Abstract
Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional “variations” among genetically identical cells, for the emergence of bistability and transition between phenotypic states.
Highlights
Individual cells of a given genotype can exhibit various phenotypes
Identifying the mechanism underlying the coexistence of multiple stable phenotypic states has been a challenging scientific problem for more than half a century, and an appropriate mathematical model at the single-cell level is in high demand
Single-cell measurements conducted in the past ten years have shown that gene-state switching is slow relative to the typical rates of active transcription and translation; the recently proposed fluctuating-rate model is a good candidate for describing the single-cell dynamics
Summary
Individual cells of a given genotype can exhibit various phenotypes. The phenotype of a cell usually refers to distinct characteristics (static and dynamic, physical or chemical) and the associative biological functions of the cell. Extending the central dogma of molecular biology, it is accepted that the behavior of a single cell is determined by both the genomic polynucleic acid sequence and the dynamics of intracellular biochemical networks in space and time. It is only through intracellular biochemistry that extracellular conditions can interact with genes. Based on this perspective, we propose the following: for a population of cells with identical genomes and extracellular conditions, each phenotype can be represented by a cluster of single-cell data defined as a peak (e.g., modal value) in the multi-dimensional histogram of biomolecular copy-numbers measured at steady state. Multiple peaks naturally discretize the space; at a given instance in time, a single cell can reside in one of these discrete states
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