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.
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.
Authors: David Croft; Gavin O'Kelly; Guanming Wu; Robin Haw; Marc Gillespie; Lisa Matthews; Michael Caudy; Phani Garapati; Gopal Gopinath; Bijay Jassal; Steven Jupe; Irina Kalatskaya; Shahana Mahajan; Bruce May; Nelson Ndegwa; Esther Schmidt; Veronica Shamovsky; Christina Yung; Ewan Birney; Henning Hermjakob; Peter D'Eustachio; Lincoln Stein Journal: Nucleic Acids Res Date: 2010-11-09 Impact factor: 16.971
Authors: David Basanta; Douglas W Strand; Ralf B Lukner; Omar E Franco; David E Cliffel; Gustavo E Ayala; Simon W Hayward; Alexander R A Anderson Journal: Cancer Res Date: 2009-08-25 Impact factor: 12.701
Authors: Emek Demir; Michael P Cary; Suzanne Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl Schaefer; Joanne Luciano; Frank Schacherer; Irma Martinez-Flores; Zhenjun Hu; Veronica Jimenez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra C Lopez-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Ozgün Babur; Michael Blinov; Erik Brauner; Dan Corwin; Sylva Donaldson; Frank Gibbons; Robert Goldberg; Peter Hornbeck; Augustin Luna; Peter Murray-Rust; Eric Neumann; Oliver Ruebenacker; Oliver Reubenacker; Matthias Samwald; Martijn van Iersel; Sarala Wimalaratne; Keith Allen; Burk Braun; Michelle Whirl-Carrillo; Kei-Hoi Cheung; Kam Dahlquist; Andrew Finney; Marc Gillespie; Elizabeth Glass; Li Gong; Robin Haw; Michael Honig; Olivier Hubaut; David Kane; Shiva Krupa; Martina Kutmon; Julie Leonard; Debbie Marks; David Merberg; Victoria Petri; Alex Pico; Dean Ravenscroft; Liya Ren; Nigam Shah; Margot Sunshine; Rebecca Tang; Ryan Whaley; Stan Letovksy; Kenneth H Buetow; Andrey Rzhetsky; Vincent Schachter; Bruno S Sobral; Ugur Dogrusoz; Shannon McWeeney; Mirit Aladjem; Ewan Birney; Julio Collado-Vides; Susumu Goto; Michael Hucka; Nicolas Le Novère; Natalia Maltsev; Akhilesh Pandey; Paul Thomas; Edgar Wingender; Peter D Karp; Chris Sander; Gary D Bader Journal: Nat Biotechnol Date: 2010-09-09 Impact factor: 54.908
Authors: Carl F Schaefer; Kira Anthony; Shiva Krupa; Jeffrey Buchoff; Matthew Day; Timo Hannay; Kenneth H Buetow Journal: Nucleic Acids Res Date: 2008-10-02 Impact factor: 16.971
Authors: Jennifer C Bailey; Abhirami K Iyer; Gourapura J Renukaradhya; Yinling Lin; Hoa Nguyen; Randy R Brutkiewicz Journal: Immunology Date: 2014-12 Impact factor: 7.397