Title :
Investigation of IL-6 and IL-10 signalling via mathematical modelling
Author :
Moya, Christian ; Huang, Z. ; Cheng, Peng ; Jayaraman, A. ; Hahn, Juergen
Author_Institution :
Artie McFerrin Dept. of Chem. Eng., Texas A&M Univ., College Station, TX, USA
fDate :
1/1/2011 12:00:00 AM
Abstract :
Steatosis, i.e., the accumulation of fat in hepatocytes, plays an important role in the progression of non-alcoholic fatty liver disease (NAFLD). It has been shown that STAT3 activation is involved in a decrease of lipid accumulation while C/EBP/ is correlated with an increase of fat content and steatosis. It is known that STAT3 and C/EBP/ are activated by IL-6 and that IL-6 signalling is also affected by IL-10, even though the exact mechanism is unclear. This paper develops a model for IL-6 and IL-10 signal transduction and then investigates the effect that stimulation with these cytokines has on the transcription factor dynamics. In an initial step, some parameters of a previously developed IL-6 signalling model are re-estimated based upon newly developed experimental data for the Jak-STAT pathway. Furthermore, the Erk-C/EBP/ pathway model is extended to also include the activated transcription factor C/EBP/ in the nucleus. Since IL-10 signals through the Jak-STAT but not the Erk-C/EBP/ pathway, a model was developed which includes interaction between IL-6 and IL-10 signalling as both mechanisms share signal transduction through the Jak-STAT pathway. Based upon the model, the activity ratio of Jak-STAT and Erk-C/EBP/ was investigated for different stimulation levels of IL-6 and IL-10.
Keywords :
cellular biophysics; diseases; fats; liver; medical computing; physiological models; Erk-C-EBP-pathway; IL-10 signal transduction; IL-10 signalling; IL-6 signal transduction; IL-6 signalling; Jak-STAT pathway; STAT3 activation; activated transcription factor; cytokines signal; fat; hepatocytes; lipid accumulation; mathematical modelling; nonalcoholic fatty liver disease; steatosis; transcription factor dynamics; transcription factors;
Journal_Title :
Systems Biology, IET
DOI :
10.1049/iet-syb.2009.0060