Nonequilibrium models of optimal enhancer function.

Area of Science:

• Molecular Biology
• Systems Biology
• Biophysics

Background:

• Thermodynamic models accurately map prokaryotic promoter sequences to gene expression.
• Eukaryotic enhancer models lack concordance with biophysical measurements, struggling to reconcile short transcription factor (TF) residence times with high regulatory specificity.
• Existing equilibrium models face challenges, while nonequilibrium models suffer from excessive parameters.

Purpose of the Study:

• To develop minimal nonequilibrium enhancer models for eukaryotes.
• To achieve desired regulatory phenotypes: low TF residence time, high specificity, and tunable cooperativity.
• To simplify the complex parameter space of nonequilibrium models for experimental inference.

Main Methods:

• Investigated minimal nonequilibrium enhancer models.
• Introduced a single extra parameter: the 'linking rate' representing TF interaction with Mediator components.
• Analyzed the trade-off between specificity and gene expression noise.

Main Results:

• A single extra parameter (linking rate) allows models to escape equilibrium limitations and achieve optimal regulatory phenotypes.
• Models remain consistent with observed phenomenology and are simple enough for experimental validation.
• High specificity in nonequilibrium models correlates with increased gene expression noise, predicting bursty dynamics.

Conclusions:

• Minimal nonequilibrium models offer a tractable framework for understanding eukaryotic gene regulation.
• The 'linking rate' is a key parameter enabling efficient and specific enhancer function.
• These models provide testable predictions for future experiments on eukaryotic transcription dynamics.