Identifying the mechanism for superdiffusivity in mouse fibroblast motility

Dry and wet wrinkling of a silk fibroin biopolymer by a shape-memory material with insight into mechanical effects on secondary structures in the silk network

Surface wrinkling provides an approach to modify the surfaces of biomedical devices to better mimic features of the extracellular matrix and guide cell attachment, proliferation, and differentiation. Biopolymer wrinkling on active materials holds promise but is poorly explored. Here we report a mechanically actuated assembly process to generate uniaxial micro-and nanosized silk fibroin (SF) wrinkles on a thermo-responsive shape-memory polymer (SMP) substrate, with wrinkling demonstrated under both dry and hydrated (cell compatible) conditions. By systematically investigating the influence of SMP programmed strain magnitude, film thickness, and aqueous media on wrinkle stability and morphology, we reveal how to control the wrinkle sizes on the micron and sub-micron length scale. Furthermore, as a parameter fundamental to SMPs, we demonstrate that the temperature during the recovery process can also affect the wrinkle characteristics and the secondary structures in the silk network. We find that with increasing SMP programmed strain magnitude, silk wrinkled topographies with increasing wavelengths and amplitudes are achieved. Furthermore, silk wrinkling is found to increase β-sheet content, with spectroscopic analysis suggesting that the effect may be due primarily to tensile (e.g., Poisson effect and high-curvature wrinkle) loading modes in the SF, despite the compressive bulk deformation (uniaxial contraction) used to produce wrinkles. Silk wrinkles fabricated from sufficiently thick films (roughly 250 nm) persist after 24 h in cell culture medium. Using a fibroblast cell line, analysis of cellular response to the wrinkled topographies reveals high viability and attachment. These findings demonstrate use of wrinkled SF films under physiologically relevant conditions and suggest the potential for biopolymer wrinkles on biomaterials surfaces to find application in cell mechanobiology, wound healing, and tissue engineering.

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.

Microinterfaces in biopolymer-based bicontinuous hydrogels guide rapid 3D cell migration

Cell migration is critical for tissue development and regeneration but requires extracellular environments that are conducive to motion. Cells may actively generate migratory routes in vivo by degrading or remodeling their environments or instead utilize existing extracellular matrix microstructures or microtracks as innate pathways for migration. While hydrogels in general are valuable tools for probing the extracellular regulators of 3-dimensional migration, few recapitulate these natural migration paths. Here, we develop a biopolymer-based bicontinuous hydrogel system that comprises a covalent hydrogel of enzymatically crosslinked gelatin and a physical hydrogel of guest and host moieties bonded to hyaluronic acid. Bicontinuous hydrogels form through controlled solution immiscibility, and their continuous subdomains and high micro-interfacial surface area enable rapid 3D migration, particularly when compared to homogeneous hydrogels. Migratory behavior is mesenchymal in nature and regulated by biochemical and biophysical signals from the hydrogel, which is shown across various cell types and physiologically relevant contexts (e.g., cell spheroids, ex vivo tissues, in vivo tissues). Our findings introduce a design that leverages important local interfaces to guide rapid cell migration.

Tuning the Topography of Dynamic 3D Scaffolds through Functional Protein Wrinkled Coatings

Surface wrinkling provides an approach to fabricate micron and sub-micron-level biomaterial topographies that can mimic features of the dynamic, in vivo cell environment and guide cell adhesion, alignment, and differentiation. Most wrinkling research to date has used planar, two-dimensional (2D) substrates, and wrinkling work on three-dimensional (3D) structures has been limited. To enable wrinkle formation on architecturally complex, biomimetic 3D structures, here, we report a simple, low-cost experimental wrinkling approach that combines natural silk fibroin films with a recently developed advanced manufacturing technique for programming strain in complex 3D shape-memory polymer (SMP) scaffolds. By systematically investigating the influence of SMP programmed strain magnitude, silk film thickness, and aqueous media on wrinkle morphology and stability, we reveal how to generate and tune silk wrinkles on the micron and sub-micron scale. We find that increasing SMP programmed strain magnitude increases wavelength and decreases amplitudes of silk wrinkled topographies, while increasing silk film thickness increases wavelength and amplitude. Silk wrinkles persist after 24 h in cell culture medium. Wrinkled topographies demonstrate high cell viability and attachment. These findings suggest the potential for fabricating biomimetic cellular microenvironments that can advance understanding and control of cell-material interactions in engineering tissue constructs.

Heterogeneous anomalous transport in cellular and molecular biology

It is well established that a wide variety of phenomena in cellular and molecular biology involve anomalous transport e.g. the statistics for the motility of cells and molecules are fractional and do not conform to the archetypes of simple diffusion or ballistic transport. Recent research demonstrates that anomalous transport is in many cases heterogeneous in both time and space. Thus single anomalous exponents and single generalised diffusion coefficients are unable to satisfactorily describe many crucial phenomena in cellular and molecular biology. We consider advances in the field ofheterogeneous anomalous transport(HAT) highlighting: experimental techniques (single molecule methods, microscopy, image analysis, fluorescence correlation spectroscopy, inelastic neutron scattering, and nuclear magnetic resonance), theoretical tools for data analysis (robust statistical methods such as first passage probabilities, survival analysis, different varieties of mean square displacements, etc), analytic theory and generative theoretical models based on simulations. Special emphasis is made on high throughput analysis techniques based on machine learning and neural networks. Furthermore, we consider anomalous transport in the context of microrheology and the heterogeneous viscoelasticity of complex fluids. HAT in the wavefronts of reaction-diffusion systems is also considered since it plays an important role in morphogenesis and signalling. In addition, we present specific examples from cellular biology including embryonic cells, leucocytes, cancer cells, bacterial cells, bacterial biofilms, and eukaryotic microorganisms. Case studies from molecular biology include DNA, membranes, endosomal transport, endoplasmic reticula, mucins, globular proteins, and amyloids.

Random walk and cell morphology dynamics in Naegleria gruberi

Amoeboid cell movement and migration are wide-spread across various cell types and species. Microscopy-based analysis of the model systems Dictyostelium and neutrophils over the years have uncovered generality in their overall cell movement pattern. Under no directional cues, the centroid movement can be quantitatively characterized by their persistence to move in a straight line and the frequency of re-orientation. Mathematically, the cells essentially behave as a persistent random walker with memory of two characteristic time-scale. Such quantitative characterization is important from a cellular-level ethology point of view as it has direct connotation to their exploratory and foraging strategies. Interestingly, outside the amoebozoa and metazoa, there are largely uncharacterized species in the excavate taxon Heterolobosea including amoeboflagellate Naegleria. While classical works have shown that these cells indeed show typical amoeboid locomotion on an attached surface, their quantitative features are so far unexplored. Here, we analyzed the cell movement of Naegleria gruberi by employing long-time phase contrast imaging that automatically tracks individual cells. We show that the cells move as a persistent random walker with two time-scales that are close to those known in Dictyostelium and neutrophils. Similarities were also found in the shape dynamics which are characterized by the appearance, splitting and annihilation of the curvature waves along the cell edge. Our analysis based on the Fourier descriptor and a neural network classifier point to importance of morphology features unique to Naegleria including complex protrusions and the transient bipolar dumbbell morphologies.

Microinterfaces in bicontinuous hydrogels guide rapid 3D cell migration

Cell migration is critical for tissue development and regeneration but requires extracellular environments that are conducive to motion. Cells may actively generate migratory routes in vivo by degrading or remodeling their environments or may instead utilize existing ECM microstructures or microtracks as innate pathways for migration. While hydrogels in general are valuable tools for probing the extracellular regulators of 3D migration, few have recapitulated these natural migration paths. Here, we developed a biopolymer-based (i.e., gelatin and hyaluronic acid) bicontinuous hydrogel system formed through controlled solution immiscibility whose continuous subdomains and high micro-interfacial surface area enabled rapid 3D migration, particularly when compared to homogeneous hydrogels. Migratory behavior was mesenchymal in nature and regulated by biochemical and biophysical signals from the hydrogel, which was shown across various cell types and physiologically relevant contexts (e.g., cell spheroids, ex vivo tissues, in vivo tissues). Our findings introduce a new design that leverages important local interfaces to guide rapid cell migration.

Printing Parameters of Fused Filament Fabrication Affect Key Properties of Four-Dimensional Printed Shape-Memory Polymers

Extrusion-based (fused filament fabrication) three-dimensional (3D) printing of shape-memory polymers (SMPs) has the potential to rapidly produce highly customized smart-material parts. Yet, the effects of printing parameters on the shape-memory properties of printed SMPs remain poorly understood. To study the extent to which the 3D printing process affects the shape-memory properties of a printed SMP part, here temperature, extrusion rate multiplier, and fiber orientation were systematically varied, and their effect on shape-memory fixing and recovery ratios was evaluated. Fiber orientation, as determined by print path relative to the direction(s) of loading during shape-memory programming, was found to significantly impact the fixing ratio and the recovery ratio. Temperature and multiplier had little effect on either fixing ratio or recovery ratio. To facilitate the use of printed SMP parts in biomedical applications, a cell viability assay was performed on 3D-printed samples prepared using varied temperature and multiplier. Reduction in multiplier was found to increase cell viability. The results indicate that fiber orientation can critically impact the shape-memory functionality of 3D-printed SMP parts, and that multiplier can affect cytocompatibility of those parts. Thus, researchers and manufacturers employing SMPs in 3D-printed parts and devices could achieve improved part functionality if print paths are designed to align fiber direction with the axis(es) in which strain will be programmed and recovered and if the multiplier is optimized in biomedical applications in which a part will contact cells.

Collective chemotaxis in a Voronoi model for confluent clusters

Collective chemotaxis, where single cells cannot climb a biochemical signaling gradient but clusters of cells can, has been observed in different biological contexts, including confluent tissues where there are no gaps or overlaps between cells. Although particle-based models have been developed that predict important features of collective chemotaxis, the mechanisms in those models depend on particle overlaps, and so it remains unclear if they can explain behavior in confluent systems. Here, we develop an open-source code that couples a two-dimensional Voronoi simulation for confluent cell mechanics to a dynamic chemical signal that can diffuse, advect, and/or degrade and use the code to study potential mechanisms for collective chemotaxis in cellular monolayers. We first study the impact of advection on collective chemotaxis and delineate a regime where advective terms are important. Next, we investigate two possible chemotactic mechanisms, contact inhibition of locomotion and heterotypic interfacial tension, and demonstrate that both can drive collective chemotaxis in certain parameter regimes. We further demonstrate that the scaling behavior of cluster motion is well captured by simple analytic theories.

Heterogeneous run-and-tumble motion accounts for transient non-Gaussian super-diffusion in haematopoietic multi-potent progenitor cells

Multi-potent progenitor (MPP) cells act as a key intermediary step between haematopoietic stem cells and the entirety of the mature blood cell system. Their eventual fate determination is thought to be achieved through migration in and out of spatially distinct niches. Here we first analyze statistically MPP cell trajectory data obtained from a series of long time-course 3D in vivo imaging experiments on irradiated mouse calvaria, and report that MPPs display transient super-diffusion with apparent non-Gaussian displacement distributions. Second, we explain these experimental findings using a run-and-tumble model of cell motion which incorporates the observed dynamical heterogeneity of the MPPs. Third, we use our model to extrapolate the dynamics to time-periods currently inaccessible experimentally, which enables us to quantitatively estimate the time and length scales at which super-diffusion transitions to Fickian diffusion. Our work sheds light on the potential importance of motility in early haematopoietic progenitor function.

Image-based cell subpopulation identification through automated cell tracking, principal component analysis, and partitioning around medoids clustering

In vitro cell culture model systems often employ monocultures, despite the fact that cells generally exist in a diverse, heterogeneous microenvironment in vivo. In response, heterogeneous cultures are increasingly being used to study how cell phenotypes interact. However, the ability to accurately identify and characterize distinct phenotypic subpopulations within heterogeneous systems remains a major challenge. Here, we present the use of a computational, image analysis-based approach-comprising automated contour-based cell tracking for feature identification, principal component analysis for feature reduction, and partitioning around medoids for subpopulation characterization-to non-destructively and non-invasively identify functionally distinct cell phenotypic subpopulations from live-cell microscopy image data. Using a heterogeneous model system of endothelial and smooth muscle cells, we demonstrate that this approach can be applied to both mono and co-culture nuclear morphometric and motility data to discern cell phenotypic subpopulations. Morphometric clustering identified minimal difference in mono- versus co-culture, while motility clustering revealed that a portion of endothelial cells and smooth muscle cells adopt increased motility rates in co-culture that are not observed in monoculture. We anticipate that this approach using non-destructive and non-invasive imaging can be applied broadly to heterogeneous cell culture model systems to advance understanding of how heterogeneity alters cell phenotype. This work presents a computational, image-analysis-based approach-comprising automated contour-based cell tracking for feature identification, principle component analysis for feature reduction, and partitioning around medoids for subpopulation characterization-to non-destructively and non-invasively identify functionally distinct cell phenotypic subpopulations from live-cell microscopy image data.

Glassy dynamics in models of confluent tissue with mitosis and apoptosis

Recent work on particle-based models of tissues has suggested that any finite rate of cell division and cell death is sufficient to fluidize an epithelial tissue. At the same time, experimental evidence has indicated the existence of glassy dynamics in some epithelial layers despite continued cell cycling. To address this discrepancy, we quantify the role of cell birth and death on glassy states in confluent tissues using simulations of an active vertex model that includes cell motility, cell division, and cell death. Our simulation data is consistent with a simple ansatz in which the rate of cell-life cycling and the rate of relaxation of the tissue in the absence of cell cycling contribute independently and additively to the overall rate of cell motion. Specifically, we find that a glass-like regime with caging behavior indicated by subdiffusive cell displacements can be achieved in systems with sufficiently low rates of cell cycling.

Stochastic and Heterogeneous Cancer Cell Migration: Experiment and Theory

Cell migration, an essential process for normal cell development and cancer metastasis, differs from a simple random walk: the mean-square displacement (〈(Δr)²(t)〉) of cells sometimes shows non-Fickian behavior, and the spatiotemporal correlation function (G(r, t)) of cells is often non-Gaussian. We find that this intriguing cell migration should be attributed to heterogeneity in a cell population, even one with a homogeneous genetic background. There are two limiting types of heterogeneity in a cell population: cellular heterogeneity and temporal heterogeneity. Cellular heterogeneity accounts for the cell-to-cell variation in migration capacity, while temporal heterogeneity arises from the temporal noise in the migration capacity of single cells. We illustrate that both cellular and temporal heterogeneity need to be taken into account simultaneously to elucidate cell migration. We investigate the two-dimensional migration of A549 lung cancer cells using time-lapse microscopy and find that the migration of A549 cells is Fickian but has a non-Gaussian spatiotemporal correlation. We find that when a theoretical model considers both cellular and temporal heterogeneity, the model reproduces all of the anomalous behaviors of cancer cell migration.

Crosshatch nanofiber networks of tunable interfiber spacing induce plasticity in cell migration and cytoskeletal response

Biomechanical cues within tissue microenvironments are critical for maintaining homeostasis, and their disruption can contribute to malignant transformation and metastasis. Once transformed, metastatic cancer cells can migrate persistently by adapting (plasticity) to changes in the local fibrous extracellular matrix, and current strategies to recapitulate persistent migration rely exclusively on the use of aligned geometries. Here, the controlled interfiber spacing in suspended crosshatch networks of nanofibers induces cells to exhibit plasticity in migratory behavior (persistent and random) and the associated cytoskeletal arrangement. At dense spacing (3 and 6 µm), unexpectedly, elongated cells migrate persistently (in 1 dimension) at high speeds in 3-dimensional shapes with thick nuclei, and short focal adhesion cluster (FAC) lengths. With increased spacing (18 and 36 µm), cells attain 2-dimensional morphologies, have flattened nuclei and longer FACs, and migrate randomly by rapidly detaching their trailing edges that strain the nuclei by ∼35%. At 54-µm spacing, kite-shaped cells become near stationary. Poorly developed filamentous actin stress fibers are found only in cells on 3-µm networks. Gene-expression profiling shows a decrease in transcriptional potential and a differential up-regulation of metabolic pathways. The consistency in observed phenotypes across cell lines supports using this platform to dissect hallmarks of plasticity in migration in vitro.-Jana, A., Nookaew, I., Singh, J., Behkam, B., Franco, A. T., Nain, A. S. Crosshatch nanofiber networks of tunable interfiber spacing induce plasticity in cell migration and cytoskeletal response.