CYTOSOLVE CASE STUDY: Massachusetts Institute of Technology (MIT)

The Massachusetts Institute of Technology (MIT) is a leading global institution in science and engineering research. Researchers from MIT’s Department of Biological Engineering, Department of Mechanical Engineering, and Laboratory for Information and Decision Systems, in collaboration with partners from Harvard Medical School and King’s College London, applied CytoSolve computational systems biology to study cardiovascular mechanotransduction. Their goal was to unravel the complex regulation of nitric oxide (NO) production in vascular endothelial cells under fluid shear stress—a key determinant of vascular health.

Challenge

Nitric oxide (NO) produced by endothelial cells lining the blood vessels is a potent vasodilator and mediator of vascular homeostasis. However, NO production is regulated by a complex network of biochemical pathways that respond to biomechanical stimuli such as shear stress from blood flow. Traditional reductionist approaches often isolate single pathways, limiting understanding of how these pathways interact dynamically in response to fluid shear forces. A systems-level mechanistic model was needed to integrate multiple signaling and regulatory pathways simultaneously and predict NO production dynamics under physiological shear stress conditions.

How CytoSolve Helped

MIT researchers used the CytoSolve platform to build a comprehensive in silico model of shear-stress-induced NO production by:

  • Performing a systematic literature review to identify molecular pathways governing endothelial nitric oxide synthase (eNOS) activation and NO synthesis.
  • Selecting four distinct quantitative molecular pathways implicated in shear-stress-mediated eNOS regulation (calcium signaling, phosphorylation cascades, transcriptional regulation via AP-1 and KLF2, and direct NO catalytic production).
  • Converting each pathway into an independently validated mathematical model using established kinetic parameters.
  • Integrating individual subsystems using CytoSolve to dynamically simulate pathway interactions under shear-stress conditions.
  • Running simulations to capture the time-dependent NO production profile and explore relative contributions of each pathway component.

This multi-model integration enabled predictive insights into complex endothelium mechanobiology that would be difficult to achieve with isolated experimental assays.

Key Benefits Realized

  • Systems integration of multiple NO regulatory pathways into a unified predictive model.
  • Quantitative simulation of shear-stress effects on NO production in endothelial cells.
  • Mechanistic insights into relative contributions of calcium signaling, eNOS phosphorylation, and transcriptional control.
  • Enhanced interpretability of pathway interactions under physiological conditions.
  • Platform extensibility for testing genetic or pharmacological perturbations in silico.

Outcome

CytoSolve’s in silico modeling provided an integrative framework capturing the dynamic regulation of nitric oxide production in response to fluid shear stress. Simulations reproduced experimentally observed NO production profiles and illuminated how calcium influx, phosphorylation events, and transcription factor-mediated eNOS expression contribute over time to NO synthesis.

By preserving individual pathway identities and enabling their dynamic coupling, the model demonstrated robustness and predictive power for exploring endothelial responses to mechanical forces. This work offers a mechanistic baseline for further studies on vascular function and has broad implications for understanding cardiovascular health, including atherosclerosis, hypertension, and flow-mediated vascular remodeling.