Abstract

Ultradian oscillations of HES Transcription Factors (TFs) at the single‐cell level enable cell state transitions. However, the tissue‐level organisation of HES5 dynamics in neurogenesis is unknown. Here, we analyse the expression of HES5 ex vivo in the developing mouse ventral spinal cord and identify microclusters of 4–6 cells with positively correlated HES5 level and ultradian dynamics. These microclusters are spatially periodic along the dorsoventral axis and temporally dynamic, alternating between high and low expression with a supra‐ultradian persistence time. We show that Notch signalling is required for temporal dynamics but not the spatial periodicity of HES5. Few Neurogenin 2 cells are observed per cluster, irrespective of high or low state, suggesting that the microcluster organisation of HES5 enables the stable selection of differentiating cells. Computational modelling predicts that different cell coupling strengths underlie the HES5 spatial patterns and rate of differentiation, which is consistent with comparison between the motoneuron and interneuron progenitor domains. Our work shows a previously unrecognised spatiotemporal organisation of neurogenesis, emergent at the tissue level from the synthesis of single‐cell dynamics.

Details

Title
A dynamic, spatially periodic, micro‐pattern of HES5 underlies neurogenesis in the mouse spinal cord
Author
Biga, Veronica 1   VIAFID ORCID Logo  ; Hawley, Joshua 1   VIAFID ORCID Logo  ; Soto, Ximena 1   VIAFID ORCID Logo  ; Johns, Emma 1   VIAFID ORCID Logo  ; Han, Daniel 2   VIAFID ORCID Logo  ; Bennett, Hayley 1 ; Adamson, Antony D 1   VIAFID ORCID Logo  ; Kursawe, Jochen 3   VIAFID ORCID Logo  ; Glendinning, Paul 2 ; Manning, Cerys S 1   VIAFID ORCID Logo  ; Papalopulu, Nancy 1   VIAFID ORCID Logo 

 Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK 
 Department of Mathematics, School of Natural Sciences, Faculty of Science and Engineering, The University of Manchester, Manchester, UK 
 School of Mathematics and Statistics, University of St Andrews, St Andrews, UK 
Section
Articles
Publication year
2021
Publication date
May 2021
Publisher
EMBO Press
e-ISSN
17444292
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2533110159
Copyright
© 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.