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microRNA input into a neural ultradian oscillator controls emergence and timing of alternative cell states

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  • Marc Goodfellow

    (Faculty of Life Sciences, Michael Smith Building, The University of Manchester
    Present address: College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, Devon EX4 4QF, UK)

  • Nicholas E. Phillips

    (Faculty of Life Sciences, Michael Smith Building, The University of Manchester)

  • Cerys Manning

    (Faculty of Life Sciences, Michael Smith Building, The University of Manchester)

  • Tobias Galla

    (Theoretical Physics, School of Physics and Astronomy, The University of Manchester)

  • Nancy Papalopulu

    (Faculty of Life Sciences, Michael Smith Building, The University of Manchester)

Abstract

Progenitor maintenance, timed differentiation and the potential to enter quiescence are three fundamental processes that underlie the development of any organ system. In the nervous system, progenitor cells show short-period oscillations in the expression of the transcriptional repressor Hes1, while neurons and quiescent progenitors show stable low and high levels of Hes1, respectively. Here we use experimental data to develop a mathematical model of the double-negative interaction between Hes1 and a microRNA, miR-9, with the aim of understanding how cells transition from one state to another. We show that the input of miR-9 into the Hes1 oscillator tunes its oscillatory dynamics, and endows the system with bistability and the ability to measure time to differentiation. Our results suggest that a relatively simple and widespread network of cross-repressive interactions provides a unifying framework for progenitor maintenance, the timing of differentiation and the emergence of alternative cell states.

Suggested Citation

  • Marc Goodfellow & Nicholas E. Phillips & Cerys Manning & Tobias Galla & Nancy Papalopulu, 2014. "microRNA input into a neural ultradian oscillator controls emergence and timing of alternative cell states," Nature Communications, Nature, vol. 5(1), pages 1-10, May.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4399
    DOI: 10.1038/ncomms4399
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    Cited by:

    1. Yujin Harada & Mayumi Yamada & Itaru Imayoshi & Ryoichiro Kageyama & Yutaka Suzuki & Takaaki Kuniya & Shohei Furutachi & Daichi Kawaguchi & Yukiko Gotoh, 2021. "Cell cycle arrest determines adult neural stem cell ontogeny by an embryonic Notch-nonoscillatory Hey1 module," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    2. Nick E Phillips & Cerys Manning & Nancy Papalopulu & Magnus Rattray, 2017. "Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes," PLOS Computational Biology, Public Library of Science, vol. 13(5), pages 1-30, May.

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