Parameter-free methods distinguish Wnt pathway models and guide design of experiments

Handle URI:
http://hdl.handle.net/10754/599139
Title:
Parameter-free methods distinguish Wnt pathway models and guide design of experiments
Authors:
MacLean, Adam L.; Rosen, Zvi; Byrne, Helen M.; Harrington, Heather A.
Abstract:
The canonical Wnt signaling pathway, mediated by β-catenin, is crucially involved in development, adult stem cell tissue maintenance, and a host of diseases including cancer. We analyze existing mathematical models of Wnt and compare them to a new Wnt signaling model that targets spatial localization; our aim is to distinguish between the models and distill biological insight from them. Using Bayesian methods we infer parameters for each model from mammalian Wnt signaling data and find that all models can fit this time course. We appeal to algebraic methods (concepts from chemical reaction network theory and matroid theory) to analyze the models without recourse to specific parameter values. These approaches provide insight into aspects of Wnt regulation: the new model, via control of shuttling and degradation parameters, permits multiple stable steady states corresponding to stem-like vs. committed cell states in the differentiation hierarchy. Our analysis also identifies groups of variables that should be measured to fully characterize and discriminate between competing models, and thus serves as a guide for performing minimal experiments for model comparison.
Citation:
MacLean AL, Rosen Z, Byrne HM, Harrington HA (2015) Parameter-free methods distinguish Wnt pathway models and guide design of experiments. Proc Natl Acad Sci USA 112: 2652–2657. Available: http://dx.doi.org/10.1073/pnas.1416655112.
Publisher:
Proceedings of the National Academy of Sciences
Journal:
Proceedings of the National Academy of Sciences
KAUST Grant Number:
KUK-C1-013-04
Issue Date:
17-Feb-2015
DOI:
10.1073/pnas.1416655112
PubMed ID:
25730853
PubMed Central ID:
PMC4352827
Type:
Article
ISSN:
0027-8424; 1091-6490
Sponsors:
We thank A. Burgess and C. Wee Tan for data and discussions about Wnt signaling. We also thank the anonymous reviewers as well as T. Dale, E. Feliu, A. Fletcher, K. Ho, P. K. Maini, E. O’Neill, A. Shiu, and B. Sturmfels for helpful discussions and/or comments on the manuscript. H.A.H. gratefully acknowledges funding from Engineering and Physical Sciences Research Council Fellowship EP/K041096/1 and the American Institute of Mathematics. Z.R. and H.A.H. acknowledge funding from Royal Society International Exchanges Scheme 2014/R1 IE140219. A.L.M. and H.M.B. acknowledge funding from the Human Frontiers in Science Program (RGP0039/2011). A.L.M., H.M.B., and H.A.H. acknowledge funding from King Abdullah University of Science and Technology KUK-C1-013-04.
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Full metadata record

DC FieldValue Language
dc.contributor.authorMacLean, Adam L.en
dc.contributor.authorRosen, Zvien
dc.contributor.authorByrne, Helen M.en
dc.contributor.authorHarrington, Heather A.en
dc.date.accessioned2016-02-25T13:53:35Zen
dc.date.available2016-02-25T13:53:35Zen
dc.date.issued2015-02-17en
dc.identifier.citationMacLean AL, Rosen Z, Byrne HM, Harrington HA (2015) Parameter-free methods distinguish Wnt pathway models and guide design of experiments. Proc Natl Acad Sci USA 112: 2652–2657. Available: http://dx.doi.org/10.1073/pnas.1416655112.en
dc.identifier.issn0027-8424en
dc.identifier.issn1091-6490en
dc.identifier.pmid25730853en
dc.identifier.doi10.1073/pnas.1416655112en
dc.identifier.urihttp://hdl.handle.net/10754/599139en
dc.description.abstractThe canonical Wnt signaling pathway, mediated by β-catenin, is crucially involved in development, adult stem cell tissue maintenance, and a host of diseases including cancer. We analyze existing mathematical models of Wnt and compare them to a new Wnt signaling model that targets spatial localization; our aim is to distinguish between the models and distill biological insight from them. Using Bayesian methods we infer parameters for each model from mammalian Wnt signaling data and find that all models can fit this time course. We appeal to algebraic methods (concepts from chemical reaction network theory and matroid theory) to analyze the models without recourse to specific parameter values. These approaches provide insight into aspects of Wnt regulation: the new model, via control of shuttling and degradation parameters, permits multiple stable steady states corresponding to stem-like vs. committed cell states in the differentiation hierarchy. Our analysis also identifies groups of variables that should be measured to fully characterize and discriminate between competing models, and thus serves as a guide for performing minimal experiments for model comparison.en
dc.description.sponsorshipWe thank A. Burgess and C. Wee Tan for data and discussions about Wnt signaling. We also thank the anonymous reviewers as well as T. Dale, E. Feliu, A. Fletcher, K. Ho, P. K. Maini, E. O’Neill, A. Shiu, and B. Sturmfels for helpful discussions and/or comments on the manuscript. H.A.H. gratefully acknowledges funding from Engineering and Physical Sciences Research Council Fellowship EP/K041096/1 and the American Institute of Mathematics. Z.R. and H.A.H. acknowledge funding from Royal Society International Exchanges Scheme 2014/R1 IE140219. A.L.M. and H.M.B. acknowledge funding from the Human Frontiers in Science Program (RGP0039/2011). A.L.M., H.M.B., and H.A.H. acknowledge funding from King Abdullah University of Science and Technology KUK-C1-013-04.en
dc.publisherProceedings of the National Academy of Sciencesen
dc.subjectExperimental designen
dc.subjectBayesian inferenceen
dc.subjectBistabilityen
dc.subjectChemical Reaction Network Theoryen
dc.subjectMatroidsen
dc.subject.meshModels, Biologicalen
dc.titleParameter-free methods distinguish Wnt pathway models and guide design of experimentsen
dc.typeArticleen
dc.identifier.journalProceedings of the National Academy of Sciencesen
dc.identifier.pmcidPMC4352827en
dc.contributor.institutionMathematical Institute, University of Oxford, Oxford OX2 6GG, United Kingdom;en
dc.contributor.institutionDepartment of Mathematics, University of California, Berkeley, CA 94720; and.en
dc.contributor.institutionMathematical Institute, University of Oxford, Oxford OX2 6GG, United Kingdom; Department of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.en
dc.contributor.institutionMathematical Institute, University of Oxford, Oxford OX2 6GG, United Kingdom; harrington@maths.ox.ac.uk.en
kaust.grant.numberKUK-C1-013-04en
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