Abstract
Nanog maintains pluripotency of embryonic stem cells (ESC's), while demonstrating high expression heterogeneity within an ESC population. Intriguingly, in ESC's, the overall heterogeneity at the Nanog mRNA level under various culture conditions gets precisely partitioned into intrinsic (~45%) and extrinsic (~55%) fluctuations. However, the dynamical origin of such a robust transcriptional noise regulation, still remains illusive. Herein, we conceived a new stochastic simulation strategy centered around Gillespie's stochastic simulation algorithm to efficiently capture fluctuations of different origins that are operative within a simple Nanog transcriptional regulatory network. Our model simulations reconcile the strict apportioning of Nanog transcriptional fluctuation, while predicting possible experimental scenarios to avoid such an exact noise segregation. Importantly, model analyses reveal that different culture conditions essentially preserve the Nanog expression heterogeneity by altering the dynamics of transcriptional events. These insights will be essential to systematically maneuver cell-fate decision making events of ESC's for therapeutic applications.