Automated, contour-based tracking and analysis of cell behaviour over long time scales in environments of varying complexity and cell density

Thermally and Photothermally Triggered Cytocompatible Triple-Shape-Memory Polymer Based on a Graphene Oxide-Containing Poly(ε-caprolactone) and Acrylate Composite

Triple-shape-memory polymers (triple-SMPs) are a class of polymers capable of fixing two temporary shapes and recovering sequentially from the first temporary shape to the second temporary shape and, last, to the permanent shape. To accomplish a sequential shape change, a triple-SMP must have two separate shape-fixing mechanisms triggerable by distinct stimuli. Despite the biomedical potential of triple-SMPs, a triple-SMP that with cells present can undergo two different shape changes via two distinct cytocompatible triggers has not previously been demonstrated. Here, we report the design and characterization of a cytocompatible triple-SMP material that responds separately to thermal and light triggers to undergo two distinct shape changes under cytocompatible conditions. Tandem triggering was achieved via a photothermally triggered component, comprising poly(ε-caprolactone) (PCL) fibers with graphene oxide (GO) particles physically attached, embedded in a thermally triggered component, comprising a tert-butyl acrylate-butyl acrylate (tBA-BA) matrix. The material was characterized in terms of thermal properties, surface morphology, shape-memory performance, and cytocompatibility during shape change. Collectively, the results demonstrate cytocompatible triple-shape behavior with a relatively larger thermal shape change (an average of 20.4 ± 4.2% strain recovered for all PCL-containing groups) followed by a smaller photothermal shape change (an average of 3.5 ± 0.8% strain recovered for all PCL-GO-containing groups; samples without GO showed no recovery) with greater than 95% cell viability on the triple-SMP materials, establishing the feasibility of triple-shape memory to be incorporated into biomedical devices and strategies.

Surface Functionalization of 4D Printed Substrates Using Polymeric and Metallic Wrinkles

Wrinkle topographies have been studied as simple, versatile, and in some cases biomimetic surface functionalization strategies. To fabricate surface wrinkles, one material phenomenon employed is the mechanical-instability-driven wrinkling of thin films, which occurs when a deforming substrate produces sufficient compressive strain to buckle a surface thin film. Although thin-film wrinkling has been studied on shape-changing functional materials, including shape-memory polymers (SMPs), work to date has been primarily limited to simple geometries, such as flat, uniaxially-contracting substrates. Thus, there is a need for a strategy that would allow deformation of complex substrates or 3D parts to generate wrinkles on surfaces throughout that complex substrate or part. Here, 4D printing of SMPs is combined with polymeric and metallic thin films to develop and study an approach for fiber-level topographic functionalization suitable for use in printing of arbitrarily complex shape-changing substrates or parts. The effect of nozzle temperature, substrate architecture, and film thickness on wrinkles has been characterized, as well as wrinkle topography on nuclear alignment using scanning electron microscopy, atomic force microscopy, and fluorescent imaging. As nozzle temperature increased, wrinkle wavelength increased while strain trapping and nuclear alignment decreased. Moreover, with increasing film thickness, the wavelength increased as well.

No Cell Left behind: Automated, Stochastic, Physics-Based Tracking of Every Cell in a Dense, Growing Colony

Motivation: Precise tracking of individual cells—especially tracking the family lineage, for example in a developing embryo—has widespread applications in biology and medicine. Due to significant noise in microscope images, existing methods have difficulty precisely tracking cell activities. These difficulties often require human intervention to resolve. Humans are helpful because our brain naturally and automatically builds a simulation “model” of any scene that we observe. Because we understand simple truths about the world—for example cells can move and divide, but they cannot instantaneously move vast distances—this model “in our heads” helps us to severely constrain the possible interpretations of what we see, allowing us to easily distinguish signal from noise, and track the motion of cells even in the presence of extreme levels of noise that would completely confound existing automated methods. Results: Here, we mimic the ability of the human brain by building an explicit computer simulation model of the scene. Our simulated cells are programmed to allow movement and cell division consistent with reality. At each video frame, we stochastically generate millions of nearby “Universes” and evolve them stochastically to the next frame. We then find and fit the best universes to reality by minimizing the residual between the real image frame and a synthetic image of the simulation. The rule-based simulation puts extremely stringent constraints on possible interpretations of the data, allowing our system to perform far better than existing methods even in the presense of extreme levels of image noise. We demonstrate the viability of this method by accurately tracking every cell in a colony that grows from 4 to over 300 individuals, doing about as well as a human can in the difficult task of tracking cell lineages.

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.

Microgrooves Encourage Endothelial Cell Adhesion and Organization on Shape-Memory Polymer Surfaces

Cardiovascular stents have become the mainstay for treating coronary and other vascular diseases; however, the need for long-term anti-platelet therapies continues to drive research on novel materials and strategies to promote in situ endothelialization of these devices, which should decrease local thrombotic response. Shape-memory polymers (SMPs) have shown promise as polymer stents due to their self-deployment capabilities and vascular biocompatibility. We previously demonstrated isotropic endothelial cell adhesion on the unmodified surfaces of a family of SMPs previously developed by our group. Here, we evaluate whether endothelial cells align preferentially along microgrooved versus unpatterned surfaces of these SMPs. Results show that micropatterning SMP surfaces enhances natural surface hydrophobicity, which helps promote endothelial cell attachment and alignment along the grooves. With the addition of microgrooves to the SMP surface, this class of SMPs may provide an improved surface and material for next-generation blood-contacting devices.

Nuclear position relative to the Golgi body and nuclear orientation are differentially responsive indicators of cell polarized motility

Cell motility is critical to biological processes from wound healing to cancer metastasis to embryonic development. The involvement of organelles in cell motility is well established, but the role of organelle positional reorganization in cell motility remains poorly understood. Here we present an automated image analysis technique for tracking the shape and motion of Golgi bodies and cell nuclei. We quantify the relationship between nuclear orientation and the orientation of the Golgi body relative to the nucleus before, during, and after exposure of mouse fibroblasts to a controlled change in cell substrate topography, from flat to wrinkles, designed to trigger polarized motility. We find that the cells alter their mean nuclei orientation, in terms of the nuclear major axis, to increasingly align with the wrinkle direction once the wrinkles form on the substrate surface. This change in alignment occurs within 8 hours of completion of the topographical transition. In contrast, the position of the Golgi body relative to the nucleus remains aligned with the pre-programmed wrinkle direction, regardless of whether it has been fully established. These findings indicate that intracellular positioning of the Golgi body precedes nuclear reorientation during mouse fibroblast directed migration on patterned substrates. We further show that both processes are Rho-associated kinase (ROCK) mediated as they are abolished by pharmacologic ROCK inhibition whereas mouse fibroblast motility is unaffected. The automated image analysis technique introduced could be broadly employed in the study of polarization and other cellular processes in diverse cell types and micro-environments. In addition, having found that the nuclei Golgi vector may be a more sensitive indicator of substrate features than the nuclei orientation, we anticipate the nuclei Golgi vector to be a useful metric for researchers studying the dynamics of cell polarity in response to different micro-environments.

Identifying the mechanism for superdiffusivity in mouse fibroblast motility

We seek to characterize the motility of mouse fibroblasts on 2D substrates. Utilizing automated tracking techniques, we find that cell trajectories are super-diffusive, where displacements scale faster than t1/2 in all directions. Two mechanisms have been proposed to explain such statistics in other cell types: run and tumble behavior with Lévy-distributed run times, and ensembles of cells with heterogeneous speed and rotational noise. We develop an automated toolkit that directly compares cell trajectories to the predictions of each model and demonstrate that ensemble-averaged quantities such as the mean-squared displacements and velocity autocorrelation functions are equally well-fit by either model. However, neither model correctly captures the short-timescale behavior quantified by the displacement probability distribution or the turning angle distribution. We develop a hybrid model that includes both run and tumble behavior and heterogeneous noise during the runs, which correctly matches the short-timescale behaviors and indicates that the run times are not Lévy distributed. The analysis tools developed here should be broadly useful for distinguishing between mechanisms for superdiffusivity in other cells types and environments.

Enzymatically triggered shape memory polymers

Cytocompatible shape memory polymers activated by thermal or photothermal triggers have been developed and established as powerful "smart material" platforms for both basic and translational research. Shape memory polymers (SMPs) that could be triggered directly by biological activity have not, in contrast, been reported. The goal of this study was to develop an SMP that responds directly to enzymatic activity and can do so under isothermal cell culture conditions. To achieve this goal, we designed an SMP with a shape fixing component, poly(ε-caprolactone) (PCL), that is vulnerable to enzymatic degradation and a shape memory component, Pellethane, that is enzymatically stable - as the shape fixing component undergoes enzymatically-catalyzed degradation, the SMP returns to its original, programmed shape. We quantitatively and qualitatively analyzed material properties, shape memory performance, and cytocompatibility of the enzymatically-catalyzed shape memory response. The results demonstrate enzymatic recovery, as contraction of tensile specimens, using bulk enzymatic degradation experiments and show that shape recovery is achieved by degradation of the PCL shape-fixing phase. The results further showed that both the materials and the process of enzymatic shape recovery are cytocompatible. Thus, the SMP design reported here represents both an enzyme responsive material capable of applying a programmed shape change or direct mechanical force and an SMP that could respond directly to biological activity. STATEMENT OF SIGNIFICANCE: Cytocompatible shape memory polymers activated by thermal or photothermal triggers have become powerful "smart material" platforms for basic and translational research. Shape memory polymers that could be triggered directly by biological activity have not, in contrast, been reported. Here we report an enzymatically triggered shape memory polymer that changes its shape isothermally in response to enzymatic activity. We successfully demonstrate enzymatic recovery using bulk enzymatic degradation experiments and show that shape recovery is achieved by degradation of the shape-fixing phase. We further show that both the materials and the process of enzymatic shape recovery are cytocompatible. This new shape memory polymer design can be anticipated to enable new applications in basic and applied materials science as a stimulus responsive material.

On-command on/off switching of progenitor cell and cancer cell polarized motility and aligned morphology via a cytocompatible shape memory polymer scaffold

In vitro biomaterial models have enabled advances in understanding the role of extracellular matrix (ECM) architecture in the control of cell motility and polarity. Most models are, however, static and cannot mimic dynamic aspects of in vivo ECM remodeling and function. To address this limitation, we present an electrospun shape memory polymer scaffold that can change fiber alignment on command under cytocompatible conditions. Cellular response was studied using the human fibrosarcoma cell line HT-1080 and the murine mesenchymal stem cell line C3H/10T1/2. The results demonstrate successful on-command on/off switching of cell polarized motility and alignment. Decrease in fiber alignment causes a change from polarized motility along the direction of fiber alignment to non-polarized motility and from aligned to unaligned morphology, while increase in fiber alignment causes a change from non-polarized to polarized motility along the direction of fiber alignment and from unaligned to aligned morphology. In addition, the findings are consistent with the hypothesis that increased fiber alignment causes increased cell velocity, while decreased fiber alignment causes decreased cell velocity. On-command on/off switching of cell polarized motility and alignment is anticipated to enable new study of directed cell motility in tumor metastasis, in cell homing, and in tissue engineering.

Shape memory activation can affect cell seeding of shape memory polymer scaffolds designed for tissue engineering and regenerative medicine

The ability of a three-dimensional scaffold to support cell seeding prior to implantation is a critical criterion for many scaffold-based tissue engineering and regenerative medicine strategies. Shape memory polymer functionality may present important new opportunities and challenges in cell seeding, but the extent to which shape memory activation can positively or negatively affect cell seeding has yet to be reported. The goal of this study was to determine whether shape memory activation can affect cell seeding. The hypothesis was that shape memory activation of porous scaffolds during cell seeding can affect both the number of cells seeded in a scaffold and the distribution (in terms of average infiltration distance) of cells following seeding. Here, we used a porous shape memory foam scaffold programmed to expand when triggered to study cell number and average cell infiltration distance following shape memory activation. We found that shape memory activation can affect both the number of cells and the average cell infiltration distance. The effect was found to be a function of rate of shape change and scaffold pore interconnectivity. Magnitude of shape change had no effect. Only reductions in cell number and infiltration distance (relative to control and benchmark) were observed. The findings suggest that strategies for tissue engineering and regenerative medicine that involve shape memory activation in the presence of a cell-containing medium in vitro or in vivo should consider how recovery rate and scaffold pore interconnectivity may ultimately impact cell seeding.

How Escherichia coli lands and forms cell clusters on a surface: a new role of surface topography

Bacterial response to surface topography during biofilm formation was studied using 5 μm tall line patterns of poly (dimethylsiloxane) (PDMS). Escherichia coli cells attached on top of protruding line patterns were found to align more perpendicularly to the orientation of line patterns when the pattern narrowed. Consistently, cell cluster formation per unit area on 5 μm wide line patterns was reduced by 14-fold compared to flat PDMS. Contrasting the reduced colony formation, cells attached on narrow patterns were longer and had higher transcriptional activities, suggesting that such unfavorable topography may present a stress to attached cells. Results of mutant studies indicate that flagellar motility is involved in the observed preference in cell orientation on narrow patterns, which was corroborated by the changes in cell rotation pattern before settling on different surface topographies. These findings led to a set of new design principles for creating antifouling topographies, which was validated using 10 μm tall hexagonal patterns.

Simultaneously targeted imaging cytoplasm and nucleus in living cell by biomolecules capped ultra-small GdOF nanocrystals

Simultaneously targeted imaging cytoplasm and nucleus in living cell by just one photoluminescent nanocrystals has been a giant challenge in nanobiotechnology and nanomedicine. Herein we report a novel Arg-Gly-Asp peptide (RGD) or cysteine (Cys) functionalized ultra-small GdOF nanocrystals for simultaneously targeted imaging cell cytoplasm and nucleus. As-prepared RGD@GdOF and Cys@GdOF nanocrystals possessed high water dispersibility, ultra-small size (about 5 nm) and double emissions (545 nm and 587 nm) with high quantum yield. Such functionalized nanocrystals presented high cellular biocompatibility and were successfully used to label living cells with very high signal to noise ratio. The living cells cytoplasm and nucleus (cancer cells and stem cells) could be imaged simultaneously through the mergence of green and red emission of nanocrystals, based on mechanism of fluorescent intensity difference. These functionalized nanocrystals also exhibited significantly higher photostability and brightness as compared to dyes. Such the ultra-small size, high photostability and intensity, double emissions, excellent biocompatibility and targeted ability, make as-prepared functionalized nanocrystals particularly promising for cellular and molecular-level bioimaging applications.

Quantitative description of fluid flows produced by left-right cilia in zebrafish

Motile cilia generate directional flows that move mucus through airways, cerebrospinal fluid through brain ventricles, and oocytes through fallopian tubes. In addition, specialized monocilia beat in a rotational pattern to create asymmetric flows that are involved in establishing the left-right (LR) body axis during embryogenesis. These monocilia, which we refer to as "left-right cilia," produce a leftward flow of extraembryonic fluid in a transient "organ of asymmetry" that directs asymmetric signaling and development of LR asymmetries in the cardiovascular system and gastrointestinal tract. The asymmetric flows are thought to establish a chemical gradient and/or activate mechanosensitive cilia to initiate calcium ion signals and a conserved Nodal (TGFβ) pathway on the left side of the embryo, but the mechanisms underlying this process remain unclear. The zebrafish organ of asymmetry, called Kupffer's vesicle, provides a useful model system for investigating LR cilia and cilia-powered fluid flows. Here, we describe methods to visualize flows in Kupffer's vesicle using fluorescent microspheres and introduce a new and freely available MATLAB particle tracking code to quantitatively describe these flows. Analysis of normal and aberrant flows indicates this approach is useful for characterizing flow properties that impact LR asymmetry and may be more broadly applicable for quantifying other cilia flows.

Gaussian memory in kinematic matrix theory for self-propellers

We extend the kinematic matrix ("kinematrix") formalism [Phys. Rev. E 89, 062304 (2014)], which via simple matrix algebra accesses ensemble properties of self-propellers influenced by uncorrelated noise, to treat Gaussian correlated noises. This extension brings into reach many real-world biological and biomimetic self-propellers for which inertia is significant. Applying the formalism, we analyze in detail ensemble behaviors of a 2D self-propeller with velocity fluctuations and orientation evolution driven by an Ornstein-Uhlenbeck process. On the basis of exact results, a variety of dynamical regimes determined by the inertial, speed-fluctuation, orientational diffusion, and emergent disorientation time scales are delineated and discussed.