dc.contributor.author | Phillips, NE | |
dc.contributor.author | Manning, CS | |
dc.contributor.author | Pettini, T | |
dc.contributor.author | Biga, V | |
dc.contributor.author | Marinopoulou, E | |
dc.contributor.author | Stanley, P | |
dc.contributor.author | Boyd, J | |
dc.contributor.author | Bagnall, J | |
dc.contributor.author | Paszek, P | |
dc.contributor.author | Spiller, DG | |
dc.contributor.author | White, MRH | |
dc.contributor.author | Goodfellow, M | |
dc.contributor.author | Galla, T | |
dc.contributor.author | Rattray, M | |
dc.contributor.author | Papalopulu, N | |
dc.date.accessioned | 2016-10-06T11:24:53Z | |
dc.date.issued | 2016 | |
dc.description.abstract | 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 posttranscriptional
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. | en_GB |
dc.description.sponsorship | This work was supported by a Wellcome Trust Senior Research Fellowship to NP (090868/Z/09/Z), a Sir Henry Wellcome Fellowship to CM (103986/Z/14/Z), a Wellcome Trust Institutional Strategic Support Award (097820/Z/11/B) and a BBSRC Doctoral Training Centre in Systems Biology studentship to NEP. PP holds a BBSRC David Phillips Research Fellowship (BB/I017976/1). MG gratefully acknowledges the financial support of the EPSRC via grant EP/N014391/1. The contribution of MG was generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA). J Boyd was funded by MRC grant MR/K015885/1. DS and MW’s work is funded by an MRC grant MR/K015885/1 and a BBSRC grant BB/K003097/1. The authors would also like to thank the Biological Services Facility (BSF), the Bioimaging and Flow Cytometry Facilities of the Computational and Systems Biology Developmental Biology and Stem Cells University of Manchester for technical support, in particular to Dr Gareth Howell for expert advice on challenging FACS sorts. We thank Dr. Ximena Soto for advice and discussions and Dr Angelica Santiago-Gomez from Robert B Clarke’s group at the MCRC, Manchester for technical support and advice with western blotting. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. | en_GB |
dc.identifier.citation | 2016;5: e16118. DOI: 10.7554/eLife.16118 | en_GB |
dc.identifier.doi | 10.7554/eLife.16118 | |
dc.identifier.uri | http://hdl.handle.net/10871/23785 | |
dc.language.iso | en | en_GB |
dc.publisher | eLife Sciences Publications | en_GB |
dc.rights | Copyright Phillips et al. This
article is distributed under the
terms of the Creative Commons
Attribution License, which
permits unrestricted use and
redistribution provided that the
original author and source are
credited. | en_GB |
dc.title | Stochasticity in the miR-9/Hes1 oscillatory network can account for clonal heterogeneity in the timing of differentiation | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2016-10-06T11:24:53Z | |
dc.identifier.issn | 2050-084X | |
dc.description | This is the final version of the article. Available from the publisher via the DOI in this record. | en_GB |
dc.identifier.journal | eLife | en_GB |