Quantitative Modeling of Signal Transduction in Bacterial Chemotaxis
细菌趋化信号转导的定量建模
基本信息
- 批准号:7500286
- 负责人:
- 金额:$ 18.85万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2007
- 资助国家:美国
- 起止时间:2007-09-24 至 2010-08-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAffinityBackBehaviorBiological ModelsCellsChemotaxisComplexDataData QualityDependenceDoseEnvironmentEscherichia coliFeedbackGoalsHealthHumanKineticsKnowledgeLeadLearningLengthLigandsMethylationModelingModificationMolecularMonte Carlo MethodNoiseOrganismPathway interactionsPhosphotransferasesPhysicsPhysiologic pulsePopulationPropertyPulse takingRampRangeRateRelaxationResearch PersonnelResearch Project GrantsResolutionRoleSensorySignal PathwaySignal TransductionSignal Transduction PathwayStimulusStructureSystemSystems AnalysisTestingTimebasecell typeconceptfeedingimprovedin vivointerestmutantpathogenprogramsreceptorreceptor expressionresponsesensory systemsimulationsizetool
项目摘要
Thelong term goal of this research project is to achieve quantitative, systems level understanding of the
signal transduction pathway in E. coli chemotaxis. We want to integrate the knowledge on the E. coli
chemotaxis signaling pathway over different (length and time) scales into a mathematical description (model)
of the system that can be used to explain and predict quantitatively the E. coli chemotaxis response to any
given temporal and spatial signal (stimulus). The models will be constructed based on known molecular
details of the signaling pathway and at the appropriate resolution comparable to experimental data. These
models will be studied by using statistical physics methods, Monte Carlo simulation and dynamical systems
analysis. The results from these models will be used to explain existing data, make testable predictions and
the comparison with experimental data will feed back to improve/refine the models. In this proposal, we will
fociis on two essential aspects of the E. coli chemotaxis pathway: 1) Signal amplification in the (fast) kinase
response. We are interested in finding out the structural basis for the observed signal amplification, e.g., how
many receptors each cooperative fucntional complex contains. We want to understand the molecular .
mechanism for the wide dynamic range of high sensitivity observed in E. coli chemotaxis. We want to
understand how cell achieve these excellent properties (high gain, high sensitivty over a wide range of
backgrounds) with variable (noisy) internal components. 2) Kinetics of the (slower) adaptationprocess.^We
want to understand the adaptation kinetics quantitatively, e.g.,how fast the system adapts and how the
adaptation time depends on the external stimulus strength. We want to .understand the adaptation kinetics to
time varying stimulus, such as exponential ramps with different ramp rates. Eventually, we want to be able to
model and predict the signaling pathway dynamics as the cell moves in its natural environment. :¿;
The concepts and tools developed in the quantitative, systems level modeling of a complete sensory signal
transduction pathway will be useful in understanding signaling pathways and sensory systems in higher
organisms, including human. The molecular level understanding of the bacterial chemotaxis pathway is
important to study the role of bacterial pathogens in human health. ;
这项研究项目的长期目标是实现对
大肠杆菌趋化作用中的信号转导途径。我们想要整合关于大肠杆菌的知识
不同(长度和时间)尺度上趋化信号通路的数学描述(模型)
该系统可以用来解释和定量预测大肠杆菌对任何
给定的时间和空间信号(刺激)。这些模型将基于已知的分子构建
信号通路的细节和与实验数据相当的适当分辨率。这些
将使用统计物理方法、蒙特卡罗模拟和动力系统来研究模型
分析。这些模型的结果将用于解释现有数据,做出可测试的预测,并
与实验数据的比较将反馈到改进/改进模型。在这项提案中,我们将
关于大肠杆菌趋化途径的两个基本方面:1)(快速)激酶中的信号放大
回应。我们有兴趣找出观察到的信号放大的结构基础,例如,如何
每个合作功能复合体都含有许多受体。我们想要了解分子。
在大肠杆菌趋化性中观察到的高敏感性的大动态范围的机制。我们想要
了解电池如何实现这些卓越的特性(高增益、高灵敏度
背景)具有可变(噪声)内部组件。2)(较慢)适应过程的动力学。
想要定量地了解适应动力学,例如,系统适应的速度有多快,以及
适应时间取决于外部刺激强度。我们想要了解适应动力学
时变刺激,例如具有不同斜坡速率的指数斜坡。最终,我们希望能够
模拟和预测细胞在其自然环境中运动时的信号通路动态。:?;
在对一个完整的感觉信号进行定量、系统级建模时发展起来的概念和工具
转导通路将有助于理解高等生物的信号通路和感觉系统。
生物体,包括人类。对细菌趋化途径的分子水平的理解是
重要的是研究细菌病原体在人类健康中的作用。;
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Yuhai Tu其他文献
Yuhai Tu的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Yuhai Tu', 18)}}的其他基金
Molecular Mechanisms and Biochemical Circuits for Adaptation in Biological Systems
生物系统适应的分子机制和生化回路
- 批准号:
10248476 - 财政年份:2019
- 资助金额:
$ 18.85万 - 项目类别:
Molecular Mechanisms and Biochemical Circuits for Adaptation in Biological Systems
生物系统适应的分子机制和生化回路
- 批准号:
10687856 - 财政年份:2019
- 资助金额:
$ 18.85万 - 项目类别:
Molecular Mechanisms and Biochemical Circuits for Adaptation in Biological Systems
生物系统适应的分子机制和生化回路
- 批准号:
10005386 - 财政年份:2019
- 资助金额:
$ 18.85万 - 项目类别:
Molecular Mechanisms and Biochemical Circuits for Adaptation in Biological Systems
生物系统适应的分子机制和生化回路
- 批准号:
10480082 - 财政年份:2019
- 资助金额:
$ 18.85万 - 项目类别:
Quantitative Modeling of Bacterial Chemotaxis Signaling Pathway
细菌趋化信号通路的定量建模
- 批准号:
8336875 - 财政年份:2007
- 资助金额:
$ 18.85万 - 项目类别:
Quantitative Modeling of Signal Transduction in Bacterial Chemotaxis
细菌趋化信号转导的定量建模
- 批准号:
7298572 - 财政年份:2007
- 资助金额:
$ 18.85万 - 项目类别:
Quantitative Modeling of Bacterial Chemotaxis Signaling Pathway
细菌趋化信号通路的定量建模
- 批准号:
9147598 - 财政年份:2007
- 资助金额:
$ 18.85万 - 项目类别:
Quantitative Modeling of Bacterial Chemotaxis Signaling Pathway
细菌趋化信号通路的定量建模
- 批准号:
8542863 - 财政年份:2007
- 资助金额:
$ 18.85万 - 项目类别:
Quantitative Modeling of Bacterial Chemotaxis Signaling Pathway
细菌趋化信号通路的定量建模
- 批准号:
8725183 - 财政年份:2007
- 资助金额:
$ 18.85万 - 项目类别:
Quantitative Modeling of Bacterial Chemotaxis Signaling Pathway
细菌趋化信号通路的定量建模
- 批准号:
9025262 - 财政年份:2007
- 资助金额:
$ 18.85万 - 项目类别:
相似海外基金
Construction of affinity sensors using high-speed oscillation of nanomaterials
利用纳米材料高速振荡构建亲和传感器
- 批准号:
23H01982 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
Affinity evaluation for development of polymer nanocomposites with high thermal conductivity and interfacial molecular design
高导热率聚合物纳米复合材料开发和界面分子设计的亲和力评估
- 批准号:
23KJ0116 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Grant-in-Aid for JSPS Fellows
Platform for the High Throughput Generation and Validation of Affinity Reagents
用于高通量生成和亲和试剂验证的平台
- 批准号:
10598276 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Development of High-Affinity and Selective Ligands as a Pharmacological Tool for the Dopamine D4 Receptor (D4R) Subtype Variants
开发高亲和力和选择性配体作为多巴胺 D4 受体 (D4R) 亚型变体的药理学工具
- 批准号:
10682794 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Collaborative Research: DESIGN: Co-creation of affinity groups to facilitate diverse & inclusive ornithological societies
合作研究:设计:共同创建亲和团体以促进多元化
- 批准号:
2233343 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Standard Grant
Collaborative Research: DESIGN: Co-creation of affinity groups to facilitate diverse & inclusive ornithological societies
合作研究:设计:共同创建亲和团体以促进多元化
- 批准号:
2233342 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Standard Grant
Molecular mechanisms underlying high-affinity and isotype switched antibody responses
高亲和力和同种型转换抗体反应的分子机制
- 批准号:
479363 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Operating Grants
Deconstructed T cell antigen recognition: Separation of affinity from bond lifetime
解构 T 细胞抗原识别:亲和力与键寿命的分离
- 批准号:
10681989 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
CAREER: Engineered Affinity-Based Biomaterials for Harnessing the Stem Cell Secretome
职业:基于亲和力的工程生物材料用于利用干细胞分泌组
- 批准号:
2237240 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Continuing Grant
ADVANCE Partnership: Leveraging Intersectionality and Engineering Affinity groups in Industrial Engineering and Operations Research (LINEAGE)
ADVANCE 合作伙伴关系:利用工业工程和运筹学 (LINEAGE) 领域的交叉性和工程亲和力团体
- 批准号:
2305592 - 财政年份:2023
- 资助金额:
$ 18.85万 - 项目类别:
Continuing Grant