Understanding Mechanisms of Robust Information Processing by NF-kappaB

了解 NF-kappaB 鲁棒信息处理的机制

• 批准号: 10371211
• 负责人: Savas Tay
• 金额: $ 35.53万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10371211
• 关键词: Affect; Attention; Autoimmune Diseases; Autoimmunity; Back; Bacteria; Biological; Biological Models; Biology; Buffers; CRISPR/Cas technology; Cell Culture Techniques; Cells; Cellular biology; Chronic; Complex; Data; Decision Making; Disease; Double-Stranded RNA; Environment; Feedback; Fibroblasts; Gene Expression; Gene Expression Regulation; Immune; Immune response; Immune signaling; Immunity; Individual; Infection; Inflammation; Knock-out; Ligands; Malignant Neoplasms; Maps; Measurement; Measures; Medical; MicroRNAs; Microfluidic Microchips; Microfluidics; Modeling; Molecular; NF-kappa B; Nature; Noise; Organism; Output; Pathway interactions; Pharmacology; Positioning Attribute; Process; Reporting; Role; Signal Pathway; Signal Transduction; Signaling Molecule; Small Interfering RNA; Stimulus; System; TNF gene; Techniques; Testing; Therapeutic; Tissues; Translations; Virus Diseases; Zymosan; cytokine; digital; experience; experimental study; fungus; improved; information processing; insight; knock-down; mathematical methods; mathematical model; network architecture; operation; pathogen; prevent; receptor; response; simulation; single cell analysis

Understanding Mechanisms of Robust Information Processing by NF-κB A major open question in biology is how do cells operate robustly despite ever-present biological noise? Inputs received by cells are unavoidably noisy due to variable translation and secretion of signaling factors, propagation in tissues and stochastic fluctuations in molecular concentrations. Yet, somehow cells are able to accurately process these noisy inputs and create appropriate responses regularly. This proposal aims to answer this fundamental question by studying the effect of noise on gene regulation by the well-known and medically important innate immune signaling pathway NF-B. Attempts at understanding dynamic gene regulation by NF-B and the molecular mechanisms that deal with noise have generally been hampered by significant cell-to-cell variability (requiring single cell analyses), and technical limitations in studying live cells under dynamical signals. Here, we will combine our experience in NF-B signaling, established microfluidic cell culture techniques and mathematical modeling to study this most interesting problem in single cells. Our lab is uniquely positioned to explore and answer this new field, as we have spent the last 10 years constructing and improving the experimental and mathematical methods to study the effect of noise in cellular decision making. Answering this question will have a profound impact on both our basic understanding of cellular decision-making processes, as well as implications in preventing and treating diseases like infection, autoimmunity and cancer.

NF-κB B对稳健信息加工机制的理解 生物学中一个主要的开放问题是，尽管存在生物噪声，细胞如何稳健地运行？ 由于信号传导因子的可变翻译和分泌， 在组织中的传播和分子浓度的随机波动。然而，不知何故， 准确地处理这些嘈杂的输入，并定期创建适当的响应。这项建议旨在 通过研究噪音对基因调控的影响来回答这个基本问题， 医学上重要的先天免疫信号传导途径NF-κ B B。尝试理解动态基因 NF-κ B B的调节和处理噪音的分子机制通常受到以下因素的阻碍： 显著的细胞间变异性（需要单细胞分析）和研究肝细胞的技术限制 动态信号下的细胞。在这里，我们将联合收割机我们的经验，NF-κ B B信号，建立 微流控细胞培养技术和数学建模来研究这个最有趣的问题， 单细胞我们的实验室是独特的定位，探索和回答这个新的领域，因为我们已经花了最后一个 10年来建立和改进实验和数学方法来研究的影响， 细胞决策中的噪音。探讨这个问题将对我们的基本 了解细胞决策过程，以及在预防和治疗 感染、自身免疫和癌症等疾病。