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Reoccurring neural stem cell divisions in the adult zebrafish telencephalon are sufficient for the emergence of aggregated spatiotemporal patterns

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  • Valerio Lupperger
  • Carsten Marr
  • Prisca Chapouton

Abstract

Regulation of quiescence and cell cycle entry is pivotal for the maintenance of stem cell populations. Regulatory mechanisms, however, are poorly understood. In particular, it is unclear how the activity of single stem cells is coordinated within the population or if cells divide in a purely random fashion. We addressed this issue by analyzing division events in an adult neural stem cell (NSC) population of the zebrafish telencephalon. Spatial statistics and mathematical modeling of over 80,000 NSCs in 36 brain hemispheres revealed weakly aggregated, nonrandom division patterns in space and time. Analyzing divisions at 2 time points allowed us to infer cell cycle and S-phase lengths computationally. Interestingly, we observed rapid cell cycle reentries in roughly 15% of newly born NSCs. In agent-based simulations of NSC populations, this redividing activity sufficed to induce aggregated spatiotemporal division patterns that matched the ones observed experimentally. In contrast, omitting redivisions leads to a random spatiotemporal distribution of dividing cells. Spatiotemporal aggregation of dividing stem cells can thus emerge solely from the cell’s history.An interdisciplinary study of the rules governing cell divisions in a population of neural stem cells in the zebrafish brain reveals the existence of aggregated spatio-temporal division patterns of rapid cell cycles in stem cells, and shows that these patterns can be explained by a simple agent-based model relying solely on the cells‘ division history.

Suggested Citation

  • Valerio Lupperger & Carsten Marr & Prisca Chapouton, 2020. "Reoccurring neural stem cell divisions in the adult zebrafish telencephalon are sufficient for the emergence of aggregated spatiotemporal patterns," PLOS Biology, Public Library of Science, vol. 18(12), pages 1-23, December.
  • Handle: RePEc:plo:pbio00:3000708
    DOI: 10.1371/journal.pbio.3000708
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    References listed on IDEAS

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    1. Marr, Carsten & Hütt, Marc-Thorsten, 2005. "Topology regulates pattern formation capacity of binary cellular automata on graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 641-662.
    2. Marzena Mura & Céline Feillet & Roberto Bertolusso & Franck Delaunay & Marek Kimmel, 2019. "Mathematical modelling reveals unexpected inheritance and variability patterns of cell cycle parameters in mammalian cells," PLOS Computational Biology, Public Library of Science, vol. 15(6), pages 1-26, June.
    3. Tom Serge Weber & Irene Jaehnert & Christian Schichor & Michal Or-Guil & Jorge Carneiro, 2014. "Quantifying the Length and Variance of the Eukaryotic Cell Cycle Phases by a Stochastic Model and Dual Nucleoside Pulse Labelling," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-17, July.
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