Single Cell Analysis Strategies to Understand Noisy and Dynamic Nf-?b Network Behavior

One of the major open questions in biology today is how cells operate robustly despite the presence of biological noise in their environment. Signaling pathways are often depicted as having defined responses to environmental signals, and their protein cascades often are shown to have specific responses to doses, timings, and signaling behavior(1, 2). One example of this robust signaling is the NF-κB immune pathway which controls responses to many pathogens and cytokines. In healthy organisms, NF-κB provides a graduated response based on dose that enables its’ subsequent clearance efficiently. In tissue, signaling molecules often have fluctuating concentrations(1, 3, 4), yet are able to still create these robust gene expression profiles(5–7). Inputs received by cells are unavoidably noisy due to variable secretion and translation of signaling factors, propagation through tissues, and fluctuations in molecular concentrations(4, 8, 9). The molecular mechanisms behind this robust signaling despite presence of input noise are not fully understood. Understanding the effect of network noise on signaling is an active area of research, however little attention has been given to the single cell specificity and sensitivity under noise. It is clear that noise is abundant in the input to NF-κB – after detecting pathogens immune cells secrete a wide range of cytokines that serve as input to nearby tissue cells. The input received by any single cell thus depends on the dynamics of cytokine secretion and is subject to the noise in the extracellular environment. Here, I take a microfluidic approach to understand how and why there is heterogeneity in activation of NF-κB, how noise in the input affects NF-κB signaling and transcription, and what mechanism the cells use to process and filter this noise