Area and Geometry Dependence of Cell Migration in Asymmetric Two-State Micropatterns

A xenogenic-free culture medium for cell micro-patterning systems as cell-instructive biomaterials for potential clinical applications

Cell micro-patterning controls cell fate and function and has potential for generating therapeutically usable mesenchymal stromal cell (MSC) populations with precise functions. However, to date, the micro-patterning of human cells in a translational context has been impossible because only ruminant media supplements, e.g. fetal bovine serum (FBS), are established for use with micro-patterns (MPs). Thus, there are currently no good manufacturing practice (GMP)-compliant media available for MPs. This study tested a xenogenic-free human plasma and platelet lysate (hP + PL) medium supplement to determine its compatibility with MPs. Unfiltered hP + PL medium resulted in significant protein deposition, creating a 'carpet-like' layer that rendered MPs ineffective. Filtration (3×/5×) eliminated this effect. Importantly, quantitative comparison using droplet digital PCR revealed that human MSCs in all media types exhibited similar profiles with strong myogenic Calponin 1/Transgelin 2 (TAGLN2) and weaker osteogenic alkaline phosphatase/Runt-related transcription factor 2 marker expression, and much weaker adipogenic (lipoprotein lipase/peroxisome proliferator-activated receptor gamma) and chondrogenic (collagen type II/aggrecan) expression, with profiles being dominated by myogenic markers. Within these similar profiles, an even stronger induction of the myogenic marker TAGLN2 by all hP + PL- compared to FBS-containing media. Overall, this suggested that FBS can be replaced with hP + PL without altering differentiation profiles. However, assessing individual MSC responses to various MP types with defined categories revealed that unfiltered hP + PL medium was unusable. Importantly, FBS- and 3× filtered hP + PL media were comparable in each differentiation category. Summarized, this study recommends 3× filtered hP + PL as a xenogenic-free and potentially GMP-compliant alternative to FBS as a culture medium supplement for micro-patterning cell populations in both basic and translational research that will ensure consistent and reliable MSC micro-patterning for therapeutic use.

Targeting Heme Oxygenase 2 (HO2) with TiNIR, a Theragnostic Approach for Managing Metastatic Non-Small Cell Lung Cancer

Despite notable advancements in cancer therapeutics, metastasis remains a primary obstacle impeding a successful prognosis. Our prior study has identified heme oxygenase 2 (HO2) as a promising therapeutic biomarker for the aggressive subsets within tumor. This study aims to systematically evaluate HO2 as a therapeutic target of cancer, with a specific emphasis on its efficacy in addressing cancer metastasis. Through targeted inhibition of HO2 by TiNIR (tumor-initiating cell probe with near infrared), we observed a marked increase in reactive oxygen species. This, in turn, orchestrated the modulation of AKT and cJUN activation, culminating in a substantial attenuation of both proliferation and migration within a metastatic cancer cell model. Furthermore, in a mouse model, clear inhibition of cancer metastasis was unequivocally demonstrated with an HO2 inhibitor administration. These findings underscore the therapeutic promise of targeting HO2 as a strategic intervention to impede cancer metastasis, enhancing the effectiveness of cancer treatments.

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

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

The role of fibronectin in mediating cell migration

Fibronectin (FN) is a major extracellular matrix (ECM) protein involved in a wide range of physiological processes, including cell migration. These FN-mediated cell migration events are essential to processes such as wound repair, cancer metastasis, and vertebrate development. This review synthesizes mainly current literature to provide an overview of the mechanoregulatory role of FN-mediated cell migration. Background on FN structure and role in mechanotransduction is provided. Cell migration concepts are introduced, including the general cell migration mechanism and classification of cell migration types. Then, FN-mediated events that directly affect cell migration are explored. Finally, a focus on FN in tissue repair and cancer migration is presented, as these topics represent a large amount of current research.

An entropy-based approach for assessing the directional persistence of cell migration

Cell migration, which is primarily characterized by directional persistence, is essential for the development of normal tissues and organs, as well as for numerous pathological processes. However, there is a lack of simple and efficient tools to analyze the systematic properties of persistence based on cellular trajectory data. Here, we present a novel approach, the entropy of angular distribution , which combines cellular turning dynamics and Shannon entropy to explore the statistical and time-varying properties of persistence that strongly correlate with cellular migration modes. Our results reveal the changes in the persistence of multiple cell lines that are tightly regulated by both intra- and extracellular cues, including Arpin protein, collagen gel/substrate, and physical constraints. Significantly, some previously unreported distinctive details of persistence have also been captured, helping to elucidate how directional persistence is distributed and evolves in different cell populations. The analysis suggests that the entropy of angular distribution-based approach provides a powerful metric for evaluating directional persistence and enables us to better understand the relationships between cellular behaviors and multiscale cues, which also provides some insights into the migration dynamics of cell populations, such as collective cell invasion.

Advances in Regulating Cellular Behavior Using Micropatterns

Micropatterns, characterized as distinct physical microstructures or chemical adhesion matrices on substance surfaces, have emerged as a powerful tool for manipulating cellular activity. By creating specific extracellular matrix microenvironments, micropatterns can influence various cell behaviors, including orientation, proliferation, migration, and differentiation. This review provides a comprehensive overview of the latest advancements in the use of micropatterns for cell behavior regulation. It discusses the influence of micropattern morphology and coating on cell behavior and the underlying mechanisms. It also highlights future research directions in this field, aiming to inspire new investigations in materials medicine, regenerative medicine, and tissue engineering. The review underscores the potential of micropatterns as a novel approach for controlling cell behavior, which could pave the way for breakthroughs in various biomedical applications.

Cyclic stretch modulates the cell morphology transition under geometrical confinement by covalently immobilized gelatin

Fibroblasts geometrically confined by photo-immobilized gelatin micropatterns were subjected to cyclic stretch on the silicone elastomer. By using covalently micropatterned surfaces, the cell morphologies such as cell area and length were quantitatively investigated under a cyclic stretch for 20 hours. The mechanical forces did not affect the cell growth but significantly altered the cellular morphology on both non-patterned and micropatterned surfaces. It was found that cells on non-patterns showed increasing cell length and decreasing cell area under the stretch. The width of the strip micropatterns provided a different extent of contact guidance for fibroblasts. The highly extended cells on the 10 μm pattern under static conditions would perform a contraction behavior once treated by cyclic stretch. In contrast, cells with a low extension on the 2 μm pattern kept elongating according to the micropattern under the cyclic stretch. The vertical stretch induced an increase in cell area and length more than the parallel stretch in both the 10 μm and 2 μm patterns. These results provided new insights into cell behaviors under geometrical confinement in a dynamic biomechanical environment and may guide biomaterial design for tissue engineering in the future.

Understanding How Cells Probe the World: A Preliminary Step towards Modeling Cell Behavior?

Cell biologists have long aimed at quantitatively modeling cell function. Recently, the outstanding progress of high-throughput measurement methods and data processing tools has made this a realistic goal. The aim of this paper is twofold: First, to suggest that, while much progress has been done in modeling cell states and transitions, current accounts of environmental cues driving these transitions remain insufficient. There is a need to provide an integrated view of the biochemical, topographical and mechanical information processed by cells to take decisions. It might be rewarding in the near future to try to connect cell environmental cues to physiologically relevant outcomes rather than modeling relationships between these cues and internal signaling networks. The second aim of this paper is to review exogenous signals that are sensed by living cells and significantly influence fate decisions. Indeed, in addition to the composition of the surrounding medium, cells are highly sensitive to the properties of neighboring surfaces, including the spatial organization of anchored molecules and substrate mechanical and topographical properties. These properties should thus be included in models of cell behavior. It is also suggested that attempts at cell modeling could strongly benefit from two research lines: (i) trying to decipher the way cells encode the information they retrieve from environment analysis, and (ii) developing more standardized means of assessing the quality of proposed models, as was done in other research domains such as protein structure prediction.

Alternative Geometries for 3D Bioprinting of Calcium Phosphate Cement as Bone Substitute

In the literature, many studies have described the 3D printing of ceramic-based scaffolds (e.g., printing with calcium phosphate cement) in the form of linear structures with layer rotations of 90°, although no right angles can be found in the human body. Therefore, this work focuses on the adaptation of biological shapes, including a layer rotation of only 1°. Sample shapes were printed with calcium phosphate cement using a 3D Bioplotter from EnvisionTec. Both straight and wavy spokes were printed in a round structure with 12 layers. Depending on the strand diameter (200 and 250 µm needle inner diameter) and strand arrangement, maximum failure loads of 444.86 ± 169.39 N for samples without subsequent setting in PBS up to 1280.88 ± 538.66 N after setting in PBS could be achieved.

Model for active particles confined in a two-state micropattern

We propose a model, based on active Brownian particles, for the dynamics of cells confined in a two-state micropattern, composed of two rectangular boxes connected by a bridge, and investigate the transition statistics. A transition between boxes occurs when the active particle crosses the center of the bridge, and the time between subsequent transitions is the dwell time. By assuming that the rotational diffusion time τ is a function of the position, some experimental observations are qualitatively recovered as, for example, the shape of the survival function. τ controls the transition from a ballistic regime at short time scales to a diffusive regime at long time scales, with an effective diffusion coefficient proportional to τ. For small values of τ, the dwell time is determined by the characteristic diffusion timescale which is constant for very low values of τ, when the rotational diffusion is much faster than the translational one and decays with τ for intermediate values of τ. For large values of τ, the interaction with the walls dominates and the particle stays mostly at the corners of the boxes increasing the dwell time. We find that there is an optimal τ for which the dwell time is minimal and its value can be tuned by changing the geometry of the pattern.

Modeling ATP-mediated endothelial cell elongation on line patterns

Endothelial cell (EC) migration is crucial for a wide range of processes including vascular wound healing, tumor angiogenesis, and the development of viable endovascular implants. We have previously demonstrated that ECs cultured on 15-μm wide adhesive line patterns exhibit three distinct migration phenotypes: (a) “running” cells that are polarized and migrate continuously and persistently on the adhesive lines with possible spontaneous directional changes, (b) “undecided” cells that are highly elongated and exhibit periodic changes in the direction of their polarization while maintaining minimal net migration, and (c) “tumbling-like” cells that migrate persistently for a certain amount of time but then stop and round up for a few hours before spreading again and resuming migration. Importantly, the three migration patterns are associated with distinct profiles of cell length. Because of the impact of adenosine triphosphate (ATP) on cytoskeletal organization and cell polarization, we hypothesize that the observed differences in EC length among the three different migration phenotypes are driven by differences in intracellular ATP levels. In the present work, we develop a mathematical model that incorporates the interactions between cell length, cytoskeletal (F-actin) organization, and intracellular ATP concentration. An optimization procedure is used to obtain the model parameter values that best fit the experimental data on EC lengths. The results indicate that a minimalist model based on differences in intracellular ATP levels is capable of capturing the different cell length profiles observed experimentally.

Micro-patterned cell populations as advanced pharmaceutical drugs with precise functional control

Human cells are both advanced pharmaceutical drugs and 'drug deliverers'. However, functional control prior to or after cell implantation remains challenging. Micro-patterning cells through geometrically defined adhesion sites allows controlling morphogenesis, polarity, cellular mechanics, proliferation, migration, differentiation, stemness, cell-cell interactions, collective cell behavior, and likely immuno-modulatory properties. Consequently, generating micro-patterned therapeutic cells is a promising idea that has not yet been realized and few if any steps have been undertaken in this direction. This review highlights potential therapeutic applications, summarizes comprehensively the many cell functions that have been successfully controlled through micro-patterning, details the established micro-pattern designs, introduces the available fabrication technologies to the non-specialized reader, and suggests a quality evaluation score. Such a broad review is not yet available but would facilitate the manufacturing of therapeutically patterned cell populations using micro-patterned cell-instructive biomaterials for improved functional control as drug delivery systems in the context of cells as pharmaceutical products.

A Programmable Multifunctional 3D Cancer Cell Invasion Micro Platform

In the research of cancer cell invasion and metastasis, recreation of physiologically relevant and faithful three-dimensional (3D) tumor models that recapitulate spatial architecture, spatiotemporal control of cell communication and signaling pathways, and integration of extracellular cues remains an open challenge. Here, a programmable multifunctional 3D cancer cell invasion microbuckets-hydrogel (Mb-H) platform is developed by integrating various function-variable microbuckets and extracellular matrix (ECM)-like hydrogels. Based on this Mb-H micro platform, the aggregation of multi-cancer cells is well controlled to form cancer cell spheroids, and the guiding relationship of single-cell migration and collective cell migration during the epithelial-mesenchymal transition (EMT) of cancer cell invasion are demonstrated. By programming and precisely assembling multiple functions in one system, the Mb-H platform with spatial-temporal controlled release of cytokine transforming growth factor beta (TGF-β) and various functionalized Mb-H platforms with intelligent adjustment of cell-matrix interactions are engineered to coordinate the 3D invasive migration of cancer cell spheroids. This programmable and adaptable 3D cancer cell invasion micro platform takes a new step toward mimicking the dynamically changing (localized) tumor microenvironment and exhibits wide potential applications in cancer research, bio-fabrication, cell signaling, and drug screening.

Influence of 3D Printing Parameters on the Mechanical Stability of PCL Scaffolds and the Proliferation Behavior of Bone Cells

Introduction The use of scaffolds in tissue engineering is becoming increasingly important as solutions need to be found for the problem of preserving human tissue, such as bone or cartilage. In this work, scaffolds were printed from the biomaterial known as polycaprolactone (PCL) on a 3D Bioplotter. Both the external and internal geometry were varied to investigate their influence on mechanical stability and biocompatibility. Materials and Methods: An Envisiontec 3D Bioplotter was used to fabricate the scaffolds. First, square scaffolds were printed with variations in the strand width and strand spacing. Then, the filling structure was varied: either lines, waves, and honeycombs were used. This was followed by variation in the outer shape, produced as either a square, hexagon, octagon, or circle. Finally, the internal and external geometry was varied. To improve interaction with the cells, the printed PCL scaffolds were coated with type-I collagen. MG-63 cells were then cultured on the scaffolds and various tests were performed to investigate the biocompatibility of the scaffolds. Results: With increasing strand thickness and strand spacing, the compressive strengths decreased from 86.18 + 2.34 MPa (200 µm) to 46.38 + 0.52 MPa (600 µm). The circle was the outer shape with the highest compressive strength of 76.07 + 1.49 MPa, compared to the octagon, which had the lowest value of 52.96 ± 0.98 MPa. Varying the external shape (toward roundness) geometry, as well as the filling configuration, resulted in the highest values of compressive strength for the round specimens with honeycomb filling, which had a value of 91.4 + 1.4 MPa. In the biocompatibility tests, the round specimens with honeycomb filling also showed the highest cell count per mm², with 1591 ± 239 live cells/mm2 after 10 days and the highest value in cell proliferation, but with minimal cytotoxic effects (9.19 ± 2.47% after 3 days).

Scaffold geometry modulation of mechanotransduction and its influence on epigenetics

The dynamics of cell mechanics and epigenetic signatures direct cell behaviour and fate, thus influencing regenerative outcomes. In recent years, the utilisation of 2D geometric (i.e. square, circle, hexagon, triangle or round-shaped) substrates for investigating cell mechanics in response to the extracellular microenvironment have gained increasing interest in regenerative medicine due to their tunable physicochemical properties. In contrast, there is relatively limited knowledge of cell mechanobiology and epigenetics in the context of 3D biomaterial matrices, i.e., hydrogels and scaffolds. Scaffold geometry provides biophysical signals that trigger a nucleus response (regulation of gene expression) and modulates cell behaviour and function. In this review, we explore the potential of additive manufacturing to incorporate multi length-scale geometry features on a scaffold. Then, we discuss how scaffold geometry direct cell and nuclear mechanosensing. We further discuss how cell epigenetics, particularly DNA/histone methylation and histone acetylation, are modulated by scaffold features that lead to specific gene expression and ultimately influence the outcome of tissue regeneration. Overall, we highlight that geometry of different magnitude scales can facilitate the assembly of cells and multicellular tissues into desired functional architectures through the mechanotransduction pathway. Moving forward, the challenge confronting biomedical engineers is the distillation of the vast knowledge to incorporate multiscaled geometrical features that would collectively elicit a favourable tissue regeneration response by harnessing the design flexibility of additive manufacturing. STATEMENT OF SIGNIFICANCE: It is well-established that cells sense and respond to their 2D geometric microenvironment by transmitting extracellular physiochemical forces through the cytoskeleton and biochemical signalling to the nucleus, facilitating epigenetic changes such as DNA methylation, histone acetylation, and microRNA expression. In this context, the current review presents a unique perspective and highlights the importance of 3D architectures (dimensionality and geometries) on cell and nuclear mechanics and epigenetics. Insight into current challenges around the study of mechanobiology and epigenetics utilising additively manufactured 3D scaffold geometries will progress biomaterials research in this space.

Cell-extracellular matrix dynamics

The sites of interaction between a cell and its surrounding microenvironment serve as dynamic signaling hubs that regulate cellular adaptations during developmental processes, immune functions, wound healing, cell migration, cancer invasion and metastasis, as well as in many other disease states. For most cell types, these interactions are established by integrin receptors binding directly to extracellular matrix proteins, such as the numerous collagens or fibronectin. For the cell, these points of contact provide vital cues by sampling environmental conditions, both chemical and physical. The overall regulation of this dynamic interaction involves both extracellular and intracellular components and can be highly variable. In this review, we highlight recent advances and hypotheses about the mechanisms and regulation of cell-ECM interactions, from the molecular to the tissue level, with a particular focus on cell migration. We then explore how cancer cell invasion and metastasis are deeply rooted in altered regulation of this vital interaction.

Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration

Cell dispersion from a confined area is fundamental in a number of biological processes, including cancer metastasis. To date, a quantitative understanding of the interplay of single-cell motility, cell proliferation, and intercellular contacts remains elusive. In particular, the role of E- and N-cadherin junctions, central components of intercellular contacts, is still controversial. Combining theoretical modeling with in vitro observations, we investigate the collective spreading behavior of colonies of human cancer cells (T24). The spreading of these colonies is driven by stochastic single-cell migration with frequent transient cell-cell contacts. We find that inhibition of E- and N-cadherin junctions decreases colony spreading and average spreading velocities, without affecting the strength of correlations in spreading velocities of neighboring cells. Based on a biophysical simulation model for cell migration, we show that the behavioral changes upon disruption of these junctions can be explained by reduced repulsive excluded volume interactions between cells. This suggests that in cancer cell migration, cadherin-based intercellular contacts sharpen cell boundaries leading to repulsive rather than cohesive interactions between cells, thereby promoting efficient cell spreading during collective migration.

Stress relaxation amplitude of hydrogels determines migration, proliferation, and morphology of cells in 3-D culture

The viscoelastic behavior of hydrogel matrices sensitively influences the cell behavior in 3-D culture and biofabricated tissue model systems. Previous reports have demonstrated that cells tend to adhere, spread, migrate and proliferate better in hydrogels with pronounced stress relaxation. However, it is currently unknown if cells respond more sensitively to the amplitude of stress relaxation, or to the relaxation time constant. To test this, we compare the behavior of fibroblasts cultured for up to 10 days in alginate and oxidized alginate hydrogels with similar Young's moduli but diverging stress relaxation behavior. We find that fibroblasts elongate, migrate and proliferate better in hydrogels that display a higher stress relaxation amplitude. By contrast, the cells' response to the relaxation time constant was less pronounced and less consistent. Together, these data suggest that it is foremost the stress relaxation amplitude of the matrix that determines the ability of cells to locally penetrate and structurally remodel the matrix on a molecular level, which subsequently leads to better spreading, faster migration, and higher cell proliferation. We conclude that the stress relaxation amplitude is a central design parameter for optimizing cell behavior in 3-D hydrogels.

Correlated escape of active particles across a potential barrier

We study the dynamics of one-dimensional active particles confined in a double-well potential, focusing on the escape properties of the system, such as the mean escape time from a well. We first consider a single-particle both in near and far-from-equilibrium regimes by varying the persistence time of the active force and the swim velocity. A non-monotonic behavior of the mean escape time is observed with the persistence time of the activity, revealing the existence of an optimal choice of the parameters favoring the escape process. For small persistence times, a Kramers-like formula with an effective potential obtained within the unified colored noise approximation is shown to hold. Instead, for large persistence times, we developed a simple theoretical argument based on the first passage theory, which explains the linear dependence of the escape time with the persistence of the active force. In the second part of the work, we consider the escape on two active particles mutually repelling. Interestingly, the subtle interplay of active and repulsive forces may lead to a correlation between particles, favoring the simultaneous jump across the barrier. This mechanism cannot be observed in the escape process of two passive particles. Finally, we find that in the small persistence regime, the repulsion favors the escape, such as in passive systems, in agreement with our theoretical predictions, while for large persistence times, the repulsive and active forces produce an effective attraction, which hinders the barrier crossing.

From collections of independent, mindless robots to flexible, mobile, and directional superstructures

A swarm of simple active particles confined in a flexible scaffold is a promising system to make mobile and deformable superstructures. These soft structures can perform tasks that are difficult to carry out for monolithic robots because they can infiltrate narrow spaces, smaller than their size, and move around obstacles. To achieve such tasks, the origin of the forces the superstructures develop, how they can be guided, and the effects of external environment, especially geometry and the presence of obstacles, need to be understood. Here, we report measurements of the forces developed by such superstructures, enclosing a number of mindless active rod-like robots, as well as the forces exerted by these structures to achieve a simple function, crossing a constriction. We relate these forces to the self-organization of the individual entities. Furthermore, and based on a physical understanding of what controls the mobility of these superstructures and the role of geometry in such a process, we devise a simple strategy where the environment can be designed to bias the mobility of the superstructure, giving rise to directional motion. Simple tasks-such as pulling a load, moving through an obstacle course, or cleaning up an arena-are demonstrated. Rudimentary control of the superstructures using light is also proposed. The results are of relevance to the making of robust flexible superstructures with nontrivial space exploration properties out of a swarm of simpler and cheaper robots.

Shannon entropy for time-varying persistence of cell migration

Cell migration, which can be significantly affected by intracellular signaling pathways and extracellular matrix, plays a crucial role in many physiological and pathological processes. Cell migration is typically modeled as a persistent random walk, which depends on two critical motility parameters, i.e., migration speed and persistence time. It is generally very challenging to efficiently and accurately quantify the migration dynamics from noisy experimental data. Here, we introduce the normalized Shannon entropy (SE) based on the FPS of cellular velocity autocovariance function to quantify migration dynamics. The SE introduced here possesses a similar physical interpretation as the Gibbs entropy for thermal systems in that SE naturally reflects the degree of order or randomness of cellular migration, attaining the maximal value of unity for purely diffusive migration (i.e., SE = 1 for the most "random" dynamics) and the minimal value of 0 for purely ballistic dynamics (i.e., SE = 0 for the most "ordered" dynamics). We also find that SE is strongly correlated with the migration persistence but is less sensitive to the migration speed. Moreover, we introduce the time-varying SE based on the WPS of cellular dynamics and demonstrate its superior utility to characterize the time-dependent persistence of cell migration, which typically results from complex and time-varying intra- or extracellular mechanisms. We employ our approach to analyze experimental data of in vitro cell migration regulated by distinct intracellular and extracellular mechanisms, exhibiting a rich spectrum of dynamic characteristics. Our analysis indicates that the SE and wavelet transform (i.e., SE-based approach) offers a simple and efficient tool to quantify cell migration dynamics in complex microenvironment.

Exploiting Substrate Cues for Co-Culturing Cells in a Micropattern

Spatial distribution of cells and their interactions between neighboring cells in native microenvironments are of fundamental importance in determining cell fate decisions such as migration, growth, and differentiation. Controlling the spatial distribution of different cell types in defined geometries can replicate these native environments, which can be a useful model for several studies. While spatiotemporal control over multiple cell arrangements is required to achieve the complex tissue architecture, unfortunately, conventional cell patterning techniques usually allow only single patterning with a single cell type. In the present study, we introduce a simple lithographic method to pattern multiple cell types in a spatially controlled manner by utilizing the biophysical cues present at the corners of the patterned geometry. By fabricating micropatterns of different shapes, we demonstrate how the cell can be constrained to pattern along the corners of patterned geometries owing to the presence of topographical cues, leaving empty voids in the center that can be further utilized for patterning a second cell type. We also demonstrate that the cell alignment along the pattern is a dynamic process and the cells migrate from a more uniform cell-adhesive region toward the topographical cues. The cytoskeleton arrangement was geometry-dependent, which was confirmed through a series of in vitro evaluations, such as scanning electron microscopy and fluorescence microscopy. These findings have not only helped us in exploring the importance of these cues in guiding the cell fate but have also allowed us to develop a technique, which self-patterns the cells without any expensive exogenous cues and can be used as a model protocol to eventually organize cells into a specific pattern with micron-scale precision in vitro.

On the influence of cell shape on dynamic reaction-diffusion polarization patterns

The distribution of signaling molecules following mechanical or chemical stimulation of a cell defines cell polarization, with regions of high active Cdc42 at the front and low active Cdc42 at the rear. As reaction-diffusion phenomena between signaling molecules, such as Rho GTPases, define the gradient dynamics, we hypothesize that the cell shape influences the maintenance of the “front-to-back” cell polarization patterns. We investigated the influence of cell shape on the Cdc42 patterns using an established computational polarization model. Our simulation results showed that not only cell shape but also Cdc42 and Rho-related (in)activation parameter values affected the distribution of active Cdc42. Despite an initial Cdc42 gradient, the in silico results showed that the maximal Cdc42 concentration shifts in the opposite direction, a phenomenon we propose to call “reverse polarization”. Additional in silico analyses indicated that “reverse polarization” only occurred in a particular parameter value space that resulted in a balance between inactivation and activation of Rho GTPases. Future work should focus on a mathematical description of the underpinnings of reverse polarization, in combination with experimental validation using, for example, dedicated FRET-probes to spatiotemporally track Rho GTPase patterns in migrating cells. In summary, the findings of this study enhance our understanding of the role of cell shape in intracellular signaling.

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

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

Inferring the Dynamics of Underdamped Stochastic Systems

Many complex systems, ranging from migrating cells to animal groups, exhibit stochastic dynamics described by the underdamped Langevin equation. Inferring such an equation of motion from experimental data can provide profound insight into the physical laws governing the system. Here, we derive a principled framework to infer the dynamics of underdamped stochastic systems from realistic experimental trajectories, sampled at discrete times and subject to measurement errors. This framework yields an operational method, Underdamped Langevin Inference, which performs well on experimental trajectories of single migrating cells and in complex high-dimensional systems, including flocks with Viscek-like alignment interactions. Our method is robust to experimental measurement errors, and includes a self-consistent estimate of the inference error.

Disentangling the behavioural variability of confined cell migration

Cell-to-cell variability is inherent to numerous biological processes, including cell migration. Quantifying and characterizing the variability of migrating cells is challenging, as it requires monitoring many cells for long time windows under identical conditions. Here, we observe the migration of single human breast cancer cells (MDA-MB-231) in confining two-state micropatterns. To describe the stochastic dynamics of this confined migration, we employ a dynamical systems approach. We identify statistics to measure the behavioural variance of the migration, which significantly exceeds that predicted by a population-averaged stochastic model. This additional variance can be explained by the combination of an ‘ageing’ process and population heterogeneity. To quantify population heterogeneity, we decompose the cells into subpopulations of slow and fast cells, revealing the presence of distinct classes of dynamical systems describing the migration, ranging from bistable to limit cycle behaviour. Our findings highlight the breadth of migration behaviours present in cell populations.