Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-κB signaling-induced gene expression responses in inflammation

BMC Bioinformatics

Methodology Article

Yan Yu Chen¹  David Shan Hill Wong¹  Shih Chi Peng²  Chuan Yi Tang²  Chien Hua Peng³  Chun Cheih Chao⁴  Yung Jen Chuang⁴  Kai Che Tung⁴ 

[1] Department of Chemical Engineering, National Tsing Hua University, 30013, Hsinchu, Taiwan, ROC;Department of Computer Science, National Tsing Hua University, 30013, Hsinchu, Taiwan, ROC;Department of Resource Center for Clinical Research, Chang Gung Memorial Hospital, 333, Taoyuan, Taiwan, ROC;Institute of Bioinformatics and Structural Biology, National Tsing Hua University, 30013, Hsinchu, Taiwan, ROC;

关键词: Independent Component Analysis;    Transcription Factor Activity;    Gene Regulatory Network;    Reverse Engineering;    Network Component Analysis;   

DOI  :  10.1186/1471-2105-11-308

 received in 2009-12-23, accepted in 2010-06-08,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundSignal transduction is the major mechanism through which cells transmit external stimuli to evoke intracellular biochemical responses. Diverse cellular stimuli create a wide variety of transcription factor activities through signal transduction pathways, resulting in different gene expression patterns. Understanding the relationship between external stimuli and the corresponding cellular responses, as well as the subsequent effects on downstream genes, is a major challenge in systems biology. Thus, a systematic approach is needed to integrate experimental data and theoretical hypotheses to identify the physiological consequences of environmental stimuli.ResultsWe proposed a systematic approach that combines forward and reverse engineering to link the signal transduction cascade with the gene responses. To demonstrate the feasibility of our strategy, we focused on linking the NF-κB signaling pathway with the inflammatory gene regulatory responses because NF-κB has long been recognized to play a crucial role in inflammation. We first utilized forward engineering (Hybrid Functional Petri Nets) to construct the NF-κB signaling pathway and reverse engineering (Network Components Analysis) to build a gene regulatory network (GRN). Then, we demonstrated that the corresponding IKK profiles can be identified in the GRN and are consistent with the experimental validation of the IKK kinase assay. We found that the time-lapse gene expression of several cytokines and chemokines (TNF-α, IL-1, IL-6, CXCL1, CXCL2 and CCL3) is concordant with the NF-κB activity profile, and these genes have stronger influence strength within the GRN. Such regulatory effects have highlighted the crucial roles of NF-κB signaling in the acute inflammatory response and enhance our understanding of the systemic inflammatory response syndrome.ConclusionWe successfully identified and distinguished the corresponding signaling profiles among three microarray datasets with different stimuli strengths. In our model, the crucial genes of the NF-κB regulatory network were also identified to reflect the biological consequences of inflammation. With the experimental validation, our strategy is thus an effective solution to decipher cross-talk effects when attempting to integrate new kinetic parameters from other signal transduction pathways. The strategy also provides new insight for systems biology modeling to link any signal transduction pathways with the responses of downstream genes of interest.

【 授权许可】

Unknown   
© Peng et al; licensee BioMed Central Ltd. 2010. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.