of Boolean network [D ] . Beijing : Peking University , 2011 .

ZHANG X , SHAO B , WU Y , et al . A reverse engineering approach to optimize experiments for the construction of biological regulatory networks [J ] . PLoS One , 2013 , 8 ( 9 )： e75931.

SHAO B , WU J , TIAN B , et al . Minimum network constraint on reverse engineering to develop biological regulatory networks [J ] . Journal of Theoretical Biology , 2015 , 380 : 9-15.

WU Y , ZHANG X , YU J , et al . Identification of a topological characteristic responsible for the biological robustness of regulatory networks [J ] . PLoS Computational Biology , 2009 , 5 ( 7 ): e1000442.

邵斌 . 生物网络逆向工程及其应用 [D ] . 北京 : 北京大学， 2016 .

SHAO B . Biological network reverse engineering and its applications [D ] . Beijing : Peking University , 2016 .

SHAO B , LIU X , ZHANG D , et al . From Boolean network model to continuous model helps in design of functional circuits [J ] . PLoS One , 2015 , 10 ( 6 ):e0128630.

张浩千 . 细菌转录调控线路的精准制造 [D ] . 北京 : 北京大学， 2016 .

ZHANG H Q . High-precision manufacturing of transcriptional regulatory circuits in bacteria [D ] . Beijing : Peking University , 2016 .

ZONG Y Q , ZHANG H M , LYU C , et al . Insulated transcriptional elements enable precise design of genetic circuits [J ] . Nature Communications , 2017 , 8 ( 1 ): 1-13.

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