Inferring signaling pathway topologies from multiple perturbation measurements of specific biochemical species

Xu, T. et al. (2010) Inferring signaling pathway topologies from multiple perturbation measurements of specific biochemical species. Science Signaling, 3(113), ra20. (doi:10.1126/scisignal.2000517)

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Abstract

The specification of biological decisions by signaling pathways is encoded by the interplay between activation dynamics and network topologies. Although we can describe complex networks, we cannot easily determine which topology the cell actually uses to transduce a specific signal. Experimental testing of all plausible topologies is infeasible because of the combinatorially large number of experiments required to explore the complete hypothesis space. Here, we demonstrate that Bayesian inference–based modeling provides an approach to explore and constrain this hypothesis space, permitting the rational ranking of pathway models. Our approach can use measurements of a limited number of biochemical species when combined with multiple perturbations. As proof of concept, we examined the activation of the extracellular signal–regulated kinase (ERK) pathway by epidermal growth factor. The predicted and experimentally validated model shows that both Raf-1 and, unexpectedly, B-Raf are needed to fully activate ERK in two different cell lines. Thus, our formal methodology rationally infers evidentially supported pathway topologies even when a limited number of biochemical and kinetic measurements are available.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Xu, Professor Tianrui and Von Kriegsheim, Mr Alexander and Houslay, Professor Miles and Baillie, Professor George and Milligan, Professor Graeme and Vyshemirsky, Dr Vladislav and Dunlop, Dr Allan and Girolami, Prof Mark
Authors: Xu, T., Vyshemirsky, V., Gormand, A., von Kriegsheim, A., Girolami, M., Baillie, G.S., Ketley, D., Dunlop, A.J., Milligan, G., Houslay, M.D., and Kolch, W.
Subjects:Q Science > QH Natural history > QH345 Biochemistry
College/School:College of Medical Veterinary and Life Sciences > Institute of Molecular Cell and Systems Biology
College of Medical Veterinary and Life Sciences > Institute of Neuroscience and Psychology
College of Science and Engineering > School of Computing Science
Journal Name:Science Signaling
ISSN:1945-0877
ISSN (Online):1937-9145
Published Online:16 March 2010

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
438301Phosphodiesterase-4 isoforms - intracellular targeting, regulation and potential therapeutic targetsMiles HouslayMedical Research Council (MRC)G0600765Institute of Neuroscience and Psychology
374281Protein interactions and compartmentalisation in cell signallingWalter KolchMedical Research Council (MRC)G0400053Biochemistry & Cell Biology
432501Transatlantic networks of excellence in cardiovascular diseaseMiles HouslayFoundation Leducq (LEDUCQ-VIL)06 CVD 02Institute of Neuroscience and Psychology
396841Probabilistic Reconstruction of Signalling Pathways & Identification of Novel Transcription Factors Employing Heterogeneous Genome-Wide dataMark GirolamiMedical Research Council (MRC)G0401466Computing Science