College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom; Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, United Kingdom; EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
Tobias Galla
Theoretical Physics, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
Magnus Rattray
Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
Recent studies suggest that cells make stochastic choices with respect to differentiation or division. However, the molecular mechanism underlying such stochasticity is unknown. We previously proposed that the timing of vertebrate neuronal differentiation is regulated by molecular oscillations of a transcriptional repressor, HES1, tuned by a post-transcriptional repressor, miR-9. Here, we computationally model the effects of intrinsic noise on the Hes1/miR-9 oscillator as a consequence of low molecular numbers of interacting species, determined experimentally. We report that increased stochasticity spreads the timing of differentiation in a population, such that initially equivalent cells differentiate over a period of time. Surprisingly, inherent stochasticity also increases the robustness of the progenitor state and lessens the impact of unequal, random distribution of molecules at cell division on the temporal spread of differentiation at the population level. This advantageous use of biological noise contrasts with the view that noise needs to be counteracted.