Investigating the relation between Stochastic Differentiation, Homeostasis and Clonal Expansion in Intestinal Crypts via Multiscale Modeling

Colorectal tumors originate and develop within intestinal crypts. Even though some of the essential phenomena that characterize crypt structure and dynamics have been effectively described in the past, the relation between the differentiation process and the overall crypt homeostasis is still only partially understood. We here investigate this relation and other important biological phenomena by introducing a novel multiscale model that combines a morphological description of the crypt with a gene regulation model: the emergent dynamical behavior of the underlying gene regulatory network drives cell growth and differentiation processes, linking the two distinct spatio-temporal levels. The model relies on a few a priori assumptions, yet accounting for several key processes related to crypt functioning, such as: dynamic gene activation patterns, stochastic differentiation, signaling pathways ruling cell adhesion properties, cell displacement, cell growth, mitosis, apoptosis and the presence of biological noise. We show that this modeling approach captures the major dynamical phenomena that characterize the regular physiology of crypts, such as cell sorting, coordinate migration, dynamic turnover, stem cell niche correct positioning and clonal expansion. All in all, the model suggests that the process of stochastic differentiation might be sufficient to drive the crypt to homeostasis, under certain crypt configurations. Besides, our approach allows to make precise quantitative inferences that, when possible, were matched to the current biological knowledge and it permits to investigate the role of gene-level perturbations, with reference to cancer development. We also remark the theoretical framework is general and may be applied to different tissues, organs or organisms

Investigating the Role of Network Topology and Dynamical Regimes on the Dynamics of a Cell Differentiation Model

The characterization of the generic properties underlying the complex interplay ruling cell differentiation is one of the goals of modern biology. To this end, we rely on a powerful and general dynamical model of cell differentiation, which defines differentiation hierarchies on the basis of the stability of gene activation patterns against biological noise. In particular, in this work we investigate the role of the topology (i.e. scale-free or random) and of the dynamical regime (i.e. ordered, critical or disordered) of gene regulatory networks on the model dynamics. Two real lineage commitment trees, i.e. intestinal crypts and hematopoietic cells, are compared with the hierarchies emerging from the dynamics of ensembles of randomly simulated networks. Briefly, critical networks with random topology seem to display a wider range of possible behaviours as compared to the others, hence suggesting an intrinsic dynamical heterogeneity that may be fundamental in defining different differentiation trees. Conversely, scale-free networks show a generally more ordered dynamics, which limit the overall variability, yet containing the effect of possible genomic perturbations. Interestingly, a considerable number of networks across all types show emergent trees that are biologically plausible, suggesting that a relatively wide portion of the networks space may be suitable, without the need for a fine tuning of the parameter