Spatial modelling of NOTCH signalling predicts tuneable dynamic heterogeneity in endothelia

Endothelial cells (ECs) are phenotypically heterogeneous to perform specialised functions across different organs and tissues. Although environmental inputs are considered key drivers, we previously observed persistent diversity in NOTCH pathway activation within quiescent endothelia, but the underlying mechanism remains unclear. Here, we developed a computational–experimental framework linking core NOTCH dynamics to emergent EC heterogeneity in space and time. We built an agent-based model of NOTCH signalling incorporating lateral inhibition, lateral induction, cis interactions, and optional HES1 autoregulation, and constrained timescales using HUVEC cultures under γ-secretase inhibition. Model exploration identified regimes with emergent asynchronous HES1 oscillations driven by productive cis interactions or by autoregulation. Contact-modulated cis / trans interactions reproduced the experimentally observed spatial distributions, whereas autoregulation produced globally synchronised dynamics inconsistent with spatial heterogeneity. Additionally, oscillation amplitude and local synchrony were tuneable by varying biologically relevant parameters. Consistent with these predictions, sparse-versus-confluent experiments showed that intercellular contact is required for spatial heterogeneity. Overall, our results support the hypothesis that intrinsic, contact-dependent NOTCH dynamics can generate heterogeneous EC phenotypes, providing a mechanistic basis for functional plasticity in quiescent monolayers. We provide the calibrated model as an open-source, extensible resource for reproducible testing of alternative NOTCH interaction hypotheses against future quantitative datasets.

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Publication Details

Journal
npj Systems Biology and Applications
Published
2026-07-23
DOI
https://doi.org/10.1038/s41540-026-00786-0
Primary Topic
Cellular Mechanics and Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatial modelling of NOTCH signalling predicts tuneable dynamic heterogeneity in endothelia

Elena Engstler, Lorenzo Veschini, Jonas Hue, Matteo Battilocchi et al.
npj Systems Biology and Applications
Cellular Mechanics and Interactions
article

Spatial modelling of NOTCH signalling predicts tuneable dynamic heterogeneity in endothelia

Elena Engstler, Lorenzo Veschini, Jonas Hue, Matteo Battilocchi, Davide Danovi, James A. Glazier, Francois Chesnais, TJ Sego
article en

Abstract

Endothelial cells (ECs) are phenotypically heterogeneous to perform specialised functions across different organs and tissues. Although environmental inputs are considered key drivers, we previously observed persistent diversity in NOTCH pathway activation within quiescent endothelia, but the underlying mechanism remains unclear. Here, we developed a computational–experimental framework linking core NOTCH dynamics to emergent EC heterogeneity in space and time. We built an agent-based model of NOTCH signalling incorporating lateral inhibition, lateral induction, cis interactions, and optional HES1 autoregulation, and constrained timescales using HUVEC cultures under γ-secretase inhibition. Model exploration identified regimes with emergent asynchronous HES1 oscillations driven by productive cis interactions or by autoregulation. Contact-modulated cis / trans interactions reproduced the experimentally observed spatial distributions, whereas autoregulation produced globally synchronised dynamics inconsistent with spatial heterogeneity. Additionally, oscillation amplitude and local synchrony were tuneable by varying biologically relevant parameters. Consistent with these predictions, sparse-versus-confluent experiments showed that intercellular contact is required for spatial heterogeneity. Overall, our results support the hypothesis that intrinsic, contact-dependent NOTCH dynamics can generate heterogeneous EC phenotypes, providing a mechanistic basis for functional plasticity in quiescent monolayers. We provide the calibrated model as an open-source, extensible resource for reproducible testing of alternative NOTCH interaction hypotheses against future quantitative datasets.

npj Systems Biology and Applications
King's College London (GB), The Francis Crick Institute (GB), University of Florida (US), Oxford Biotherapeutics (United Kingdom) (GB), Indiana University Bloomington (US), National Dental Centre of Singapore (SG), Columbia University (US)
King's College London
Openalex Percentile: Top 12%
Cellular Mechanics and Interactions
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