基于细胞 — 计算机交互的细胞控制方法

颜钱明; 张鹏程; 乔榕; 古槿; 汪小我

doi:10.16383/j.aas.c190528

基于细胞 — 计算机交互的细胞控制方法

doi: 10.16383/j.aas.c190528

颜钱明^{1, 2,},
张鹏程^{1, 2,},
乔榕^{1, 2,},
古槿^{1, 2,},
汪小我^{1, 2,}

1.
清华大学自动化系合成与系统生物学研究中心, 生物信息学教育部重点实验室北京 100084
2.
北京信息科学与技术国家研究中心生物信息学研究部北京 100084

基金项目: 国家自然科学基金(61773230, 61721003)资助

详细信息

作者简介:
颜钱明：清华大学自动化系博士研究生. 2018年获得清华大学自动化系学士学位. 主要研究方向为生物系统的建模与控制, 细胞与计算机的耦合控制. E-mail: yanqm18@mails.tsinghua.edu.cn

张鹏程：清华大学自动化系博士研究生. 2018年获得北京理工大学生命学院学士学位. 主要研究方向为光遗传学与细胞控制. E-mail: zhangpc18@mails.tsinghua.edu.cn

乔榕：清华大学自动化系硕士研究生. 2018年获得吉林大学通信工程学院学士学位. 主要研究方向为分子竞争调控网络的计算. E-mail: qiaor18@mails.tsinghua.edu.cn

古槿：清华大学自动化系副教授. 2009年于清华大学自动化系获得工学博士学位. 主要研究方向为生物信息学与机器学习. E-mail: jgu@tsinghua.edu.cn

汪小我：清华大学自动化系长聘教授. 分别于2003年和2008年获得清华大学学士和博士学位. 主要研究方向为生物系统的建模与控制, 模式识别与机器学习. 本文通信作者. E-mail: xwwang@tsinghua.edu.cn

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出版历程
- 收稿日期: 2019-07-15
- 录用日期: 2019-10-16
- 刊出日期: 2021-04-02

Control Cells Based on Cell-Computer Interfacing

YAN Qian-Ming^{1, 2
,},
ZHANG Peng-Cheng^{1, 2
,},
QIAO Rong^{1, 2
,},
GU Jin^{1, 2
,},
WANG Xiao-Wo^{1, 2
,}

1.
Ministry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084
2.
Bioinformation Division, Beijing National Research Center for Information Science and Technology, Beijing 100084

Funds: Supported by National Natural Science Foundation of China (61773230, 61721003)

More Information

Author Bio:
YAN Qian-Ming　Ph.D. candidate in the Department of Automation, Tsinghua University. He received his bachelor degree from the Department of Automation, Tsinghua University in 2018. His research interest covers modeling and control of biological systems, and coupling control of cells and computer

ZHANG Peng-Cheng　Ph.D. candidate in the Department of Automation, Tsinghua University. He received his bachelor degree from Beijing Institute of Technology in 2018. His research interest covers optogenetics and cell control

QIAO Rong　Master student in the Department of Automation, Tsinghua University. She received her bachelor degree from Jilin University in 2018. Her research interest covers computation with competition in molecular regulatory network

GU Jin　Associate professor in the Department of Automation, Tsinghua University. He received his Ph.D. degree from the Department of Automation, Tsinghua University in 2009. His research interest covers bioinformatics and machine learning

WANG Xiao-Wo　Professor in the Department of Automation, Tsinghua University. He received his bachelor and Ph.D. degrees from Tsinghua University in 2003 and 2008, respectively. His research interest covers modeling and control of biological systems, pattern recognition, and machine learning. Corresponding author of this paper

摘要

摘要:
Wiener在控制论(Cybernetics)中强调了两大类控制对象: 机器与动物. 半个世纪以来, 机器控制领域已形成一套较为完备且先进的控制理论, 而在生物控制方面, 由于生物系统的特殊性和复杂性, 对生命的基本组成单位—细胞的控制仍然进展缓慢. 近年来, 随着合成生物学技术的发展, 基于细胞—计算机交互的胞外控制手段开始引起研究者们的关注, 为细胞控制带来了前所未有的机遇. 胞机交互的方式能够适应生物系统的特殊性, 发挥计算机控制的优势, 实现细胞的自动化实时控制, 为人类研究细胞内部基因调控机制与其他各项生命活动提供了大量的数据与方法支持. 本文根据目前基于胞机交互的细胞控制工作, 归纳与总结了胞机交互中常用的生物学工具以及控制算法, 分析了细胞控制的特殊性与难点, 指出研究实现细胞智能控制的可行性与重要性.
- 胞机交互 /
- 反馈控制 /
- 合成生物学 /
- 人工生物系统 /
- 光遗传学
Abstract:
Wiener emphasized two major categories of control objects in cybernetics: machines and animals. In the past half century, a relatively complete and advanced control theory has been formed in the field of machine control. However, due to the particularity and complexity of biological systems, the control of cell, the basic unit of life, is still progressing slowly. In recent years, with the development of synthetic biology tools, in silico control methods based on cell-computer interfacing has drawn researchers＇ attention, bringing unprecedented opportunities for cell control. These methods can adapt to the particularity of biological system, take advantages of in silico control, realize automatic real-time cell control and provide a large amount of data and methods for human research on endogenous gene regulation mechanism or other activities. Based on current progress, this review summarized the biological tools and control algorithms used in cell-machine interfacing, illustrated the particularities and difficulties and pointed out the feasibility and importance to achieve intelligent cell control.
- Cell-computer interfacing /
- feedback control /
- synthetic biology /
- artificial biosystem /
- optogenetics

HTML全文

图 1 利用人工合成基因线路控制细胞的基因表达

Fig. 1 Control gene expression using artificial synthetic gene circuits

下载: 全尺寸图片幻灯片

图 2 胞机交互系统示意图

Fig. 2 A scheme for cell-computer interface

下载: 全尺寸图片幻灯片

图 3 利用光遗传学工具控制细胞的基因表达

Fig. 3 Control gene expression using optogenetic tools

下载: 全尺寸图片幻灯片

表 1 细胞控制常用控制算法优缺点比较

Table 1 Pros and cons of several control algorithms in cell control

控制算法	是否需要精确建模	优点	缺点
PID控制	否	稳定性好, 计算简便, 不依赖模型	在快速变化的、长时延的系统上效果较差
模型预测控制	是	适用于时变的、有时延的系统, 能够预测未来状态	计算复杂度高, 易受噪声影响, 建模过程繁琐
起停式控制	否	结构最简单方便	控制动作不连续, 容易造成系统振荡
ZAD控制	是	适用于时变的、有时延的系统, 减少了输入开关数量	在快速变化系统中的表现略逊于模型预测控制^[20]

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