Abstract
BackgroundDevelopment in systems biology research has accelerated in recent years, and the reconstructions for molecular networks can provide a global view to enable in-depth investigation on numerous system properties in biology. However, we still lack a systematic approach to reconstruct the dynamic protein-protein association networks at different time stages from high-throughput data to further analyze the possible cross-talks among different signaling/regulatory pathways.MethodsIn this study we integrated protein-protein interactions from different databases to construct the rough protein-protein association networks (PPANs) during TNFα-induced inflammation. Next, the gene expression profiles of TNFα-induced HUVEC and a stochastic dynamic model were used to rebuild the significant PPANs at different time stages, reflecting the development and progression of endothelium inflammatory responses. A new cross-talk ranking method was used to evaluate the potential core elements in the related signaling pathways of toll-like receptor 4 (TLR-4) as well as receptors for tumor necrosis factor (TNF-R) and interleukin-1 (IL-1R).ResultsThe highly ranked cross-talks which are functionally relevant to the TNFα pathway were identified. A bow-tie structure was extracted from these cross-talk pathways, suggesting the robustness of network structure, the coordination of signal transduction and feedback control for efficient inflammatory responses to different stimuli. Further, several characteristics of signal transduction and feedback control were analyzed.ConclusionsA systematic approach based on a stochastic dynamic model is proposed to generate insight into the underlying defense mechanisms of inflammation via the construction of corresponding signaling networks upon specific stimuli. In addition, this systematic approach can be applied to other signaling networks under different conditions in different species. The algorithm and method proposed in this study could expedite prospective systems biology research when better experimental techniques for protein expression detection and microarray data with multiple sampling points become available in the future.
Highlights
Development in systems biology research has accelerated in recent years, and the reconstructions for molecular networks can provide a global view to enable in-depth investigation on numerous system properties in biology
Construction of refined protein-protein association networks (PPANs) at different time stages of inflammatory system The proposed method was used to investigate the refined PPANs at different time stages of inflammatory system
The inferred functional modules supported by literature evidences in the refined PPAN are further shown in Supplementary Table S2 [Additional file 3]
Summary
Development in systems biology research has accelerated in recent years, and the reconstructions for molecular networks can provide a global view to enable in-depth investigation on numerous system properties in biology. Molecular networks including protein-protein interaction networks, gene regulatory networks, metabolic networks and gene co-expression networks These molecular networks have been demonstrated with great potentials to discover basic functions and to reveal essential mechanisms for various biological phenomena, by understanding biological systems not on an individual component level but on a system-wide level [2]. Products from bacteria and viruses that stimulate leukocyte and endothelial release of cytokines, chemokines, and lipid mediators may play a role in inflammation These stimuli can alter gene regulation of endothelial leukocyte adhesion molecules, cell signal transduction pathways, and endothelial permeability. Two protein families have been implicated in the signaling pathway mediated by the receptors for tumor necrosis factor (TNF-R). These include the death domain-containing proteins (TNFR1, TRADD, RIP and FADD) and the TRAF domain-containing proteins (TNFR2, CD40, and TRAF16). Because both responses are initiated by ligand binding to a single receptor, it is clear that TNF activates multiple signal transductions [11]
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