Modeling the Intra- and Extracellular Cytokine Signaling Pathway under Heat Stroke in the Liver

<div><p>Heat stroke (HS) is a life-threatening illness induced by prolonged exposure to a hot environment that causes central nervous system abnormalities and severe hyperthermia. Current data suggest that the pathophysiological responses to heat stroke may not only be due to the immediate effects of heat exposure <i>per se</i> but also the result of a systemic inflammatory response syndrome (SIRS). The observation that pro- (<i>e.g.</i>, IL-1) and anti-inflammatory (<i>e.g.</i>, IL-10) cytokines are elevated concomitantly during recovery suggests a complex network of interactions involved in the manifestation of heat-induced SIRS. In this study, we measured a set of circulating cytokine/soluble cytokine receptor proteins and liver cytokine and receptor mRNA accumulation in wild-type and tumor necrosis factor (TNF) receptor knockout mice to assess the effect of neutralization of TNF signaling on the SIRS following HS. Using a systems approach, we developed a computational model describing dynamic changes (intra- and extracellular events) in the cytokine signaling pathways in response to HS that was fitted to novel genomic (liver mRNA accumulation) and proteomic (circulating cytokines and receptors) data using global optimization. The model allows integration of relevant biological knowledge and formulation of new hypotheses regarding the molecular mechanisms behind the complex etiology of HS that may serve as future therapeutic targets. Moreover, using our unique modeling framework, we explored cytokine signaling pathways with three <i>in silico</i> experiments (<i>e.g.</i> by simulating different heat insult scenarios and responses in cytokine knockout strains <i>in silico</i>).</p></div

Liver fold-change in mRNA accumulation during heat stroke recovery in WT and TNFR KO mice for NF-B and AP-1 related genes.

<p>Data represent fold-change in liver mRNA accumulation relative to controls at the same time point. Bold fonts represent significantly higher than time-matched controls (one-way ANOVA, P);</p>†<p>represents significant difference from T;</p>§<p>represents significant difference from return-to-baseline;</p>a<p>represents significant difference between genotypes within each gene. T, maximum core temperature (42.4°C); TNFR KO, tumor necrosis factor receptor knockout; WT, wild-type strain (B6129F₂).</p

Model simulation (solid and dashed lines) versus experimental data (markers) for the TNF family.

<p>(A) represents the plasma concentration of TNF- for WT and TNFR KO, and (B) the plasma concentration of the soluble isoforms of receptors TNF-RI and TNF-RII for WT.</p

Model simulation (solid and dashed lines) versus experimental data (markers) for the mRNA accumulation of HSP70 under heat stroke.

<p>The model accurately fits the WT data; moreover, it predicts a slightly delayed and attenuated response for the TNFR KO mice in agreement with the experimental data (data used for validation only).</p