Emergent structures and dynamics of cell colonies by contact inhibition of locomotion

Generic theory of interacting, spinning, active polar particles: A model for cell aggregates

We present a generic framework for describing interacting, spinning, active polar particles, aimed at modeling dense cell aggregates, where cells are treated as polar, rotating objects that interact mechanically with one another and their surrounding environment. Using principles from nonequilibrium thermodynamics, we derive constitutive equations for interaction forces, torques, and polarity dynamics. We subsequently use this framework to analyze the spontaneous motion of cell doublets, uncovering a rich phase diagram of collective behaviors, including steady rotation driven by flow-polarity coupling or interactions between polarity and cell position.

Physical aspects of epithelial cell-cell interactions: hidden system complexities

The maintenance of homeostasis and the retention of ordered epithelial cell self-organization are essential for morphogenesis, wound healing, and the spread of cancer across the epithelium. However, cell-cell interactions in an overcrowded environment introduce a diversity of complications. Such interactions arise from an interplay between the cell compressive and shear stress components that accompany increased cell packing density. They can lead to various kinds of cell rearrangement such as: the epithelial-to-mesenchymal cell state transition; live cell extrusion; and cell jamming. All of these scenarios of cell rearrangement under mechanical stress relate to changes in the strengths of the cell-cell and cell-matrix adhesion contacts. The objective of this review study is twofold: first, to provide a comprehensive summary of the biological and physical factors influencing the effects of cell mechanical stress on cell-cell interactions, and the consequences of these interactions for the status of cell-cell and cell-matrix adhesion contacts; and secondly, to offer a bio-physical/mathematical analysis of the aforementioned biological aspects. By presenting these two approaches in conjunction, we seek to highlight the intricate nature of biological systems, which manifests in the form of complex bio-physical/mathematical equations. Furthermore, the juxtaposition of these apparently disparate approaches underscores the importance of conducting experiments to determine the multitude of parameters that contribute to the development of these intricate bio-physical/mathematical models.

Systematic simulation of tumor cell invasion and migration in response to time-varying rotating magnetic field

Cancer invasion and migration play a pivotal role in tumor malignancy, which is a major cause of most cancer deaths. Rotating magnetic field (RMF), one of the typical dynamic magnetic fields, can exert substantial mechanical influence on cells. However, studying the effects of RMF on cell is challenging due to its complex parameters, such as variation of magnetic field intensity and direction. Here, we developed a systematic simulation method to explore the influence of RMF on tumor invasion and migration, including a finite element method (FEM) model and a cell-based hybrid numerical model. Coupling with the data of magnetic field from FEM, the cell-based hybrid numerical model was established to simulate the tumor cell invasion and migration. This model employed partial differential equations (PDEs) and finite difference method to depict cellular activities and solve these equations in a discrete system. PDEs were used to depict cell activities, and finite difference method was used to solve the equations in discrete system. As a result, this study provides valuable insights into the potential applications of RMF in tumor treatment, and a series of in vitro experiments were performed to verify the simulation results, demonstrating the model's reliability and its capacity to predict experimental outcomes and identify pertinent factors. Furthermore, these findings shed new light on the mechanical and chemical interplay between cells and the ECM, offering new insights and providing a novel foundation for both experimental and theoretical advancements in tumor treatment by using RMF.

Self-aligning active agents with inertia and active torque

We extend the study of the inertial effects on the two-dimensional dynamics of active agents to the case where self-alignment is present. In contrast with the most common models of active particles, we find that self-alignment, which couples the rotational dynamics to the translational one, produces unexpected and nontrivial dynamics, already at the deterministic level. Examining first the motion of a free particle, we contrast the role of inertia depending on the sign of the self-aligning torque. When positive, inertia does not alter the steady-state linear motion of an a-chiral self-propelled particle. On the contrary, for a negative self-aligning torque, inertia leads to the destabilization of the linear motion into a spontaneously broken chiral symmetry orbiting dynamics. Adding an active torque, or bias, to the angular dynamics, the bifurcation becomes imperfect in favor of the chiral orientation selected by the bias. In the case of a positive self-alignment, the interplay of the active torque and inertia leads to the emergence, out of a saddle-node bifurcation, of solutions which coexist with the simply biased linear motion. In the context of a free particle, the rotational inertia leaves unchanged the families of steady-state solutions but sets their stability properties. The situation is radically different when considering the case of a collision with a wall, where a very singular oscillating dynamics takes place which can only be captured if both translational and rotational inertia are present.

Dynamics of multicellular swirling on micropatterned substrates

Chirality plays a crucial role in biology, as it is highly conserved and fundamentally important in the developmental process. To better understand the relationship between the chirality of individual cells and that of tissues and organisms, we develop a generalized mechanics model of chiral polarized particles to investigate the swirling dynamics of cell populations on substrates. Our analysis reveals that cells with the same chirality can form distinct chiral patterns on ring-shaped or rectangular substrates. Interestingly, our studies indicate that an excessively strong or weak individual cellular chirality hinders the formation of such chiral patterns. Our studies also indicate that there exists the influence distance of substrate boundaries in chiral patterns. Smaller influence distances are observed when cell-cell interactions are weaker. Conversely, when cell-cell interactions are too strong, multiple cells tend to be stacked together, preventing the formation of chiral patterns on substrates in our analysis. Additionally, we demonstrate that the interaction between cells and substrate boundaries effectively controls the chiral distribution of cellular orientations on ring-shaped substrates. This research highlights the significance of coordinating boundary features, individual cellular chirality, and cell-cell interactions in governing the chiral movement of cell populations and provides valuable mechanics insights into comprehending the intricate connection between the chirality of single cells and that of tissues and organisms.

Short-range correlation of stress chains near solid-to-liquid transition in active monolayers

Using a three-dimensional model of cell monolayers, we study the spatial organization of active stress chains as the monolayer transitions from a solid to a liquid state. The critical exponents that characterize this transition map the isotropic stress percolation onto the two-dimensional random percolation universality class, suggesting short-range stress correlations near this transition. This mapping is achieved via two distinct, independent pathways: (i) cell-cell adhesion and (ii) active traction forces. We unify our findings by linking the nature of this transition to high-stress fluctuations, distinctly linked to each pathway. The results elevate the importance of the transmission of mechanical information in dense active matter and provide a new context for understanding the non-equilibrium statistical physics of phase transition in active systems.

Confinement induces internal flows in adherent cell aggregates

During mesenchymal migration, F-actin protrusion at the leading edge and actomyosin contraction determine the retrograde flow of F-actin within the lamella. The coupling of this flow to integrin-based adhesions determines the force transmitted to the extracellular matrix and the net motion of the cell. In tissues, motion may also arise from convection, driven by gradients in tissue-scale surface tensions and pressures. However, how migration coordinates with convection to determine the net motion of cellular ensembles is unclear. To explore this, we study the spreading of cell aggregates on adhesive micropatterns on compliant substrates. During spreading, a cell monolayer expands from the aggregate towards the adhesive boundary. However, cells are unable to stabilize the protrusion beyond the adhesive boundary, resulting in retraction of the protrusion and detachment of cells from the matrix. Subsequently, the cells move upwards and rearwards, yielding a bulk convective flow towards the centre of the aggregate. The process is cyclic, yielding a steady-state balance between outward (protrusive) migration along the surface, and 'retrograde' (contractile) flows above the surface. Modelling the cell aggregates as confined active droplets, we demonstrate that the interplay between surface tension-driven flows within the aggregate, radially outward monolayer flow and conservation of mass leads to an internal circulation.

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.

Fat2 polarizes Lar and Sema5c to coordinate the motility of collectively migrating epithelial cells

Migrating epithelial cells globally align their migration machinery to achieve tissue-level movement. Biochemical signaling across leading-trailing cell-cell interfaces can promote this alignment by partitioning migratory behaviors like protrusion and retraction to opposite sides of the interface. However, how signaling proteins become organized at interfaces to accomplish this is poorly understood. The follicular epithelial cells of Drosophila melanogaster have two signaling modules at their leading-trailing interfaces - one composed of the atypical cadherin Fat2 (also known as Kugelei) and the receptor tyrosine phosphatase Lar, and one composed of Semaphorin5c and its receptor Plexin A. Here, we show that these modules form one interface signaling system with Fat2 at its core. Trailing edge-enriched Fat2 concentrates both Lar and Semaphorin5c at leading edges of cells, but Lar and Semaphorin5c play little role in the localization of Fat2. Fat2 is also more stable at interfaces than Lar or Semaphorin5c. Once localized, Lar and Semaphorin5c act in parallel to promote collective migration. We propose that Fat2 serves as the organizer of this interface signaling system by coupling and polarizing the distributions of multiple effectors that work together to align the migration machinery of neighboring cells.

Effect of contact inhibition locomotion on confined cellular organization

Experiments performed using micro-patterned one dimensional collision assays have allowed a precise quantitative analysis of the collective manifestation of contact inhibition locomotion (CIL) wherein, individual migrating cells reorient their direction of motion when they come in contact with other cells. Inspired by these experiments, we present a discrete, minimal 1D Active spin model that mimics the CIL interaction between cells in one dimensional channels. We analyze the emergent collective behaviour of migrating cells in such confined geometries, as well as the sensitivity of the emergent patterns to driving forces that couple to cell motion. In the absence of vacancies, akin to dense cell packing, the translation dynamics is arrested and the model reduces to an equilibrium spin model which can be solved exactly. In the presence of vacancies, the interplay of activity-driven translation, cell polarity switching, and CIL results in an exponential steady cluster size distribution. We define a dimensionless Péclet number Q-the ratio of the translation rate and directional switching rate of particles in the absence of CIL. While the average cluster size increases monotonically as a function of Q, it exhibits a non-monotonic dependence on CIL strength, when the Q is sufficiently high. In the high Q limit, an analytical form of average cluster size can be obtained approximately by effectively mapping the system to an equivalent equilibrium process involving clusters of different sizes wherein the cluster size distribution is obtained by minimizing an effective Helmholtz free energy for the system. The resultant prediction of exponential dependence on CIL strength of the average cluster size and [Formula: see text] dependence of the average cluster size is borne out to reasonable accuracy as long as the CIL strength is not very large. The consequent prediction of a single scaling function of Q, particle density and CIL interaction strength, characterizing the distribution function of the cluster sizes and resultant data collapse is observed for a range of parameters.

Soliton approximation in continuum models of leader-follower behavior

Complex biological processes involve collective behavior of entities (bacteria, cells, animals) over many length and time scales and can be described by discrete models that track individuals or by continuum models involving densities and fields. We consider hybrid stochastic agent-based models of branching morphogenesis and angiogenesis (new blood vessel creation from preexisting vasculature), which treat cells as individuals that are guided by underlying continuous chemical and/or mechanical fields. In these descriptions, leader (tip) cells emerge from existing branches and follower (stalk) cells build the new sprout in their wake. Vessel branching and fusion (anastomosis) occur as a result of tip and stalk cell dynamics. Coarse graining these hybrid models in appropriate limits produces continuum partial differential equations (PDEs) for endothelial cell densities that are more analytically tractable. While these models differ in nonlinearity, they produce similar equations at leading order when chemotaxis is dominant. We analyze this leading order system in a simple quasi-one-dimensional geometry and show that the numerical solution of the leading order PDE is well described by a soliton wave that evolves from vessel to source. This wave is an attractor for intermediate times until it arrives at the hypoxic region releasing the growth factor. The mathematical techniques used here thus identify common features of discrete and continuum approaches and provide insight into general biological mechanisms governing their collective dynamics.

Generative models of morphogenesis in developmental biology

Understanding the mechanism by which cells coordinate their differentiation and migration is critical to our understanding of many fundamental processes such as wound healing, disease progression, and developmental biology. Mathematical models have been an essential tool for testing and developing our understanding, such as models of cells as soft spherical particles, reaction-diffusion systems that couple cell movement to environmental factors, and multi-scale multi-physics simulations that combine bottom-up rule-based models with continuum laws. However, mathematical models can often be loosely related to data or have so many parameters that model behaviour is weakly constrained. Recent methods in machine learning introduce new means by which models can be derived and deployed. In this review, we discuss examples of mathematical models of aspects of developmental biology, such as cell migration, and how these models can be combined with these recent machine learning methods.

Robust statistical properties of T1 transitions in a multi-phase field model of cell monolayers

Large-scale tissue deformation which is fundamental to tissue development hinges on local cellular rearrangements, such as T1 transitions. In the realm of the multi-phase field model, we analyse the statistical and dynamical properties of T1 transitions in a confluent monolayer. We identify an energy profile that is robust to changes in several model parameters. It is characterized by an asymmetric profile with a fast increase in energy before the T1 transition and a sudden drop after the T1 transition, followed by a slow relaxation. The latter being a signature of the fluidity of the cell monolayer. We show that T1 transitions are sources of localised large deformation of the cells undergoing the neighbour exchange, and they induce other T1 transitions in the nearby cells leading to a chaining of events that propagate local cell deformation to large scale tissue flows.

Mechanical basis and topological routes to cell elimination

Cell layers eliminate unwanted cells through the extrusion process, which underlines healthy versus flawed tissue behaviors. Although several biochemical pathways have been identified, the underlying mechanical basis including the forces involved in cellular extrusion remains largely unexplored. Utilizing a phase-field model of a three-dimensional cell layer, we study the interplay of cell extrusion with cell-cell and cell-substrate interactions in a flat monolayer. Independent tuning of cell-cell versus cell-substrate adhesion forces reveals that extrusion events can be distinctly linked to defects in nematic and hexatic orders associated with cellular arrangements. Specifically, we show that by increasing relative cell-cell adhesion forces the cell monolayer can switch between the collective tendency towards fivefold, hexatic, disclinations relative to half-integer, nematic, defects for extruding a cell. We unify our findings by accessing three-dimensional mechanical stress fields to show that an extrusion event acts as a mechanism to relieve localized stress concentration.

Multi-scale nature of the tissue surface tension: Theoretical consideration on tissue model systems

Tissue surface tension is one of the key parameters that govern tissue rearrangement, shaping, and segregation within various compartments during organogenesis, wound healing, and cancer diseases. Deeper insight into the relationship between tissue surface tension and cell residual stress accumulation caused by collective cell migration can help us to understand the multi-scale nature of cell rearrangement with pronounced oscillatory trend. Oscillatory change of cell velocity that caused strain and generated cell residual stress were discussed in the context of mechanical waves. The tissue surface tension also showed oscillatory behaviour. The main goal of this theoretical consideration is to emphasize an inter-relation between various scenarios of cell rearrangement and tissue surface tension by distinguishing liquid-like and solid-like surfaces. This complex phenomenon is discussed in the context of an artificial tissue model system, namely cell aggregate rounding after uni-axial compression between parallel plates. Experimentally obtained oscillatory changes in the cell aggregate shape during the aggregate rounding, which is accompanied by oscillatory decrease in the aggregate surface area, points to oscillatory changes in the tissue surface tension. Besides long-time oscillations, cell surface tension can perform short time relaxation cycles. This behaviour of the tissue surface tension distinguishes living matter from other soft matter systems. This complex phenomenon is discussed based on dilatational viscoelasticity and thermodynamic approach.

Curvature induces active velocity waves in rotating spherical tissues

The multicellular organization of diverse systems, including embryos, intestines, and tumors relies on coordinated cell migration in curved environments. In these settings, cells establish supracellular patterns of motion, including collective rotation and invasion. While such collective modes have been studied extensively in flat systems, the consequences of geometrical and topological constraints on collective migration in curved systems are largely unknown. Here, we discover a collective mode of cell migration in rotating spherical tissues manifesting as a propagating single-wavelength velocity wave. This wave is accompanied by an apparently incompressible supracellular flow pattern featuring topological defects as dictated by the spherical topology. Using a minimal active particle model, we reveal that this collective mode arises from the effect of curvature on the active flocking behavior of a cell layer confined to a spherical surface. Our results thus identify curvature-induced velocity waves as a mode of collective cell migration, impacting the dynamical organization of 3D curved tissues.

A computational framework for testing hypotheses of the minimal mechanical requirements for cell aggregation using early annual killifish embryogenesis as a model

Introduction: Deciphering the biological and physical requirements for the outset of multicellularity is limited to few experimental models. The early embryonic development of annual killifish represents an almost unique opportunity to investigate de novo cellular aggregation in a vertebrate model. As an adaptation to seasonal drought, annual killifish employs a unique developmental pattern in which embryogenesis occurs only after undifferentiated embryonic cells have completed epiboly and dispersed in low density on the egg surface. Therefore, the first stage of embryogenesis requires the congregation of embryonic cells at one pole of the egg to form a single aggregate that later gives rise to the embryo proper. This unique process presents an opportunity to dissect the self-organizing principles involved in early organization of embryonic stem cells. Indeed, the physical and biological processes required to form the aggregate of embryonic cells are currently unknown. Methods: Here, we developed an in silico, agent-based biophysical model that allows testing how cell-specific and environmental properties could determine the aggregation dynamics of early Killifish embryogenesis. In a forward engineering approach, we then proceeded to test two hypotheses for cell aggregation (cell-autonomous and a simple taxis model) as a proof of concept of modeling feasibility. In a first approach (cell autonomous system), we considered how intrinsic biophysical properties of the cells such as motility, polarity, density, and the interplay between cell adhesion and contact inhibition of locomotion drive cell aggregation into self-organized clusters. Second, we included guidance of cell migration through a simple taxis mechanism to resemble the activity of an organizing center found in several developmental models. Results: Our numerical simulations showed that random migration combined with low cell-cell adhesion is sufficient to maintain cells in dispersion and that aggregation can indeed arise spontaneously under a limited set of conditions, but, without environmental guidance, the dynamics and resulting structures do not recapitulate in vivo observations. Discussion: Thus, an environmental guidance cue seems to be required for correct execution of early aggregation in early killifish development. However, the nature of this cue (e.g., chemical or mechanical) can only be determined experimentally. Our model provides a predictive tool that could be used to better characterize the process and, importantly, to design informed experimental strategies.

Fat2 polarizes Lar and Sema5c to coordinate the motility of collectively migrating epithelial cells

Migrating epithelial cells globally align their migration machinery to achieve tissue-level movement. Biochemical signaling across leading-trailing cell-cell interfaces can promote this alignment by partitioning migratory behaviors like protrusion and retraction to opposite sides of the interface. However, how the necessary signaling proteins become organized at this site is poorly understood. The follicular epithelial cells of Drosophila melanogaster have two signaling modules at their leading-trailing interfaces-one composed of the atypical cadherin Fat2 and the receptor tyrosine phosphatase Lar, and one composed of Semaphorin 5c and its receptor Plexin A. Here we show that these modules form one interface signaling system with Fat2 at its core. Trailing edge-enriched Fat2 concentrates both Lar and Sema5c at cells' leading edges, likely by slowing their turnover at this site. Once localized, Lar and Sema5c act in parallel to promote collective migration. Our data suggest a model in which Fat2 couples and polarizes the distributions of multiple effectors that work together to align the migration machinery of neighboring cells.

Mechanochemical subcellular-element model of crawling cells

Constructing physical models of living cells and tissues is an extremely challenging task because of the high complexities of both intra- and intercellular processes. In addition, the force that a single cell generates vanishes in total due to the law of action and reaction. The typical mechanics of cell crawling involve periodic changes in the cell shape and in the adhesion characteristics of the cell to the substrate. However, the basic physical mechanisms by which a single cell coordinates these processes cooperatively to achieve autonomous migration are not yet well understood. To obtain a clearer grasp of how the intracellular force is converted to directional motion, we develop a basic mechanochemical model of a crawling cell based on subcellular elements with the focus on the dependence of the protrusion and contraction as well as the adhesion and de-adhesion processes on intracellular biochemical signals. By introducing reaction-diffusion equations that reproduce traveling waves of local chemical concentrations, we clarify that the chemical dependence of the cell-substrate adhesion dynamics determines the crawling direction and distance with one chemical wave. Finally, we also perform multipole analysis of the traction force to compare it with the experimental results. Our present work sheds light on how intracellular chemical reactions are converted to a directional cell migration under the force-free condition. Although the detailed mechanisms of actual cells are far more complicated than our simple model, we believe that this mechanochemical model is a good prototype for more realistic models.

Collective motion of cells modeled as ring polymers

In this article, we use a coarse-grained model of disjoint semi-flexible ring polymers to investigate computationally the spatiotemporal collective behavior of cell colonies. A ring polymer in this model is self-propelled by a motility force along the cell's polarity, which depends on its historical kinetics. Despite the repulsive interaction between the cells, a collective behavior sets in as a result of cells pushing against each other. This cooperative motion emerges as the amplitude of the motility force is increased and/or their areal density is increased. The degree of collectivity, characterized by the average cluster size, the velocity field order parameter, and the polarity field nematic order parameter, is found to increase with increasing the amplitude of the motility force and area coverage of the cells. Furthermore, the degree of alignment exhibited by the cell velocity field within a cluster is found to be stronger than that exhibited by the cell polarity. Comparison between the collective behavior of elongated cells and that of circular cells, at the same area coverage and motility force, shows that elongated cells exhibit a stronger collective behavior than circular cells, in agreement with earlier studies of self-propelled anisotropic particles. An investigation of two-cell collisions shows that while two clustered cells move in tandem, their polarities are misaligned. As such the cells push against each other while moving coherently.

Self assembling cluster crystals from DNA based dendritic nanostructures

Cluster crystals are periodic structures with lattice sites occupied by several, overlapping building blocks, featuring fluctuating site occupancy, whose expectation value depends on thermodynamic conditions. Their assembly from atomic or mesoscopic units is long-sought-after, but its experimental realization still remains elusive. Here, we show the existence of well-controlled soft matter cluster crystals. We fabricate dendritic-linear-dendritic triblock composed of a thermosensitive water-soluble polymer and nanometer-scale all-DNA dendrons of the first and second generation. Conclusive small-angle X-ray scattering (SAXS) evidence reveals that solutions of these triblock at sufficiently high concentrations undergo a reversible phase transition from a cluster fluid to a body-centered cubic (BCC) cluster crystal with density-independent lattice spacing, through alteration of temperature. Moreover, a rich concentration-temperature phase diagram demonstrates the emergence of various ordered nanostructures, including BCC cluster crystals, birefringent cluster crystals, as well as hexagonal phases and cluster glass-like kinetically arrested states at high densities.

Experimental realization of cluster crystals- periodic structures with lattice sites occupied by several, overlapping building blocks, has been elusive. Here, the authors show the existence of well-controlled soft matter cluster crystals composed of a thermosensitive water-soluble polymer and nanometer-scale all-DNA dendrons.

Cooperation between melanoma cell states promotes metastasis through heterotypic cluster formation

Melanomas can have multiple coexisting cell states, including proliferative (PRO) versus invasive (INV) subpopulations that represent a "go or grow" trade-off; however, how these populations interact is poorly understood. Using a combination of zebrafish modeling and analysis of patient samples, we show that INV and PRO cells form spatially structured heterotypic clusters and cooperate in the seeding of metastasis, maintaining cell state heterogeneity. INV cells adhere tightly to each other and form clusters with a rim of PRO cells. Intravital imaging demonstrated cooperation in which INV cells facilitate dissemination of less metastatic PRO cells. We identified the TFAP2 neural crest transcription factor as a master regulator of clustering and PRO/INV states. Isolation of clusters from patients with metastatic melanoma revealed a subset with heterotypic PRO-INV clusters. Our data suggest a framework for the co-existence of these two divergent cell populations, in which heterotypic clusters promote metastasis via cell-cell cooperation.

Investigating the nature of active forces in tissues reveals how contractile cells can form extensile monolayers

Actomyosin machinery endows cells with contractility at a single-cell level. However, within a monolayer, cells can be contractile or extensile based on the direction of pushing or pulling forces exerted by their neighbours or on the substrate. It has been shown that a monolayer of fibroblasts behaves as a contractile system while epithelial or neural progentior monolayers behave as an extensile system. Through a combination of cell culture experiments and in silico modelling, we reveal the mechanism behind this switch in extensile to contractile as the weakening of intercellular contacts. This switch promotes the build-up of tension at the cell-substrate interface through an increase in actin stress fibres and traction forces. This is accompanied by mechanotransductive changes in vinculin and YAP activation. We further show that contractile and extensile differences in cell activity sort cells in mixtures, uncovering a generic mechanism for pattern formation during cell competition, and morphogenesis.

spheresDT/Mpacts-PiCS: Cell Tracking and Shape Retrieval in Membrane-labeled Embryos

Motivation

Uncovering the cellular and mechanical processes that drive embryo formation requires an accurate read out of cell geometries over time. However, automated extraction of 3D cell shapes from time-lapse microscopy remains challenging, especially when only membranes are labeled.

Results

We present an image analysis framework for automated tracking and three-dimensional cell segmentation in confocal time lapses. A sphere clustering approach allows for local thresholding and application of logical rules to facilitate tracking and unseeded segmentation of variable cell shapes. Next, the segmentation is refined by a discrete element method simulation where cell shapes are constrained by a biomechanical cell shape model. We apply the framework on Caenorhabditis elegans embryos in various stages of early development and analyze the geometry of the 7- and 8-cell stage embryo, looking at volume, contact area and shape over time.

Availability and implementation

The Python code for the algorithm and for measuring performance, along with all data needed to recreate the results is freely available at 10.5281/zenodo.5108416 and 10.5281/zenodo.4540092. The most recent version of the software is maintained at https://bitbucket.org/pgmsembryogenesis/sdt-pics.

Supplementary information

Supplementary data are available at Bioinformatics online.

Collective effects in confined active Brownian particles

We investigate a two-dimensional system of active particles confined to a narrow annular domain. Despite the absence of explicit interactions among the velocities or the active forces of different particles, the system displays a transition from a disordered and stuck state to an ordered state of global collective motion where the particles rotate persistently clockwise or anticlockwise. We describe this behavior by introducing a suitable order parameter, the velocity polarization, measuring the global alignment of the particles' velocities along the tangential direction of the ring. We also measure the spatial velocity correlation function and its correlation length to characterize the two states. In the rotating phase, the velocity correlation displays an algebraic decay that is analytically predicted together with its correlation length, while in the stuck regime, the velocity correlation decays exponentially with a correlation length that increases with the persistence time. In the first case, the correlation (and, in particular, its correlation length) does not depend on the active force but the system size only. The global collective motion, an effect caused by the interplay between finite-size, periodicity, and persistent active forces, disappears as the size of the ring becomes infinite, suggesting that this phenomenon does not correspond to a phase transition in the usual thermodynamic sense.

Distinct Modes of Tissue Expansion in Free Versus Earlier-Confined Boundaries for More Physiological Modeling of Wound Healing, Cancer Metastasis, and Tissue Formation

Collective cell migration is often seen in many biological processes like embryogenesis, cancer metastasis, and wound healing. Despite extensive experimental and theoretical research, the unified mechanism responsible for collective cell migration is not well known. Most of the studies have investigated artificial model wound to study the collective cell migration in an epithelial monolayer. These artificial model wounds possess a high cell number density compared to the physiological scenarios like wound healing (cell damage due to applied cut) and cancer metastasis (smaller cell clusters). Therefore, both systems may not completely relate to each other, and further investigation is needed to understand the collective cell migration in physiological scenarios. In an effort to fill this existing knowledge gap, we investigated the freely expanding monolayer that closely represented the physiological scenarios and compared it with the artificially created model wound. In the present work, we report the effect of initial boundary conditions (free and confined) on the collective cell migration of the epithelial cell monolayer. The expansion and migration aspects of the freely expanding and earlier-confined monolayer were investigated at the tissue and cellular levels. The freely expanding monolayer showed significantly higher expansion and lower migration in comparison to the earlier-confined monolayer. The expansion and migration rate of the monolayer exhibited a strong negative correlation. The study highlights the importance of initial boundary conditions in the collective cell migration of the expanding tissue and provides useful insights that might be helpful in the future to tune the collective cell migration in wound healing, cancer metastasis, and tissue formation.

Spatial velocity correlations in inertial systems of active Brownian particles

Recently, it has been discovered that systems of active Brownian particles (APB) at high density organise their velocities into coherent domains showing large spatial structures in the velocity field. This collective behavior occurs spontaneously, i.e. is not caused by any specific interparticle force favoring the alignment of the velocities. This phenomenon was investigated in the absence of thermal noise and in the overdamped regime where inertial forces could be neglected. In this work, we demonstrate through numerical simulations and theoretical analysis that velocity alignment is a robust property of ABP and persists even in the presence of inertial forces and thermal fluctuations. We also show that a single dimensionless parameter, such as the Péclet number customarily employed in the description of self-propelled particles, is not sufficient to fully characterize this phenomenon either in the regimes of large viscosity or small mass. Indeed, the size of the velocity domains, measured through the correlation length of the spatial velocity correlation, remains constant when the swim velocity increases and decreases as the rotational diffusion becomes larger. We find that, contrary to the common belief, the spatial velocity correlation not only depends on inertia but is also non-symmetrically affected by mass and inverse viscosity variations. We conclude that in self-propelled systems, at variance with passive systems, variations in the inertial time (mass over solvent viscosity) and mass act as independent control parameters. Finally, we highlight the non-thermal nature of the spatial velocity correlations that are fairly insensitive both to solvent and active temperatures.

Differences in mechanical properties lead to anomalous phase separation in a model cell co-culture

During the morphogenesis of tissues and tumors, cells often interact with neighbors with different mechanical properties, but the understanding of its role is lacking. We use active Brownian dynamics simulations to study a model co-culture consisting of two types of cells with the same size and self-propulsion speed, but different mechanical stiffness and cell-cell adhesion. As time evolves, the system phase separates out into clusters with distinct morphologies and transport properties for the two cell types. The density structure factors and the growth of cell clusters deviate from behavior characteristic of the phase separation in binary fluids. Our results capture emergent structure and motility previously observed in co-culture experiments and provide mechanistic insights into intercellular phase separation during development and disease.

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.

Nonlinear mechanics of lamin filaments and the meshwork topology build an emergent nuclear lamina

The nuclear lamina—a meshwork of intermediate filaments termed lamins—is primarily responsible for the mechanical stability of the nucleus in multicellular organisms. However, structural-mechanical characterization of lamin filaments assembled in situ remains elusive. Here, we apply an integrative approach combining atomic force microscopy, cryo-electron tomography, network analysis, and molecular dynamics simulations to directly measure the mechanical response of single lamin filaments in three-dimensional meshwork. Endogenous lamin filaments portray non-Hookean behavior – they deform reversibly at a few hundred picoNewtons and stiffen at nanoNewton forces. The filaments are extensible, strong and tough similar to natural silk and superior to the synthetic polymer Kevlar^®. Graph theory analysis shows that the lamin meshwork is not a random arrangement of filaments but exhibits small-world properties. Our results suggest that lamin filaments arrange to form an emergent meshwork whose topology dictates the mechanical properties of individual filaments. The quantitative insights imply a role of meshwork topology in laminopathies.

Mechanical strength of in situ assembled nuclear lamin filaments arranged in a 3D meshwork is unclear. Here, using mechanical, structural and simulation tools, the authors report the hierarchical organization of the lamin meshwork that imparts strength and toughness to lamin filaments at par with silk and Kevlar^®

Bridging from single to collective cell migration: A review of models and links to experiments

Mathematical and computational models can assist in gaining an understanding of cell behavior at many levels of organization. Here, we review models in the literature that focus on eukaryotic cell motility at 3 size scales: intracellular signaling that regulates cell shape and movement, single cell motility, and collective cell behavior from a few cells to tissues. We survey recent literature to summarize distinct computational methods (phase-field, polygonal, Cellular Potts, and spherical cells). We discuss models that bridge between levels of organization, and describe levels of detail, both biochemical and geometric, included in the models. We also highlight links between models and experiments. We find that models that span the 3 levels are still in the minority.

Tracking collective cell motion by topological data analysis

By modifying and calibrating an active vertex model to experiments, we have simulated numerically a confluent cellular monolayer spreading on an empty space and the collision of two monolayers of different cells in an antagonistic migration assay. Cells are subject to inertial forces and to active forces that try to align their velocities with those of neighboring ones. In agreement with experiments in the literature, the spreading test exhibits formation of fingers in the moving interfaces, there appear swirls in the velocity field, and the polar order parameter and the correlation and swirl lengths increase with time. Numerical simulations show that cells inside the tissue have smaller area than those at the interface, which has been observed in recent experiments. In the antagonistic migration assay, a population of fluidlike Ras cells invades a population of wild type solidlike cells having shape parameters above and below the geometric critical value, respectively. Cell mixing or segregation depends on the junction tensions between different cells. We reproduce the experimentally observed antagonistic migration assays by assuming that a fraction of cells favor mixing, the others segregation, and that these cells are randomly distributed in space. To characterize and compare the structure of interfaces between cell types or of interfaces of spreading cellular monolayers in an automatic manner, we apply topological data analysis to experimental data and to results of our numerical simulations. We use time series of data generated by numerical simulations to automatically group, track and classify the advancing interfaces of cellular aggregates by means of bottleneck or Wasserstein distances of persistent homologies. These techniques of topological data analysis are scalable and could be used in studies involving large amounts of data. Besides applications to wound healing and metastatic cancer, these studies are relevant for tissue engineering, biological effects of materials, tissue and organ regeneration.

Evolution of multicellularity by collective integration of spatial information

At the origin of multicellularity, cells may have evolved aggregation in response to predation, for functional specialisation or to allow large-scale integration of environmental cues. These group-level properties emerged from the interactions between cells in a group, and determined the selection pressures experienced by these cells. We investigate the evolution of multicellularity with an evolutionary model where cells search for resources by chemotaxis in a shallow, noisy gradient. Cells can evolve their adhesion to others in a periodically changing environment, where a cell's fitness solely depends on its distance from the gradient source. We show that multicellular aggregates evolve because they perform chemotaxis more efficiently than single cells. Only when the environment changes too frequently, a unicellular state evolves which relies on cell dispersal. Both strategies prevent the invasion of the other through interference competition, creating evolutionary bi-stability. Therefore, collective behaviour can be an emergent selective driver for undifferentiated multicellularity.

Information and motility exchange in collectives of active particles

We examine the interplay of motility and information exchange in a model of run-and-tumble active particles where the particle's motility is encoded as a bit of information that can be exchanged upon contact according to the rules of AND and OR logic gates in a circuit. Motile AND particles become non-motile upon contact with a non-motile particle. Conversely, motile OR particles remain motile upon collision with their non-motile counterparts. AND particles that have become non-motile additionally "reawaken", i.e., recover their motility, at a fixed rate μ, as in the SIS (susceptible, infected, susceptible) model of epidemic spreading, where an infected agent can become healthy again, but keeps no memory of the recent infection, hence it is susceptible to a renewed infection. For μ = 0, both AND and OR particles relax irreversibly to absorbing states of all non-motile or all motile particles, respectively. The relaxation kinetics is, however, faster for OR particles that remain active throughout the process. At finite μ, the AND dynamics is controlled by the interplay between reawakening and collision rates. The system evolves to a state of all motile particles (an absorbing state in the language of absorbing phase transitions) for μ > μc and to a mixed state with coexisting motile and non-motile particles (an active state in the language of absorbing phase transitions) for μ < μc. The final state exhibits a rich structure controlled by motility-induced aggregation. Our work can be relevant to biochemical signaling in motile bacteria, the spreading of epidemics and of social consensus, as well as light-controlled organization of active colloids.

Control of cell colony growth by contact inhibition

Contact inhibition is a cell property that limits the migration and proliferation of cells in crowded environments. Here we investigate the growth dynamics of a cell colony composed of migrating and proliferating cells on a substrate using a minimal model that incorporates the mechanisms of contact inhibition of locomotion and proliferation. We find two distinct regimes. At early times, when contact inhibition is weak, the colony grows exponentially in time, fully characterised by the proliferation rate. At long times, the colony boundary moves at a constant speed, determined only by the migration speed of a single cell and independent of the proliferation rate. Further, the model demonstrates how cell-cell alignment speeds up colony growth. Our model illuminates how simple local mechanical interactions give rise to contact inhibition, and from this, how cell colony growth is self-organised and controlled on a local level.

Collective dynamics of coherent motile cells on curved surfaces

Cellular dynamic behaviors in organ morphogenesis and embryogenesis are affected by geometrical constraints. In this paper, we investigate how the surface topology and curvature of the underlying substrate tailor collective cell migration. An active vertex model is developed to explore the collective dynamics of coherent cells crawling on curved surfaces. We show that cells can self-organize into rich dynamic patterns including local swirling, global rotation, spiral crawling, serpentine crawling, and directed migration, depending on the interplay between cell-cell interactions and geometric constraints. Increasing substrate curvature results in higher cell-cell bending energy and thus tends to suppress local swirling and enhance density fluctuations. Substrate topology is revealed to regulate both the collective migration modes and density fluctuations of cell populations. In addition, upon increasing noise intensity, a Kosterlitz-Thouless-like ordering transition can emerge on both undevelopable and developable surfaces. This study paves the way to investigate various in vivo morphomechanics that involve surface curvature and topology.

3D Printed Cartilage-Like Tissue Constructs with Spatially Controlled Mechanical Properties

Developing biomimetic cartilaginous tissues that support locomotion while maintaining chondrogenic behavior is a major challenge in the tissue engineering field. Specifically, while locomotive forces demand tissues with strong mechanical properties, chondrogenesis requires a soft microenvironment. To address this challenge, 3D cartilage-like tissue is bioprinted using two biomaterials with different mechanical properties: a hard biomaterial to reflect the macromechanical properties of native cartilage, and a soft biomaterial to create a chondrogenic microenvironment. To this end, a hard biomaterial (MPa order compressive modulus) composed of an interpenetrating polymer network (IPN) of polyethylene glycol (PEG) and alginate hydrogel is developed as an extracellular matrix (ECM) with self-healing properties, but low diffusive capacity. Within this bath supplemented with thrombin, fibrinogen containing human mesenchymal stem cell (hMSC) spheroids is bioprinted forming fibrin, as the soft biomaterial (kPa order compressive modulus) to simulate cartilage's pericellular matrix and allow a fast diffusion of nutrients. The bioprinted hMSC spheroids improve viability and chondrogenic-like behavior without adversely affecting the macromechanical properties of the tissue. Therefore, the ability to print locally soft and cell stimulating microenvironments inside of a mechanically robust hydrogel is demonstrated, thereby uncoupling the micro- and macromechanical properties of the 3D printed tissues such as cartilage.

Adapting a Plant Tissue Model to Animal Development: Introducing Cell Sliding into VirtualLeaf

Cell-based, mathematical modeling of collective cell behavior has become a prominent tool in developmental biology. Cell-based models represent individual cells as single particles or as sets of interconnected particles and predict the collective cell behavior that follows from a set of interaction rules. In particular, vertex-based models are a popular tool for studying the mechanics of confluent, epithelial cell layers. They represent the junctions between three (or sometimes more) cells in confluent tissues as point particles, connected using structural elements that represent the cell boundaries. A disadvantage of these models is that cell-cell interfaces are represented as straight lines. This is a suitable simplification for epithelial tissues, where the interfaces are typically under tension, but this simplification may not be appropriate for mesenchymal tissues or tissues that are under compression, such that the cell-cell boundaries can buckle. In this paper, we introduce a variant of VMs in which this and two other limitations of VMs have been resolved. The new model can also be seen as on off-the-lattice generalization of the Cellular Potts Model. It is an extension of the open-source package VirtualLeaf, which was initially developed to simulate plant tissue morphogenesis where cells do not move relative to one another. The present extension of VirtualLeaf introduces a new rule for cell-cell shear or sliding, from which cell rearrangement (T1) and cell extrusion (T2) transitions emerge naturally, allowing the application of VirtualLeaf to problems of animal development. We show that the updated VirtualLeaf yields different results than the traditional vertex-based models for differential adhesion-driven cell sorting and for the neighborhood topology of soft cellular networks.

Mechanisms of Neural Crest Migration

Neural crest cells are a transient embryonic cell population that migrate collectively to various locations throughout the embryo to contribute a number of cell types to several organs. After induction, the neural crest delaminates and undergoes an epithelial-to-mesenchymal transition before migrating through intricate yet characteristic paths. The neural crest exhibits a variety of migratory behaviors ranging from sheet-like mass migration in the cephalic regions to chain migration in the trunk. During their journey, neural crest cells rely on a range of signals both from their environment and within the migrating population for navigating through the embryo as a collective. Here we review these interactions and mechanisms, including chemotactic cues of neural crest cells' migration.

Role of Substrate Stiffness in Tissue Spreading: Wetting Transition and Tissue Durotaxis

Living tissues undergo wetting transitions: On a surface, they can either form a dropletlike cell aggregate or spread as a monolayer of migrating cells. Tissue wetting depends not only on the chemical but also on the mechanical properties of the substrate. Here, we study the role of substrate stiffness in tissue spreading, which we describe by means of an active polar fluid model. Taking into account that cells exert larger active traction forces on stiffer substrates, we predict a tissue wetting transition at a critical substrate stiffness that decreases with tissue size. On substrates with a stiffness gradient, we find that the tissue spreads faster on the stiffer side. Furthermore, we show that the tissue can wet the substrate on the stiffer side while dewetting from the softer side. We also show that, by means of viscous forces transmitted across the tissue, the stiffer-side interface can transiently drag the softer-side interface toward increasing stiffness, against its spreading tendency. These two effects result in directed tissue migration up the stiffness gradient. This phenomenon-tissue durotaxis-can thus emerge both from dewetting on the soft side and from hydrodynamic interactions between the tissue interfaces. Overall, our work unveils mechanisms whereby substrate stiffness impacts the collective migration and the active wetting properties of living tissues, which are relevant in development, regeneration, and cancer.

Active Fingering Instability in Tissue Spreading

During the spreading of epithelial tissues, the advancing tissue front often develops fingerlike protrusions. Their resemblance to traditional viscous fingering patterns in driven fluids suggests that epithelial fingers could arise from an interfacial instability. However, the existence and physical mechanism of such a putative instability remain unclear. Here, based on an active polar fluid model for epithelial spreading, we analytically predict a generic instability of the tissue front. On the one hand, active cellular traction forces impose a velocity gradient that leads to an accelerated front, which is, thus, unstable to long-wavelength perturbations. On the other hand, contractile intercellular stresses typically dominate over surface tension in stabilizing short-wavelength perturbations. Finally, the finite range of hydrodynamic interactions in the tissue selects a wavelength for the fingering pattern, which is, thus, given by the smallest between the tissue size and the hydrodynamic screening length. Overall, we show that spreading epithelia experience an active fingering instability based on a simple kinematic mechanism. Moreover, our results underscore the crucial role of long-range hydrodynamic interactions in the dynamics of tissue morphology.

Emergent functions of proteins in non-stoichiometric supramolecular assemblies

Proteins are the basic functional units of the cell, carrying out myriads of functions essential for life. There are countless reports in molecular cell biology addressing the functioning of proteins under physiological and pathological conditions, aiming to understand life at the atomistic-molecular level and thereby being able to develop remedies against diseases. The central theme in most of these studies is that the functional unit under study is the protein itself. Recent rapid progress has radically challenged and extended this protein-function paradigm, by demonstrating that novel function(s) may emerge when proteins form dynamic and non-stoichiometric supramolecular assemblies. There is an increasing number of cases for such collective functions, such as targeting, localization, protection/shielding and filtering effects, as exemplified by signaling complexes and prions, biominerals and mucus, amphibian adhesions and bacterial biofilms, and a broad range of membraneless organelles (bio-condensates) formed by liquid-liquid phase separation in the cell. In this short review, we show that such non-stoichiometric organization may derive from the heterogeneity of the system, a mismatch in valency and/or geometry of the partners, and/or intrinsic structural disorder and multivalency of the component proteins. Either way, the resulting functional features cannot be simply described by, or predicted from, the properties of the isolated single protein(s), as they belong to the collection of proteins.

Active wetting of epithelial tissues

Development, regeneration and cancer involve drastic transitions in tissue morphology. In analogy with the behavior of inert fluids, some of these transitions have been interpreted as wetting transitions. The validity and scope of this analogy are unclear, however, because the active cellular forces that drive tissue wetting have been neither measured nor theoretically accounted for. Here we show that the transition between two-dimensional epithelial monolayers and three-dimensional spheroidal aggregates can be understood as an active wetting transition whose physics differs fundamentally from that of passive wetting phenomena. By combining an active polar fluid model with measurements of physical forces as a function of tissue size, contractility, cell-cell and cell-substrate adhesion, and substrate stiffness, we show that the wetting transition results from the competition between traction forces and contractile intercellular stresses. This competition defines a new intrinsic lengthscale that gives rise to a critical size for the wetting transition in tissues, a striking feature that has no counterpart in classical wetting. Finally, we show that active shape fluctuations are dynamically amplified during tissue dewetting. Overall, we conclude that tissue spreading constitutes a prominent example of active wetting - a novel physical scenario that may explain morphological transitions during tissue morphogenesis and tumor progression.

Dynamic Migration Modes of Collective Cells

Collective cell migration occurs in a diversity of physiological processes such as wound healing, cancer metastasis, and embryonic morphogenesis. In the collective context, cohesive cells may move as a translational solid, swirl as a fluid, or even rotate like a disk, with scales ranging from several to dozens of cells. In this work, an active vertex model is presented to explore the regulatory roles of social interactions of neighboring cells and environmental confinements in collective cell migration in a confluent monolayer. It is found that the competition between two kinds of intercellular social interactions-local alignment and contact inhibition of locomotion-drives the cells to self-organize into various dynamic coherent structures with a spatial correlation scale. The interplay between this intrinsic length scale and the external confinement dictates the migration modes of collective cells confined in a finite space. We also show that the local alignment-contact inhibition of locomotion coordination can induce giant density fluctuations in a confluent cell monolayer without gaps, which triggers the spontaneous breaking of orientational symmetry and leads to phase separation.

Lens-free microscopy for 3D + time acquisitions of 3D cell culture

Thanks to a novel three-dimensional imaging platform based on lens-free microscopy, it is possible to perform multi-angle acquisitions and holographic reconstructions of 3D cell cultures directly into the incubator. Being able of reconstructing volumes as large as ~5 mm3 over a period of time covering several days, allows us to observe a broad range of migration strategies only present in 3D environment, whether it is single cell migration, collective migrations of cells and dispersal of cells. In addition we are able to distinguish new interesting phenomena, e.g. large-scale cell-to-matrix interactions (>1 mm), fusion of cell clusters into large aggregate (~10,000 µm2) and conversely, total dissociation of cell clusters into clumps of migrating cells. This work on a novel 3D + time lens-free microscopy technique thus expands the repertoire of phenomena that can be studied within 3D cell cultures.

From Neural Crest Development to Cancer and Vice Versa: How p75NTR and (Pro)neurotrophins Could Act on Cell Migration and Invasion?

The p75 neurotrophin receptor (p75^NTR), also known as low-affinity nerve growth factor, belongs to the tumor necrosis factor family of receptors. p75^NTR is widely expressed in the nervous system during the development, as well as, in the neural crest population, since p75^NTR has been described as ubiquitously expressed and considered as a neural crest marker. Neural crest cells (NCCs) constitute an transient population accurately migrating and invading, with precision, defined sites of the embryo. During migration, NCCs are guided along distinct migratory pathways by specialized molecules present in the extracellular matrix or on the surfaces of those cells. Two main processes direct NCC migration during the development: (1) an epithelial-to-mesenchymal transition and (2) a process known as contact inhibition of locomotion. In adults, p75^NTR remains expressed by NCCs and has been identified in an increasing number of cancer cells. Nonetheless, the regulation of the expression of p75^NTR and the underlying mechanisms in stem cell biology or cancer cells have not yet been sufficiently addressed. The main objective of this review is therefore to analyze elements of our actual knowledge regarding p75^NTR roles during the development (mainly focusing on neural crest development) and see how we can transpose that information from development to cancer (and vice versa) to better understand the link between p75^NTR and cell migration and invasion. In this review, we successively analyzed the molecular mechanisms of p75^NTR when it interacts with several coreceptors and/or effectors. We then analyzed which signaling pathways are the most activated or linked to NCC migration during the development. Regarding cancer, we analyzed the described molecular pathways underlying cancer cell migration when p75^NTR was correlated to cancer cell migration and invasion. From those diverse sources of information, we finally summarized potential molecular mechanisms underlying p75^NTR activation in cell migration and invasion that could lead to new research areas to develop new therapeutic protocols.

Architecture, space and information in constructions built by humans and social insects: a conceptual review

The similarities between the structures built by social insects and by humans have led to a convergence of interests between biologists and architects. This new, de facto interdisciplinary community of scholars needs a common terminology and theoretical framework in which to ground its work. In this conceptually oriented review paper, we review the terms 'information', 'space' and 'architecture' to provide definitions that span biology and architecture. A framework is proposed on which interdisciplinary exchange may be better served, with the view that this will aid better cross-fertilization between disciplines, working in the areas of collective behaviour and analysis of the structures and edifices constructed by non-humans; and to facilitate how this area of study may better contribute to the field of architecture. We then use these definitions to discuss the informational content of constructions built by organisms and the influence these have on behaviour, and vice versa. We review how spatial constraints inform and influence interaction between an organism and its environment, and examine the reciprocity of space and information on construction and the behaviour of humans and social insects.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.