Regulated Fluctuations in Nanog Expression Mediate Cell Fate Decisions in Embryonic Stem Cells

Abstract

There is evidence that pluripotency of mouse embryonic stem (ES) cells is associated with the activity of a network of transcription factors with Sox2, Oct4, and Nanog at the core. Using fluorescent reporters for the expression of Nanog, we observed that a population of ES cells is best described by a dynamic distribution of Nanog expression characterized by two peaks defined by high (HN) and low (LN) Nanog expression. Typically, the LN state is 5%–20% of the total population, depending on the culture conditions. Modelling of the activity of Nanog reveals that a simple network of Oct4/Sox2 and Nanog activity can account for the observed distribution and its properties as long as the transcriptional activity is tuned by transcriptional noise. The model also predicts that the LN state is unstable, something that is born out experimentally. While in this state, cells can differentiate. We suggest that transcriptional fluctuations in Nanog expression are an essential element of the pluripotent state and that the function of Sox2, Oct4, and Nanog is to act as a network that promotes and maintains transcriptional noise to interfere with the differentiation signals. Embryonic stem (ES) cells are a pluripotent cell population derived from early mammalian embryos. An intrinsic feature of ES cells is their phenotypic heterogeneity: they display promiscuous activation of lineage-specific genes and exhibit a fluctuating flow of differentiating cells. A gene regulatory network (GRN) centred around the transcription factors Sox2, Oct4, and Nanog is essential for the establishment and the maintenance of the pluripotent state. Previous studies had suggested that ES cells can reversibly change their state of Nanog expression without losing pluripotency. Here, we extend these studies by quantifying and monitoring the expression of Nanog in a Nanog-GFP reporter cell line. We show that Nanog levels undergo slow, random fluctuations in ES cells, giving rise to heterogeneous cell populations. We identify two states, one stable, characterized by high levels of expression (HN), and another with low levels of Nanog expression (LN), which is highly unstable. While in the LN state, cells are more likely to differentiate depending on the culture medium. Mathematical modelling shows that a simple excitable system driven by transcriptional noise can account for the observed distributions and behaviours in gene expression. Our study suggests that rather than a discrete state dependent on the fixed expression of a small set of genes, pluripotency is best represented by a state of dynamic heterogeneity of a population driven by transcriptional noise, and that the function of the gene regulatory network centred around Nanog might be to generate dynamic heterogeneities at the population level.