Collective cell migration in development

Confinement, jamming, and adhesion in cancer cells dissociating from a collectively invading strand

When cells in a primary tumor work together to invade into nearby tissue, this can lead to cell dissociations-cancer cells breaking off from the invading front-leading to metastasis. What controls the dissociation of cells, and whether they break off singly or in small groups? Can this be determined by cell-cell adhesion or chemotactic cues given to cells? We develop a physical model for this question, based on experiments that mimic aspects of cancer cell invasion using microfluidic devices with microchannels of different widths. Experimentally, most dissociation events ("ruptures") involve single cells breaking off, but we observe some ruptures of large groups ( ∼ 20 cells) in wider channels. The rupture probability is nearly independent of channel width. We recapitulate the experimental results with a phase field cell motility model by introducing three different cell states (follower, guided, and high-motility metabolically active leader cells) based on their spatial position. These leader cells may explain why single-cell rupture is the universal most probable outcome. Our simulation results show that cell-channel adhesion is necessary for cells in narrow channels to invade, and strong cell-cell adhesion leads to fewer but larger ruptures. Chemotaxis also influences the rupture behavior: Strong chemotaxis strength leads to larger and faster ruptures. Finally, we study the relationship between biological jamming transitions and cell dissociations. Our results suggest unjamming is necessary but not sufficient to create ruptures.

Maximum likelihood phylogeographic inference of cell motility and cell division from spatial lineage tracing data

MOTIVATION

Recently developed spatial lineage tracing technologies induce somatic mutations at specific genomic loci in a population of growing cells and then measure these mutations in the sampled cells along with the physical locations of the cells. These technologies enable high-throughput studies of developmental processes over space and time. However, these applications rely on accurate reconstruction of a spatial cell lineage tree describing both past cell divisions and cell locations. Spatial lineage trees are related to phylogeographic models that have been well-studied in the phylogenetics literature. We demonstrate that standard phylogeographic models based on Brownian motion are inadequate to describe the spatial symmetric displacement (SD) of cells during cell division.

RESULTS

We introduce a new model-the SD model for cell motility that includes symmetric displacements of daughter cells from the parental cell followed by independent diffusion of daughter cells. We show that this model more accurately describes the locations of cells in a real spatial lineage tracing of mouse embryonic stem cells. Combining the spatial SD model with an evolutionary model of DNA mutations, we obtain a phylogeographic model for spatial lineage tracing. Using this model, we devise a maximum likelihood framework-MOLLUSC (Maximum Likelihood Estimation Of Lineage and Location Using Single-Cell Spatial Lineage tracing Data)-to co-estimate time-resolved branch lengths, spatial diffusion rate, and mutation rate. On both simulated and real data, we show that MOLLUSC accurately estimates all parameters. In contrast, the Brownian motion model overestimates spatial diffusion rate in all test cases. In addition, the inclusion of spatial information improves accuracy of branch length estimation compared to sequence data alone. On real data, we show that spatial information has more signal than sequence data for branch length estimation, suggesting augmenting lineage tracing technologies with spatial information is useful to overcome the limitations of genome-editing in developmental systems.

AVAILABILITY AND IMPLEMENTATION

The python implementation of MOLLUSC is available at https://github.com/raphael-group/MOLLUSC.

Chemotactic Interactions Drive Migration of Membraneless Active Droplets

In nature, chemotactic interactions are ubiquitous and play a critical role in driving the collective behavior of living organisms. Reproducing these interactions in vitro is still a paramount challenge due to the complexity of mimicking and controlling cellular features, such as tangled metabolic networks, cytosolic macromolecular crowding, and cellular migration, on a microorganism size scale. Here, we generate enzymatically active cell-sized droplets able to move freely, and by following a chemical gradient, able to interact with the surrounding droplets in a collective manner. The enzyme within the droplets generates a pH gradient that extends outside the edge of the droplets. We discovered that the external pH gradient triggers droplet migration and controls its directionality, which is selectively toward the neighboring droplets. Hence, by changing the enzyme activity inside the droplet, we tuned the droplet migration speed. Furthermore, we showed that these cellular-like features can facilitate the reconstitution of a simple and linear protometabolic pathway and increase the final reaction product generation. Our work suggests that simple and stable membraneless droplets can reproduce complex biological phenomena, opening new perspectives as bioinspired materials and synthetic biology tools.

Migrasome, a migration-dependent organelle

Migrasomes are organelles produced by migrating cells that form on retraction fibers and are released during cell migration. Migrasomes are involved in physiological and pathological processes such as intercellular communication, cell homeostasis maintenance, signal transduction, disease occurrence and development, and cancer metastasis. In addition, methods and techniques for studying migrasomes are constantly evolving. Here, we review the discovery, formation process, regulation, and known functions of migrasomes, summarize the commonly used specific markers of migrasomes, and the methods for observing migrasomes. Meanwhile, this review also discusses the potential applications of migrasomes in physiological processes, disease diagnosis, treatment, and prognosis, and looks forward to their wider application in biomedicine. In addition, the study of migrasomes will also reveal a new perspective on the mechanism of intercellular communication and promote the further development of life science.

Prevented Cell Clusters' Migration Via Microdot Biomaterials for Inhibiting Scar Adhesion

Cluster-like collective cell migration of fibroblasts is one of the main factors of adhesion in injured tissues. In this research, a microdot biomaterial system is constructed using α-helical polypeptide nanoparticles and anti-inflammatory micelles, which are prepared by ring-opening polymerization of α-amino acids-N-carboxylic anhydrides (NCAs) and lactide, respectively. The microdot biomaterial system slowly releases functionalized polypeptides targeting mitochondria and promoting the influx of extracellular calcium ions under the inflammatory environment, thus inhibiting the expression of N-cadherin mediating cell-cell interaction, and promoting apoptosis of cluster fibroblasts, synergistically inhibiting the migration of fibroblast clusters at the site of tendon injury. Meanwhile, the anti-inflammatory micelles are celecoxib (Cex) solubilized by PEG/polyester, which can improve the inflammatory microenvironment at the injury site for a long time. In vitro, the microdot biomaterial system can effectively inhibit the migration of the cluster fibroblasts by inhibiting the expression of N-cadherin between cell-cell and promoting apoptosis. In vivo, the microdot biomaterial system can promote apoptosis while achieving long-acting anti-inflammation effects, and reduce the expression of vimentin and α-smooth muscle actin (α-SMA) in fibroblasts. Thus, this microdot biomaterial system provides new ideas for the prevention and treatment of tendon adhesion by inhibiting the cluster migration of fibroblasts.

Low-Concentration Gelatin Methacryloyl Hydrogel with Tunable 3D Extrusion Printability and Cytocompatibility: Exploring Quantitative Process Science and Biophysical Properties

Three-dimensional (3D) bioprinting of hydrogels with a wide spectrum of compositions has been widely investigated. Despite such efforts, a comprehensive understanding of the correlation among the process science, buildability, and biophysical properties of the hydrogels for a targeted clinical application has not been developed in the scientific community. In particular, the quantitative analysis across the entire developmental path for 3D extrusion bioprinting of such scaffolds is not widely reported. In the present work, we addressed this gap by using widely investigated biomaterials, such as gelatin methacryloyl (GelMA), as a model system. Using extensive experiments and quantitative analysis, we analyzed how the individual components of methacrylated carboxymethyl cellulose (mCMC), needle-shaped nanohydroxyapatite (nHAp), and poly(ethylene glycol)diacrylate (PEGDA) with GelMA as baseline matrix of the multifunctional bioink can influence the biophysical properties, printability, and cellular functionality. The complex interplay among the biomaterial ink formulations, viscoelastic properties, and printability toward the large structure buildability (structurally stable cube scaffolds with 15 mm edge) has been explored. Intriguingly, the incorporation of PEGDA into the GelMA/mCMC matrix offered improved compressive modulus (∼40-fold), reduced swelling ratio (∼2-fold), and degradation rates (∼30-fold) compared to pristine GelMA. The correlation among microstructural pore architecture, biophysical properties, and cytocompatibility is also established for the biomaterial inks. These photopolymerizable bio(material)inks served as the platform for the growth and development of bone and cartilage matrix when human mesenchymal stem cells (hMSCs) are either seeded on two-dimensional (2D) substrates or encapsulated on 3D scaffolds. Taken together, this present study unequivocally establishes a significant step forward in the development of a broad spectrum of shape-fidelity compliant bioink for the 3D bioprinting of multifunctional scaffolds and emphasizes the need for invoking more quantitative analysis in establishing process-microstructure-property correlation.

PIEZO1 regulates leader cell formation and cellular coordination during collective keratinocyte migration

The collective migration of keratinocytes during wound healing requires both the generation and transmission of mechanical forces for individual cellular locomotion and the coordination of movement across cells. Leader cells along the wound edge transmit mechanical and biochemical cues to ensuing follower cells, ensuring their coordinated direction of migration across multiple cells. Despite the observed importance of mechanical cues in leader cell formation and in controlling coordinated directionality of cell migration, the underlying biophysical mechanisms remain elusive. The mechanically-activated ion channel PIEZO1 was recently identified to play an inhibitory role during the reepithelialization of wounds. Here, through an integrative experimental and mathematical modeling approach, we elucidate PIEZO1's contributions to collective migration. Time-lapse microscopy reveals that PIEZO1 activity inhibits leader cell formation at the wound edge. To probe the relationship between PIEZO1 activity, leader cell formation and inhibition of reepithelialization, we developed an integrative 2D continuum model of wound closure that links observations at the single cell and collective cell migration scales. Through numerical simulations and subsequent experimental validation, we found that coordinated directionality plays a key role during wound closure and is inhibited by upregulated PIEZO1 activity. We propose that PIEZO1-mediated retraction suppresses leader cell formation which inhibits coordinated directionality between cells during collective migration.

Basak U, Mohiuddin M, Toda M, Komatsuzaki T. Inferring the roles of individuals in collective systems using information-theoretic measures of influence

In collective systems, influence of individuals can permeate an entire group through indirect interactionscom-plicating any scheme to understand individual roles from observations. A typical approach to understand an individuals influence on another involves consideration of confounding factors, for example, by conditioning on other individuals outside of the pair. This becomes unfeasible in many cases as the number of individuals increases. In this article, we review some of the unforeseen problems that arise in understanding individual influence in a collective such as single cells, as well as some of the recent works which address these issues using tools from information theory.

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.

Machine learning topological defects in confluent tissues

Active nematics is an emerging paradigm for characterizing biological systems. One aspect of particularly intense focus is the role active nematic defects play in these systems, as they have been found to mediate a growing number of biological processes. Accurately detecting and classifying these defects in biological systems is, therefore, of vital importance to improving our understanding of such processes. While robust methods for defect detection exist for systems of elongated constituents, other systems, such as epithelial layers, are not well suited to such methods. Here, we address this problem by developing a convolutional neural network to detect and classify nematic defects in confluent cell layers. Crucially, our method is readily implementable on experimental images of cell layers and is specifically designed to be suitable for cells that are not rod shaped, which we demonstrate by detecting defects on experimental data using the trained model. We show that our machine learning model outperforms current defect detection techniques and that this manifests itself in our method as requiring less data to accurately capture defect properties. This could drastically improve the accuracy of experimental data interpretation while also reducing costs, advancing the study of nematic defects in biological systems.

Geometry-Sensitive Protrusion Growth Directs Confined Cell Migration

The migratory dynamics of cells can be influenced by the complex microenvironment through which they move. It remains unclear how the motility machinery of confined cells responds and adapts to their microenvironment. Here, we propose a biophysical mechanism for a geometry-dependent coupling between cellular protrusions and the nucleus that leads to directed migration. We apply our model to geometry-guided cell migration to obtain insights into the origin of directed migration on asymmetric adhesive micropatterns and the polarization enhancement of cells observed under strong confinement. Remarkably, for cells that can choose between channels of different size, our model predicts an intricate dependence for cellular decision making as a function of the two channel widths, which we confirm experimentally.

Cell nucleus elastography with the adjoint-based inverse solver

BACKGROUND AND OBJECTIVES

The mechanics of the nucleus depends on cellular structures and architecture, and impact a number of diseases. Nuclear mechanics is yet rather complex due to heterogeneous distribution of dense heterochromatin and loose euchromatin domains, giving rise to spatially variable stiffness properties.

METHODS

In this study, we propose to use the adjoint-based inverse solver to identify for the first time the nonhomogeneous elastic property distribution of the nucleus. Inputs of the inverse solver are deformation fields measured with microscopic imaging in contracting cardiomyocytes.

RESULTS

The feasibility of the proposed method is first demonstrated using simulated data. Results indicate accurate identification of the assumed heterochromatin region, with a maximum relative error of less than 5%. We also investigate the influence of unknown Poisson's ratio on the reconstruction and find that variations of the Poisson's ratio in the range [0.3-0.5] result in uncertainties of less than 15% in the identified stiffness. Finally, we apply the inverse solver on actual deformation fields acquired within the nuclei of two cardiomyocytes. The obtained results are in good agreement with the density maps obtained from microscopy images.

CONCLUSIONS

Overall, the proposed approach shows great potential for nuclear elastography, with promising value for emerging fields of mechanobiology and mechanogenetics.

Studying Cell Migration (Random and Wound Healing) Parameters with Imaging and MATLAB Analysis

Cell migration is an essential biological process for organisms, in processes including embryonic development, immune response, and cancer metastasis. To elucidate the regulatory machinery of this vital process, methods that mimic in vivo migration, including in vitro wound healing assay and random migration assay, are widely used for cell behavior investigation. However, several concerns are raised with traditional cell migration experiment analysis. First, a manually scratched wound often presents irregular edges, causing the speed analysis difficult. Second, only the migration speed of leading cells is considered in the wound healing assay. Here, we provide a reliable analysis method to trace each cell in the time-lapse images, eliminating the concern about wound shape and creating a more comprehensive understanding of cell migration-not only of collective migration speed but also single-cell directionality and coordination between cells.

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.

Mobility gene expression differences among wild-type, Mmp20 null and Mmp20 over-expresser mice plus visualization of 3D mouse ameloblast directional movement

Enamel forming ameloblasts move away from the dentino-enamel junction and also move relative to each other to establish enamel shape during the secretory stage of enamel development. Matrix metalloproteinase-20 (MMP20) is a tooth specific proteinase essential for proper enamel formation. We previously reported that MMP20 cleaves cadherins and may regulate ameloblast movement. Here, we used an Amelx promoter driven tdTomato reporter to label mouse ameloblasts. With these transgenic mice, we assessed ameloblast mobility group dynamics and gene expression. Three-dimensional imaging of mouse ameloblasts were observed in hemi-mandibles by using a tissue clearing technique. The three-dimensional ameloblast layer in Tg(Amelx-Mmp20) mice that overexpress MMP20 was uneven and the ameloblasts migrated away from this layer. Mouse ameloblast movement toward incisal tips was monitored by ex vivo time-lapse imaging. Gene expression related to cell migration and adhesion was analyzed in ameloblasts from wild-type mice, Mmp20-/- mice with no functional MMP20 and from Tg(Amelx-Mmp20) overexpressing mice. Gene expression was altered in Mmp20-/- and Tg(Amelx-Mmp20) mice compared to wild type. Among the genes assessed, those encoding laminins and a gap junction protein were upregulated in Mmp20-/- mice. New techniques and findings described in this study may lead to an improved understanding of ameloblast movement during enamel formation.

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

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

Phase-separation facilitated one-step fabrication of multiscale heterogeneous two-aqueous-phase gel

Engineering heterogeneous hydrogels with distinct phases at various lengths, which resemble biological tissues with high complexity, remains challenging by existing fabricating techniques that require complicated procedures and are often only applicable at bulk scales. Here, inspired by ubiquitous phase separation phenomena in biology, we present a one-step fabrication method based on aqueous phase separation to construct two-aqueous-phase gels that comprise multiple phases with distinct physicochemical properties. The gels fabricated by this approach exhibit enhanced interfacial mechanics compared with their counterparts obtained from conventional layer-by-layer methods. Moreover, two-aqueous-phase gels with programmable structures and tunable physicochemical properties can be conveniently constructed by adjusting the polymer constituents, gelation conditions, and combining different fabrication techniques, such as 3D-printing. The versatility of our approach is demonstrated by mimicking the key features of several biological architectures at different lengths: macroscale muscle-tendon connections; mesoscale cell patterning; microscale molecular compartmentalization. The present work advances the fabrication approach for designing heterogeneous multifunctional materials for various technological and biomedical applications.

The coherent motions of thermal active Brownian particles

Active matter exhibits many intriguing non-equilibrium characteristics, for instance, without any attractive and aligned interactions, the active Brownian particle (ABP) system undergoing motility-induced phase separation forms a high-density phase with both structural ordering and dynamical coherence. Recently, the velocity correlation among the particles in this high-density phase was found in non-thermal overdamped ABP systems. However, it seemed to disappear if thermal noises were included, bringing some confusion about the generality of the consistency between structures and dynamics in ABPs. Here, we demonstrate that the thermal noises imposing a large random term on the instantaneous velocity of ABPs hinder the observation of the inherent correlation in the motions of ABPs. By averaging the instantaneous velocity (or equivalently, calculating the displacement), we show that the inherent motions of thermal-fluctuated ABPs are highly coherent. Whether there is thermal noise or not, the inherent collective motions of ABPs do exist, and the collective motion domains are consistent spatially with the ordered clusters of ABPs in the high-density phase. At the boundary of these ordered clusters, the active forces of the particles tend to point inward and compress to sustain these clusters, thus the particles in the clusters move coherently to form some vortex-like or aligned velocity domains.

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure.

E-cadherin-dependent coordinated epithelial rotation on a two-dimensional discoidal pattern

In vivo, cells collectively migrate in a variety of developmental and pathological contexts. Coordinated epithelial rotation represents a unique type of collective cell migrations, which has been modeled in vitro under spatially confined conditions. Although it is known that the coordinated rotation depends on intercellular interactions, the contribution of E-cadherin, a major cell-cell adhesion molecule, has not been directly addressed on two-dimensional (2D) confined substrates. Here, using well-controlled fibronectin-coated surfaces, we tracked and compared the migratory behaviors of MDCK cells expressing or lacking E-cadherin. We observed that wild-type MDCK II cells exhibited persistent and coordinated rotations on discoidal patterns, while E-cadherin knockout cells migrated in a less coordinated manner without large-scale rotation. Our comparison of the collective dynamics between these two cell types revealed a series of changes in migratory behavior caused by the loss of E-cadherin, including a decreased global migration speed, less regularity in quantified coordination, and increased average density of topological defects. Taken together, these data demonstrate that spontaneous initiation of collective epithelial rotations depends on E-cadherin under 2D discoidal confinements.

"In medio stat virtus": Insights into hybrid E/M phenotype attitudes

Epithelial-mesenchymal plasticity (EMP) refers to the ability of cells to dynamically interconvert between epithelial (E) and mesenchymal (M) phenotypes, thus generating an array of hybrid E/M intermediates with mixed E and M features. Recent findings have demonstrated how these hybrid E/M rather than fully M cells play key roles in most of physiological and pathological processes involving EMT. To this regard, the onset of hybrid E/M state coincides with the highest stemness gene expression and is involved in differentiation of either normal and cancer stem cells. Moreover, hybrid E/M cells are responsible for wound healing and create a favorable immunosuppressive environment for tissue regeneration. Nevertheless, hybrid state is responsible of metastatic process and of the increasing of survival, apoptosis and therapy resistance in cancer cells. The present review aims to describe the main features and the emerging concepts regulating EMP and the formation of E/M hybrid intermediates by describing differences and similarities between cancer and normal hybrid stem cells. In particular, the comprehension of hybrid E/M cells biology will surely advance our understanding of their features and how they could be exploited to improve tissue regeneration and repair.

ChemChaste: Simulating spatially inhomogeneous biochemical reaction-diffusion systems for modeling cell-environment feedbacks

BACKGROUND

Spatial organization plays an important role in the function of many biological systems, from cell fate specification in animal development to multistep metabolic conversions in microbial communities. The study of such systems benefits from the use of spatially explicit computational models that combine a discrete description of cells with a continuum description of one or more chemicals diffusing within a surrounding bulk medium. These models allow the in silico testing and refinement of mechanistic hypotheses. However, most existing models of this type do not account for concurrent bulk and intracellular biochemical reactions and their possible coupling.

CONCLUSIONS

Here, we describe ChemChaste, an extension for the open-source C++ computational biology library Chaste. ChemChaste enables the spatial simulation of both multicellular and bulk biochemistry by expanding on Chaste's existing capabilities. In particular, ChemChaste enables (i) simulation of an arbitrary number of spatially diffusing chemicals, (ii) spatially heterogeneous chemical diffusion coefficients, and (iii) inclusion of both bulk and intracellular biochemical reactions and their coupling. ChemChaste also introduces a file-based interface that allows users to define the parameters relating to these functional features without the need to interact directly with Chaste's core C++ code. We describe ChemChaste and demonstrate its functionality using a selection of chemical and biochemical exemplars, with a focus on demonstrating increased ability in modeling bulk chemical reactions and their coupling with intracellular reactions.

AVAILABILITY AND IMPLEMENTATION

ChemChaste version 1.0 is a free, open-source C++ library, available via GitHub at https://github.com/OSS-Lab/ChemChaste under the BSD license, on the Zenodo archive at zendodo doi, as well as on BioTools (biotools:chemchaste) and SciCrunch (RRID:SCR022208) databases.

A machine learning based model accurately predicts cellular response to electric fields in multiple cell types

Many cell types migrate in response to naturally generated electric fields. Furthermore, it has been suggested that the external application of an electric field may be used to intervene in and optimize natural processes such as wound healing. Precise cell guidance suitable for such optimization may rely on predictive models of cell migration, which do not generalize. Here, we present a machine learning model that can forecast directedness of cell migration given a timeseries of previous directedness and electric field values. This model is trained using time series galvanotaxis data of mammalian cranial neural crest cells obtained through time-lapse microscopy of cells cultured at 37 °C in a galvanotaxis chamber at ambient pressure. Next, we show that our modeling approach can be used for a variety of cell types and experimental conditions with very limited training data using transfer learning methods. We adapt the model to predict cell behavior for keratocytes (room temperature, ~ 18–20 °C) and keratinocytes (37 °C) under similar experimental conditions with a small dataset (~ 2–5 cells). Finally, this model can be used to perform in silico studies by simulating cell migration lines under time-varying and unseen electric fields. We demonstrate this by simulating feedback control on cell migration using a proportional–integral–derivative (PID) controller. This data-driven approach provides predictive models of cell migration that may be suitable for designing electric field based cellular control mechanisms for applications in precision medicine such as wound healing.

Receptor, Signal, Nucleus, Action: Signals That Pass through Akt on the Road to Head and Neck Cancer Cell Migration

This review aims to provide evidence for the role of the tumour microenvironment in cancer progression, including invasion and metastasis. The tumour microenvironment is complex and consists of tumour cells and stromal-derived cells, in addition to a modified extracellular matrix. The cellular components synthesise growth factors such as EGF, TGFα and β, VEGF, and NGF, which have been shown to initiate paracrine signalling in head and neck cancer cells by binding to cell surface receptors. One example is the phosphorylation, and hence activation, of the signalling protein Akt, which can ultimately induce oral cancer cell migration in vitro. Blocking of Akt activation by an inhibitor, MK2206, leads to a significant decrease, in vitro, of cancer-derived cell migration, visualised in both wound healing and scatter assays. Signalling pathways have therefore been popular targets for the design of chemotherapeutic agents, but drug resistance has been observed and is related to direct tumour-tumour cell communication, the tumour-extracellular matrix interface, and tumour-stromal cell interactions. Translation of this knowledge to patient care is reliant upon a comprehensive understanding of the complex relationships present in the tumour microenvironment and could ultimately lead to the design of efficacious treatment regimens such as targeted therapy or novel therapeutic combinations.

Cellular protrusions in 3D: Orchestrating early mouse embryogenesis

Cellular protrusions generated by the actin cytoskeleton are central to the process of building the body of the embryo. Problems with cellular protrusions underlie human diseases and syndromes, including implantation defects and pregnancy loss, congenital birth defects, and cancer. Cells use protrusive activity together with actin-myosin contractility to create an ordered body shape of the embryo. Here, I review how actin-rich protrusions are used by two major morphological cell types, epithelial and mesenchymal cells, during collective cell migration to sculpt the mouse embryo body. Pre-gastrulation epithelial collective migration of the anterior visceral endoderm is essential for establishing the anterior-posterior body axis. Gastrulation mesenchymal collective migration of the mesoderm wings is crucial for body elongation, and somite and heart formation. Analysis of mouse mutants with disrupted cellular protrusions revealed the key role of protrusions in embryonic morphogenesis and embryo survival. Recent technical approaches have allowed examination of the mechanisms that control cell and tissue movements in vivo in the complex 3D microenvironment of living mouse embryos. Advancing our understanding of protrusion-driven morphogenesis should provide novel insights into human developmental disorders and cancer metastasis.

Accelerating Cell Migration along Radially Aligned Nanofibers through the Addition of Electrosprayed Nanoparticles in a Radial Density Gradient

Scaffolds capable of promoting cell migration from the periphery towards the center along the radial direction hold promises for tissue regeneration. Here we report a simple and general method based on masked electrospray for the fabrication of such scaffolds by depositing collagen nanoparticles on radially-aligned nanofibers in a radial density gradient. Placed between the metallic needle and the collector, an aperture with tunable opening sizes serves as the mask. By increasing the size of the opening at a fixed speed, the electrosprayed particles take a radial density gradient that decreases from the center to the periphery. When deposited on a glass slide, the radial density gradient of collagen nanoparticles promotes the migration of fibroblasts from the periphery towards the center. By replacing the glass slide with a scaffold comprised of radially-aligned nanofibers, a synergetic effect arises to further accelerate cell migration along the radial direction. The synergistic effect can be attributed to a unique combination of the topographic cue arising from the aligned nanofibers and the haptotactic cue enabled by the graded nanoparticles. This work demonstrates a method to maximize cell migration from the periphery towards the center through a combination of topographic and haptotactic cues.

Brownian motion in a growing population of ballistic particles

We investigate the motility of a growing population of cells in a idealized setting: We consider a system of hard disks in which new particles are added according to prescribed growth kinetics, thereby dynamically changing the number density. As a result, the expected Brownian motion of the hard disks is modified. We compute the density-dependent friction of the hard disks and insert it in an effective Langevin equation to describe the system, assuming that the intercollision time is smaller than the timescale of the growth. We find that the effective Langevin description captures the changes in motility, in agreement with the simulation results. Our framework can be extended to other systems in which the transport coefficient varies with time.

Effect of substrate stiffness on friction in collective cell migration

In collective cell migration, the motion results from forces produced by each cell and transmitted to the neighboring cells and to the substrate. Because inertia is negligible and the migration occurs over long time scales, the cell layer exhibits viscous behavior, where force and motion are connected by an apparent friction that results from the breaking and forming of adhesive bonds at the cell–cell and cell–substrate interfaces. Most theoretical models for collective migration include an apparent friction to connect force and motion, with many models making predictions that depend on the ratio of cell–cell and cell–substrate friction. However, little is known about factors that affect friction, leaving predictions of many theoretical models untested. Here, we considered how substrate stiffness and the number of adhesions affected friction at the cell–substrate interface. The experimental data were interpreted through prior theoretical models, which led to the same conclusion, that increased substrate stiffness increased the number of cell–substrate adhesions and caused increased cell–substrate friction. In turn, the friction affected the collective migration by altering the curvature at the edge of the cell layer. By revealing underlying factors affecting friction and demonstrating how friction perturbs the collective migration, this work provides experimental evidence supporting prior theoretical models and motivates the study of other ways to alter the collective migration by changing friction.

Creating stem cell-derived neuromuscular junctions in vitro

Recent development of novel therapies has improved mobility and quality of life for people suffering from inheritable neuromuscular disorders. Despite this progress, the majority of neuromuscular disorders are still incurable, in part due to a lack of predictive models of neuromuscular junction (NMJ) breakdown. Improvement of predictive models of a human NMJ would be transformative in terms of expanding our understanding of the mechanisms that underpin development, maintenance, and disease, and as a testbed with which to evaluate novel therapeutics. Induced pluripotent stem cells (iPSCs) are emerging as a clinically relevant and non‐invasive cell source to create human NMJs to study synaptic development and maturation, as well as disease modeling and drug discovery. This review will highlight the recent advances and remaining challenges to generating an NMJ capable of eliciting contraction of stem cell‐derived skeletal muscle in vitro. We explore the advantages and shortcomings of traditional NMJ culturing platforms, as well as the pioneering technologies and novel, biomimetic culturing systems currently in use to guide development and maturation of the neuromuscular synapse and extracellular microenvironment. Then, we will explore how this NMJ‐in‐a‐dish can be used to study normal assembly and function of the efferent portion of the neuromuscular arc, and how neuromuscular disease‐causing mutations disrupt structure, signaling, and function.

Tracking cell migration by cellular force footprint recorded with a mechano-optical biosensor

Conventional cell migration assays require time-lapse imaging of live cells to trace cell migration paths, consequently demanding cumbersome hardware setup and suffering from low data throughput. In this work, we developed an assay named Tracking Cells by Footprint (TCF) based on a mechano-optical biosensor that irreversibly becomes fluorescent when sensing local cell adhesive force. Cell migration paths are visualized and recorded as fluorescent footprints on glass or elastic substrates coated with such biosensor. From the footprints, cell migration ranges, speeds and persistence are analyzed and quantified without the need of time-lapse imaging. The feasibility of TCF assays was demonstrated with three types of cells with different migratory capabilities. TCF was then applied to evaluating cell motility affected by biochemical or biomechanical cues. The results show that fibroblast motility is reduced by blebbistatin and vinblastine but promoted by bFGF (basic fibroblast growth factor), and the motility correlates with the substrate rigidity. TCF is also compatible with 96-well plates which, combined with static imaging and large-area scanning, provides high data throughput with minimal additional effort.

Mechanics of developmental migration

The ability to migrate is a fundamental property of animal cells which is essential for development, homeostasis and disease progression. Migrating cells sense and respond to biochemical and mechanical cues by rapidly modifying their intrinsic repertoire of signalling molecules and by altering their force generating and transducing machinery. We have a wealth of information about the chemical cues and signalling responses that cells use during migration. Our understanding of the role of forces in cell migration is rapidly evolving but is still best understood in the context of cells migrating in 2D and 3D environments in vitro. Advances in live imaging of developing embryos combined with the use of experimental and theoretical tools to quantify and analyse forces in vivo, has begun to shed light on the role of mechanics in driving embryonic cell migration. In this review, we focus on the recent studies uncovering the physical basis of embryonic cell migration in vivo. We look at the physical basis of the classical steps of cell migration such as protrusion formation and cell body translocation and review the recent research on how these processes work in the complex 3D microenvironment of a developing organism.

Self-organized cell migration across scales - from single cell movement to tissue formation

Self-organization is a key feature of many biological and developmental processes, including cell migration. Although cell migration has traditionally been viewed as a biological response to extrinsic signals, advances within the past two decades have highlighted the importance of intrinsic self-organizing properties to direct cell migration on multiple scales. In this Review, we will explore self-organizing mechanisms that lay the foundation for both single and collective cell migration. Based on in vitro and in vivo examples, we will discuss theoretical concepts that underlie the persistent migration of single cells in the absence of directional guidance cues, and the formation of an autonomous cell collective that drives coordinated migration. Finally, we highlight the general implications of self-organizing principles guiding cell migration for biological and medical research.

Repulsive expansion dynamics in colony growth and gene expression

Spatial expansion of a population of cells can arise from growth of microorganisms, plant cells, and mammalian cells. It underlies normal or dysfunctional tissue development, and it can be exploited as the foundation for programming spatial patterns. This expansion is often driven by continuous growth and division of cells within a colony, which in turn pushes the peripheral cells outward. This process generates a repulsion velocity field at each location within the colony. Here we show that this process can be approximated as coarse-grained repulsive-expansion kinetics. This framework enables accurate and efficient simulation of growth and gene expression dynamics in radially symmetric colonies with homogenous z-directional distribution. It is robust even if cells are not spherical and vary in size. The simplicity of the resulting mathematical framework also greatly facilitates generation of mechanistic insights.

Spatiotemporal dynamics are ubiquitous in biology. To understand these phenomena in nature or to program them using synthetic gene circuits, it is critical to resort to mathematical modeling to deduce mechanistic insights or to explore plausible outcomes. Historically, modeling of spatiotemporal dynamics depends on the use of agent-based models or their continuum counterparts consisting of partial differential equations. Here, we show that a class of colony expansion can be treated as being driven by the steric force generated by growing and diving cells. This approximation leads to a drastically simplified framework consisting of only ordinary differential equations. This framework greatly improves the computational efficiency and facilitates development of mechanistic insights into the dynamics of colony growth and pattern formation.

Hierarchical Approach for Comparing Collective Behavior Across Scales: Cellular Systems to Honey Bee Colonies

How individuals in a group lead to collective behavior is a fundamental question across biological systems, from cellular systems, to animal groups, to human organizations. Recent technological advancements have enabled an unprecedented increase in our ability to collect, quantify, and analyze how individual responses lead to group behavior. However, despite a wealth of data demonstrating that collective behavior exists across biological scales, it is difficult to make general statements that apply in different systems. In this perspective, we present a cohesive framework for comparing groups across different levels of biological organization, using an intermediate link of “collective mechanisms” that connects individual responses to group behavior. Using this approach we demonstrate that an effective way of comparing different groups is with an analysis hierarchy that asks complementary questions, including how individuals in a group implement various collective mechanisms, and how these various mechanisms are used to achieve group function. We apply this framework to compare two collective systems—cellular systems and honey bee colonies. Using a case study of a response to a disturbance, we compare and contrast collective mechanisms used in each system. We then discuss how inherent differences in group structure and physical constraints lead to different combinations of collective mechanisms to solve a particular problem. Together, we demonstrate how a hierarchical approach can be used to compare and contrast different systems, lead to new hypotheses in each system, and form a basis for common research questions in collective behavior.

The effects of coating culture dishes with collagen on fibroblast cell shape and swirling pattern formation

Motile human-skin fibroblasts form macroscopic swirling patterns when grown to confluence on a culture dish. In this paper, we investigate the effect of coating the culture-dish surface with collagen on the resulting pattern, using human-skin fibroblast NB1RGB cells as the model system. The presence of the collagen coating is expected to enhance the adherence of the fibroblasts to the dish surface, and thereby also enhance the traction that the fibroblasts have as they move. We find that, contrary to our initial expectation, the coating does not significantly affect the motility of the fibroblasts. Their eventual number density at confluence is also unaffected. However, the coherence length of cell orientation in the swirling pattern is diminished. We also find that the fibroblasts cultured in collagen-coated dishes are rounder in shape and shorter in perimeter, compared with those cultured in uncoated polystyrene or glass culture dishes. We hypothesise that the rounder cell-shape which weakens the cell-cell nematic contact interaction is responsible for the change in coherence length. A simple mathematical model of the migrating fibroblasts is constructed, which demonstrates that constant motility with weaker nematic interaction strength does indeed lead to the shortening of the coherence length.

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.

Lamellipodia-like protrusions and focal adhesions contribute to collective cell migration in zebrafish

Collective cell migration is a process where cohorts of cells exhibit coordinated migratory behavior. During individual and collective cellular migration, cells must extend protrusions to interact with the extracellular environment, sense chemotactic cues, and act as points of attachment. The mechanisms and regulators of protrusive behavior have been widely studied in individually migrating cells; however, how this behavior is regulated throughout collectives is not well understood. To address this, we used the zebrafish posterior lateral line primordium (pLLP) as a model. The pLLP is a cluster of ~150 ​cells that migrates along the zebrafish trunk, depositing groups of cells that will become sensory organs. To define protrusive behavior, we performed mosaic analysis to sparsely label pLLP cells with a transgene marking filamentous actin. This approach revealed an abundance of brush-like protrusions throughout the pLLP that orient in the direction of migration. Formation of these protrusions depends on the Arp2/3 complex, a regulator of dendritic actin. This argues that these brush-like protrusions are an in vivo example of lamellipodia. Mosaic analysis demonstrated that these lamellipodia-like protrusions are located in a close proximity to the overlying skin. Immunostaining revealed an abundance of focal adhesion complexes surrounding the pLLP. Disruption of these complexes specifically in pLLP cells led to impaired pLLP migration. Finally, we show that Erk signaling, a known regulator of focal adhesions, is required for proper formation of lamellipodia-like protrusions and pLLP migration. Altogether, our results suggest a model where the coordinated dynamics of lamellipodia-like protrusions, making contact with either the overlying skin or the extracellular matrix through focal adhesions, promotes migration of pLLP cells.

Plasticity of cancer cell invasion: Patterns and mechanisms

Cancer cell migration and invasion are integral components of metastatic disease, which is the major cause of death in cancer patients. Cancer cells can disseminate and migrate via several alternative mechanisms including amoeboid cell migration, mesenchymal cell migration, and collective cell migration. These diverse movement strategies display certain specific and distinct hallmarks in cell-cell junctions, actin cytoskeleton, matrix adhesion, and protease activity. During tumor progression, cells pass through complex microenvironments and adapt their migration strategies by reversible mesenchymal-amoeboid and individual-collective transitions. This plasticity in motility patterns enables cancer cells disseminate further and thus limit the efficiency of anti-metastasis therapies. In this review, we discuss the modes and mechanisms of cancer cell migration and focus on the plasticity of tumor cell movement as well as potential emerging therapeutic options for reducing cancer cell invasion.

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.

Anteroposterior Wnt-RA Gradient Defines Adhesion and Migration Properties of Neural Progenitors in Developing Spinal Cord

Mammalian embryos exhibit a transition from head morphogenesis to trunk elongation to meet the demand of axial elongation. The caudal neural tube (NT) is formed with neural progenitors (NPCs) derived from neuromesodermal progenitors localized at the tail tip. However, the molecular and cellular basis of elongating NT morphogenesis is yet elusive. Here, we provide evidence that caudal NPCs exhibit strong adhesion affinity that is gradually decreased along the anteroposterior (AP) axis in mouse embryonic spinal cord and human cellular models. Strong cell-cell adhesion causes collective migration, allowing AP alignment of NPCs depending on their birthdate. We further validated that this axial adhesion gradient is associated with the extracellular matrix and is under the control of graded Wnt signaling emanating from tail buds and antagonistic retinoic acid (RA) signaling. These results suggest that progressive reduction of NPC adhesion along the AP axis is under the control of Wnt-RA molecular networks, which is essential for a proper elongation of the spinal cord.

Multi-scale analysis and modelling of collective migration in biological systems

Collective migration has become a paradigm for emergent behaviour in systems of moving and interacting individual units resulting in coherent motion. In biology, these units are cells or organisms. Collective cell migration is important in embryonic development, where it underlies tissue and organ formation, as well as pathological processes, such as cancer invasion and metastasis. In animal groups, collective movements may enhance individuals' decisions and facilitate navigation through complex environments and access to food resources. Mathematical models can extract unifying principles behind the diverse manifestations of collective migration. In biology, with a few exceptions, collective migration typically occurs at a 'mesoscopic scale' where the number of units ranges from only a few dozen to a few thousands, in contrast to the large systems treated by statistical mechanics. Recent developments in multi-scale analysis have allowed linkage of mesoscopic to micro- and macroscopic scales, and for different biological systems. The articles in this theme issue on 'Multi-scale analysis and modelling of collective migration' compile a range of mathematical modelling ideas and multi-scale methods for the analysis of collective migration. These approaches (i) uncover new unifying organization principles of collective behaviour, (ii) shed light on the transition from single to collective migration, and (iii) allow us to define similarities and differences of collective behaviour in groups of cells and organisms. As a common theme, self-organized collective migration is the result of ecological and evolutionary constraints both at the cell and organismic levels. Thereby, the rules governing physiological collective behaviours also underlie pathological processes, albeit with different upstream inputs and consequences for the group. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.

Collective cell migration of fibroblasts is affected by horizontal vibration of the cell culture dish

Regulating the collective migration of cells is an important issue in bioengineering. Enhancing or suppressing cell migration and controlling the migration direction is useful for various physiological phenomena such as wound healing. Several methods of migration regulation based on different mechanical stimuli have been reported. While vibrational stimuli, such as sound waves, show promise for regulating migration, the effect of the vibration direction on collective cell migration has not been studied in depth. Therefore, we fabricated a vibrating system that can apply horizontal vibration to a cell culture dish. Here, we evaluated the effect of the vibration direction on the collective migration of fibroblasts in a wound model comprising two culture areas separated by a gap. Results showed that the vibration direction affects the cell migration distance: vibration orthogonal to the gap enhances the collective cell migration distance while vibration parallel to the gap suppresses it. Results also showed that conditions leading to enhanced migration distance were also associated with elevated glucose consumption. Furthermore, under conditions promoting cell migration, the cell nuclei become elongated and oriented orthogonal to the gap. In contrast, under conditions that reduce the migration distance, cell nuclei were oriented to the direction parallel to the gap.

Relationship between surrounding tissue morphology and directional collective migration of the posterior lateral line primordium in zebrafish

Collective cell migration, in which cells assemble and move together, is an essential process in embryonic development, wound healing and cancer metastasis. Chemokine signaling guides cell assemblies to their destinations. In zebrafish posterior lateral line primordium (PLLP), a model system for collective cell migration, it has been proposed that the chemokine ligand Cxcl12a secreted from muscle pioneer cells (MPs) and muscle fast fibers (MFFs), which are distributed along with the horizontal midline, binds to the receptor Cxcr4b in PLLP and that Cxcl12a-Cxcr4b signaling guides the anterior-to-posterior migration of PLLP along the horizontal midline. However, how the surrounding tissues affect PLLP migration remains to be elucidated. Here, we investigated the relationship between the PLLP and the surrounding tissues and found that a furrow between the dorsal and ventral myotomes is generated by Sonic hedgehog (Shh) signaling-dependent MP and MFF differentiation and that the PLLP migrates in this furrow. When transient inhibition of Shh signaling impaired both the furrow formation and differentiation of cxcl12a-expressing MPs/MFFs, directional PLLP migration was severely perturbed. Furthermore, when differentiated MPs and MFFs were ablated by femtosecond laser irradiations, the furrow remained and PLLP migration was relatively unaffected. These results suggest that the furrow formation between the dorsal and ventral myotomes is associated with the migratory behavior of PLLP.

CompuCell3D Simulations Reproduce Mesenchymal Cell Migration on Flat Substrates

Mesenchymal cell crawling is a critical process in normal development, in tissue function, and in many diseases. Quantitatively predictive numerical simulations of cell crawling thus have multiple scientific, medical, and technological applications. However, we still lack a low-computational-cost approach to simulate mesenchymal three-dimensional (3D) cell crawling. Here, we develop a computationally tractable 3D model (implemented as a simulation in the CompuCell3D simulation environment) of mesenchymal cells crawling on a two-dimensional substrate. The Fürth equation, the usual characterization of mean-squared displacement (MSD) curves for migrating cells, describes a motion in which, for increasing time intervals, cell movement transitions from a ballistic to a diffusive regime. Recent experiments have shown that for very short time intervals, cells exhibit an additional fast diffusive regime. Our simulations' MSD curves reproduce the three experimentally observed temporal regimes, with fast diffusion for short time intervals, slow diffusion for long time intervals, and intermediate time -interval-ballistic motion. The resulting parameterization of the trajectories for both experiments and simulations allows the definition of time- and length scales that translate between computational and laboratory units. Rescaling by these scales allows direct quantitative comparisons among MSD curves and between velocity autocorrelation functions from experiments and simulations. Although our simulations replicate experimentally observed spontaneous symmetry breaking, short-timescale diffusive motion, and spontaneous cell-motion reorientation, their computational cost is low, allowing their use in multiscale virtual-tissue simulations. Comparisons between experimental and simulated cell motion support the hypothesis that short-time actomyosin dynamics affects longer-time cell motility. The success of the base cell-migration simulation model suggests its future application in more complex situations, including chemotaxis, migration through complex 3D matrices, and collective cell motion.

Dense active matter model of motion patterns in confluent cell monolayers

Epithelial cell monolayers show remarkable displacement and velocity correlations over distances of ten or more cell sizes that are reminiscent of supercooled liquids and active nematics. We show that many observed features can be described within the framework of dense active matter, and argue that persistent uncoordinated cell motility coupled to the collective elastic modes of the cell sheet is sufficient to produce swirl-like correlations. We obtain this result using both continuum active linear elasticity and a normal modes formalism, and validate analytical predictions with numerical simulations of two agent-based cell models, soft elastic particles and the self-propelled Voronoi model together with in-vitro experiments of confluent corneal epithelial cell sheets. Simulations and normal mode analysis perfectly match when tissue-level reorganisation occurs on times longer than the persistence time of cell motility. Our analytical model quantitatively matches measured velocity correlation functions over more than a decade with a single fitting parameter.

Talin B regulates collective cell migration via PI3K signaling in Dictyostelium discoideum mounds

Collective cell migration is a key process during the development of multicellular organisms, in which the migrations of individual cells are coordinated through chemical guidance and physical contact between cells. Talin has been implicated in mechanical linkage between actin-based motile machinery and adhesion molecules, but how talin contributes to collective cell migration is unclear. Here we show that talin B is involved in chemical coordination between cells for collective cell migration at the multicellular mound stage in the development of Dictyostelium discoideum. From early aggregation to the mound formation, talB-null cells exhibited collective migration normally with cAMP relay. Subsequently, talB-null cells showed developmental arrest at the mound stage, and at the same time, they had impaired collective migration and cAMP relay, while wild-type cells exhibited rotational cell migration continuously in concert with cAMP relay during the mound stage. Genetic suppression of PI3K activity partially restored talB-null phenotypes in collective cell migration and cAMP relay. Overall, our observations suggest that talin B regulates chemical coordination via PI3K-mediated signaling in a stage-specific manner for the multicellular development of Dictyostelium cells.

The versatile biomedical applications of bismuth-based nanoparticles and composites: therapeutic, diagnostic, biosensing, and regenerative properties

Studies of nanosized forms of bismuth (Bi)-containing materials have recently expanded from optical, chemical, electronic, and engineering fields towards biomedicine, as a result of their safety, cost-effective fabrication processes, large surface area, high stability, and high versatility in terms of shape, size, and porosity. Bi, as a nontoxic and inexpensive diamagnetic heavy metal, has been used for the fabrication of various nanoparticles (NPs) with unique structural, physicochemical, and compositional features to combine various properties, such as a favourably high X-ray attenuation coefficient and near-infrared (NIR) absorbance, excellent light-to-heat conversion efficiency, and a long circulation half-life. These features have rendered bismuth-containing nanoparticles (BiNPs) with desirable performance for combined cancer therapy, photothermal and radiation therapy (RT), multimodal imaging, theranostics, drug delivery, biosensing, and tissue engineering. Bismuth oxyhalides (BiO_x, where X is Cl, Br or I) and bismuth chalcogenides, including bismuth oxide, bismuth sulfide, bismuth selenide, and bismuth telluride, have been heavily investigated for therapeutic purposes. The pharmacokinetics of these BiNPs can be easily improved via the facile modification of their surfaces with biocompatible polymers and proteins, resulting in enhanced colloidal stability, extended blood circulation, and reduced toxicity. Desirable antibacterial effects, bone regeneration potential, and tumor growth suppression under NIR laser radiation are the main biomedical research areas involving BiNPs that have opened up a new paradigm for their future clinical translation. This review emphasizes the synthesis and state-of-the-art progress related to the biomedical applications of BiNPs with different structures, sizes, and compositions. Furthermore, a comprehensive discussion focusing on challenges and future opportunities is presented.

2D or 3D? How cell motility measurements are conserved across dimensions in vitro and translate in vivo

Cell motility is a critical aspect of several processes, such as wound healing and immunity; however, it is dysregulated in cancer. Current limitations of imaging tools make it difficult to study cell migration in vivo. To overcome this, and to identify drivers from the microenvironment that regulate cell migration, bioengineers have developed 2D (two-dimensional) and 3D (three-dimensional) tissue model systems in which to study cell motility in vitro, with the aim of mimicking elements of the environments in which cells move in vivo. However, there has been no systematic study to explicitly relate and compare cell motility measurements between these geometries or systems. Here, we provide such analysis on our own data, as well as across data in existing literature to understand whether, and which, metrics are conserved across systems. To our surprise, only one metric of cell movement on 2D surfaces significantly and positively correlates with cell migration in 3D environments (percent migrating cells), and cell invasion in 3D has a weak, negative correlation with glioblastoma invasion in vivo. Finally, to compare across complex model systems, in vivo data, and data from different labs, we suggest that groups report an effect size, a statistical tool that is most translatable across experiments and labs, when conducting experiments that affect cellular motility.

Plasma membrane localization of MLC1 regulates cellular morphology and motility

Background

Megalencephalic leukoencephalopathy with subcortical cysts (MLC) is a rare form of infantile-onset leukodystrophy. The disorder is caused primarily by mutations of MLC1 that leads to a series of phenotypic outcomes including vacuolation of myelin and astrocytes, subcortical cysts, brain edema, and macrocephaly. Recent studies have indicated that functional interactions among MLC1, GlialCAM, and ClC-2 channels play key roles in the regulation of neuronal, glial and vascular homeostasis. However, the physiological role of MLC1 in cellular homeostatic communication remains poorly understood. In the present study, we investigated the cellular function of MLC1 and its effects on cell–cell interactions.

Methods

MLC1-dependent cellular morphology and motility were analyzed by using confocal and live cell imaging technique. Biochemical approaches such as immunoblotting, co-immunoprecipitation, and surface biotinylation were conducted to support data.

Results

We found that the altered MLC1 expression and localization led to a great alteration in cellular morphology and motility through actin remodeling. MLC1 overexpression induced filopodia formation and suppressed motility. And, MLC1 proteins expressed in patient-derived MLC1 mutants resulted in trapping in the ER although no changes in morphology or motility were observed. Interestingly knockdown of Mlc1 induced Arp3-Cortactin interaction, lamellipodia formation, and increased the membrane ruffling of the astrocytes. These data indicate that subcellular localization of expressed MLC1 at the plasma membrane is critical for changes in actin dynamics through ARP2/3 complex. Thus, our results suggest that misallocation of pathogenic mutant MLC1 may disturbs the stable cell-cell communication and the homeostatic regulation of astrocytes in patients with MLC.

Cell-based simulations of biased epithelial lung growth

During morphogenesis, epithelial tubes elongate. In the case of the mammalian lung, biased elongation has been linked to a bias in cell shape and cell division, but it has remained unclear whether a bias in cell shape along the axis of outgrowth is sufficient for biased outgrowth and how it arises. Here, we use our 2D cell-based tissue simulation software [Formula: see text] to investigate the conditions for biased epithelial outgrowth. We show that the observed bias in cell shape and cell division can result in the observed bias in outgrowth only in the case of strong cortical tension, and comparison to biological data suggests that the cortical tension in epithelia is likely sufficient. We explore mechanisms that may result in the observed bias in cell division and cell shapes. To this end, we test the possibility that the surrounding tissue or extracellular matrix acts as a mechanical constraint that biases growth in the longitudinal direction. While external compressive forces can result in the observed bias in outgrowth, we find that they do not result in the observed bias in cell shapes. We conclude that other mechanisms must exist that generate the bias in lung epithelial outgrowth.