Cellular defense processes regulated by pathogen-elicited receptor signaling

Vertebrates are constantly threatened by the invasion of microorganisms and have evolved systems of immunity to eliminate infectious pathogens in the body. Initial sensing of microbial agents is mediated by the recognition of pathogens by means of molecular structures expressed uniquely by microbes of a given type. So-called 'Toll-like receptors' are expressed on host epithelial barrier cells play an essential role in the host defense against microbial pathogens by inducing cell responses (e.g., proliferation, death, cytokine secretion) via activation of intracellular signaling networks. As these networks, comprising multiple interconnecting dynamic pathways, represent highly complex multi-variate "information processing" systems, the signaling activities particularly critical for governing the host cell responses are poorly understood and not easily ascertained by a priori theoretical notions. We have developed over the past half-decade a "data-driven" computational modeling approach, on a 'cue-signal-response' combined experiment/computation paradigm, to elucidate key multi-variate signaling relationships governing the cell responses. In an example presented here, we study how a canonical set of six kinase pathways combine to effect microbial agent-induced apoptotic death of a macrophage cell line. One modeling technique, partial least-squares regression, yielded the following key insights: {a} signal combinations most strongly correlated to apoptotic death are orthogonal to those most strongly correlated with release of inflammatory cytokines; {b} the ratio of two key pathway activities is the most powerful predictor of microbe-induced macrophage apoptotic death; {c} the most influential time-window of this signaling activity ratio is surprisingly fast: less than one hour after microbe stimulation.United States. Army Research Office (Institute for Collaborative Biotechnologies)National Institute of General Medical Sciences (U.S.) (Center for Cell Decision Processes

Flexible informatics for linking experimental data to mathematical models via DataRail

MOTIVATION: Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all normalization, scaling, and fusion routines used to assemble the training data from primary results. RESULTS: We describe the implementation of DataRail, an open source MATLAB-based toolbox that stores experimental data in flexible multi-dimensional arrays, transforms arrays so as to maximize information content, and then constructs models using internal or external tools. Data integrity is maintained via a containment hierarchy for arrays, imposition of a metadata standard based on a newly proposed MIDAS format, assignment of semantically typed universal identifiers, and implementation of a procedure for storing the history of all transformations with the array. We illustrate the utility of DataRail by processing a newly collected set of ~22,000 measurements of protein activities obtained from cytokine-stimulated primary and transformed human liver cells

Elevated GM-CSF and IL-1β levels compromise the ability of p38 MAPK inhibitors to modulate TNFα levels in the human monocytic/macrophage U937 cell line

Rheumatoid arthritis (RA) is a complex, multicellular disease involving a delicate balance between both pro- and anti-inflammatory cytokines which ultimately determines the disease phenotype. The simultaneous presence of multiple signaling molecules, and more specifically their relative levels, potentially influences the efficacy of directed therapies. Using the human U937 monocytic cell line, we generated a self-consistent dataset measuring 50 cytokines and 23 phosphoproteins in the presence of 6 small molecule inhibitors under 15 stimulatory conditions throughout a 24 hour time course. From this dataset, we are able to explore phosphoprotein and cytokine relationships, as well as evaluate the significance of cellular context on the ability of small molecule inhibitors to block inflammatory processes. We show that the ability of a p38 inhibitor to attenuate TNFα production is influenced by local levels of GM-CSF and IL-1β, two cytokines known to be elevated in the joints of RA patients. Within the cell, compensatory mechanisms between signaling pathways are apparent, as selective p38 MAPK inhibition results in the increased phosphorylation of other MAPKs (ERK and JNK) and their downstream substrates (CREB, c-Jun, and ATF-2). Further, we demonstrate that TNFα-neutralizing antibodies have secondary effects on cytokine production, impacting more than just TNFα alone. p38 MAPK inhibition using a small molecule inhibitor also blocks production of anti-inflammatory cytokines including IL-10, IL-1ra and IL-2ra. Collectively, the impact of cell context on TNFα production and unintended blockade of anti-inflammatory cytokines may compromise the efficacy of p38 inhibitors in a clinical setting. The effort described in this work evaluates the effect of inhibitors on multiple endpoints (both intra- and extracellular), under a range of biologically relevant conditions, thus providing a unique means for differentiation of compounds and potential opportunity for improved pharmacological manipulation of disease endpoints in RA