Since the beginning of the project, we have made progress on all aims of the grant.
Following the plans of Aim 1, we have in particular worked on a number of collaborations with cell and developmental biologists to compare and contrast the branching strategies of a number of different organs and cells. As planned in Aim 1.1 we have in particular shown that a number of quantitative features of liver branching architecture in vivo (Hankeova et al, eLife, 2021) and pancreatic cancer organoids in vitro (Randriamanantsoa et al, Nat Comm, 2022) were highly stochastic and heterogeneous both within a given tree and among different experiments/animals. Beyond epithelial branched trees, we have also investigated the branching structure of neurons. In particular, Mehmet Can Ucar (a postdoc in the lab) developed a theoretical framework for a stochastic self-organized branching process in the presence of external cues (Can Ucar et al, Nat Comm, 2022). We have also made significant progresses towards the aim 1.2 by studying the principles of optimal coverage during lymphatic branching morphogenesis – this work by Mehmet Can Ucar as first author is currently under revision in Nature Communication.
We have also made a number of progresses towards the completion of Aim 2, in particular Aim 2.1. In particular, Bernat Corominas-Murtra – a postdoc in the lab now assistant professor in the University of Graz, worked on a theory of stem cell dynamics as a stochastic competition for access to a spatially localized niche. In this model (Corominas-Murtra*, Scheele* et al, PNAS, 2020), cell divisions produce a steady cellular stream which advects cells away from the niche, while random rearrangements enable cells away from the niche to be favorably repositioned. Importantly, even when assuming that all cells in a tissue are molecularly equivalent, we predict a common (“universal”) functional dependence of the long-term clonal survival probability on distance from the niche, as well as the emergence of a well-defined number of functional stem cells, dependent only on the rate of random movements vs. mitosis-driven advection. We test the predictions of this theory on datasets of pubertal mammary gland tips and embryonic kidney tips, finding good agreement for the predicted functional dependency of the competition as a function of position, and thus functional stem cell number in each organ. This argues for a key role of positional fluctuations in dictating stem cell number and dynamics. Interesting, we also recently showed that the same model could apply beyond the setting of branching morphogenesis – being relevant to understand the homeostasis of the mouse intestinal epithelium (Azkanaz, Corominas-Murtra* et al, Nature, 2022). In particular, experiments revealed highly different dynamics and functional stem cell numbers in small vs large intestine results. We show theoretically that the number of effective stem cells is determined by different amounts of Wnt-dependent active retrograde movement, revealing a new channel of stem cell regulation that can be experimentally and pharmacologically manipulated.
Finally, we have also advanced towards both subaims of Aim 3 by looking at the mechano-chemical principles of 3D epithelium shape deformations. As planned in aim 3.1 we have developed analytical theories of 3D vertex model models with changing fluid pressure. As a proof of concept for experimental applications, we have worked on intestinal organoid morphogenesis, which undergo a budding transition (which can be seen as a simple elemental deformation and a first step to understand more complex phenomena such as branching), showing how mechano-osmotic forces coordinate this process (Yang*, Xue* et al, NCB, 2021). As planned in aim 3.2 we have also started to investigate the interplay between curvature and mechanics as a patterning mechanism. Again, we have first collaborated with experimentalists working on simpler systems such as MDCK monolayers to validate the ideas – including mechano-chemical ERK waves arising from coupling between cell shape and ERK signalling (Boocock*, Hino* et al, Nat Phys, 2021) as well as curvature sensing via active nuclear mechanosensation (Luciano*, Hannezo* et al, Nat Phys, 2021).
