Size-dependent patterns of cell proliferation and migration in freely-expanding epithelia

The impact of cell density variations on nanoparticle uptake across bioprinted A549 gradients

Introduction

The safe-by-design of engineered nanoparticles (NPs) for any application requires a detailed understanding of how the particles interact with single cells. Most studies are based on two-dimensional, uniformly dense cell cultures, which do not represent the diverse and inhomogeneous cell environments found in situ. In-vitro models that accurately represent tissue complexity, including realistic cell densities, are essential to increase the predictive accuracy of studies on cell-NP interactions. This study uses a bioprinted cell gradient model to examine the relation between cell density and NP uptake in one dish.

Method

A549 lung epithelial cell density gradients within single inserts were produced with a bioprinter by modulating inter-droplet distances. After two days in culture, cells were exposed to Cy5-labeled silica NPs (SiO2 NPs, ∼112 nm, 20 μg/mL) for up to 48 h. Confocal fluorescence microscopy and 3D image analysis were used to quantify NP uptake, cell surface area, and cell volume. The relationship between NP uptake and the other parameters was then investigated statistically.

Results

Bioprinting enabled the creation of reproducible linear cell density gradients, allowing controlled modeling of density variations while preserving cell viability throughout the experiment. Increasing inter-droplet distances, from 0.1 mm to 0.6 mm, were used to achieve uniformly decreasing cell densities. SiO2 NP uptake per cell was around 50% higher in low-density regions compared to high-density areas across all time points, i.e., 6, 24, and 48 h post-exposure. This inverse relationship correlated with greater average cell surface area in lower-density regions, while differences in the proliferation rates of the A549 cells at varying densities did not significantly impact uptake, did not significantly impact uptake.

Conclusion

SiO2 NP uptake is significantly enhanced at lower cell densities, mainly due to the increased available surface area, revealing potential cell-NP interaction differences in tissues that present cell density variability. Our drop-on-demand bioprinting gradient model successfully supports the implementation of cell density gradients in in-vitro models to increase their relevance as new approach methodologies (NAMs) for next-generation risk assessment strategies.

Substrate stress relaxation regulates monolayer fluidity and leader cell formation for collectively migrating epithelia

Collective migration of epithelial tissues is a critical feature of developmental morphogenesis and tissue homeostasis. Coherent motion of cell collectives requires large-scale coordination of motion and force generation and is influenced by mechanical properties of the underlying substrate. While tissue viscoelasticity is a ubiquitous feature of biological tissues, its role in mediating collective cell migration is unclear. Here, we have investigated the impact of substrate stress relaxation on the migration of micropatterned epithelial monolayers. Epithelial monolayers exhibit faster collective migration on viscoelastic alginate substrates with slower relaxation timescales, which are more elastic, relative to substrates with faster stress relaxation, which exhibit more viscous loss. Faster migration on slow-relaxing substrates is associated with reduced substrate deformation, greater monolayer fluidity, and enhanced leader cell formation. In contrast, monolayers on fast-relaxing substrates generate substantial substrate deformations and are more jammed within the bulk, with reduced formation of transient lamellipodial protrusions past the monolayer edge leading to slower overall expansion. This work reveals features of collective epithelial dynamics on soft, viscoelastic materials and adds to our understanding of cell-substrate interactions at the tissue scale.

Tissue Active Matter: Integrating Mechanics and Signaling into Dynamical Models

The importance of physical forces in the morphogenesis, homeostatic function, and pathological dysfunction of multicellular tissues is being increasingly characterized, both theoretically and experimentally. Analogies between biological systems and inert materials such as foams, gels, and liquid crystals have provided striking insights into the core design principles underlying multicellular organization. However, these connections can seem surprising given that a key feature of multicellular systems is their ability to constantly consume energy, providing an active origin for the forces that they produce. Key emerging questions are, therefore, to understand whether and how this activity grants tissues novel properties that do not have counterparts in classical materials, as well as their consequences for biological function. Here, we review recent discoveries at the intersection of active matter and tissue biology, with an emphasis on how modeling and experiments can be combined to understand the dynamics of multicellular systems. These approaches suggest that a number of key biological tissue-scale phenomena, such as morphogenetic shape changes, collective migration, or fate decisions, share unifying design principles that can be described by physical models of tissue active matter.

A new paradigm considering multicellular adhesion, repulsion and attraction represent diverse cellular tile patterns

Cell sorting by differential adhesion is one of the basic mechanisms explaining spatial organization of neurons in early stage brain development of fruit flies. The columnar arrangements of neurons determine the large-scale patterns in the fly visual center. Experimental studies indicate that hexagonal configurations regularly appear in the fly compound eye, which is connected to the visual center by photoreceptor axons, while tetragonal configurations can be induced in mutants. We need a mathematical framework to study the mechanisms of such a transition between hexagonal and tetragonal arrangements. Here, we propose a new mathematical model based on macroscopic approximations of agent-based models that produces a similar behavior changing from hexagonal to tetragonal steady configurations when medium-range repulsion and longer-range attraction between individuals are incorporated in previous successful models for cell sorting based on adhesion and volume constraints. We analyze the angular configurations of these patterns based on angle summary statistics and compare between experimental data and parameter fitted ARA (Adhesion-Repulsion-Attraction) models showing that intermediate patterns between hexagonal and tetragonal configuration are common in experimental data as well as in our ARA mathematical model. Our studies indicate an overall qualitative agreement of ARA models in tile patterning and pave the way for their quantitative studies. Our study opens up a new avenue to explore tile pattern transitions, found not only in the column arrangement in the brain, but also in the other related biological processes.

Large-scale control over collective cell migration using light-activated epidermal growth factor receptors

Receptor tyrosine kinases (RTKs) play key roles in coordinating cell movement at both single-cell and tissue scales. The recent development of optogenetic tools for controlling RTKs and their downstream signaling pathways suggests that these responses may be amenable to engineering-based control for sculpting tissue shape and function. Here, we report that a light-controlled epidermal growth factor (EGF) receptor (OptoEGFR) can be deployed in epithelial cells for precise, programmable control of long-range tissue movements. We show that in OptoEGFR-expressing tissues, light can drive millimeter-scale cell rearrangements to densify interior regions or produce rapid outgrowth at tissue edges. Light-controlled tissue movements are driven primarily by phosphoinositide 3-kinase (PI3K) signaling, rather than diffusible ligands, tissue contractility, or ERK kinase signaling as seen in other RTK-driven migration contexts. Our study suggests that synthetic, light-controlled RTKs could serve as a powerful platform for controlling cell positions and densities for diverse applications, including wound healing and tissue morphogenesis.

Quantifying cell cycle regulation by tissue crowding

The spatiotemporal coordination and regulation of cell proliferation is fundamental in many aspects of development and tissue maintenance. Cells have the ability to adapt their division rates in response to mechanical constraints, yet we do not fully understand how cell proliferation regulation impacts cell migration phenomena. Here, we present a minimal continuum model of cell migration with cell cycle dynamics, which includes density-dependent effects and hence can account for cell proliferation regulation. By combining minimal mathematical modeling, Bayesian inference, and recent experimental data, we quantify the impact of tissue crowding across different cell cycle stages in epithelial tissue expansion experiments. Our model suggests that cells sense local density and adapt cell cycle progression in response, during G1 and the combined S/G2/M phases, providing an explicit relationship between each cell-cycle-stage duration and local tissue density, which is consistent with several experimental observations. Finally, we compare our mathematical model's predictions to different experiments studying cell cycle regulation and present a quantitative analysis on the impact of density-dependent regulation on cell migration patterns. Our work presents a systematic approach for investigating and analyzing cell cycle data, providing mechanistic insights into how individual cells regulate proliferation, based on population-based experimental measurements.

Fast yet force-effective mode of supracellular collective cell migration due to extracellular force transmission

Cell collectives, like other motile entities, generate and use forces to move forward. Here, we ask whether environmental configurations alter this proportional force-speed relationship, since aligned extracellular matrix fibers are known to cause directed migration. We show that aligned fibers serve as active conduits for spatial propagation of cellular mechanotransduction through matrix exoskeleton, leading to efficient directed collective cell migration. Epithelial (MCF10A) cell clusters adhered to soft substrates with aligned collagen fibers (AF) migrate faster with much lesser traction forces, compared to random fibers (RF). Fiber alignment causes higher motility waves and transmission of normal stresses deeper into cell monolayer while minimizing shear stresses and increased cell-division based fluidization. By contrast, fiber randomization induces cellular jamming due to breakage in motility waves, disrupted transmission of normal stresses, and heightened shear driven flow. Using a novel motor-clutch model, we explain that such 'force-effective' fast migration phenotype occurs due to rapid stabilization of contractile forces at the migrating front, enabled by higher frictional forces arising from simultaneous compressive loading of parallel fiber-substrate connections. We also model 'haptotaxis' to show that increasing ligand connectivity (but not continuity) increases migration efficiency. According to our model, increased rate of front stabilization via higher resistance to substrate deformation is sufficient to capture 'durotaxis'. Thus, our findings reveal a new paradigm wherein the rate of leading-edge stabilization determines the efficiency of supracellular collective cell migration.

A programmable, open-source robot that scratches cultured tissues to investigate cell migration, healing, and tissue sculpting

Despite the widespread popularity of the "scratch assay," where a pipette is dragged manually through cultured tissue to create a gap to study cell migration and healing, it carries significant drawbacks. Its heavy reliance on manual technique can complicate quantification, reduce throughput, and limit the versatility and reproducibility. We present an open-source, low-cost, accessible, robotic scratching platform that addresses all of the core issues. Compatible with nearly all standard cell culture dishes and usable directly in a sterile culture hood without specialized training, our robot makes highly reproducible scratches in a variety of complex cultured tissues with high throughput. Moreover, the robot demonstrates precise removal of tissues for sculpting arbitrary tissue and wound shapes, enabling complex co-culture experiments. This system significantly improves the usefulness of the conventional scratch assay and opens up new possibilities in complex tissue engineering for realistic wound healing and migration research.

Minimal cellular automaton model with heterogeneous cell sizes predicts epithelial colony growth

Regulation of cell proliferation is a crucial aspect of tissue development and homeostasis and plays a major role in morphogenesis, wound healing, and tumor invasion. A phenomenon of such regulation is contact inhibition, which describes the dramatic slowing of proliferation, cell migration and individual cell growth when multiple cells are in contact with each other. While many physiological, molecular and genetic factors are known, the mechanism of contact inhibition is still not fully understood. In particular, the relevance of cellular signaling due to interfacial contact for contact inhibition is still debated. Cellular automata (CA) have been employed in the past as numerically efficient mathematical models to study the dynamics of cell ensembles, but they are not suitable to explore the origins of contact inhibition as such agent-based models assume fixed cell sizes. We develop a minimal, data-driven model to simulate the dynamics of planar cell cultures by extending a probabilistic CA to incorporate size changes of individual cells during growth and cell division. We successfully apply this model to previous in-vitro experiments on contact inhibition in epithelial tissue: After a systematic calibration of the model parameters to measurements of single-cell dynamics, our CA model quantitatively reproduces independent measurements of emergent, culture-wide features, like colony size, cell density and collective cell migration. In particular, the dynamics of the CA model also exhibit the transition from a low-density confluent regime to a stationary postconfluent regime with a rapid decrease in cell size and motion. This implies that the volume exclusion principle, a mechanical constraint which is the only inter-cellular interaction incorporated in the model, paired with a size-dependent proliferation rate is sufficient to generate the observed contact inhibition. We discuss how our approach enables the introduction of effective bio-mechanical interactions in a CA framework for future studies.

Cellular Energy Cycle Mediates an Advection-Like Forward Cell Flow to Support Collective Invasion

Collective cell migration is a model for nonequilibrium biological dynamics, which is important for morphogenesis, pattern formation, and cancer metastasis. The current understanding of cellular collective dynamics is based primarily on cells moving within a 2D epithelial monolayer. However, solid tumors often invade surrounding tissues in the form of a stream-like 3D structure, and how biophysical cues are integrated at the cellular level to give rise to this collective streaming remains unclear. Here, it is shown that cell cycle-mediated bioenergetics drive a forward advective flow of cells and energy to the front to support 3D collective invasion. The cell division cycle mediates a corresponding energy cycle such that cellular adenosine triphosphate (ATP) energy peaks just before division. A reaction-advection-diffusion (RAD) type model coupled with experimental measurements further indicates that most cells enter an active division cycle at rear positions during 3D streaming. Once the cells progress to a later stage toward division, the high intracellular energy allows them to preferentially stream toward the tip and become leader cells. This energy-driven cellular flow may be a fundamental characteristic of 3D collective dynamics based on thermodynamic principles important for not only cancer invasion but also tissue morphogenesis.

Clonal dynamics of surface-driven growing tissues

The self-organization of cells into complex tissues relies on a tight coordination of cell behavior. Identifying the cellular processes driving tissue growth is key to understanding the emergence of tissue forms and devising targeted therapies for aberrant growth, such as in cancer. Inferring the mode of tissue growth, whether it is driven by cells on the surface or by cells in the bulk, is possible in cell culture experiments but difficult in most tissues in living organisms (in vivo). Genetic tracing experiments, where a subset of cells is labeled with inheritable markers, have become important experimental tools to study cell fate in vivo. Here we show that the mode of tissue growth is reflected in the size distribution of the progeny of marked cells. To this end, we derive the clone size distributions using analytical calculations in the limit of negligible cell migration and cell death, and we test our predictions with an agent-based stochastic sampling technique. We show that for surface-driven growth the clone size distribution takes a characteristic power-law form with an exponent determined by fluctuations of the tissue surface. Our results propose a possible way of determining the mode of tissue growth from genetic tracing experiments.

Discovering dynamic laws from observations: The case of self-propelled, interacting colloids

Active matter spans a wide range of time and length scales, from groups of cells and synthetic self-propelled colloids to schools of fish and flocks of birds. The theoretical framework describing these systems has shown tremendous success in finding universal phenomenology. However, further progress is often burdened by the difficulty of determining forces controlling the dynamics of individual elements within each system. Accessing this local information is pivotal for the understanding of the physics governing an ensemble of active particles and for the creation of numerical models capable of explaining the observed collective phenomena. In this work, we present ActiveNet, a machine-learning tool consisting of a graph neural network that uses the collective motion of particles to learn active and two-body forces controlling their individual dynamics. We verify our approach using numerical simulations of active Brownian particles, active particles undergoing underdamped Langevin dynamics, and chiral active Brownian particles considering different interaction potentials and values of activity. Interestingly, ActiveNet can equally learn conservative or nonconservative forces as well as torques. Moreover, ActiveNet has proven to be a useful tool to learn the stochastic contribution to the forces, enabling the estimation of the diffusion coefficients. Therefore, all coefficients of the equation of motion of Active Brownian Particles are captured. Finally, we apply ActiveNet to experiments of electrophoretic Janus particles, extracting the active and two-body forces controlling colloids' dynamics. On the one side, we have learned that the active force depends on the electric field and area fraction. On the other side, we have also discovered a dependence of the two-body interaction with the electric field that leads us to propose that the dominant force between active colloids is a screened electrostatic interaction with a constant length scale. We believe that the proposed methodological tool, ActiveNet, might open a new avenue for the study and modeling of experimental suspensions of active particles.

Large-scale control over collective cell migration using light-controlled epidermal growth factor receptors

Receptor tyrosine kinases (RTKs) are thought to play key roles in coordinating cell movement at single-cell and tissue scales. The recent development of optogenetic tools for controlling RTKs and their downstream signaling pathways suggested these responses may be amenable to engineering-based control for sculpting tissue shape and function. Here, we report that a light-controlled EGF receptor (OptoEGFR) can be deployed in epithelial cell lines for precise, programmable control of long-range tissue movements. We show that in OptoEGFR-expressing tissues, light can drive millimeter-scale cell rearrangements to densify interior regions or produce rapid outgrowth at tissue edges. Light-controlled tissue movements are driven primarily by PI 3-kinase signaling, rather than diffusible signals, tissue contractility, or ERK kinase signaling as seen in other RTK-driven migration contexts. Our study suggests that synthetic, light-controlled RTKs could serve as a powerful platform for controlling cell positions and densities for diverse applications including wound healing and tissue morphogenesis.

Collective Cell Radial Ordered Migration in Spatial Confinement

Collective cells, a typical active matter system, exhibit complex coordinated behaviors fundamental for various developmental and physiological processes. The present work discovers a collective radial ordered migration behavior of NIH3T3 fibroblasts that depends on persistent top-down regulation with 2D spatial confinement. Remarkably, individual cells move in a weak-oriented, diffusive-like rather than strong-oriented ballistic manner. Despite this, the collective movement is spatiotemporal heterogeneous and radial ordering at supracellular scale, manifesting as a radial ordered wavefront originated from the boundary and propagated toward the center of pattern. Combining bottom-up cell-to-extracellular matrix (ECM) interaction strategy, numerical simulations based on a developed mechanical model well reproduce and explain above observations. The model further predicts the independence of geometric features on this ordering behavior, which is validated by experiments. These results together indicate such radial ordered collective migration is ascribed to the couple of top-down regulation with spatial restriction and bottom-up cellular endogenous nature.

Mechanical control of cell proliferation patterns in growing epithelial monolayers

Cell proliferation plays a crucial role in regulating tissue homeostasis and development. However, our understanding of how cell proliferation is controlled in densely packed tissues is limited. Here we develop a computational framework to predict the patterns of cell proliferation in growing epithelial tissues, connecting single-cell behaviors and cell-cell interactions to tissue-level growth. Our model incorporates probabilistic rules governing cell growth, division, and elimination, also taking into account their feedback with tissue mechanics. In particular, cell growth is suppressed and apoptosis is enhanced in regions of high cell density. With these rules and model parameters calibrated using experimental data for epithelial monolayers, we predict how tissue confinement influences cell size and proliferation dynamics and how single-cell physical properties influence the spatiotemporal patterns of tissue growth. In this model, mechanical feedback between tissue confinement and cell growth leads to enhanced cell proliferation at tissue boundaries, whereas cell growth in the bulk is arrested, recapitulating experimental observations in epithelial tissues. By tuning cellular elasticity and contact inhibition of proliferation we can regulate the emergent patterns of cell proliferation, ranging from uniform growth at low contact inhibition to localized growth at higher contact inhibition. We show that the cell size threshold at G1/S transition governs the homeostatic cell density and tissue turnover rate, whereas the mechanical state of the tissue governs the dynamics of tissue growth. In particular, we find that the cellular parameters affecting tissue pressure play a significant role in determining the overall growth rate. Our computational study thus underscores the impact of cell mechanical properties on the spatiotemporal patterns of cell proliferation in growing epithelial tissues.

E-cadherin biomaterials reprogram collective cell migration and cell cycling by forcing homeostatic conditions

Cells attach to the world through either cell-extracellular matrix adhesion or cell-cell adhesion, and traditional biomaterials imitate the matrix for integrin-based adhesion. However, materials incorporating cadherin proteins that mimic cell-cell adhesion offer an alternative to program cell behavior and integrate into living tissues. We investigated how cadherin substrates affect collective cell migration and cell cycling in epithelia. Our approach involved biomaterials with matrix proteins on one-half and E-cadherin proteins on the other, forming a "Janus" interface across which we grew a single sheet of cells. Tissue regions over the matrix side exhibited normal collective dynamics, but an abrupt behavior shift occurred across the Janus boundary onto the E-cadherin side, where cells attached to the substrate via E-cadherin adhesions, resulting in stalled migration and slowing of the cell cycle. E-cadherin surfaces disrupted long-range mechanical coordination and nearly doubled the length of the G0/G1 phase of the cell cycle, linked to the lack of integrin focal adhesions on the E-cadherin surface.

Density-Polarity Coupling in Confined Active Polar Films: Asters, Spirals, and Biphasic Orientational Phases

Topological defects in active polar fluids can organize spontaneous flows and influence macroscopic density patterns. Both of them play an important role during animal development. Yet the influence of density on active flows is poorly understood. Motivated by experiments on cell monolayers confined to disks, we study the coupling between density and polar order for a compressible active polar fluid in the presence of a +1 topological defect. As in the experiments, we find a density-controlled spiral-to-aster transition. In addition, biphasic orientational phases emerge as a generic outcome of such coupling. Our results highlight the importance of density gradients as a potential mechanism for controlling flow and orientational patterns in biological systems.

Bridging the gap between collective motility and epithelial-mesenchymal transitions through the active finite voronoi model

We introduce an active version of the recently proposed finite Voronoi model of epithelial tissue. The resultant Active Finite Voronoi (AFV) model enables the study of both confluent and non-confluent geometries and transitions between them, in the presence of active cells. Our study identifies six distinct phases, characterized by aggregation-segregation, dynamical jamming-unjamming, and epithelial-mesenchymal transitions (EMT), thereby extending the behavior beyond that observed in previously studied vertex-based models. The AFV model with rich phase diagram provides a cohesive framework that unifies the well-observed progression to collective motility via unjamming with the intricate dynamics enabled by EMT. This approach should prove useful for challenges in developmental biology systems as well as the complex context of cancer metastasis. The simulation code is also provided.

Morphology as indicator of adaptive changes of model tissues in osmotically and chemically changing environments

We investigate the formation and maintenance of the homeostatic state in the case of 2D epithelial tissues following an induction of hyperosmotic conditions, using media enriched with 80 to 320 mOsm of mannitol, NaCl, and urea. We characterise the changes in the tissue immediately after the osmotic shock, and follow it until the new homeostatic state is formed. We characterise changes in cooperative motility and proliferation pressure in the tissue upon treatment with the help of a theoretical model based on the delayed Fisher-Kolmogorov formalism, where the delay in density evolution is induced by the the finite time of the cell division. Finally we explore the adaptation of the homeostatic tissue to highly elevated osmotic conditions by evaluating the morphology and topology of cells after 20 days in incubation. We find that hyperosmotic environments together with changes in the extracellular matrix induce different mechanical states in viable tissues, where only some remain functional. The perspective is a relation between tissue topology and function, which could be explored beyond the scope of this manuscript. Experimental investigation of morphological effect of change of osmotic conditions on long-term tissue morphology and topology Effect of osmotic changes on transient tissue growth behaviour Analysis of recovery process of tissues post-osmotic-shock Toxicity limits of osmolytes in mid- to long-term tissue evolution Tissue adaptation to physiological changes in environment Long-term tissue stabilisation under altered osmotic conditions.

Free and Interfacial Boundaries in Individual-Based Models of Multicellular Biological systems

Coordination of cell behaviour is key to a myriad of biological processes including tissue morphogenesis, wound healing, and tumour growth. As such, individual-based computational models, which explicitly describe inter-cellular interactions, are commonly used to model collective cell dynamics. However, when using individual-based models, it is unclear how descriptions of cell boundaries affect overall population dynamics. In order to investigate this we define three cell boundary descriptions of varying complexities for each of three widely used off-lattice individual-based models: overlapping spheres, Voronoi tessellation, and vertex models. We apply our models to multiple biological scenarios to investigate how cell boundary description can influence tissue-scale behaviour. We find that the Voronoi tessellation model is most sensitive to changes in the cell boundary description with basic models being inappropriate in many cases. The timescale of tissue evolution when using an overlapping spheres model is coupled to the boundary description. The vertex model is demonstrated to be the most stable to changes in boundary description, though still exhibits timescale sensitivity. When using individual-based computational models one should carefully consider how cell boundaries are defined. To inform future work, we provide an exploration of common individual-based models and cell boundary descriptions in frequently studied biological scenarios and discuss their benefits and disadvantages.

Epithelial tissue confinement inhibits cell growth and leads to volume-reducing divisions

Cell proliferation is a central process in tissue development, homeostasis, and disease, yet how proliferation is regulated in the tissue context remains poorly understood. Here, we introduce a quantitative framework to elucidate how tissue growth dynamics regulate cell proliferation. Using MDCK epithelial monolayers, we show that a limiting rate of tissue expansion creates confinement that suppresses cell growth; however, this confinement does not directly affect the cell cycle. This leads to uncoupling between rates of cell growth and division in epithelia and, thereby, reduces cell volume. Division becomes arrested at a minimal cell volume, which is consistent across diverse epithelia in vivo. Here, the nucleus approaches the minimum volume capable of packaging the genome. Loss of cyclin D1-dependent cell-volume regulation results in an abnormally high nuclear-to-cytoplasmic volume ratio and DNA damage. Overall, we demonstrate how epithelial proliferation is regulated by the interplay between tissue confinement and cell-volume regulation.

Comparison of particle image velocimetry and the underlying agents dynamics in collectively moving self propelled particles

Collective migration of cells is a fundamental behavior in biology. For the quantitative understanding of collective cell migration, live-cell imaging techniques have been used using e.g., phase contrast or fluorescence images. Particle tracking velocimetry (PTV) is a common recipe to quantify cell motility with those image data. However, the precise tracking of cells is not always feasible. Particle image velocimetry (PIV) is an alternative to PTV, corresponding to Eulerian picture of fluid dynamics, which derives the average velocity vector of an aggregate of cells. However, the accuracy of PIV in capturing the underlying cell motility and what values of the parameters should be chosen is not necessarily well characterized, especially for cells that do not adhere to a viscous flow. Here, we investigate the accuracy of PIV by generating images of simulated cells by the Vicsek model using trajectory data of agents at different noise levels. It was found, using an alignment score, that the direction of the PIV vectors coincides with the direction of nearby agents with appropriate choices of PIV parameters. PIV is found to accurately measure the underlying motion of individual agents for a wide range of noise level, and its condition is addressed.

E-cadherin biointerfaces reprogram collective cell migration and cell cycling by forcing homeostatic conditions

Cells attach to the world around them in two ways-cell:extracellular-matrix adhesion and cell:cell adhesion-and conventional biomaterials are made to resemble the matrix to encourage integrin-based cell adhesion. However, interest is growing for cell-mimetic interfaces that mimic cell-cell interactions using cadherin proteins, as this offers a new way to program cell behavior and design synthetic implants and objects that can integrate directly into living tissues. Here, we explore how these cadherin-based materials affect collective cell behaviors, focusing specifically on collective migration and cell cycle regulation in cm-scale epithelia. We built culture substrates where half of the culture area was functionalized with matrix proteins and the contiguous half was functionalized with E-cadherin proteins, and we grew large epithelia across this 'Janus' interface. Parts of the tissues in contact with the matrix side of the Janus interface exhibited normal collective dynamics, but an abrupt shift in behaviors happened immediately across the Janus boundary onto the E-cadherin side, where cells formed hybrid E-cadherin junctions with the substrate, migration effectively froze in place, and cell-cycling significantly decreased. E-cadherin materials suppressed long-range mechanical correlations in the tissue and mechanical information reflected off the substrate interface. These effects could not be explained by conventional density, shape index, or contact inhibition explanations. E-cadherin surfaces nearly doubled the length of the G0/G1 phase of the cell cycle, which we ultimately connected to the exclusion of matrix focal adhesions induced by the E-cadherin culture surface.

Mechanical control of cell proliferation patterns in growing tissues

Cell proliferation plays a crucial role in regulating tissue homeostasis and development. However, our understanding of how cell proliferation is controlled in densely packed tissues is limited. Here we develop a computational framework to predict the patterns of cell proliferation in growing tissues, connecting single-cell behaviors and cell-cell interactions to tissue-level growth. Our model incorporates probabilistic rules governing cell growth, division, and elimination, while also taking into account their feedback with tissue mechanics. In particular, cell growth is suppressed and apoptosis is enhanced in regions of high cell density. With these rules and model parameters calibrated using experimental data, we predict how tissue confinement influences cell size and proliferation dynamics, and how single-cell physical properties influence the spatiotemporal patterns of tissue growth. Our findings indicate that mechanical feedback between tissue confinement and cell growth leads to enhanced cell proliferation at tissue boundaries, whereas cell growth in the bulk is arrested. By tuning cellular elasticity and contact inhibition of proliferation we can regulate the emergent patterns of cell proliferation, ranging from uniform growth at low contact inhibition to localized growth at higher contact inhibition. Furthermore, mechanical state of the tissue governs the dynamics of tissue growth, with cellular parameters affecting tissue pressure playing a significant role in determining the overall growth rate. Our computational study thus underscores the impact of cell mechanical properties on the spatiotemporal patterns of cell proliferation in growing tissues.

Quantifying tissue growth, shape and collision via continuum models and Bayesian inference

Although tissues are usually studied in isolation, this situation rarely occurs in biology, as cells, tissues and organs coexist and interact across scales to determine both shape and function. Here, we take a quantitative approach combining data from recent experiments, mathematical modelling and Bayesian parameter inference, to describe the self-assembly of multiple epithelial sheets by growth and collision. We use two simple and well-studied continuum models, where cells move either randomly or following population pressure gradients. After suitable calibration, both models prove to be practically identifiable, and can reproduce the main features of single tissue expansions. However, our findings reveal that whenever tissue-tissue interactions become relevant, the random motion assumption can lead to unrealistic behaviour. Under this setting, a model accounting for population pressure from different cell populations is more appropriate and shows a better agreement with experimental measurements. Finally, we discuss how tissue shape and pressure affect multi-tissue collisions. Our work thus provides a systematic approach to quantify and predict complex tissue configurations with applications in the design of tissue composites and more generally in tissue engineering.

Collective rotational motion of freely expanding T84 epithelial cell colonies

Coordinated rotational motion is an intriguing, yet still elusive mode of collective cell migration, which is relevant in pathological and morphogenetic processes. Most of the studies on this topic have been carried out on epithelial cells plated on micropatterned substrates, where cell motion is confined in regions of well-defined shapes coated with extracellular matrix adhesive proteins. The driver of collective rotation in such conditions has not been clearly elucidated, although it has been speculated that spatial confinement can play an essential role in triggering cell rotation. Here, we study the growth of epithelial cell colonies freely expanding (i.e. with no physical constraints) on the surface of cell culture plates and focus on collective cell rotation in such conditions, a case which has received scarce attention in the literature. One of the main findings of our work is that coordinated cell rotation spontaneously occurs in cell clusters in the free growth regime, thus implying that cell confinement is not necessary to elicit collective rotation as previously suggested. The extent of collective rotation was size and shape dependent: a highly coordinated disc-like rotation was found in small cell clusters with a round shape, while collective rotation was suppressed in large irregular cell clusters generated by merging of different clusters in the course of their growth. The angular motion was persistent in the same direction, although clockwise and anticlockwise rotations were equally likely to occur among different cell clusters. Radial cell velocity was quite low as compared to the angular velocity, in agreement with the free expansion regime where cluster growth is essentially governed by cell proliferation. A clear difference in morphology was observed between cells at the periphery and the ones in the core of the clusters, the former being more elongated and spread out as compared to the latter. Overall, our results, to our knowledge, provide the first quantitative and systematic evidence that coordinated cell rotation does not require a spatial confinement and occurs spontaneously in freely expanding epithelial cell colonies, possibly as a mechanism for the system.

Determination of the nanoparticle- and cell-specific toxicological mechanisms in 3D liver spheroids using scRNAseq analysis

Engineered nanomaterials (ENMs) are commonly used in consumer products, allowing exposure to target organs such as the lung, liver, and skin that could lead to adverse health effects in humans. To better reflect on toxicological effects in liver cells, it is important to consider the contribution of hepatocyte morphology, function, and intercellular interactions in a dynamic 3D microenvironment. Herein, we used a 3D liver spheroid model containing hepatocyte and Kupffer cells (KCs) to study the effects of three different material compositions, namely vanadium pentoxide (V2O5), titanium dioxide (TiO2), or graphene oxide (GO). Additionally, we used single-cell RNA sequencing (scRNAseq) to determine the nanoparticle (NP) and cell-specific toxicological responses. A general finding was that hepatocytes exhibit more variation in gene expression and adaptation of signaling pathways than KCs. TNF-α production tied to the NF-κB pathway was a commonly affected pathway by all NPs while impacts on the metabolic function of hepatocytes were unique to V2O5. V2O5 NPs also showed the largest number of differentially expressed genes in both cell types, many of which are related to pro-inflammatory and apoptotic response pathways. There was also evidence of mitochondrial ROS generation and caspase-1 activation after GO and V2O5 treatment, in association with cytokine production. All considered, this study provides insight into the impact of nanoparticles on gene responses in key liver cell types, providing us with a scRNAseq platform that can be used for high-content screening of nanomaterial impact on the liver, for use in biosafety and biomedical applications.

Soft nano and microstructures for the photomodulation of cellular signaling and behavior

Photoresponsive soft materials are everywhere in the nature, from human's retina tissues to plants, and have been the inspiration for engineers in the development of modern biomedical materials. Light as an external stimulus is particularly attractive because it is relatively cheap, noninvasive to superficial biological tissues, can be delivered contactless and offers high spatiotemporal control. In the biomedical field, soft materials that respond to long wavelength or that incorporate a photon upconversion mechanism are desired to overcome the limited UV-visible light penetration into biological tissues. Upon light exposure, photosensitive soft materials respond through mechanisms of isomerization, crosslinking or cleavage, hyperthermia, photoreactions, electrical current generation, among others. In this review, we discuss the most recent applications of photosensitive soft materials in the modulation of cellular behavior, for tissue engineering and regenerative medicine, in drug delivery and for phototherapies.

Promotion of Melanoma Cell Proliferation by Cyclic Straining through Regulatory Morphogenesis

The genotype and phenotype of acral melanoma are obviously different from UV-radiation-induced melanoma. Based on the clinical data, mechanical stimulation is believed to be a potential cause of acral melanoma. In this case, it is desirable to clarify the role of mechanical stimulation in the progression of acral melanoma. However, the pathological process of cyclic straining that stimulates acral melanoma is still unclear. In this study, the influence of cyclic straining on melanoma cell proliferation was analyzed by using a specifically designed cell culture system. In the results, cyclic straining could promote melanoma cell proliferation but was inefficient after the disruption of cytoskeleton organization. Therefore, the mechanotransduction mechanism of promoted proliferation was explored. Both myosin and actin polymerization were demonstrated to be related to cyclic straining and further influenced the morphogenesis of melanoma cells. Additionally, the activation of mechanosensing transcription factor YAP was related to regulatory morphogenesis. Furthermore, expression levels of melanoma-involved genes were regulated by cyclic straining and, finally, accelerated DNA synthesis. The results of this study will provide supplementary information for the understanding of acral melanoma.

Self-assembly of tessellated tissue sheets by expansion and collision

Tissues do not exist in isolation—they interact with other tissues within and across organs. While cell-cell interactions have been intensely investigated, less is known about tissue-tissue interactions. Here, we studied collisions between monolayer tissues with different geometries, cell densities, and cell types. First, we determine rules for tissue shape changes during binary collisions and describe complex cell migration at tri-tissue boundaries. Next, we propose that genetically identical tissues displace each other based on pressure gradients, which are directly linked to gradients in cell density. We present a physical model of tissue interactions that allows us to estimate the bulk modulus of the tissues from collision dynamics. Finally, we introduce TissEllate, a design tool for self-assembling complex tessellations from arrays of many tissues, and we use cell sheet engineering techniques to transfer these composite tissues like cellular films. Overall, our work provides insight into the mechanics of tissue collisions, harnessing them to engineer tissue composites as designable living materials.

Tissue boundaries in our body separate organs and enable healing, but boundary mechanics are not well known. Here, the authors define mechanical rules for colliding cell monolayers and use these rules to make complex, predictable tessellations.

Learning the rules of collective cell migration using deep attention networks

Collective, coordinated cellular motions underpin key processes in all multicellular organisms, yet it has been difficult to simultaneously express the ‘rules’ behind these motions in clear, interpretable forms that effectively capture high-dimensional cell-cell interaction dynamics in a manner that is intuitive to the researcher. Here we apply deep attention networks to analyze several canonical living tissues systems and present the underlying collective migration rules for each tissue type using only cell migration trajectory data. We use these networks to learn the behaviors of key tissue types with distinct collective behaviors—epithelial, endothelial, and metastatic breast cancer cells—and show how the results complement traditional biophysical approaches. In particular, we present attention maps indicating the relative influence of neighboring cells to the learned turning decisions of a ‘focal cell’–the primary cell of interest in a collective setting. Colloquially, we refer to this learned relative influence as ‘attention’, as it serves as a proxy for the physical parameters modifying the focal cell’s future motion as a function of each neighbor cell. These attention networks reveal distinct patterns of influence and attention unique to each model tissue. Endothelial cells exhibit tightly focused attention on their immediate forward-most neighbors, while cells in more expansile epithelial tissues are more broadly influenced by neighbors in a relatively large forward sector. Attention maps of ensembles of more mesenchymal, metastatic cells reveal completely symmetric attention patterns, indicating the lack of any particular coordination or direction of interest. Moreover, we show how attention networks are capable of detecting and learning how these rules change based on biophysical context, such as location within the tissue and cellular crowding. That these results require only cellular trajectories and no modeling assumptions highlights the potential of attention networks for providing further biological insights into complex cellular systems.

Collective behaviors are crucial to the function of multicellular life, with large-scale, coordinated cell migration enabling processes spanning organ formation to coordinated skin healing. However, we lack effective tools to discover and cleanly express collective rules at the level of an individual cell. Here, we employ a carefully structured neural network to extract collective information directly from cell trajectory data. The network is trained on data from various systems, including canonical collective cell systems (HUVEC and MDCK cells) which display visually distinct forms of collective motion, and metastatic cancer cells (MDA-MB-231) which are highly uncoordinated. Using these trained networks, we can produce attention maps for each system, which indicate how a cell within a tissue takes in information from its surrounding neighbors, as a function of weights assigned to those neighbors. Thus for a cell type in which cells tend to follow the path of the cell in front, the attention maps will display high weights for cells spatially forward of the focal cell. We present results in terms of additional metrics, such as accuracy plots and number of interacting cells, and encourage future development of improved metrics.

Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics

The ability to program collective cell migration can allow us to control critical multicellular processes in development, regenerative medicine, and invasive disease. However, while various technologies exist to make individual cells migrate, translating these tools to control myriad, collectively interacting cells within a single tissue poses many challenges. For instance, do cells within the same tissue interpret a global migration 'command' differently based on where they are in the tissue? Similarly, since no stimulus is permanent, what are the long-term effects of transient commands on collective cell dynamics? We investigate these questions by bioelectrically programming large epithelial tissues to globally migrate 'rightward' via electrotaxis. Tissues clearly developed distinct rear, middle, side, and front responses to a single global migration stimulus. Furthermore, at no point poststimulation did tissues return to their prestimulation behavior, instead equilibrating to a 3rd, new migratory state. These unique dynamics suggested that programmed migration resets tissue mechanical state, which was confirmed by transient chemical disruption of cell-cell junctions, analysis of strain wave propagation patterns, and quantification of cellular crowd dynamics. Overall, this work demonstrates how externally driving the collective migration of a tissue can reprogram baseline cell-cell interactions and collective dynamics, even well beyond the end of the global migratory cue, and emphasizes the importance of considering the supracellular context of tissues and other collectives when attempting to program crowd behaviors.

Avalanches during epithelial tissue growth; Uniform Growth and a drosophila eye disc model

Epithelial tissues constitute an exotic type of active matter with non-linear properties reminiscent of amorphous materials. In the context of a proliferating epithelium, modeled by the quasistatic vertex model, we identify novel discrete tissue scale rearrangements, i.e. cellular rearrangement avalanches, which are a form of collective cell movement. During the avalanches, the vast majority of cells retain their neighbors, and the resulting cellular trajectories are radial in the periphery, a vortex in the core. After the onset of these avalanches, the epithelial area grows discontinuously. The avalanches are found to be stochastic, and their strength is correlated with the density of cells in the tissue. Overall, avalanches redistribute accumulated local spatial pressure along the tissue. Furthermore, the distribution of avalanche magnitudes is found to obey a power law, with an exponent consistent with sheer induced avalanches in amorphous materials. To understand the role of avalanches in organ development, we simulate epithelial growth of the Drosophila eye disc during the third instar using a computational model, which includes both chemical and mechanistic signaling. During the third instar, the morphogenetic furrow (MF), a ~10 cell wide wave of apical area constriction propagates through the epithelium. These simulations are used to understand the details of the growth process, the effect of the MF on the growth dynamics on the tissue scale, and to make predictions for experimental observations. The avalanches are found to depend on the strength of the apical constriction of cells in the MF, with a stronger apical constriction leading to less frequent and more pronounced avalanches. The results herein highlight the dependence of simulated tissue growth dynamics on relaxation timescales, and serve as a guide for in vitro experiments.

An Easy-to-Fabricate Cell Stretcher Reveals Density-Dependent Mechanical Regulation of Collective Cell Movements in Epithelia

Introduction

Mechanical forces regulate many facets of cell and tissue biology. Studying the effects of forces on cells requires real-time observations of single- and multi-cell dynamics in tissue models during controlled external mechanical input. Many of the existing devices used to conduct these studies are costly and complicated to fabricate, which reduces the availability of these devices to many laboratories.

Methods

We show how to fabricate a simple, low-cost, uniaxial stretching device, with readily available materials and instruments that is compatible with high-resolution time-lapse microscopy of adherent cell monolayers. In addition, we show how to construct a pressure controller that induces a repeatable degree of stretch in monolayers, as well as a custom MATLAB code to quantify individual cell strains.

Results

As an application note using this device, we show that uniaxial stretch slows down cellular movements in a mammalian epithelial monolayer in a cell density-dependent manner. We demonstrate that the effect on cell movement involves the relocalization of myosin downstream of Rho-associated protein kinase (ROCK).

Conclusions

This mechanical device provides a platform for broader involvement of engineers and biologists in this important area of cell and tissue biology. We used this device to demonstrate the mechanical regulation of collective cell movements in epithelia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-021-00689-6.

Come together: On-chip bioelectric wound closure

There is a growing interest in bioelectric wound treatment and electrotaxis, the process by which cells detect an electric field and orient their migration along its direction, has emerged as a potential cornerstone of the endogenous wound healing response. Despite recognition of the importance of electrotaxis in wound healing, no experimental demonstration to date has shown that the actual closing of a wound can be accelerated solely by the electrotaxis response itself, and in vivo systems are too complex to resolve cell migration from other healing stages such as proliferation and inflammation. This uncertainty has led to a lack of standardization between stimulation methods, model systems, and electrode technology required for device development. In this paper, we present a 'healing-on-chip' approach that is a standardized, low-cost, model for investigating electrically accelerated wound healing. Our device provides a biomimetic convergent field geometry that more closely resembles actual wound fields. We validate this device by using electrical stimulation to close a 1.5 mm gap between two large (30 mm2) layers of primary skin keratinocyte to completely heal the gap twice as quickly as in an unstimulated tissue. This demonstration proves that convergent electrotaxis is both possible and can accelerate healing and offers an accessible 'healing-on-a-chip' platform to explore future bioelectric interfaces.

Fingering instability in spreading epithelial monolayers: roles of cell polarisation, substrate friction and contractile stresses

Collective cell migration plays a crucial role in many developmental processes that underlie morphogenesis, wound healing, or cancer progression. In such coordinated behaviours, cells are organised in coherent structures and actively migrate to serve different biological purposes. In some contexts, namely during epithelial wound healing, it is well known that a migrating free-edge monolayer develops finger-like instabilities, yet the onset is still under debate. Here, by means of theory and numerical simulations, we shed light on the main mechanisms driving the instability process, analysing the linear and nonlinear dynamics of a continuum compressible polar fluid. In particular, we assess the role of cell polarisation, substrate friction, and contractile stresses. Linear theory shows that it is crucial to analyse the perturbation transient dynamics, since we unravel a plethora of crossovers between different exponential growth rates during the linear regime. Numerical simulations suggest that cell-substrate friction could be the mechanism responsible for the formation of complex finger-like structures at the edge, since it triggers secondary fingering instabilities and tip-splitting phenomena. Finally, we obtain a critical contractile stress that depends on cell-substrate friction and the initial-to-nematic length ratio, characterising an active wetting-dewetting transition. In the dewetting scenario, the monolayer retracts and becomes stable without developing finger-like structures.

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.

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.

Size-dependent patterns of cell proliferation and migration in freely-expanding epithelia

The coordination of cell proliferation and migration in growing tissues is crucial in development and regeneration but remains poorly understood. Here, we find that, while expanding with an edge speed independent of initial conditions, millimeter-scale epithelial monolayers exhibit internal patterns of proliferation and migration that depend not on the current but on the initial tissue size, indicating memory effects. Specifically, the core of large tissues becomes very dense, almost quiescent, and ceases cell-cycle progression. In contrast, initially-smaller tissues develop a local minimum of cell density and a tissue-spanning vortex. To explain vortex formation, we propose an active polar fluid model with a feedback between cell polarization and tissue flow. Taken together, our findings suggest that expanding epithelia decouple their internal and edge regions, which enables robust expansion dynamics despite the presence of size- and history-dependent patterns in the tissue interior.