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


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Article Info

DATE

2010-06-08

AUTHORS

Shih Chi Peng, David Shan Hill Wong, Kai Che Tung, Yan Yu Chen, Chun Cheih Chao, Chien Hua Peng, Yung Jen Chuang, Chuan Yi Tang

ABSTRACT

BACKGROUND: Signal 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. RESULTS: We 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-kappaB signaling pathway with the inflammatory gene regulatory responses because NF-kappaB has long been recognized to play a crucial role in inflammation. We first utilized forward engineering (Hybrid Functional Petri Nets) to construct the NF-kappaB 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-alpha, IL-1, IL-6, CXCL1, CXCL2 and CCL3) is concordant with the NF-kappaB activity profile, and these genes have stronger influence strength within the GRN. Such regulatory effects have highlighted the crucial roles of NF-kappaB signaling in the acute inflammatory response and enhance our understanding of the systemic inflammatory response syndrome. CONCLUSION: We 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-kappaB 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. More... »

PAGES

308-308

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2105-11-308

DOI

http://dx.doi.org/10.1186/1471-2105-11-308

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041106926

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20529327


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114 relationship
115 response
116 response syndrome
117 role
118 signal transduction
119 signal transduction pathways
120 signaling-induced gene expression responses
121 solution
122 stimuli
123 stimulus strength
124 strategies
125 strength
126 stronger influence strength
127 subsequent effects
128 such regulatory effects
129 syndrome
130 systematic approach
131 systemic inflammatory response syndrome
132 systems biology
133 theoretical hypotheses
134 time-lapse gene expression
135 transcription factor activity
136 transduction
137 transduction pathways
138 understanding
139 validation
140 variety
141 wide variety
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