Understanding Mechanisms of Robust Information Processing by NF-kappaB

了解 NF-kappaB 鲁棒信息处理的机制

基本信息

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
项目类别：
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

项目摘要

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.

了解NF-κB的强大信息处理机制生物学中的一个主要开放问题是细胞如何运作dospite dospite的生物噪声？由于可变的翻译和信号传导因子的分泌，细胞收到的输入是不可避免的噪声，分子浓度的组织和随机波动的传播。然而，某种程度上的细胞能够准确处理这些噪音输入并定期创建适当的响应。该建议旨在通过研究噪声对知名和知名和医学上重要的先天免疫信号通路NF-B。尝试理解动态基因的尝试 NF-B的调节和处理噪声的分子机制通常受到了阻碍明显的细胞间变异性（需要单细胞分析）和研究实时的技术限制动态信号下的细胞。在这里，我们将在NF-B信号中结合经验，建立微流体细胞培养技术和数学建模，以研究这个最有趣的问题单细胞。我们的实验室独特地探索和回答这个新领域，因为我们花了最后一个十年来构建和改进实验和数学方法，以研究细胞决策中的噪音。回答这个问题将对我们的两个基本了解蜂窝决策过程，以及预防和治疗的影响感染，自身免疫和癌症等疾病。