Aggregated spatio-temporal division patterns emerge from reoccurring divisions of neural stem cells

Abstract

The 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 brains revealed weakly aggregated, non-random division patterns in space and time. Analyzing divisions at two timepoints allowed us to infer cell cycle and S-phase lengths computationally. Interestingly, we observed rapid cell cycle re-entries in roughly 15% of newly born NSCs. In agent based simulations of NSC populations, this re-dividing activity sufficed to induce aggregated spatio-temporal division patterns that matched the ones observed experimentally. In contrast, omitting re-divisions lead to a random spatio-temporal distribution of dividing cells. Spatio-temporal aggregation of dividing stem cells can thus emerge from the cell's history, regardless of possible feedback mechanisms in the population. Lupperger et al. draft 2020Main text

Dynamic spatiotemporal coordination of neural stem cell fate decisions through local feedback in the adult vertebrate brain

“…An "in vivo to modeling" cross-talk to study the spatiotemporal control of NSC decisions in the adult vertebrate brain Recent studies described a random spatial distribution of NSCs in S phase (Lupperger et al, 2018(Lupperger et al, , 2020, but alternative hypotheses such as local spatiotemporal regulation could not be excluded, and these studies were short-term (72 hours) and merged distinct neuroanatomical domains with reported differences in NSC activation frequencies (Dray et al, 2015). Analyzing the spatiotemporal dynamics of adult NSC populations is challenging: (i) it requires dynamic analyses of cell fate preserving NSC arrangements in their physiological niche, (ii) it involves recording jointly the behavior of each individual NSC and its neighbors, and (iii) it faces the extremely slow dynamics of NSC fate decisions, with quiescence times over months.…”