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.
Original language | English (US) |
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Pages (from-to) | 2652-2657 |
Number of pages | 6 |
Journal | Proceedings of the National Academy of Sciences |
Volume | 112 |
Issue number | 9 |
DOIs | |
State | Published - Feb 17 2015 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: 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.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.