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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.
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