DEMSIM: a discrete event based mechanistic simulation platform for gene expression and regulation dynamics

Area of Science:

• Systems Biology
• Computational Biology
• Molecular Biology

Background:

• Gene expression involves complex regulatory networks.
• Accurate modeling of these networks is crucial for understanding cellular function.
• Stochasticity plays a significant role in gene regulation.

Purpose of the Study:

• To develop a discrete event-based mechanistic simulation platform (DEMSIM) for testing gene regulatory interactions.
• To model transcription, translation, and decay processes with superimposed regulatory circuitry.
• To capture inherent stochasticity in gene expression using Monte Carlo methods.

Main Methods:

• Developed a discrete event-based mechanistic simulation platform (DEMSIM).
• Modeled gene expression processes (transcription, translation, decay) as modules.
• Incorporated regulatory circuitry and used Monte Carlo sampling for stochasticity.
• Applied the framework to lac operon, SOS response, and araBAD operon systems in E. coli.

Main Results:

• DEMSIM accurately captures gene regulation dynamics in the lac operon system.
• The framework predicts system behavior under perturbations for the SOS response system.
• DEMSIM distinguishes between plausible regulatory mechanisms for the araBAD system.
• Validated the platform's effectiveness across multiple well-studied bacterial systems.

Conclusions:

• DEMSIM is an effective tool for simulating and validating gene regulatory interactions.
• The platform aids in understanding the dynamics and predicting the behavior of gene regulatory networks.
• DEMSIM facilitates the exploration of alternative hypotheses for observed gene expression profiles.