生物分子网络的建模与动力学分析
摘要
本文就生物分子网络的建模与动力学分析方面做了一些相关的工作。首先,对相关的研究内容作一简单的介绍,包括系统生物学和合成生物学简介、生物分子网络简介、microRNAs简介、化学反应动力学简介以及分岔理论简介；然后,介绍了本文的研究工作,可以概括为以下两个方面：
(1) MicroRNA介导的混合反馈环诱导双稳态和振荡的机制
过去,人们一直认为在所有生物体中基因表达的调控都是调控蛋白的任务。因此,关于基因调控的大部分研究主要是集中在转录调控和翻译后调控上近年来,由于大规模实验和计算技术的发展,研究人员发现了越来越多通过非编码RNA实现的转录后调控。现在人们已经认识到,转录后调控在细胞内几乎所有细胞过程中都起到非常重要的调控作用。MicroRNAs是一类长度约为22核苷酸的单链小分子非编码RNA。当参与细胞过程时,microRNAs主要是通过与靶mRNAs的碱基互补配对而在转录后水平上对基因的表达进行负调控,最终导致靶mRNAs编码的蛋白质表达水平的下降。近来的计算和实验研究发现了大量microRNAs和转录因子共同参与的网络模体。最简单microRNA介导的模体是由一个microRNA和一个转录因子组成的混合反馈环(MFL),其中转录因子调控microRNA的表达,而转录因子本身受这个microRNA的负调控。我们基于简单的生化调控对MFL进行数学建模,并通过分岔分析对MFL模型的动力学行为进行详细的研究。研究结果表明,依赖于转录因子是抑制子或激活子,MFL可以充当双稳态开关或振子。这个功能特征与microRNAs普遍存在于诸如增殖、分化以及凋亡等发育过程是相符合的。有趣的是,我们发现在转录因子和nicroRNA的相互作用下,即使没有转录因子的协同绑定,MFL模型也可以在大参数范围内充当双稳态开关。另外,MFL模型中microRNA诱导的振荡既不需要一个额外的正反馈环,也不需要基因的自激活、转录因子的协同绑定以及饱和降解。因此,MFL可能提供了一个一般网络结构来诱导双稳态或振荡。我们期望这个结果可以为microRNAs如何调控基因的表达提供新的观点,并进一步指导实验。另外,我们也期望本研究可以为探讨由简单模块组装成的更复杂的生物分子网络提供基础。
(2)生物分子系统中各种细胞信号形成的方式：耦合开关与振子
随着关于调控元件和相互作用的生物数据快速的积累,生物分子网络变得越来越错综复杂。因此,要理解这些复杂生物分子网络的动力学特征,仅靠直觉推理是不可能的。为了理解一个复杂生物分子网络是如何实现其功能的,一般需要对该网络进行准确的分解和整合,以便为该网络的各种动力学行为的调控机制和定性信息提供新的见解。遗憾的是,到目前为止还没有通用的准则可以说明如何将一个复杂的网络分解成简单的模块。一种可选的方法是,先将一个复杂的网络解耦为具有特定功能的小模块或子系统,例如开关和振子；然后通过分析它们之间的相互作用来整合它们。我们通过一个具体的双向耦合网络,即耦合拨动开关和压制振子,并分析该网络的各种动力学行为来说明该方法的主要思想。虽然这种方法可能对一般的生物分子网络也成立。研究结果表明,通过调节子系统之间的耦合可以产生生物分子系统中的各种细胞信号。我们希望这里提出的方法可以有助于简化和分析更加复杂的生物分子网络。
This thesis is devoted to study some related work on the modeling and dynami-cal analysis of biomolecular networks. Firstly, a brief description of relevant researchcontexts is given, including the systems biology and synthetic biology, biomolecularnetworks, microRNA, as well as chemical reactive dynamics and bifurcation theory.Secondly, the research work of the thesis is introduced, which focuses mainly on thefollowing two aspects:
(1) Mechanisms generating bistability and oscillations in microRNA-mediated mo-tifs
In the past, it was believed that the regulation of gene expression is a task of reg-ulatory proteins in all organisms, and thus most research on gene regulation focusedmainly on transcriptional and post-translational regulations. In recent years, a post-transcriptional regulation manifested by small noncoding RNAs is being uncovered dueto the development of large-scale experimental and computational techniques. It has beenrecognized that the post-transcriptional regulation plays important roles in the regulationof many cellular processes. MicroRNAs are a class of about22-nucleotide non-codingRNAs. When participating in cellular processes, microRNAs mainly regulate gene ex-pression post-transcriptionally through canonical base pairing to its target mRNAs, ul-timately leading to a reduction in the levels of protein encoded by the target mRNAs.Recently computational and experimental studies have identified an abundance of mo-tifs involving microRNAs and transcriptional factors. The simplest motif is a two-nodemicroRNA-mediated feedback loop (MFL) in which a transcriptional factor regulates anmicroRNA and the transcriptional factor itself is negatively regulated by the microRNA.Here we present a general computational model for the MFL based on biochemical reg-ulations and explore its dynamics by using bifurcation analysis. Our results show thatthe MFL can behave either as switches or as oscillators, depending on the transcrip-tional factor as a repressor or an activator. These functional features are consistent withthe widespread appearance of microRNAs in fate decisions such as proliferation, dif-ferentiation, and apoptosis during development. We found that under the interplay of atranscriptional factor and an microRNA, the MFL model can behave as switches for wideranges of parameters even without cooperative binding of the transcriptional factor. Inaddition, oscillations induced by the microRNA in the MFL model require neither an ad-ditional positive feedback loop, nor self-activation of the gene, nor cooperative bindingof the transcriptional factor, nor saturated degradation. Therefore, the MFL may providea general network structure to induce bistability or oscillations. It is hoped that the resultspresented here will provide a new view on how gene expression is regulated by microR-NAs and further guidance for experiments. Moreover, the insight gained from this studyis also expected to provide a basis for the investigation of more complex biomolecularnetworks assembled by simple building blocks.
(2) Coupling switches and oscillators as a means to shape cellular signals inbiomolecular systems
As biological data on regulatory components and interactions are quickly accu-mulating, biomolecular networks underlying cellular functions are becoming more andmore complicated. Dynamical properties of these complicated biomolecular networksare impossible to understand by intuitive reasoning alone. To understand how a com-plex biomolecular network functions, a decomposition or a reconstruction process of thenetwork is often needed so as to provide new insights into the regulatory mechanismsunderlying various dynamical behaviors and also to gain qualitative knowledge of thenetwork. Unfortunately, it seems that there are still no general rules on how to decom-pose a complex network into simple modules. An alternative resolution is to decomposea complex network into small modules or subsystems with specified functions such asswitches and oscillators and then integrate them by analyzing the interactions betweenthem. The main idea of this approach can be illustrated by consider-ing a bidirectionallycoupled network in this paper, i.e., coupled Toggle switch and Repressilator, and analyz-ing the occurrence of various dynamics, although the theoretical principle may hold fora general class of networks. We show that various biomolecular signals can be shapedby regulating the coupling between the subsystems. The approach presented here can beexpected to simplify and analyze even more complex biomolecular networks.
(1) MicroRNA介导的混合反馈环诱导双稳态和振荡的机制
过去,人们一直认为在所有生物体中基因表达的调控都是调控蛋白的任务。因此,关于基因调控的大部分研究主要是集中在转录调控和翻译后调控上近年来,由于大规模实验和计算技术的发展,研究人员发现了越来越多通过非编码RNA实现的转录后调控。现在人们已经认识到,转录后调控在细胞内几乎所有细胞过程中都起到非常重要的调控作用。MicroRNAs是一类长度约为22核苷酸的单链小分子非编码RNA。当参与细胞过程时,microRNAs主要是通过与靶mRNAs的碱基互补配对而在转录后水平上对基因的表达进行负调控,最终导致靶mRNAs编码的蛋白质表达水平的下降。近来的计算和实验研究发现了大量microRNAs和转录因子共同参与的网络模体。最简单microRNA介导的模体是由一个microRNA和一个转录因子组成的混合反馈环(MFL),其中转录因子调控microRNA的表达,而转录因子本身受这个microRNA的负调控。我们基于简单的生化调控对MFL进行数学建模,并通过分岔分析对MFL模型的动力学行为进行详细的研究。研究结果表明,依赖于转录因子是抑制子或激活子,MFL可以充当双稳态开关或振子。这个功能特征与microRNAs普遍存在于诸如增殖、分化以及凋亡等发育过程是相符合的。有趣的是,我们发现在转录因子和nicroRNA的相互作用下,即使没有转录因子的协同绑定,MFL模型也可以在大参数范围内充当双稳态开关。另外,MFL模型中microRNA诱导的振荡既不需要一个额外的正反馈环,也不需要基因的自激活、转录因子的协同绑定以及饱和降解。因此,MFL可能提供了一个一般网络结构来诱导双稳态或振荡。我们期望这个结果可以为microRNAs如何调控基因的表达提供新的观点,并进一步指导实验。另外,我们也期望本研究可以为探讨由简单模块组装成的更复杂的生物分子网络提供基础。
(2)生物分子系统中各种细胞信号形成的方式：耦合开关与振子
随着关于调控元件和相互作用的生物数据快速的积累,生物分子网络变得越来越错综复杂。因此,要理解这些复杂生物分子网络的动力学特征,仅靠直觉推理是不可能的。为了理解一个复杂生物分子网络是如何实现其功能的,一般需要对该网络进行准确的分解和整合,以便为该网络的各种动力学行为的调控机制和定性信息提供新的见解。遗憾的是,到目前为止还没有通用的准则可以说明如何将一个复杂的网络分解成简单的模块。一种可选的方法是,先将一个复杂的网络解耦为具有特定功能的小模块或子系统,例如开关和振子；然后通过分析它们之间的相互作用来整合它们。我们通过一个具体的双向耦合网络,即耦合拨动开关和压制振子,并分析该网络的各种动力学行为来说明该方法的主要思想。虽然这种方法可能对一般的生物分子网络也成立。研究结果表明,通过调节子系统之间的耦合可以产生生物分子系统中的各种细胞信号。我们希望这里提出的方法可以有助于简化和分析更加复杂的生物分子网络。
This thesis is devoted to study some related work on the modeling and dynami-cal analysis of biomolecular networks. Firstly, a brief description of relevant researchcontexts is given, including the systems biology and synthetic biology, biomolecularnetworks, microRNA, as well as chemical reactive dynamics and bifurcation theory.Secondly, the research work of the thesis is introduced, which focuses mainly on thefollowing two aspects:
(1) Mechanisms generating bistability and oscillations in microRNA-mediated mo-tifs
In the past, it was believed that the regulation of gene expression is a task of reg-ulatory proteins in all organisms, and thus most research on gene regulation focusedmainly on transcriptional and post-translational regulations. In recent years, a post-transcriptional regulation manifested by small noncoding RNAs is being uncovered dueto the development of large-scale experimental and computational techniques. It has beenrecognized that the post-transcriptional regulation plays important roles in the regulationof many cellular processes. MicroRNAs are a class of about22-nucleotide non-codingRNAs. When participating in cellular processes, microRNAs mainly regulate gene ex-pression post-transcriptionally through canonical base pairing to its target mRNAs, ul-timately leading to a reduction in the levels of protein encoded by the target mRNAs.Recently computational and experimental studies have identified an abundance of mo-tifs involving microRNAs and transcriptional factors. The simplest motif is a two-nodemicroRNA-mediated feedback loop (MFL) in which a transcriptional factor regulates anmicroRNA and the transcriptional factor itself is negatively regulated by the microRNA.Here we present a general computational model for the MFL based on biochemical reg-ulations and explore its dynamics by using bifurcation analysis. Our results show thatthe MFL can behave either as switches or as oscillators, depending on the transcrip-tional factor as a repressor or an activator. These functional features are consistent withthe widespread appearance of microRNAs in fate decisions such as proliferation, dif-ferentiation, and apoptosis during development. We found that under the interplay of atranscriptional factor and an microRNA, the MFL model can behave as switches for wideranges of parameters even without cooperative binding of the transcriptional factor. Inaddition, oscillations induced by the microRNA in the MFL model require neither an ad-ditional positive feedback loop, nor self-activation of the gene, nor cooperative bindingof the transcriptional factor, nor saturated degradation. Therefore, the MFL may providea general network structure to induce bistability or oscillations. It is hoped that the resultspresented here will provide a new view on how gene expression is regulated by microR-NAs and further guidance for experiments. Moreover, the insight gained from this studyis also expected to provide a basis for the investigation of more complex biomolecularnetworks assembled by simple building blocks.
(2) Coupling switches and oscillators as a means to shape cellular signals inbiomolecular systems
As biological data on regulatory components and interactions are quickly accu-mulating, biomolecular networks underlying cellular functions are becoming more andmore complicated. Dynamical properties of these complicated biomolecular networksare impossible to understand by intuitive reasoning alone. To understand how a com-plex biomolecular network functions, a decomposition or a reconstruction process of thenetwork is often needed so as to provide new insights into the regulatory mechanismsunderlying various dynamical behaviors and also to gain qualitative knowledge of thenetwork. Unfortunately, it seems that there are still no general rules on how to decom-pose a complex network into simple modules. An alternative resolution is to decomposea complex network into small modules or subsystems with specified functions such asswitches and oscillators and then integrate them by analyzing the interactions betweenthem. The main idea of this approach can be illustrated by consider-ing a bidirectionallycoupled network in this paper, i.e., coupled Toggle switch and Repressilator, and analyz-ing the occurrence of various dynamics, although the theoretical principle may hold fora general class of networks. We show that various biomolecular signals can be shapedby regulating the coupling between the subsystems. The approach presented here can beexpected to simplify and analyze even more complex biomolecular networks.
引文
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