Abstract
The Notch pathway plays a vital role in determining whether cells in the intestinal epithelium adopt a secretory or an absorptive phenotype. Cell fate specification is coordinated via Notch’s interaction with the canonical Wnt pathway. Here, we propose a new mathematical model of the Notch and Wnt pathways, in which the Hes1 promoter acts as a hub for pathway crosstalk. Computational simulations of the model can assist in understanding how healthy intestinal tissue is maintained, and predict the likely consequences of biochemical knockouts upon cell fate selection processes. Chemical reaction network theory (CRNT) is a powerful, generalised framework which assesses the capacity of our model for monostability or multistability, by analysing properties of the underlying network structure without recourse to specific parameter values or functional forms for reaction rates. CRNT highlights the role of β-catenin in stabilising the Notch pathway and damping oscillations, demonstrating that Wnt-mediated actions on the Hes1 promoter can induce dynamic transitions in the Notch system, from multistability to monostability. Time-dependent model simulations of cell pairs reveal the stabilising influence of Wnt upon the Notch pathway, in which β-catenin- and Dsh-mediated action on the Hes1 promoter are key in shaping the subcellular dynamics. Where Notch-mediated transcription of Hes1 dominates, there is Notch oscillation and maintenance of fate flexibility; Wnt-mediated transcription of Hes1 favours bistability akin to cell fate selection. Cells could therefore regulate the proportion of Wnt- and Notch-mediated control of the Hes1 promoter to coordinate the timing of cell fate selection as they migrate through the intestinal epithelium and are subject to reduced Wnt stimuli. Furthermore, mutant cells characterised by hyperstimulation of the Wnt pathway may, through coupling with Notch, invert cell fate in neighbouring healthy cells, enabling an aberrant cell to maintain its neighbours in mitotically active states.
| Original language | English (US) |
|---|---|
| Pages (from-to) | e1005400 |
| Journal | PLOS Computational Biology |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 28 2017 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: SKK was supported by an EPSRC-funded Systems Biology Doctoral Training Centre studentship (EP/D508142/1, EP/F500017/1, www.epsrc.ac.uk) and a Google EMEA Scholarship. HAH was supported by an EPSRC Fellowship (EP/K041096/1, www.epsrc.ac.uk) and funding from the King Abdullah University of Science and Technology (KAUST) (KUK-C1-013-04, www.kaust.edu.sa). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.