All living cells are capable of extracting information from their micro-environment and mounting appropriate responses to a variety of associated challenges. The underlying signal transduction networks can be quite complex, necessitating for their unraveling a combination of sophisticated computational modeling and precise experimentation. Unfortunately, current computational and experimental analysis of cell signaling frequently suffers from such pitfalls as isolation of a pathway from surrounding signaling network, disregard of the cell-cell variability in the signaling outputs or studying signaling out of the context provided of by cell-cell communication in the native tissues. This renewal proposal is aimed at providing a framework for addressing these research limitations through development of novel methods and tools, and putting forward a detailed plan of a more realistic integrative analysis of signaling in response to a chemokine, tumor necrosis factor (TNF). A particular emphasis of our analysis will be on understanding of the information transfer properties of signaling pathways and its role in defining the precision of the phenotypic outcomes, including regulation of gene expression. The results of the analysis will provide a new platform for investigation of the relationship between the single cell and population responses and drive the development of the information theory based understanding of intracellular signal processing and cell communication. We anticipate that the quantitative understanding of the complexity of signaling cross-talk, regulation of diversity of cell responses to the same stimulus and nuances of cell-cell communication will facilitate development of a more realistic framework for understanding of the human disease, including functioning of the immune system, and drug development aimed at regulation of the NF-kappaB and JNK signaling.

Public Health Relevance

Cells respond to their external environment by extracting information out of chemical signals they receive from other cells. This leads to changes in protein activity and gene expression, ultimately deciding the function and fate of the cell. These responses are complicated by differences between individual cells as well as communication between cells. Understanding the responses may benefit from analyses that combine experiment and mathematical modeling. In this context, we propose to study in detail two signals induced by inflammation in mammalian cells. Through such analyses we anticipate to uncover novel principles and mechanisms by which cells respond to external stimuli.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Brazhnik, Paul
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Johns Hopkins University
Biomedical Engineering
Schools of Engineering
United States
Zip Code
Levchenko, Andre; Nemenman, Ilya (2014) Cellular noise and information transmission. Curr Opin Biotechnol 28:156-64
Loriaux, Paul Michael; Tesler, Glenn; Hoffmann, Alexander (2013) Characterizing the relationship between steady state and response using analytical expressions for the steady states of mass action models. PLoS Comput Biol 9:e1002901
Behar, Marcelo; Barken, Derren; Werner, Shannon L et al. (2013) The dynamics of signaling as a pharmacological target. Cell 155:448-61
Loriaux, Paul Michael; Hoffmann, Alexander (2013) A protein turnover signaling motif controls the stimulus-sensitivity of stress response pathways. PLoS Comput Biol 9:e1002932
Chang, Hao; Levchenko, Andre (2013) Adaptive molecular networks controlling chemotactic migration: dynamic inputs and selection of the network architecture. Philos Trans R Soc Lond B Biol Sci 368:20130117
Wang, C Joanne; Bergmann, Adriel; Lin, Benjamin et al. (2012) Diverse sensitivity thresholds in dynamic signaling responses by social amoebae. Sci Signal 5:ra17
Loriaux, Paul M; Hoffmann, Alexander (2012) A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness. Methods Cell Biol 110:81-109
Cheong, Raymond; Rhee, Alex; Wang, Chiaochun Joanne et al. (2011) Information transduction capacity of noisy biochemical signaling networks. Science 334:354-8
Ni, Qiang; Ganesan, Ambhighainath; Aye-Han, Nwe-Nwe et al. (2011) Signaling diversity of PKA achieved via a Ca2+-cAMP-PKA oscillatory circuit. Nat Chem Biol 7:34-40
Hur, Eun-Mi; Yang, In Hong; Kim, Deok-Ho et al. (2011) Engineering neuronal growth cones to promote axon regeneration over inhibitory molecules. Proc Natl Acad Sci U S A 108:5057-62

Showing the most recent 10 out of 26 publications