Understanding Mechanisms of Robust Information Processing by NF-?B 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.
Signals received by cells in tissue are unavoidably noisy due to variable secretion of signaling factors, propagation in tissues and stochastic fluctuations of molecules. How cells are able to accurately process such noisy inputs and create appropriate responses is not understood. This proposal aims to understand the molecular mechanisms behind the robust operation of the medically important signaling pathway NF-?B by combining our experience in NF-?B signaling, established microfluidic single-cell analysis techniques and mathematical modeling.
