Ultradian oscillations of HES Transcription Factors (TFs) at the single-cell level enable cell state transitions. However, the tissuelevel 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.
Hes genes are transcriptional repressors activated by Notch. In the developing mouse neural tissue, HES5 expression oscillates in neural progenitors (Manning et al. 2019 Nat. Commun. 10 , 1–19 ( doi:10.1038/s41467-019-10734-8 )) and is spatially organized in small clusters of cells with synchronized expression (microclusters). Furthermore, these microclusters are arranged with a spatial periodicity of three–four cells in the dorso-ventral axis and show regular switching between HES5 high/low expression on a longer time scale and larger amplitude than individual temporal oscillators (Biga et al. 2021 Mol. Syst. Biol. 17 , e9902 ( doi:10.15252/msb.20209902 )). However, our initial computational modelling of coupled HES5 could not explain these features of the experimental data. In this study, we provide theoretical results that address these issues with biologically pertinent additions. Here, we report that extending Notch signalling to non-neighbouring progenitor cells is sufficient to generate spatial periodicity of the correct size. In addition, introducing a regular perturbation of Notch signalling by the emerging differentiating cells induces a temporal switching in the spatial pattern, which is longer than an individual cell’s periodicity. Thus, with these two new mechanisms, a computational model delivers outputs that closely resemble the complex tissue-level HES5 dynamics. Finally, we predict that such dynamic patterning spreads out differentiation events in space, complementing our previous findings whereby the local synchronization controls the rate of differentiation.
her6 is a zebrafish ortholog of Hes1, known for its role in maintaining neural progenitors during neural development. Here, we characterise the population-level effect of altering Her6 protein expression dynamics at the single-cell level in the embryonic zebrafish telencephalon. Using an endogenous Her6:Venus reporter and 4D single-cell tracking, we show that Her6 oscillates in neural telencephalic progenitors and that fusion of a protein destabilisation domain (PEST) to Her6:Venus alters its expression dynamics causing most cells to downregulate Her6 prematurely. However, in PEST mutants, a higher proportion of cells exhibit Her6 oscillations and while expression is reduced in most cells, some cells express Her6 at wild-type levels resulting in increased heterogeneity of Her6 expression in the population. Despite the profound differences in the single-cell Her6 dynamics, differentiation markers do not exhibit major differences early on, while an increase in differentiation is observed at later developmental stages (vglut2a, gad1 and gad2). At the same time, at late stage the overall size of the telencephalon remains the same. Computational modelling that simulates changes in Her6 protein stability reveals that the increase in population Her6 expression heterogeneity is an emergent property of finely tuned Notch signalling coupling between single cells. Our study suggests that such cell coupling provides a compensation strategy whereby a normal phenotype is maintained while single-cell dynamics are abnormal, although the limit of this compensation is reached at late developmental stages. We conclude that in the neural progenitor population, cell coupling controls Her6 expression heterogeneity and in doing so, it provides phenotypic robustness when individual cells lose Her6 expression prematurely.
Some regulatory transcription factors (TFs), such as the Helix-loop-Helix TF, HES5, show dynamic expression including ultradian oscillations, when imaged in real time at the single cell level. Such dynamic expression is key for enabling cell state transitions in a tissue environment. In somitogenesis, such expression is highly synchronised in blocks of tissue (somites), however, in neurogenesis it is not known how single cell dynamics are coordinated, the multiscale pattern that emerges and the significance for differentiation. In this study, we monitor the expression of HES5 protein ex-vivo in the developing spinal cord and identify the existence of microclusters of HES5 expressing progenitors that are spatially periodic along the dorso-ventral (D-V) axis and that in addition are temporally dynamic. We use multiscale computational modelling to show that such microclusters arise at least in part from local synchronisation in HES5 levels between single cells mediated by Notch-Delta interactions. We find that the HES5 microclusters are less dynamic in the presence of a Notch inhibitor showing that Notch mediated cell-cell communication is required for temporal characteristics. Moreover, predictions from the computational modelling and experimental data show that the strength of interaction between neighbouring cells is a key factor controlling the rate of differentiation in a domain specific manner. Our work provides evidence of co-ordination between single cells in the tissue environment during the progenitor to neural transition and shows the functional role of complexity arising from simple interactions between cells.
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