Analysis of a Bistable Chromatin Modification Network
Author(s)
Wang, Hengyu
Del Vecchio, Domitilla
Date Issued
2026
Journal
Proceedings of the 65th IEEE Conference on Decision and Control (CDC 2026)
Publisher
Institute of Electrical and Electronics Engineers
Citation
H. Wang and D. Del Vecchio, “Analysis of a Bistable Chromatin Modification Network,” accepted for presentation at the 65th IEEE Conference on Decision and Control (CDC 2026), Honolulu, HI, USA, 2026.
Abstract
Bistable biomolecular networks that can be switched between two stable states through user-defined inputs have applications in many areas, from targeted drug delivery and directed differentiation, to biosensing. While the design of these networks has been considered in synthetic biology since its inception, today, the engineering of such bistable systems in mammalian cells such that the two stable states can be maintained for long time despite the influence of noise is still an area of investigation. In fact, stochastic fluctuations in the biochemical reactions generally cause unwanted switches between the two states, and design principles to make these switches less probable are of interest. In this paper, we propose a design of a bistable network in mammalian cells that uses DNA methylation as opposed to transcription-factor based gene repression, in order to achieve long-term memory. We introduce the chemical reaction model, we perform deterministic analysis to provide mathematical conditions on the parameters to achieve bistability, and then we perform stochastic analysis of the system. This analysis relies on the theory of singularly perturbed continuous-time Markov chains to provide an analytical investigation of how the probability of switching between the memory states depends on biochemical parameters. This analysis provides guidelines for the practical design of this system in mammalian cells and illustrates the benefit of using chromatin modifications as a regulatory mechanism to achieve long-term memories.
Subjects
epigenetic memory
chromatin modification
continuous-time Markov chains
synthetic biology
DNA methylation
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
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