PErPetuating Stemness: From single-cell analysis to mechanistic spatio-temporal models of neural stem cell dynamics

Neural stem cell (NSC) populations in the vertebrate brain generate adult-born neurons for plasticity, growth, and repair. Neurogenic and gliogenic capacity, based on long-term NSC maintenance, functionally define stemness.

Stemness embodies massive NSC heterogeneity at the single cell level and requires control of maintenance or differentiation decisions at the population level. These features remain mechanistically unreconciled.

We hypothesise that spatiotemporal interactions among heterogeneous NSCs are coordinated to control the population behaviour.

Thus, we propose a multi-dimensional project exploring these features in time and space, to decode the mechanistic principles of stemness.

To this end, we bring together experimental and theoretical groups with complementary expertise in NSC biology, biostatistics and mathematical modelling.

In an iterative experimental-mathematical approach, we will (1) solve the topology of individual NSC trajectories in transcriptomic space, (2) identify local cell-cell coordination mechanisms that impact these trajectories in situ, and (3) decode the resulting systemic properties and outputs of NSC ensembles at long-term and large spatial scales.

This programme will result in original methods, including retrospective transcriptomics in single cells, innovative barcode transfers, and a novel mathematical framework to describe structured spatio-temporal population dynamics.

We will focus on two biological model systems, the adult mouse ventricular sub-ventricular zone and zebrafish pallium, where NSC ensembles display comparable heterogeneity but differ in spatial organisation and fate dynamics.

Together, PEPS will uncover the general principles and regulatory mechanisms of perpetuating stemness in time and space.

It will lay the conceptual and methodological foundation to manipulate stem cell systems to improve their stability or output, and also produce new methods of universal value for studying cellular systems.