Éditeur(s) : HAL CCSD
Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM)
Rennes, France

hal-00760183
https://hal.inria.fr/hal-00760183

Éditeur(s) : HAL CCSD
Résumé : International audience
ISMB 2012
Long Beach, United States

hal-00760189
https://hal.inria.fr/hal-00760189

Éditeur(s) : HAL CCSD
Résumé : Cell signaling contains the whole biological mecanisms allowing the response of a cell to its microenvironnement in an adapted way. Many extremely intertwinned biological reactions are involved in a network that behaves as a complex system. The understanding of cell response requires the development of data acquisition technics and methods to formalize data into models. This point is the main drive of this thesis. We present here two approaches in order to analyse different granularities of cell signaling. In the first one, we used differential model to study the role of a new component of TGF-β canonical pathway. In the second one, we explored the combinatorial complexity of cell signaling, developing a discrete formalism based on guarded transitions. In this approach, we interpreted the whole database Pathway Interaction Database into a single unified model of signal transduction. Simulation and analysis methods, such as reachability and invariance research, have been developed. The interests are presented through an application on cell cycle regulation by cell signaling, and a global analysis on the regulation of genes compared to experimental data.
La signalisation cellulaire regroupe l'ensemble des mécanismes biologiques permettant à une cellule de répondre de façon adaptée à son microenvironnement. Pour ce faire, de nombreuses réactions biologiques entrent en jeux avec un important enchevêtrement, créant ainsi un réseau dont le comportement s'apparente à un système complexe. Le compréhension de la réponse cellulaire à une stimulation passe par le développement conjoint des techniques d'acquisition de données, et des méthodes permettant de formaliser ces données dans un modèle. C'est sur ce dernier point que s'inscrivent les travaux exposés dans cette thèse. Nous présentons ici deux approches visant à répondre à des questions de natures différentes sur la signalisation cellulaire. Dans la première nous utilisons un modèle différentiel pour étudier le rôle d'un nouvel interactant dans la voie canonique du TGF-beta. Dans la seconde nous avons exploré la combinatoire de la signalisation cellulaire en développant un formalisme discret basé sur les transitions gardées. Cette approche regroupe l'interprétation de la base de données Pathway Interaction Database dans un unique modèle dynamique de propagation du signal. Des méthodes de simulations et d'analyses inspirées des techniques de vérification de modèles telles que l'atteignabilité et l'invariance ont été développées. En outre, nous avons étudié la régulation du cycle cellulaire en réponse à la signalisation, ainsi que la régulation des gènes de notre modèle en comparaison avec des données d'expressions.
https://tel.archives-ouvertes.fr/tel-00926487

Droits : info:eu-repo/semantics/OpenAccess
tel-00926487
https://tel.archives-ouvertes.fr/tel-00926487
https://tel.archives-ouvertes.fr/tel-00926487/document
https://tel.archives-ouvertes.fr/tel-00926487/file/AndrieuxThese.pdf

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
TIF1γ (Transcriptional Intermediary Factor 1 γ) has been implicated in Smad-dependent signaling by Transforming Growth Factor beta (TGF-β). Paradoxically, TIF1γ functions both as a transcriptional repressor or as an alternative transcription factor that promotes TGF-β signaling. Using ordinary differential-equation models, we have investigated the effect of TIF1γ on the dynamics of TGF-β signaling. An integrative model that includes the formation of transient TIF1γ-Smad2-Smad4 ternary complexes is the only one that can account for TGF-β signaling compatible with the different observations reported for TIF1γ. In addition, our model predicts that varying TIF1γ/Smad4 ratios play a critical role in the modulation of the transcriptional signal induced by TGF-β, especially for short stimulation times that mediate higher threshold responses. Chromatin immunoprecipitation analyses and quantification of the expression of TGF-β target genes as a function TIF1γ/Smad4 ratios fully validate this hypothesis. Our integrative model, which successfully unifies the seemingly opposite roles of TIF1γ, also reveals how changing TIF1γ/Smad4 ratios affect the cellular response to stimulation by TGF-β, accounting for a highly graded determination of cell fate.
ISSN: 1932-6203

hal-00851483
https://hal.archives-ouvertes.fr/hal-00851483
https://hal.archives-ouvertes.fr/hal-00851483/document
https://hal.archives-ouvertes.fr/hal-00851483/file/pone.0033761.pdf
DOI : 10.1371/journal.pone.0033761

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
BACKGROUND: The TGF-β transforming growth factor is the most pleiotropic cytokine controlling a broad range of cellular responses that include proliferation, differentiation and apoptosis. The context-dependent multifunctional nature of TGF-β is associated with complex signaling pathways. Differential models describe the dynamics of the TGF-β canonical pathway, but modeling the non-canonical networks constitutes a major challenge. Here, we propose a qualitative approach to explore all TGF-β-dependent signaling pathways. RESULTS: Using a new formalism, CADBIOM, which is based on guarded transitions and includes temporal parameters, we have built the first discrete model of TGF-β signaling networks by automatically integrating the 137 human signaling maps from the Pathway Interaction Database into a single unified dynamic model. Temporal property-checking analyses of 15934 trajectories that regulate 145 TGF-β target genes reveal the association of specific pathways with distinct biological processes. We identify 31 different combinations of TGF-β with other extracellular stimuli involved in non-canonical TGF-β pathways that regulate specific gene networks. Extensive analysis of gene expression data further demonstrates that genes sharing CADBIOM trajectories tend to be co-regulated. CONCLUSIONS: As applied here to TGF-β signaling, CADBIOM allows, for the first time, a full integration of highly complex signaling pathways into dynamic models that permit to explore cell responses to complex microenvironment stimuli.
ISSN: 1752-0509

inserm-00978313
http://www.hal.inserm.fr/inserm-00978313
http://www.hal.inserm.fr/inserm-00978313/document
http://www.hal.inserm.fr/inserm-00978313/file/1752-0509-8-30.pdf
DOI : 10.1186/1752-0509-8-30