Computational cell model based on autonomous cell movement regulated by cell-cell signalling successfully recapitulates the "inside and outside" pattern of cell sorting

Archetypal Architecture Construction, Patterning, and Scaling Invariance in a 3D Embryoid Body Differentiation Model

Self-organized patterning and architecture construction studying is a priority goal for fundamental developmental and stem cell biology. To study the spatiotemporal patterning of pluripotent stem cells of different origins, we developed a three-dimensional embryoid body (EB) differentiation model quantifying volumetric parameters and investigated how the EB architecture formation, patterning, and scaling depend on the proliferation, cavitation, and differentiation dynamics, external environmental factors, and cell numbers. We identified three similar spatiotemporal patterns in the EB architectures, regardless of cell origin, which constitute the EB archetype and mimick the pre-gastrulation embryonic patterns. We found that the EB patterning depends strongly on cellular positional information, culture media factor/morphogen content, and free diffusion from the external environment and between EB cell layers. However, the EB archetype formation is independent of the EB size and initial cell numbers forming EBs; therefore, it is capable of scaling invariance and patterning regulation. Our findings indicate that the underlying principles of reaction-diffusion and positional information concepts can serve as the basis for EB architecture construction, patterning, and scaling. Thus, the 3D EB differentiation model represents a highly reproducible and reliable platform for experimental and theoretical research on developmental and stem cell biology issues.

How does Reelin control neuronal migration and layer formation in the developing mammalian neocortex?

The mammalian neocortex has a laminar structure that develops in a birth-date-dependent "inside-out" pattern. Its layered structure is established by neuronal migration accompanied by sequential changes in migratory mode regulated by several signaling cascades. Although Reelin was discovered about two decades ago and is one of the best known molecules that is indispensable to the establishment of the "inside-out" neuron layers, the cellular and molecular functions of Reelin in layer formation are still largely unknown. In this review article, we summarize our recent understanding of Reelin's functions during neuronal migration. Reelin acts in at least two different steps of neuronal migration: the final step of neuronal migration (somal/terminal translocation) just beneath the marginal zone (MZ) and the regulation of cell polarity step when the neurons change their migratory mode from multipolar migration to locomotion. During the translocation mode, Reelin activates integrin α5β1 through an intracellular pathway that triggers the translocation and activates N-cadherin in concert with the nectin-afadin system. Reelin is also involved in the termination of neuronal migration by degrading Dab1 via the SOCS7-Cullin5-Rbx2 system, and Reelin has been found to induce the birth-date-dependent neuronal aggregation in vivo. Based on these findings, we hypothesize that the molecular function of Reelin during neuronal migration is to control cell-adhesiveness during development by regulating the expression/activation of cell adhesion molecules.

Self-organization of developing embryo using scale-invariant approach

BACKGROUND

Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos.

METHODS

In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing C. elegans during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method.

RESULTS AND CONCLUSION

The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.

Cell sorting in development

During the development of multicellular organisms, cell fate specification is followed by the sorting of different cell types into distinct domains from where the different tissues and organs are formed. Cell sorting involves both the segregation of a mixed population of cells with different fates and properties into distinct domains, and the active maintenance of their segregated state. Because of its biological importance and apparent resemblance to fluid segregation in physics, cell sorting was extensively studied by both biologists and physicists over the last decades. Different theories were developed that try to explain cell sorting on the basis of the physical properties of the constituent cells. However, only recently the molecular and cellular mechanisms that control the physical properties driving cell sorting, have begun to be unraveled. In this review, we will provide an overview of different cell-sorting processes in development and discuss how these processes can be explained by the different sorting theories, and how these theories in turn can be connected to the molecular and cellular mechanisms driving these processes.

Self-propelled particle model for cell-sorting phenomena

A self-propelled particle model is introduced to study cell sorting occurring in some living organisms. This allows us to evaluate the influence of intrinsic cell motility separately from differential adhesion with fluctuations, a mechanism previously shown to be sufficient to explain a variety of cell rearrangement processes. We find that the tendency of cells to actively follow their neighbors greatly reduces segregation time scales. A finite-size analysis of the sorting process reveals clear algebraic growth laws as in physical phase-ordering processes, albeit with unusual scaling exponents.