title: Computational analysis of the interferon alpha signalling pathway using a systems biology modelling approach
creator: Maiwald, Tim
subject: ddc-570
subject: 570 Life sciences
description: In this thesis, signalling dynamics of the interferon alpha stimulated JAK/STAT pathway have been studied using a computational modelling approach. A model simulating the kinetic response of an interferon alpha stimulated Huh7.5 cell was developed using literature data and experimental measurements. The model was used for predictions regarding the kinetic behaviour of the signal transduction. IRF-9, a transcription factor necessary for the transcriptionally active ISGF-3 complex, was predicted to be a major contributor to the time dependent kinetic behaviour of the interferon alpha stimulated signal transduction. An overexpression of IRF-9 was predicted to enhance and accelerate the anti-viral response following interferon alpha stimulation. Furthermore, constitutive negative feedback by nuclear phosphatases and induced negative feedback by SOCS proteins were predicted to have a major impact on the JAK/STAT signalling pathway. Additionally, phosphatase protection of the ISGF-3 complex by DNA binding was proposed to be necessary for the observed kinetic measurements. Predictions regarding IRF-9 were validated by experimental measurements comparing wild-type cells to IRF-9 overexpression cells. Both cell lines showed the predicted behaviour after interferon alpha stimulation for active signal transducers. Furthermore, the effect was observed on a genetic level, as an array experiment showed upregulation and acceleration of prominent anti-viral genes such as Mx1 in the IRF-9 overexpressing cells in comparison to the wild-type environment. Therefore, overexpression of IRF-9 was identified as a method to enhance the JAK/STAT signalling pathway. A bioinformatical approach was used to predict underlying mechanisms controlling individual gene induction patterns observed in the array experiment. Results showed that hub-gene IRF1 could be involved in a transcriptional network controlling early and late anti-viral responses following interferon alpha stimulation. To improve model predictions and to identify key reactions for additional experimental design, a two-phase model reduction and parameter estimation approaches were performed. For the first reduction, the model was decreased from 61 free parameters to 33 free parameters. After a parameter fitting approach, the model retained its ability to accurately fit the experimental data. Furthermore, the second model reduction lead to a minimal model with 22 free parameters, which was able to fit the experimental data well. 
date: 2012
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/13164/1/Dissertation_Maiwald.pdf
identifier: DOI:10.11588/heidok.00013164
identifier: urn:nbn:de:bsz:16-opus-131643
identifier:   Maiwald, Tim  (2012) Computational analysis of the interferon alpha signalling pathway using a systems biology modelling approach.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/13164/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng