From genetic architecture to adaptation dynamics

从遗传结构到适应动力学

基本信息

批准号：
7478548
负责人：
KATHLEEN S MATTHEWS
金额：
$ 28.33万
依托单位：
RICE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-08-01 至 2010-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7478548
关键词：
Accounting Affect Affinity Algorithms Architecture Behavior Binding Biological Models Cell Adhesion Cell Cycle Kinetics Cells Characteristics Complex Condition Coupled Coupling Data Dependence Drug Formulations Equilibrium Experimental Models Flow Cytometry Fluorescence Microscopy Gene Expression Regulation Genes Genetic Genetic Heterogeneity Germ Cells Green Fluorescent Proteins Individual Lac Operon Microscopy Modeling Modification Molecular Biology Techniques Phenotype Population Population Distributions Population Heterogeneity Regulator Genes Relative (related person)Reporter Research Personnel Source Structure Surface Synthetic Genes System Techniques Temperature Testing Validation Variant Video Microscopy base cell population study computer framework environmental change neglect programs promoter research study response simulation

项目摘要

DESCRIPTION (provided by applicant): The overarching objective of the proposed theoretical and experimental studies is to elucidate the complex relationship between genetic architecture and the ability of a cell population to adapt to environmental challenges. Adaptation is tightly coupled with the dynamics of regulatory networks, which, in turn, determine the phenotype of each individual cell. However, cell populations are heterogeneous systems in the sense that phenotypic responses vary between genetically identical cells. To study cell population heterogeneity and its relationship to regulation of gene expression, we developed a general cell population balance modeling framework and the numerical algorithms necessary for its efficient simulation. We also employed flow cytometry and microscopy to study the distribution characteristics of E.coli cell populations. The E.coli cells contained an artificial genetic network, known as the genetic toggle, consisting of two promoter-repressor pairs and the green fluorescent protein (GFP) as a reporter. Both the experimental and simulation results indicated that neglecting population heterogeneity leads to significant qualitative and quantitative errors in predicting system behavior. In addition, we applied our modeling and computational framework to the well-characterized lac operon system and studied the effects that a) systemic parameters such as binding affinities and promoter strengths, b) operating conditions, and c) specific modifications of network topology have on the distribution of cellular phenotypes. Moreover, the modeling/computational framework was used to study the dependence of adaptation dynamics on the initial cell distribution characteristics. Our preliminary studies led to the formulation of the following hypotheses: A) The structure of regulatory networks as well as their systemic characteristics, will vastly influence the distribution characteristics of heterogeneous cell populations and B) The initial distribution characteristics of heterogeneous cell populations will have a profound, predictable impact on the dynamics of adaptation to sudden changes in environmental conditions. To test these hypotheses, we propose to develop an integrated modeling and experimental framework. We will use the lac operon genetic network as well as its combination with two specific artificial genetic networks as our model systems. The comparison between modeling and experimental results will be used for model validation and refinement.

描述（由申请人提供）：所提出的理论和实验研究的总体目标是阐明遗传结构与细胞种群适应环境挑战之间的复杂关系。适应性与调节网络的动力学紧密结合，从而确定每个单个单元的表型。然而，细胞群是异质系统，从遗传相同细胞之间的表型反应变化。为了研究细胞种群的异质性及其与基因表达的调节的关系，我们开发了一种一般细胞种群平衡建模框架和其有效模拟所需的数值算法。我们还采用流式细胞术和显微镜研究大肠杆菌细胞群的分布特征。大肠杆菌细胞包含一个人工遗传网络，称为遗传切换，由两个启动子压迫剂对组成，绿色荧光蛋白（GFP）作为记者。实验和仿真结果都表明，忽略人口异质性会导致预测系统行为的重大定性和定量错误。此外，我们将建模和计算框架应用于特征良好的LAC操纵子系统，并研究了a）诸如结合亲密关系和启动子强度的系统性参数，b）操作条件以及c）网络拓扑的特定修饰对细胞表型的分布。此外，使用建模/计算框架来研究适应动力学对初始细胞分布特征的依赖性。我们的初步研究导致了以下假设的制定：a）调节网络及其系统特征的结构将极大地影响异质细胞群体的分布特征，b）异质细胞种群的初始分布特征将对环境条件突然变化的适应动态产生深远的可预测影响。为了检验这些假设，我们建议开发一个集成的建模和实验框架。我们将使用LAC操纵子遗传网络，并将其与两个特定的人工遗传网络作为模型系统结合使用。建模和实验结果之间的比较将用于模型验证和改进。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Stochastic and deterministic simulations of heterogeneous cell population dynamics.

异质细胞群动态的随机和确定性模拟。

DOI：
10.1016/j.jtbi.2006.01.005
发表时间：
2006
期刊：
Journal of theoretical biology
影响因子：
2
作者：
Mantzaris,NikosV
通讯作者：
Mantzaris,NikosV

Cell population heterogeneity in expression of a gene-switching network with fluorescent markers of different half-lives.

具有不同半衰期的荧光标记的基因开关网络表达的细胞群异质性。

DOI：
10.1016/j.jbiotec.2006.09.026
发表时间：
2007
期刊：
Journal of biotechnology
影响因子：
4.1
作者：
Portle,Stephanie;Causey,ThomasB;Wolf,Kim;Bennett,GeorgeN;San,Ka-Yiu;Mantzaris,Nikos
通讯作者：
Mantzaris,Nikos

Environmentally-modulated changes in fluorescence distribution in cells with oscillatory genetic network dynamics.