NFkB is an inducible transcription factor that is activated in response to stress, cytokines and bacterial and viral pathogens, and is a major regulator of immune responses. The NFkB regulatory network processes signals that originate at a variety of cell membrane receptors to control the transcription of genes involved in immune and inflammatory responses, cell proliferation and survival. NFkB signaling has been linked to a number of human inflammatory diseases, such as arthritis and asthma, and because its activity is often up- regulated in tumors, NFkB signaling is actively being pursued as a target for cancer therapies. A detailed understanding of the signaling pathways that culminate in NFkB activation will be crucial for the discovery of effective NFkB inhibitors. To this end, this project will develop and experimentally validate computational models with predictive capabilities that can be used to understand the complexities of NFkB signaling in mammalian cells.
Each aim will investigate a particular aspect of NFkB signaling through a combination of modeling and quantitative single-cell experiments performed in controlled microfluidic environments. Specifically, the first aim will develop a stochastic delay-based computational model of NFkB dynamics driven by transient TNF signals. For this, novel cell lines will be created that allow IKK and NFkB expression to be tracked in real time by fluorescence microscopy. Modeling will be used to predict the network response to various driving conditions and mutations in network architecture.
The second aim will focus on the role of the IKK regulatory cycle in amplifying or filtering fluctuations in signals emanating from receptors. The rate of IKK turnover within the cycle will be varied to study the propagation of upstream fluctuations into the core of the NFkB module.
The third aim will address the role of two parallel pathways (MyD88 and TRIF) initiated by pathogen-derived lipopolysaccharide (LPS) signals. Experiments involving either carefully controlled pulses of external LPS or invasive E. coli will be used in conjunction with mathematical modeling to characterize the dynamics and variability of the LPS-NFkB pathways. In the fourth aim, the role of cell-to-cell signaling in generating NFkB-mediated responses will be addressed by examining autocrine and paracrine TNF signaling. The successful completion of this project will result not only in a predictive computational model for NFkB signaling but also in insights into how this central regulatory network processes information in response to stimulation, inhibition, and drug modulation.
Nuclear factor B (NFB) is a key regulator of innate and adaptive immune responses. Misregulation of NFB may lead to a wide range of human diseases such as cancer, neurodegenerative disorders, and pathological inflammatory conditions. The central goal of this proposal is to develop and experimentally validate a reliable quantitative modeling approach that can be used to describe the NFB signaling network and predict its behavior in dynamic natural environments. 1
|Selimkhanov, Jangir; Taylor, Brooks; Yao, Jason et al. (2014) Systems biology. Accurate information transmission through dynamic biochemical signaling networks. Science 346:1370-3|
|Tsimring, Lev S (2014) Noise in biology. Rep Prog Phys 77:026601|
|Behar, Marcelo; Barken, Derren; Werner, Shannon L et al. (2013) The dynamics of signaling as a pharmacological target. Cell 155:448-61|
|Mather, William H; Hasty, Jeff; Tsimring, Lev S et al. (2013) Translational cross talk in gene networks. Biophys J 104:2564-72|
|Longo, Diane M; Selimkhanov, Jangir; Kearns, Jeffrey D et al. (2013) Dual delayed feedback provides sensitivity and robustness to the NF-?B signaling module. PLoS Comput Biol 9:e1003112|
|Kolnik, Martin; Tsimring, Lev S; Hasty, Jeff (2012) Vacuum-assisted cell loading enables shear-free mammalian microfluidic culture. Lab Chip 12:4732-7|
|Selimkhanov, Jangir; Hasty, Jeff; Tsimring, Lev S (2012) Recent advances in single-cell studies of gene regulation. Curr Opin Biotechnol 23:34-40|
|Mather, William H; Hasty, Jeff; Tsimring, Lev S (2012) Fast stochastic algorithm for simulating evolutionary population dynamics. Bioinformatics 28:1230-8|
|Mather, W H; Hasty, J; Tsimring, L S et al. (2011) Factorized time-dependent distributions for certain multiclass queueing networks and an application to enzymatic processing networks. Queueing Syst 69:313-328|
|Schrofelbauer, Barbel; Hoffmann, Alexander (2011) How do pleiotropic kinase hubs mediate specific signaling by TNFR superfamily members? Immunol Rev 244:29-43|
Showing the most recent 10 out of 11 publications