Polar pattern formation induced by contact following locomotion in a multicellular system

Learning dynamical models of single and collective cell migration: a review

Single and collective cell migration are fundamental processes critical for physiological phenomena ranging from embryonic development and immune response to wound healing and cancer metastasis. To understand cell migration from a physical perspective, a broad variety of models for the underlying physical mechanisms that govern cell motility have been developed. A key challenge in the development of such models is how to connect them to experimental observations, which often exhibit complex stochastic behaviours. In this review, we discuss recent advances in data-driven theoretical approaches that directly connect with experimental data to infer dynamical models of stochastic cell migration. Leveraging advances in nanofabrication, image analysis, and tracking technology, experimental studies now provide unprecedented large datasets on cellular dynamics. In parallel, theoretical efforts have been directed towards integrating such datasets into physical models from the single cell to the tissue scale with the aim of conceptualising the emergent behaviour of cells. We first review how this inference problem has been addressed in both freely migrating and confined cells. Next, we discuss why these dynamics typically take the form of underdamped stochastic equations of motion, and how such equations can be inferred from data. We then review applications of data-driven inference and machine learning approaches to heterogeneity in cell behaviour, subcellular degrees of freedom, and to the collective dynamics of multicellular systems. Across these applications, we emphasise how data-driven methods can be integrated with physical active matter models of migrating cells, and help reveal how underlying molecular mechanisms control cell behaviour. Together, these data-driven approaches are a promising avenue for building physical models of cell migration directly from experimental data, and for providing conceptual links between different length-scales of description.

Structure formation induced by non-reciprocal cell-cell interactions in a multicellular system

Collective cellular behavior plays a crucial role in various biological processes, ranging from developmental morphogenesis to pathological processes such as cancer metastasis. Our previous research has revealed that a mutant cell of Dictyostelium discoideum exhibits collective cell migration, including chain migration and traveling band formation, driven by a unique tail-following behavior at contact sites, which we term "contact following locomotion" (CFL). Here, we uncover an imbalance of forces between the front and rear cells within cell chains, leading to an additional propulsion force in the rear cells. Drawing inspiration from this observation, we introduce a theoretical model that incorporates non-reciprocal cell-cell interactions. Our findings highlight that the non-reciprocal interaction, in conjunction with self-alignment interactions, significantly contributes to the emergence of the observed collective cell migrations. Furthermore, we present a comprehensive phase diagram, showing distinct phases at both low and intermediate cell densities. This phase diagram elucidates a specific regime that corresponds to the experimental system.

The Role of Mechanotransduction in Contact Inhibition of Locomotion and Proliferation

Contact inhibition (CI) represents a crucial tumor-suppressive mechanism responsible for controlling the unbridled growth of cells, thus preventing the formation of cancerous tissues. CI can be further categorized into two distinct yet interrelated components: CI of locomotion (CIL) and CI of proliferation (CIP). These two components of CI have historically been viewed as separate processes, but emerging research suggests that they may be regulated by both distinct and shared pathways. Specifically, recent studies have indicated that both CIP and CIL utilize mechanotransduction pathways, a process that involves cells sensing and responding to mechanical forces. This review article describes the role of mechanotransduction in CI, shedding light on how mechanical forces regulate CIL and CIP. Emphasis is placed on filamin A (FLNA)-mediated mechanotransduction, elucidating how FLNA senses mechanical forces and translates them into crucial biochemical signals that regulate cell locomotion and proliferation. In addition to FLNA, trans-acting factors (TAFs), which are proteins or regulatory RNAs capable of directly or indirectly binding to specific DNA sequences in distant genes to regulate gene expression, emerge as sensitive players in both the mechanotransduction and signaling pathways of CI. This article presents methods for identifying these TAF proteins and profiling the associated changes in chromatin structure, offering valuable insights into CI and other biological functions mediated by mechanotransduction. Finally, it addresses unanswered research questions in these fields and delineates their possible future directions.

A Mutant of Dictyostelium discoideum, KI-Cell, as a Model of Collective Cell Migration Independent of Chemotaxis

Collective cell migration occurs when the orientation of cell polarity is aligned with each other in a group of cells. Such collective polarization depends on a reciprocal process between cell intrinsic mechanisms such as cell-cell adhesion and extracellular guidance mechanism such as wound healing and chemotaxis. As part of its development life cycle, individual single cells of Dictyostelium discoideum exhibit chemotaxis toward cAMP, which is secreted from a certain population of cells. During the formation of multicellular body by chemotaxis-dependent cell aggregation, D. discoideum is also known to relay on multiple cell-cell adhesion mechanisms. In particular, tail-following behavior at the contact site, called contact following of locomotion (CFL), plays a pivotal role on the formation of the multicellular body. However, whether and how CFL alone can lead to a formation of collective behavior was not well understood. KI cell is a mutant of D. discoideum that lacks all chemotactic activity. Yet, it can exhibit the CFL activity and show nontrivial collective cell migration. This mutant provides an excellent model system to analyze the mechanism of the CFL and the macroscopic phenomena brought by the CFL. This chapter describes protocols for using KI cell to understand the biophysics and cell biology behind the collective cell migration induced by CFL.

Organizing collective cell migration through guidance by followers

Morphogenesis, wound healing, and some cancer metastases rely on the collective migration of groups of cells. In these processes, guidance and coordination between cells and tissues are critical. While strongly adherent epithelial cells have to move collectively, loosely organized mesenchymal cells can migrate as individual cells. Nevertheless, many of them migrate collectively. This article summarizes how migratory reactions to cell-cell contacts, also called "contact regulation of locomotion" behaviors, organize mesenchymal collective cell migration. It focuses on one recently discovered mechanism called "guidance by followers", through which a cell is oriented by its immediate followers. In the gastrulating zebrafish embryo, during embryonic axis elongation, this phenomenon is responsible for the collective migration of the leading tissue, the polster, and its guidance by the following posterior axial mesoderm. Such guidance of migrating cells by followers ensures long-range coordination of movements and developmental robustness. Along with other "contact regulation of locomotion" behaviors, this mechanism contributes to organizing collective migration of loose populations of cells.

D-Allulose Ameliorates Dysregulated Macrophage Function and Mitochondrial NADH Homeostasis, Mitigating Obesity-Induced Insulin Resistance

D-allulose, a rare sugar, has been proposed to have potential benefits in addressing metabolic disorders such as obesity and type 2 diabetes (T2D). However, the precise mechanisms underlying these effects remain poorly understood. We aimed to elucidate the mechanisms by which D-allulose influences obesity-induced insulin resistance. We conducted gene set enrichment analysis on the liver and white adipose tissue of mice exposed to a high-fat diet (HFD) along with the white adipose tissue of individuals with obesity. Our study revealed that D-allulose effectively suppressed IFN-γ, restored chemokine signaling, and enhanced macrophage function in the livers of HFD-fed mice. This implies that D-allulose curtails liver inflammation, alleviating insulin resistance and subsequently impacting adipose tissue. Furthermore, D-allulose supplementation improved mitochondrial NADH homeostasis and translation in both the liver and white adipose tissue of HFD-fed mice. Notably, we observed decreased NADH homeostasis and mitochondrial translation in the omental tissue of insulin-resistant obese subjects compared to their insulin-sensitive counterparts. Taken together, these results suggest that supplementation with allulose improves obesity-induced insulin resistance by mitigating the disruptions in macrophage and mitochondrial function. Furthermore, our data reinforce the crucial role that mitochondrial energy expenditure plays in the development of insulin resistance triggered by obesity.

A cell membrane model that reproduces cortical flow-driven cell migration and collective movement

Many fundamental biological processes are dependent on cellular migration. Although the mechanical mechanisms of single-cell migration are relatively well understood, those underlying migration of multiple cells adhered to each other in a cluster, referred to as cluster migration, are poorly understood. A key reason for this knowledge gap is that many forces-including contraction forces from actomyosin networks, hydrostatic pressure from the cytosol, frictional forces from the substrate, and forces from adjacent cells-contribute to cell cluster movement, making it challenging to model, and ultimately elucidate, the final result of these forces. This paper describes a two-dimensional cell membrane model that represents cells on a substrate with polygons and expresses various mechanical forces on the cell surface, keeping these forces balanced at all times by neglecting cell inertia. The model is discrete but equivalent to a continuous model if appropriate replacement rules for cell surface segments are chosen. When cells are given a polarity, expressed by a direction-dependent surface tension reflecting the location dependence of contraction and adhesion on a cell boundary, the cell surface begins to flow from front to rear as a result of force balance. This flow produces unidirectional cell movement, not only for a single cell but also for multiple cells in a cluster, with migration speeds that coincide with analytical results from a continuous model. Further, if the direction of cell polarity is tilted with respect to the cluster center, surface flow induces cell cluster rotation. The reason why this model moves while keeping force balance on cell surface (i.e., under no net forces from outside) is because of the implicit inflow and outflow of cell surface components through the inside of the cell. An analytical formula connecting cell migration speed and turnover rate of cell surface components is presented.

Collision-induced torque mediates the transition of chiral dynamic patterns formed by active particles

Controlling the patterns formed by self-propelled particles through dynamic self-organization is a challenging task. Although varieties of patterns associated with chiral self-propelled particles have been reported, essential factors that determine the morphology of the patterns have remained unclear. Here, we explore theoretically how torque formed upon collision of the particles affects the dynamic self-organization of the particles and determine the patterns. Based on a particle-based model with collision-induced torque and torque associated with self-propulsion, we find that introducing collision-induced torque turns the homogeneous bi-directionally aligned particles into rotating mono-polar flocks, which helps resolve a discrepancy in the earlier observations in microfilament gliding assays.

Picking winners in cell-cell collisions: Wetting, speed, and contact

Groups of eukaryotic cells can coordinate their crawling motion to follow cues more effectively, stay together, or invade new areas. This collective cell migration depends on cell-cell interactions, which are often studied by colliding pairs of cells together. Can the outcome of these collisions be predicted? Recent experiments on trains of colliding epithelial cells suggest that cells with a smaller contact angle to the surface or larger speeds are more likely to maintain their direction ("win") upon collision. When should we expect shape or speed to correlate with the outcome of a collision? To investigate this question, we build a model for two-cell collisions within the phase field framework, which allows for cell shape changes. We can reproduce the observation that cells with high speed and small contact angles are more likely to win with two different assumptions for how cells interact: (1) velocity aligning, in which we hypothesize that cells sense their own velocity and align to it over a finite timescale, and (2) front-front contact repolarization, where cells polarize away from cell-cell contact, akin to contact inhibition of locomotion. Surprisingly, though we simulate collisions between cells with widely varying properties, in each case, the probability of a cell winning is completely captured by a single summary variable: its relative speed (in the velocity-aligning model) or its relative contact angle (in the contact repolarization model). Both models are currently consistent with reported experimental results, but they can be distinguished by varying cell contact angle and speed through orthogonal perturbations.

Dynamic self-organization of migrating cells under constraints by spatial confinement and epithelial integrity

Understanding how migrating cells can establish both dynamic structures and coherent dynamics may provide mechanistic insights to study how living systems acquire complex structures and functions. Recent studies revealed that intercellular contact communication plays a crucial role for establishing cellular dynamic self-organization (DSO) and provided a theoretical model of DSO for migrating solitary cells in a free space. However, to apply those understanding to situations in living organisms, we need to know the role of cell-cell communication for tissue dynamics under spatial confinements and epithelial integrity. Here, we expand the previous numerical studies on DSO to migrating cells subjected spatial confinement and/or epithelial integrity. An epithelial monolayer is simulated by combining the model of cellular DSO and the cellular vertex model in two dimensions for apical integrity. Under confinement to a small space, theoretical models of both solitary and epithelial cells exhibit characteristic coherent dynamics, including apparent swirling. We also find that such coherent dynamics can allow the cells to overcome the strong constraint due to spatial confinement and epithelial integrity. Furthermore, we demonstrate how epithelial cell clusters behave without spatial confinement and find various cluster dynamics, including spinning, migration and elongation.

Collective cell migration driven by filopodia-New insights from the social behavior of myotubes

Collective migration is a key process that is critical during development, as well as in physiological and pathophysiological processes including tissue repair, wound healing and cancer. Studies in genetic model organisms have made important contributions to our current understanding of the mechanisms that shape cells into different tissues during morphogenesis. Recent advances in high-resolution and live-cell-imaging techniques provided new insights into the social behavior of cells based on careful visual observations within the context of a living tissue. In this review, we will compare Drosophila testis nascent myotube migration with established in vivo model systems, elucidate similarities, new features and principles in collective cell migration.

Higher order solitary solutions to the meta-model of diffusively coupled Lotka-Volterra systems

A meta-model of diffusively coupled Lotka-Volterra systems used to model various biomedical phenomena is considered in this paper. Necessary and sufficient conditions for the existence of nth order solitary solutions are derived via a modified inverse balancing technique. It is shown that as the highest possible solitary solution order n is increased, the number of nonzero solution parameter values remains constant for solitary solutions of order n > 3 . Analytical and computational experiments are used to illustrate the obtained results.

Learning the dynamics of cell-cell interactions in confined cell migration

The migratory dynamics of cells in physiological processes, ranging from wound healing to cancer metastasis, rely on contact-mediated cell-cell interactions. These interactions play a key role in shaping the stochastic trajectories of migrating cells. While data-driven physical formalisms for the stochastic migration dynamics of single cells have been developed, such a framework for the behavioral dynamics of interacting cells still remains elusive. Here, we monitor stochastic cell trajectories in a minimal experimental cell collider: a dumbbell-shaped micropattern on which pairs of cells perform repeated cellular collisions. We observe different characteristic behaviors, including cells reversing, following, and sliding past each other upon collision. Capitalizing on this large experimental dataset of coupled cell trajectories, we infer an interacting stochastic equation of motion that accurately predicts the observed interaction behaviors. Our approach reveals that interacting noncancerous MCF10A cells can be described by repulsion and friction interactions. In contrast, cancerous MDA-MB-231 cells exhibit attraction and antifriction interactions, promoting the predominant relative sliding behavior observed for these cells. Based on these experimentally inferred interactions, we show how this framework may generalize to provide a unifying theoretical description of the diverse cellular interaction behaviors of distinct cell types.

Dynamic Self-Organization of Idealized Migrating Cells by Contact Communication

This Letter investigates what forms of cellular dynamic self-organization are caused through intercellular contact communication based on a theoretical model in which migrating cells perform contact following and contact inhibition and attraction of locomotion. Tuning those strengths causes varieties of dynamic patterns. This further includes a novel form of collective migration, snakelike dynamic assembly. Scrutinizing this pattern reveals that cells in this state can accurately respond to an external directional cue but have no spontaneous global polar order.

Mechanics as a Means of Information Propagation in Development

New research demonstrates that mechanics can serve as a means of information propagation in developing embryos. Historically, the study of embryonic development has had a dichotomy between morphogens and pattern formation on the one hand and morphogenesis and mechanics on the other. Secreted signals are the preeminent means of information propagation between cells and used to control cell fate, while physical forces act downstream or in parallel to shape tissue morphogenesis. However, recent work has blurred this division of function by demonstrating that mechanics can serve as a means of information propagation. Adhesive or repulsive interactions can propagate through a tissue as a wave. These waves are rapid and directional and can be used to control the flux of cells through a developmental trajectory. Here, two examples are reviewed in which mechanics both guides and mediates morphogenesis and two examples in which mechanics intertwines with morphogens to regulate cell fate.

Interplay of mesoscale physics and agent-like behaviors in the parallel evolution of aggregative multicellularity

Myxobacteria and dictyostelids are prokaryotic and eukaryotic multicellular lineages, respectively, that after nutrient depletion aggregate and develop into structures called fruiting bodies. The developmental processes and resulting morphological outcomes resemble one another to a remarkable extent despite their independent origins, the evolutionary distance between them and the lack of traceable homology in molecular mechanisms. We hypothesize that the morphological parallelism between the two lineages arises as the consequence of the interplay within multicellular aggregates between generic processes, physical and physicochemical processes operating similarly in living and non-living matter at the mesoscale (~10^-3-10^-1 m) and agent-like behaviors, unique to living systems and characteristic of the constituent cells, considered as autonomous entities acting according to internal rules in a shared environment. Here, we analyze the contributions of generic and agent-like determinants in myxobacteria and dictyostelid development and their roles in the generation of their common traits. Consequent to aggregation, collective cell-cell contacts mediate the emergence of liquid-like properties, making nascent multicellular masses subject to novel patterning and morphogenetic processes. In both lineages, this leads to behaviors such as streaming, rippling, and rounding-up, as seen in non-living fluids. Later the aggregates solidify, leading them to exhibit additional generic properties and motifs. Computational models suggest that the morphological phenotypes of the multicellular masses deviate from the predictions of generic physics due to the contribution of agent-like behaviors of cells such as directed migration, quiescence, and oscillatory signal transduction mediated by responses to external cues. These employ signaling mechanisms that reflect the evolutionary histories of the respective organisms. We propose that the similar developmental trajectories of myxobacteria and dictyostelids are more due to shared generic physical processes in coordination with analogous agent-type behaviors than to convergent evolution under parallel selection regimes. Insights from the biology of these aggregative forms may enable a unified understanding of developmental evolution, including that of animals and plants.