Cell signaling model for arterial mechanobiology

Abstract

Arterial growth and remodeling at the tissue level is driven by mechanobiological processes at cellular and sub-cellular levels. Although it is widely accepted that cells seek to promote tissue homeostasis in response to biochemical and biomechanical cues-such as increased wall stress in hypertension-the ways by which these cues translate into tissue maintenance, adaptation, or maladaptation are far from understood. In this paper, we present a logic-based computational model for cell signaling within the arterial wall, aiming to predict changes in extracellular matrix turnover and cell phenotype in response to pressure-induced wall stress, flow-induced wall shear stress, and exogenous sources of angiotensin II, with particular interest in mouse models of hypertension. We simulate a number of experiments from the literature at both the cell and tissue level, involving single or combined inputs, and achieve high qualitative agreement in most cases. Additionally, we demonstrate the utility of this modeling approach for simulating alterations (in this case knockdowns) of individual nodes within the signaling network. Continued modeling of cellular signaling will enable improved mechanistic understanding of arterial growth and remodeling in health and disease, and will be crucial when considering potential pharmacological interventions.

Complementary roles of mechanotransduction and inflammation in vascular homeostasis

“…Nevertheless, there is also a need for more mechanistic modelling, e.g. incorporating appropriate cell signalling models [56] within the current continuum framework to enable modelling from transcript to tissue.…”

Uncertainty quantification in subject-specific estimation of local vessel mechanical properties

“…Future directions include the application of the presented pipeline to mechanobiological network-based models of cell signaling as well as predictive models of vascular development, growth, and remodeling. [29][30][31] Other potential applications in disease include the comparison of aneurysmal, tortuous, dissected, and/or thrombotic regions of the vessel wall to their normal counterparts. 7,48 The approach can also be extended by accounting for uncertainties in the acquired data, including histologically prescribed tissue constituent mass fractions, OCT-derived local thickness estimates, and experimental vessel deformations relative to the unloaded configuration.…”

“…29,30 These quantities include direction-specific material stiffness, stress components, and stored energy, among others. 8,31 In addition to uncertainties in the model parameters themselves, it is thus crucial to report uncertainties in these derived quantities of interest, especially for the purposes of model selection, future experimental design, computational (e.g., finite element) simulations, and application studies involving subject-specific and/or tissue-location-specific hypothesis testing. Extending the parameter estimation and uncertainty quantification pipeline presented in Section 2.4.1, we explored two approaches for propagating model parameter uncertainties: Monte Carlo sampling and an analytic approximation based on Taylor series expansion.…”

The mechanobiological theory: a unifying hypothesis on the pathogenesis of moyamoya disease based on a systematic review

“…MMP-2 and MMP-9, both gelatinases, have a remarkable ability to degrade type IV collagen, a major component of the extracellular matrix. 21 The activity and levels of MMPs are regulated by TIMP and reversion-inducing-cysteine-rich protein with kazal motifs (RECK), a negative regulator for MMP-9. Under low WSS conditions, TGFβ-1 is a crucial mediator of intimal thickening.…”

“…Shear stress-induced vascular remodeling involving ECs and SMCs is mediated by NO signaling pathways and ET-1. 21 An impaired soluble guanylate cyclase-mediated response and the loss of inhibition on ET-1 of endothelium disrupts downstream pathways involving PI3K and MAPK/ERL, resulting in SMC proliferation and degradation of the extracellular matrix through uncontrolled MMP (MMP-2 and MMP-9) activity. Thus, the blood vessel wall loses its homeostatic balance between shear stress and vessel wall integrity.…”