Comparative analysis of information transfer in NF-kapppaB and MAPK pathways

NF-kapppaB 和 MAPK 通路信息传递的比较分析

• 批准号: 8544477
• 负责人: Andre Levchenko
• 金额: $ 7.72万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-05 至 2013-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8544477
• 关键词: Accounting; Address; Affect; Biochemical; Biochemical Process; Biochemical Reaction; Biophysical Process; Cell Communication; Cell Differentiation process; Cell Signaling Process; Cell Surface Receptors; Cell Survival; Cells; Cellular Stress Response; Chemicals; Communication; Complex; Computer Analysis; Computer Simulation; Conflict (Psychology); Coupling; Decision Making; Detection; Development; Disease; Environment; Environmental Exposure; Event; Feedback; Funding; Gene Expression; Gene Expression Regulation; Genes; Genome; Immune System Diseases; Immune response; Immune system; Individual; Inflammation; Information Theory; Investigation; Learning; Life; MAP Kinase Gene; MAPK8 gene; Malignant Neoplasms; Mammalian Cell; Mediating; Methods; Microfluidic Microchips; Mission; Modeling; Molecular; NF-kappa B; Organism; Outcome; Output; Pathway interactions; Population; Positioning Attribute; Process; Property; Protein Isoforms; Proteins; Recording of previous events; Regulation; Relative (related person); Research; Role; Sensory; Signal Pathway; Signal Transduction; Signaling Molecule; Stimulus; System; Systems Analysis; Tissues; Transcription Factor AP-1; Tumor Necrosis Factor-alpha; Work; base; cell type; chemokine; comparative; drug development; experimental analysis; human disease; improved; in vivo; information processing; mathematical model; novel; programs; public health relevance; receptor; research study; response; success; tool

DESCRIPTION (provided by applicant): All living cells are capable of extracting information from their micro-environment and mounting appropriate responses to a variety of associated challenges. The underlying signal transduction networks can be quite complex, necessitating for their unraveling a combination of sophisticated computational modeling and precise experimentation. Unfortunately, current computational and experimental analysis of cell signaling frequently suffers from such pitfalls as isolation of a pathway from surrounding signaling network, disregard of the cell-cell variability in the signaling outputs or studying signaling out of the context provided of by cell-cell communication in the native tissues. This renewal proposal is aimed at providing a framework for addressing these research limitations through development of novel methods and tools, and putting forward a detailed plan of a more realistic integrative analysis of signaling in response to a chemokine, tumor necrosis factor (TNF). A particular emphasis of our analysis will be on understanding of the information transfer properties of signaling pathways and its role in defining the precision of the phenotypic outcomes, including regulation of gene expression. The results of the analysis will provide a new platform for investigation of the relationship between the single cell and population responses and drive the development of the information theory based understanding of intracellular signal processing and cell communication. We anticipate that the quantitative understanding of the complexity of signaling cross-talk, regulation of diversity of cell responses to the same stimulus and nuances of cell-cell communication will facilitate development of a more realistic framework for understanding of the human disease, including functioning of the immune system, and drug development aimed at regulation of the NF-kappaB and JNK signaling. PUBLIC HEALTH RELEVANCE: Cells respond to their external environment by extracting information out of chemical signals they receive from other cells. This leads to changes in protein activity and gene expression, ultimately deciding the function and fate of the cell. These responses are complicated by differences between individual cells as well as communication between cells. Understanding the responses may benefit from analyses that combine experiment and mathematical modeling. In this context, we propose to study in detail two signals induced by inflammation in mammalian cells. Through such analyses we anticipate to uncover novel principles and mechanisms by which cells respond to external stimuli.

描述（由申请人提供）：所有活细胞都能够从其微环境中提取信息，并对各种相关挑战进行适当的反应。基础信号转导网络可能非常复杂，这是必要的，以阐明复杂的计算建模和精确实验的结合。不幸的是，电池信号传导的当前计算和实验分析经常受到诸如从周围信号网络中隔离途径的陷阱，无视信号输出中的细胞细胞可变性或从天然组织中细胞细胞通信提供的上下文中研究信号传导。该更新建议旨在提供一个框架，通过开发新方法和工具来解决这些研究局限性，并为响应趋化因子，肿瘤坏死因子（TNF）提出了对信号传导更现实的综合分析的详细计划。我们的分析的一个特殊重点将是了解信号通路的信息传递特性及其在定义表型结果的精度（包括基因表达的调节）中的作用。分析的结果将为调查单个细胞和人群响应之间的关系提供一个新的平台，并推动基于信息理论的开发对细胞内信号处理和细胞通信的理解。我们预计，对信号传导串扰的复杂性的定量理解，细胞对相同刺激的反应多样性的调节以及细胞 - 细胞通信的差异将有助于发展更现实的框架，以理解对人类疾病的功能，包括免疫系统的功能以及旨在调节NF-Kappab和JNK信号的药物开发。 公共卫生相关性：细胞通过从其他细胞中收到的化学信号中提取信息来响应其外部环境。这导致蛋白质活性和基因表达的变化，最终决定细胞的功能和命运。这些反应因单个细胞之间的差异以及细胞之间的通信而变得复杂。了解响应可能会受益于结合实验和数学建模的分析。在这种情况下，我们建议详细研究哺乳动物细胞炎症引起的两个信号。通过这样的分析，我们预计会发现细胞对外部刺激反应的新颖原理和机制。