Literature DB >> 18171696

Network topology determines dynamics of the mammalian MAPK1,2 signaling network: bifan motif regulation of C-Raf and B-Raf isoforms by FGFR and MC1R.

Melissa Muller1, Mandri Obeyesekere, Gordon B Mills, Prahlad T Ram.   

Abstract

Activation of the fibroblast growth factor (FGFR) and melanocyte stimulating hormone (MC1R) receptors stimulates B-Raf and C-Raf isoforms that regulate the dynamics of MAPK1,2 signaling. Network topology motifs in mammalian cells include feed-forward and feedback loops and bifans where signals from two upstream molecules integrate to modulate the activity of two downstream molecules. We computationally modeled and experimentally tested signal processing in the FGFR/MC1R/B-Raf/C-Raf/MAPK1,2 network in human melanoma cells; identifying 7 regulatory loops and a bifan motif. Signaling from FGFR leads to sustained activation of MAPK1,2, whereas signaling from MC1R results in transient activation of MAPK1,2. The dynamics of MAPK activation depends critically on the expression level and connectivity to C-Raf, which is critical for a sustained MAPK1,2 response. A partially incoherent bifan motif with a feedback loop acts as a logic gate to integrate signals and regulate duration of activation of the MAPK signaling cascade. Further reducing a 106-node ordinary differential equations network encompassing the complete network to a 6-node network encompassing rate-limiting processes sustains the feedback loops and the bifan, providing sufficient information to predict biological responses.

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Year:  2008        PMID: 18171696     DOI: 10.1096/fj.07-9100com

Source DB:  PubMed          Journal:  FASEB J        ISSN: 0892-6638            Impact factor:   5.191


  10 in total

1.  DARPP-32 is required for MAPK/ERK signaling in thyroid cells.

Authors:  Ana Chocarro-Calvo; Miguel A Zaballos; Pilar Santisteban; Custodia García-Jiménez
Journal:  Mol Endocrinol       Date:  2012-02-02

2.  Identification of optimal drug combinations targeting cellular networks: integrating phospho-proteomics and computational network analysis.

Authors:  Sergio Iadevaia; Yiling Lu; Fabiana C Morales; Gordon B Mills; Prahlad T Ram
Journal:  Cancer Res       Date:  2010-07-19       Impact factor: 12.701

Review 3.  Network analyses in systems pharmacology.

Authors:  Seth I Berger; Ravi Iyengar
Journal:  Bioinformatics       Date:  2009-07-30       Impact factor: 6.937

Review 4.  Bioinformatics and systems biology.

Authors:  Prahlad T Ram; John Mendelsohn; Gordon B Mills
Journal:  Mol Oncol       Date:  2012-02-17       Impact factor: 6.603

5.  Network, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system.

Authors:  Paolo Tieri; Andrea Grignolio; Alexey Zaikin; Michele Mishto; Daniel Remondini; Gastone C Castellani; Claudio Franceschi
Journal:  Theor Biol Med Model       Date:  2010-08-11       Impact factor: 2.432

6.  Nonparametric simulation of signal transduction networks with semi-synchronized update.

Authors:  Isar Nassiri; Ali Masoudi-Nejad; Mahdi Jalili; Ali Moeini
Journal:  PLoS One       Date:  2012-06-21       Impact factor: 3.240

7.  Kinome siRNA-phosphoproteomic screen identifies networks regulating AKT signaling.

Authors:  Y Lu; M Muller; D Smith; B Dutta; K Komurov; S Iadevaia; D Ruths; J T Tseng; S Yu; Q Yu; L Nakhleh; G Balazsi; J Donnelly; M Schurdak; S Morgan-Lappe; S Fesik; P T Ram; G B Mills
Journal:  Oncogene       Date:  2011-06-13       Impact factor: 9.867

8.  Reducing the complexity of complex gene coexpression networks by coupling multiweighted labeling with topological analysis.

Authors:  Alfredo Benso; Paolo Cornale; Stefano Di Carlo; Gianfranco Politano; Alessandro Savino
Journal:  Biomed Res Int       Date:  2013-10-07       Impact factor: 3.411

9.  Inhibitory effects of ginsenosides on basic fibroblast growth factor-induced melanocyte proliferation.

Authors:  Ji Eun Lee; Jong Il Park; Cheol Hwan Myung; Jae Sung Hwang
Journal:  J Ginseng Res       Date:  2016-05-14       Impact factor: 6.060

10.  The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

Authors:  Derek Ruths; Melissa Muller; Jen-Te Tseng; Luay Nakhleh; Prahlad T Ram
Journal:  PLoS Comput Biol       Date:  2008-02-29       Impact factor: 4.475

  10 in total

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