Geometry-mediated bridging drives nonadhesive stripe wound healing

In vitro regulation of collective cell migration: Understanding the role of physical and chemical microenvironments

Collective cell migration is the primary mode of cellular movement during embryonic morphogenesis, tissue repair and regeneration, and cancer invasion. Distinct from single-cell migration, collective cell migration involves complex intercellular signaling cascades and force transmission. Consequently, cell collectives exhibit intricate and diverse migration patterns under the influence of the microenvironment in vivo. Investigating the patterns and mechanisms of collective cell migration within complex environmental factors in vitro is essential for elucidating collective cell migration in vivo. This review elucidates the influence of physical and chemical factors in vitro microenvironment on the migration patterns and efficiency of cell collectives, thereby enhancing our comprehension of the phenomenon. Furthermore, we concisely present the effects of characteristic properties of common biomaterials on collective cell migration during tissue repair and regeneration, as well as the features and applications of tumor models of different dimensions (2D substrate or 3D substrate) in vitro. Finally, we highlight the challenges facing the research of collective cell migration behaviors in vitro microenvironment and propose that modulating collective cell migration may represent a potential strategy to promote tissue repair and regeneration and to control tumor invasion and metastasis.

Learning Dynamics from Multicellular Graphs with Deep Neural Networks

Multicellular self-assembly into functional structures is a dynamic process that is critical in the development and diseases, including embryo development, organ formation, tumor invasion, and others. Being able to infer collective cell migratory dynamics from their static configuration is valuable for both understanding and predicting these complex processes. However, the identification of structural features that can indicate multicellular motion has been difficult, and existing metrics largely rely on physical instincts. Here we show that using a graph neural network (GNN), the motion of multicellular collectives can be inferred from a static snapshot of cell positions, in both experimental and synthetic datasets.

The cellular Potts model on disordered lattices

The cellular Potts model, also known as the Glazier-Graner-Hogeweg model, is a lattice-based approach by which biological tissues at the level of individual cells can be numerically studied. Traditionally, a square or hexagonal underlying lattice structure is assumed for two-dimensional systems, and this is known to introduce artifacts in the structure and dynamics of the model tissues. That is, on regular lattices, cells can assume shapes that are dictated by the symmetries of the underlying lattice. Here, we developed a variant of this method that can be applied to a broad class of (ir)regular lattices. We show that on an irregular lattice deriving from a fluid-like configuration, two types of artifacts can be removed. We further report on the transition between a fluid-like disordered and a solid-like hexagonally ordered phase present for monodisperse confluent cells as a function of their surface tension. This transition shows the hallmarks of a first-order phase transition and is different from the glass/jamming transitions commonly reported for the vertex and active Voronoi models. We emphasize this by analyzing the distribution of shape parameters found in our state space. Our analysis provides a useful reference for the future study of epithelia using the (ir)regular cellular Potts model.

Recent trends and perspectives in reconstruction and regeneration of intra/extra-oral wounds using tissue-engineered oral mucosa equivalents

Many conditions, including cancer, trauma, and congenital anomalies, can damage the oral mucosa. Multiple cultures of oral mucosal cells have been used for biocompatibility tests and oral biology studies. In recent decades, the clinical translation of tissue-engineered products has progressed significantly in developing tangible therapies and inspiring advancements in medical science. However, the reconstruction of an intraoral mucosa defect remains a significant challenge. Despite the drawbacks of donor-site morbidity and limited tissue supply, the use of autologous oral mucosa remains the gold standard for oral mucosa reconstruction and repair. Tissue engineering offers a promising solution for repairing and reconstructing oral mucosa tissues. Cell- and scaffold-based tissue engineering approaches have been employed to treat various soft tissue defects, suggesting the potential clinical use of tissue-engineered oral mucosa (TEOMs). In this review, we first cover the recent trends in the reconstruction and regeneration of extra-/intra-oral wounds using TEOMs. Next, we describe the current status and challenges of TEOMs. Finally, future strategic approaches and potential technologies to support the advancement of TEOMs for clinical use are discussed.

Physical forces guide curvature sensing and cell migration mode bifurcating

The ability of cells to sense and adapt to curvy topographical features has been implicated in organ morphogenesis, tissue repair, and tumor metastasis. However, how individual cells or multicellular assemblies sense and differentiate curvatures remains elusive. Here, we reveal a curvature sensing mechanism in which surface tension can selectively activate either actin or integrin flows, leading to bifurcating cell migration modes: focal adhesion formation that enables cell crawling at convex front edges and actin cable assembly that pulls cells forward at concave front edges. The molecular flows and curved front morphogenesis are sustained by coordinated cellular tension generation and transmission. We track the molecular flows and mechanical force transduction pathways by a phase-field model, which predicts that multicellular curvature sensing is more efficient than individual cells, suggesting collective intelligence of cells. The unique ability of cells in curvature sensing and migration mode bifurcating may offer insights into emergent collective patterns and functions of living active systems at different length scales.