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Abstract An agent-based discrete computational model biologically calibrated toPseudomonas aeruginosamigration is used to explore the impacts of bacterial reversals and wrap mode on the efficiency of motion in different environments, both with and without chemotaxis. It is first shown that wrap mode increases the exploration of continuous multimodal chemotactic profiles such as those produced by biologically relevant fungal networks. For cells undergoing a run-reverse pattern, it is shown that the bacteria are likely to remain at the first local chemoattractant maximal production site on a hypha they find. However, with wrap mode, the bacteria can more easily escape these local sites to further explore their neighboring environment along the fungi, suggesting that wrap mode may be beneficial for migration along the fungi in liquid. In a different set of simulations of bacterial motion close to an isolated chemotactic source, wrap mode is shown to increase the ability of a bacterium to reorient toward the source while reducing the overall motion required for similar chemotactic efficiency as a run-reverse strategy, suggesting a potential metabolic benefit. In contrast, model simulations show that wrap mode can increase the rate of dispersal ofP. aeruginosain a nonchemotactic environment. 

Over the last 10 years, it has been shown that multi-scale modeling approaches combined with machine learning provide a powerful method for developing robust predictive models for studying many biomedical processes and exploring massive data sets [1,2]. Recently, the concept of digital twins has gained increasing attention in biology, biomedicine, and healthcare communities. This collection explores the construction of digital twins and multiscale models as they relate to predictive biology and medicine. 

Early stages of metastasis depend on the collective behavior of cancer cells and their interaction with the extracellular matrix (ECM). Cancer cell clusters are known to exhibit higher metastatic potential than single cells. To explore clustering dynamics, we developed a calibrated computational model describing how motile cancer cells biochemically and biomechanically interact with the ECM during the initial invasion phase, including ECM degradation and mechanical remodeling. The model reveals that cluster formation time, size, and shape are influenced by ECM degradation rates and cellular compliance to external stresses (durotaxis). The results align with experimental observations, demonstrating distinct cell trajectories and cluster morphologies shaped by biomechanical parameters. The simulations provide valuable insights into cancer invasion dynamics and may suggest potential therapeutic strategies targeting early-stage invasive cells. 

Abstract In epithelial wounds, physically enlarged cells emerge along injury edges where they interact with regular-size cells during collective migration to repair tissue continuity. Although such large cells are often interpreted as migration leaders, recent observations suggest that regular-size cells can reciprocally influence them and that mixed-size cell clusters engage in distinct rotational motion before merging into confluent sheets. How cell size, polarity and adhesive coupling jointly control distinct collective migration modes remains unclear. Because many features of collective epithelial migration, including large and regular-size cell phenotypes, are conserved betweenin vivoandin vitrosystems, here we developed a multi-scale computational model of interacting epithelial cells in two-dimensional culture with dynamic cell-substrate adhesion, cell-cell interactions, protrusion-based polarity, and contact-induced myosin redistribution as polarity regulator. We also explicitly modeled two functionally distinct cell states, featuring regular and large sizes respectively. Simulations showed that symmetric and asymmetric myosin redistribution at cell-cell junctions can produce stable cell contacts and persistent rotational motions by cell doublets. Intriguingly, in mixed-size cell clusters, straight translation can arise both from leader-like large cell and regular-size cell-mediated motion, whereas rotation emerges when large-cell-generated torque overcomes translation while cell-cell adhesion is maintained. Thus, collective migration mode depends on the balance among myosin-driven torque, regular-size cell-mediated translation, substrate coupling, and cell-cell adhesion. These modeling results suggest that collective epithelial migration can emergein vitrofrom reciprocal biomechanical interactions between distinct cell states, rather than from leader-like cell behavior alone, and that such interactions can produce a predator-prey-like pursuit-escape mode of collective migration. Our model also provides a framework for investigating the biochemical and biomechanical regulation of collective cellular migration. It can be readily extended fromin vitrotoin vivocontext and can incorporate the effects of substrate topology and soluble signaling factor-driven chemotaxis. Author summaryWhen epithelial cells repair a wound, they move as coordinated groups rather than as isolated individuals. Cells of different sizes may contribute in distinct but connected ways. We developed a computational model to examine how a large cell and neighboring regular-size cells move together. In the model, cells attach to the underlying surface and one another, form protrusions that set their direction, and redistribute the force-generating protein myosin after contact. We found that group motion depends on a balance among surface attachment, cell-cell adhesion, movement of regular-size cells toward the large cell, and myosin-driven turning of the large cell. Depending on this balance, a mixed-size cluster can travel along a nearly straight path or rotate persistently, exhibiting pursuit-and-escape-like interactions between the large cell and surrounding regular-size cells. Rotation occurs when the large cell’s turning effect outweighs the translational motion driven by regular-size cells, while cell-cell adhesion keeps the cluster together. Our results show that collective migration can emerge from reciprocal mechanical interactions between cells in different states, not only from a “leader” cell acting alone. The model also provides experimentally testable predictions for how cell size, adhesion, and internal myosin distribution shape cell cluster movement. 

Tracking plant cells in three-dimensional (3D) tissue captured through light microscopy presents significant challenge due to the large number of densely packed cells, non-uniform growth patterns, and variations in cell division planes across different cell layers. In addition, images of deeper tissue layers are often noisy, and systemic imaging errors further exacerbate the complexity of the task. In this paper, we propose a novel learning-based method DEGAST3D: Learning Deformable 3D GrAph Similarity to Track Plant Cells in Unregistered Time Lapse Images exploits the tightly packed 3D cell structure of plant cells to create a three-dimensional graph for accurate cell tracking. We also propose a novel algorithm for cell division detection and an effective three-dimensional registration, improving state-of-the-art algorithms. On a public dataset, our novel cell pair matching method outperforms the baseline by 6.83%, 5.96%, 6.40% in precision, recall, and F-1 score, respectively. On the same dataset, our proposed novel cell division technique improves the results of the baseline method by 15.38% and 14.78% in terms of recall and Fl-score, respectively. 

Abstract How a developing organ robustly coordinates the cellular mechanics and growth to reach a final size and shape remains poorly understood. Through iterations between experiments and model simulations that include a mechanistic description of interkinetic nuclear migration, we show that the local curvature, height, and nuclear positioning of cells in theDrosophilawing imaginal disc are defined by the concurrent patterning of actomyosin contractility, cell-ECM adhesion, ECM stiffness, and interfacial membrane tension. We show that increasing cell proliferation via different growth-promoting pathways results in two distinct phenotypes. Triggering proliferation through insulin signaling increases basal curvature, but an increase in growth through Dpp signaling and Myc causes tissue flattening. These distinct phenotypic outcomes arise from differences in how each growth pathway regulates the cellular cytoskeleton, including contractility and cell-ECM adhesion. The coupled regulation of proliferation and cytoskeletal regulators is a general strategy to meet the multiple context-dependent criteria defining tissue morphogenesis. 

Understanding the mechanisms of the cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short cell cycle, and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. By analyzing experimental data, this study shows that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional multiscale chemical-mechanical model was developed and used to suggest and test hypothesized impacts of aging on bud morphogenesis. Experimentally calibrated model simulations showed that during the early stage of budding, tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip, a process guided by the polarized Cdc42 signal. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage as observed in experiments in this work. The model simulation results suggest that the localization of new cell surface material insertion, regulated by chemical signal polarization, could be weakened due to cellular aging in yeast and other cell types, leading to the change and stabilization of the bud aspect ratio. 

How a developing organ robustly coordinates the cellular mechanics and growth to reach a final size and shape remains poorly understood. Through iterations between experiments and model simulations that include a mechanistic description of interkinetic nuclear migration, we show that the local curvature, height, and nuclear positioning of cells in the Drosophila wing imaginal disc are defined by the concurrent patterning of actomyosin contractility, cell-ECM adhesion, ECM stiffness, and interfacial membrane tension. We show that increasing cell proliferation via different growth-promoting pathways results in two distinct phenotypes. Triggering proliferation through insulin signaling increases basal curvature, but an increase in growth through Dpp signaling and Myc causes tissue flattening. These distinct phenotypic outcomes arise from differences in how each growth pathway regulates the cellular cytoskeleton, including contractility and cell-ECM adhesion. The coupled regulation of proliferation and cytoskeletal regulators is a general strategy to meet the multiple context-dependent criteria defining tissue morphogenesis. 

Abstract The exact mechanism controlling cell growth remains a grand challenge in developmental biology and regenerative medicine. The Drosophila wing disc tissue serves as an ideal biological model to study mechanisms involved in growth regulation. Most existing computational models for studying tissue growth focus specifically on either chemical signals or mechanical forces. Here we developed a multiscale chemical-mechanical model to investigate the growth regulation mechanism based on the dynamics of a morphogen gradient. By comparing the spatial distribution of dividing cells and the overall tissue shape obtained in model simulations with experimental data of the wing disc, it is shown that the size of the domain of the Dpp morphogen is critical in determining tissue size and shape. A larger tissue size with a faster growth rate and more symmetric shape can be achieved if the Dpp gradient spreads in a larger domain. Together with Dpp absorbance at the peripheral zone, the feedback regulation that downregulates Dpp receptors on the cell membrane allows for further spreading of the morphogen away from its source region, resulting in prolonged tissue growth at a more spatially homogeneous growth rate.