An approach to investigate intracellular protein network responses

Modern toxicological evaluations have evolved to consider toxicity as a perturbation of biological pathways or networks. As such, toxicity testing approaches are shifting from common end point evaluations to pathway based approaches, where the degree of perturbation of select biological pathways is monitored. These new approaches are greatly increasing the data available to toxicologists, but methods of analyses to determine the inter-relationships between potentially affected pathways are needed to fully understand the consequences of exposure. An approach to construct dose-response curves that use graph theory to describe network perturbations among three disparate mitogen-activated protein kinase (MAPK) pathways is presented. Mitochondrial stress was induced in human hepatocytes (HepG2) by exposing the cells to increasing doses of the complex I inhibitor, deguelin. The relative phosphorylation responses of proteins involved in the regulation of the stress response were measured. Graph theory was applied to the phosphorylation data to obtain parameters describing the network perturbations at each individual dose tested. The graph theory results depicted the dynamic nature of the relationship between p38, JNK, and ERK1/2 under conditions of mitochondrial stress and revealed shifts in the relationships between these MAPK pathways at low doses. The inter-relationship, or crosstalk, among these 3 traditionally linear MAPK cascades was further probed by coexposing cells to deguelin plus SB202190 (JNK and p38 inhibitor) or deguelin plus SB202474 (JNK inhibitor). The cells exposed to deguelin plus SB202474 resulted in significantly decreased viability, which could be visualized and attributed to the decrease of ERK1/2 network centrality. The approach presented here allows for the construction and visualization of dose-response curves that describe network perturbations induced by chemical stress, which provides an informative and sensitive means of assessing toxicological effects on biological systems.