# DMS/NIGMS 2: The mathematics of epigenetic regulation in human cells

> **NIH NIH R01** · UNIVERSITY OF TEXAS DALLAS · 2024 · $294,647

## Abstract

A major challenge at the interface of mathematics and molecular and cellular biology remains the
 development of accurate and predictive models of epigenetic mechanisms. While eukaryotic transcription
 is substantially influenced via epigenetic mechanisms, the majority of mathematical models pay little
attention to this crucial regulation modality. Herein we propose a theoretical, computational, and
experimental framework to model epigenetic regulatory networks in single cells. Herein we introduce a
theoretical, computational, and experimental framework to model epigenetic regulatory networks in single
cells. Specifically, we propose to assemble and stably integrate epigenetic regulators and increasingly
 complex circuits in human cells. These stably integrated circuits will serve as biomolecular "ground truth"
for inference and characterization techniques comprising theory and computational analysis in an iterative
manner. Using theoretical analysis coupled with experimentation, we will comprehensively characterize
 the circuits to identify general principles of epigenetic mechanisms with emphasis on probing their
 dynamic behavior and stability. The transforming quality of our proposal is based on the following notions.
We will establish a methodology to rapidly assemble and stably integrate libraries of CRISPR-based
 epigenetic regulators in human cells. These libraries will cover a wide parameter space providing wealth
 of data for extracting parameters to inform the mathematic models. Our methodology for rapid library
assembly is a significant advance for the mammalian synthetic biology field, where progress is hampered
 by slow experimental timescales. We will study the properties of epigenetic circuits stably integrated in a
 panel of human cell lines. We will test the boundaries of genome editing of safe harbor loci and develop
 new methods for integrating large DNA cassettes. We will develop a theoretical and computational
framework to model single-cell stochastic gene expression kinetics in hybrid gene regulatory networks.
We will validate and calibrate the models using experimental data generated using custom epigenetic
 regulators. We will correlate the effects of network topology and mode of regulation on the stationary and
 dynamic behavior of stochastic gene expression. Validated models of epigenetic regulation will be used to
 predict the conditions capable to produce multistability, critical phase transitions, and oscillations.

## Key facts

- **NIH application ID:** 11043483
- **Project number:** 1R01GM157608-01
- **Recipient organization:** UNIVERSITY OF TEXAS DALLAS
- **Principal Investigator:** Leonidas Bleris
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $294,647
- **Award type:** 1
- **Project period:** 2024-09-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11043483

## Citation

> US National Institutes of Health, RePORTER application 11043483, DMS/NIGMS 2: The mathematics of epigenetic regulation in human cells (1R01GM157608-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11043483. Licensed CC0.

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