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A spatio-temporal model to reveal oscillator phenotypes in molecular clocks : parameter estimation elucidates circadian gene transcription dynamics in single-cells

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Unosson, Måns, Brancaccio, Marco, Hastings, Michael H., Johansen, Adam M. and Finkenstädt, Bärbel (2021) A spatio-temporal model to reveal oscillator phenotypes in molecular clocks : parameter estimation elucidates circadian gene transcription dynamics in single-cells. PLoS Computational Biology, 17 (12). e1009698. doi:10.1371/journal.pcbi.1009698

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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1009698

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Abstract

We propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatio-temporal gene expression in intact networks of cells. The model describes the oscillating time evolution of molecular mRNA counts through a negative transcriptional-translational feedback loop encoded in a chemical Langevin equation with a probabilistic delay distribution. The model is extended spatially by means of a multiplicative random effects model with a first order Markov random field prior distribution. Our methodology effectively separates intrinsic molecular noise, measurement noise, and extrinsic noise and phenotypic variation driving cell heterogeneity, while being amenable to parameter identification and inference. Based on the single-cell model we propose a novel computational stability analysis that allows us to infer two key characteristics, namely the robustness of the oscillations, i.e. whether the reaction network exhibits sustained or damped oscillations, and the profile of the regulation, i.e. whether the inhibition occurs over time in a more distributed versus a more direct manner, which affects the cells’ ability to phase-shift to new schedules. We show how insight into the spatio-temporal characteristics of the circadian feedback loop in the suprachiasmatic nucleus (SCN) can be gained by applying the methodology to bioluminescence-reported expression of the circadian core clock gene Cry1 across mouse SCN tissue. We find that while (almost) all SCN neurons exhibit robust cell-autonomous oscillations, the parameters that are associated with the regulatory transcription profile give rise to a spatial division of the tissue between the central region whose oscillations are resilient to perturbation in the sense that they maintain a high degree of synchronicity, and the dorsal region which appears to phase shift in a more diversified way as a response to large perturbations and thus could be more amenable to entrainment.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Q Science > QH Natural history
Q Science > QP Physiology
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Gene expression, Gene expression -- Statistical methods, Messenger RNA, Langevin equations , Cell cycle , Suprachiasmatic nucleus
Journal or Publication Title: PLoS Computational Biology
Publisher: Public Library of Science
ISSN: 1553-7358
Official Date: 17 December 2021
Dates:
DateEvent
17 December 2021Published
29 November 2021Accepted
Volume: 17
Number: 12
Article Number: e1009698
DOI: 10.1371/journal.pcbi.1009698
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
1791198[ESRC] Economic and Social Research Councilhttp://dx.doi.org/10.13039/501100000269
EP/R034710/1 [EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/T004134/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
UNSPECIFIEDLloyd's Register Foundationhttp://dx.doi.org/10.13039/100008885

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