Uncovering minimal control of cell fate by natural dynamics.

Abstract

It is crucial to identify cues that induce cell fate transitions for applications ranging from cell therapy to drug discovery. Computational analysis of logical models of gene regulatory networks can identify such cues, which can then be used by control strategies to direct cell fate. However, current control strategies emphasize permanent interventions that cripple natural regulatory responses, undermining phenotypic plasticity and risking unexpected behavior. We illustrate how, conversely, single-time temporary control preserves natural regulatory interactions. For this purpose we develop NUDGE: a computational framework formally guaranteed to find all minimal interventions for a desired phenotype that conserve natural dynamics, alongside an efficient approximation for large networks. We then apply our framework to existing biological networks. These case studies reveal how control of natural dynamics recovers cardiomyocyte restoration cues central to heart regeneration, resolves a mast cell fate controversy, and matches cytokine response diversity to the spectrum of anti-inflammatory macrophages. Instead of controlling cell fate at the expense of phenotypic diversity and viability, NUDGE pioneers an alternative paradigm that preserves the functionality of the system encoded by natural dynamics.