Cellular Motion Research Articles

Applications of Light-Sheet Microscopy in Microdevices.

Light-sheet fluorescence microscopy (LSFM) has been present in cell biology laboratories for quite some time, mainly as custom-made systems, with imaging applications ranging from single cells (in the micrometer scale) to small organisms (in the millimeter scale). Such microscopes distinguish themselves for having very low phototoxicity levels and high spatial and temporal resolution, properties that make them ideal for a large range of applications. These include the study of cellular dynamics, in particular cellular motion which is essential to processes such as tumor metastasis and tissue development. Experimental setups make extensive use of microdevices (bioMEMS) that provide better control over the substrate environment than traditional cell culture experiments. For example, to mimic in vivo conditions, experiment biochemical dynamics, and trap, move or count cells. Microdevices provide a higher degree of empirical complexity but, so far, most have been designed to be imaged through wide-field or confocal microscopes. Nonetheless, the properties of LSFM render it ideal for 3D characterization of active cells. When working with microdevices, confocal microscopy is more widespread than LSFM even though it suffers from higher phototoxicity and slower acquisition speeds. It is sometimes possible to illuminate with a light-sheet microdevices designed for confocal microscopes. However, these bioMEMS must be redesigned to exploit the full potential of LSFM and image more frequently on a wider scale phenomena such as motion, traction, differentiation, and diffusion of molecules. The use of microdevices for LSFM has extended beyond cell tracking studies into experiments regarding cytometry, spheroid cultures and lab-on-a-chip automation. Due to light-sheet microscopy being in its early stages, a setup of these characteristics demands some degree of optical expertise; and designing three-dimensional microdevices requires facilities, ingenuity, and experience in microfabrication. In this paper, we explore different approaches where light-sheet microscopy can achieve single-cell and subcellular resolution within microdevices, and provide a few pointers on how these experiments may be improved.

Characterization of Biological Motion Using Motion Sensing Superpixels.

Precise spatiotemporal regulation is the foundation for the healthy development and maintenance of living organisms. All cells must correctly execute their function in the right place at the right time. Cellular motion is thus an important dynamic readout of signaling in key disease-relevant molecular pathways. However despite the rapid advancement of imaging technology, a comprehensive quantitative description of motion imaged under different imaging modalities at all spatiotemporal scales; molecular, cellular and tissue-level is still lacking. Generally, cells move either 'individually' or 'collectively' as a group with nearby cells. Current computational tools specifically focus on one or the other regime, limiting their general applicability. To address this, we recently developed and reported a new computational framework, Motion Sensing Superpixels (MOSES). Incorporating the individual advantages of single cell trackers for individual cell and particle image velocimetry (PIV) for collective cell motion analyses, MOSES enables 'mesoscale' analysis of both single-cell and collective motion over arbitrarily long times. At the same time, MOSES readily complements existing single-cell tracking workflows with additional characterization of global motion patterns and interaction analysis between cells and also operates directly on PIV extracted motion fields to yield rich motion trajectories analogous for single-cell tracks suitable for high-throughput motion phenotyping. This protocol provides a step-by-step practical guide for those interested in applying MOSES to their own datasets. The protocol highlights the salient features of a MOSES analysis and demonstrates the ease-of-use and wide applicability of MOSES to biological imaging through demo experimental analyses with ready-to-use code snippets of four datasets from different microscope modalities; phase-contrast, fluorescent, lightsheet and intra-vital microscopy. In addition we discuss critical points of consideration in the analysis.

Substrate-rigidity dependent migration of an idealized twitching bacterium.

Mechanical properties of the extracellular matrix are important determinants of cellular migration in diverse processes, such as immune response, wound healing, and cancer metastasis. Moreover, recent studies indicate that even bacterial surface colonization can depend on the mechanics of the substrate. Here, we focus on physical mechanisms that can give rise to substrate-rigidity dependent migration. We study a "twitcher", a cell driven by extension-retraction cycles, to idealize bacteria and perhaps eukaryotic cells that employ a slip-stick mode of motion. The twitcher is asymmetric and always pulls itself forward at its front. Analytical calculations show that the migration speed of a twitcher depends non-linearly on substrate rigidity. For soft substrates, deformations do not lead to build-up of significant force and the migration speed is therefore determined by stochastic adhesion unbinding. For rigid substrates, forced adhesion rupture determines the migration speed. Depending on the force-sensitivity of front and rear adhesions, forced bond rupture implies an increase or a decrease of the migration speed. A requirement for the occurrence of rigidity-dependent stick-slip migration is a "sticky" substrate, with binding rates being an order of magnitude larger than unbinding rates in absence of force. Computer simulations show that small stall forces of the driving machinery lead to a reduced movement on high rigidities, regardless of force-sensitivities of bonds. The simulations also confirm the occurrence of rigidity-dependent migration speed in a generic model for slip-stick migration of cells on a sticky substrate.

Self-organized and self-propelled aero-GaN with dual hydrophilic-hydrophobic behaviour

Nature utilizes hydrophilic-hydrophobic biomolecular entities to perform self-organized structural and functional tasks, including the formation of cellular compartments and motion, separation of chemicals or self-healing properties in a highly energy efficient manner. So far, no inorganic artificial micro/nanostructure units are known that self-organize and mimic such functions just by adding liquid. Here we develop the first nanomaterial exhibiting hydrophobic wetting and hydrophilic dewetting. Consisting of gallium nitride nanoscopically thin membranes shaped as hollow microtetrapods, which we term aerogalnite (AGaN), the nanomaterial is extremely porous, mechanically flexible, stretchable, and exhibits hydrophilicity under tension and hydrophobicity when compressed against water. Self-assembling the AGaN tetrapods on water enabled us to develop self-healing waterproof rafts carrying liquid droplets 500-times as heavy as rafts, and to demonstrate self-propelled liquid marbles exhibiting velocity of rotation as high as 750 rot/min. The specific force of the detachment of AGaN from the water surface was experimentally determined equal to 35 mN/cm2. The new developed material aerogalnite and its peculiar characteristics are promising for applications in sensorics, microfluidic devices and microrobotics.

Force-dependent diffusion coefficient of molecular Brownian ratchets.

We study the mean velocity and diffusion constant in three related models of molecular Brownian ratchets. Brownian ratchets can be used to describe translocation of biopolymers like DNA through nanopores in cells in the presence of chaperones on the trans side of the pore. Chaperones can bind to the polymer and prevent it from sliding back through the pore. First, we study a simple model that describes the translocation in terms of an asymmetric random walk. It serves as an introductory example but already captures the main features of a Brownian ratchet. We then provide an analytical expression for the diffusion constant in the classical model of a translocation ratchet that was first proposed by Peskin etal. [C. S. Peskin, G. M. Odell, and G. F. Oster, Cellular motions and thermal fluctuations: The Brownian ratchet, Biophys. J. 65, 316 (1993)BIOJAU0006-349510.1016/S0006-3495(93)81035-X]. This model is based on the assumption that the binding and unbinding of the chaperones are much faster than the diffusion of the DNA strand. To remedy this shortcoming, we propose a modified model that is also applicable if the (un)binding rates are finite. We calculate the force-dependent mean velocity and diffusivity for this model and compare the results to the original one. Our analysis shows that for large pulling forces the predictions of both models can differ strongly even if the (un)binding rates are large in comparison to the diffusion timescale but still finite. Furthermore, implications of the thermodynamic uncertainty relation on the efficiency of Brownian ratchets are discussed.

Reduced modeling of porous media convection in a minimal flow unit at large Rayleigh number

Direct numerical simulations (DNS) indicate that at large values of the Rayleigh number (Ra) convection in porous media self-organizes into narrowly-spaced columnar flows, with more complex spatiotemporal features being confined to boundary layers near the top and bottom walls. In this investigation of high-Ra porous media convection in a minimal flow unit, two reduced modeling strategies are proposed that exploit these specific flow characteristics. Both approaches utilize the idea of decomposition since the flow exhibits different dynamics in different regions of the domain: small-scale cellular motions generally are localized within the thermal and vorticity boundary layers near the upper and lower walls, while in the interior, the flow exhibits persistent large-scale structures and only a few low (horizontal) wavenumber Fourier modes are active. Accordingly, in the first strategy, the domain is decomposed into two near-wall regions and one interior region. Our results confirm that suppressing the interior high-wavenumber modes has negligible impact on the essential structural features and transport properties of the flow. In the second strategy, a hybrid reduced model is constructed by using Galerkin projection onto a fully a priori eigenbasis drawn from energy stability and upper bound theory, thereby extending the model reduction strategy developed by Chini et al. (2011) [45] to large Ra. The results indicate that the near-wall upper-bound eigenmodes can economically represent the small-scale rolls within the exquisitely-thin thermal boundary layers. Relative to DNS, the hybrid algorithm enables over an order-of-magnitude increase in computational efficiency with only a modest loss of accuracy.

Biodynamic digital holography of chemoresistance in a pre-clinical trial of canine B-cell lymphoma.

Biodynamic digital holography was used to obtain phenotypic profiles of canine non-Hodgkin B-cell lymphoma biopsies treated with standard-of-care chemotherapy. Biodynamic signatures from the living 3D tissues were extracted using fluctuation spectroscopy from intracellular Doppler light scattering in response to the molecular mechanisms of action of therapeutic drugs that modify a range of internal cellular motions. The standard-of-care to treat B-cell lymphoma in both humans and dogs is a combination CHOP therapy that consists of doxorubicin, prednisolone, cyclophosphamide and vincristine. The proportion of dogs experiencing durable cancer remission following CHOP chemotherapy was 68%, with 13 out of 19 dogs responding favorably to therapy and 6 dogs failing to have progression-free survival times greater than 100 days. Biodynamic signatures were found that correlate with inferior survival times, and biomarker selection was optimized to identify specific Doppler signatures related to chemoresistance. A machine learning classifier was constructed based on feature vector correlations and linear separability in high-dimensional feature space. Hold-out validation predicted patient response to therapy with 84% accuracy. These results point to the potential for biodynamic profiling to contribute to personalized medicine by aiding the selection of chemotherapy for cancer patients.

Cellular dynamics of bovine aortic smooth muscle cells measured using MEMS force sensors

Adhesive cells perceive the mechanical properties of the substrates to which they adhere, adjusting their cellular mechanical forces according to their biological characteristics. This mechanical interaction subsequently affects the growth, locomotion, and differentiation of the cell. However, little is known about the detailed mechanism that underlies this interaction between adherent cells and substrates because dynamically measuring mechanical phenomena is difficult. Here, we utilize microelectromechamical systems force sensors that can measure cellular traction forces with high temporal resolution (~2.5 µs) over long periods (~3 h). We found that the cellular dynamics reflected physical phenomena with time scales from milliseconds to hours, which contradicts the idea that cellular motion is slow. A single focal adhesion (FA) generates an average force of 7 nN, which disappears in ms via the action of trypsin-ethylenediaminetetraacetic acid. The force-changing rate obtained from our measurements suggests that the time required for an FA to decompose was nearly proportional to the force acting on the FA.

Integrating transient cellular and nuclear motions to comprehensively describe cell migration patterns

Various subcellular activities, such as protrusion and detachment, compose a cell migration process. The molecular mechanisms of these subcellular activities have been elucidated. However, there is no method that can assess the contributions of these subcellular activities to the global cell migration pattern of a given cell type. Hence, we develop a powerful approach based on CN correlations that quantitatively profiles the cell migration pattern of a given cell type in terms of assembled subcellular activities. In this way, we bridge migration data at the cellular level with underlying molecular mechanisms. The CN correlation profile is found to uniquely and consistently represent the cell migration pattern of each cell type probed. It can clearly reveal the effects of molecular perturbations, such as Y27632 and Cdc42 knockdown on each subcellular migratory activity. As a result, the CN correlation approach serves as a cell dynamic descriptor that can extract comprehensive quantitative data from cell migration movies for integrative biological analyses.

Optophysiology of cardiomyocytes: characterizing cellular motion with quantitative phase imaging.

Quantitative phase imaging enables precise characterization of cellular shape and motion. Variation of cell volume in populations of cardiomyocytes can help distinguish their types, while changes in optical thickness during beating cycle identify contraction and relaxation periods and elucidate cell dynamics. Parameters such as characteristic cycle shape, beating frequency, duration and regularity can be used to classify stem-cell derived cardiomyocytes according to their health and, potentially, cell type. Unlike classical patch-clamp based electrophysiological characterization of cardiomyocytes, this interferometric approach enables rapid and non-destructive analysis of large populations of cells, with longitudinal follow-up, and applications to tissue regeneration, personalized medicine, and drug testing.

Optophysiology of cardiomyocytes: characterizing cellular motion with quantitative phase imaging.

Quantitative phase imaging enables precise characterization of cellular shape and motion. Variation of cell volume in populations of cardiomyocytes can help distinguish their types, while changes in optical thickness during beating cycle identify contraction and relaxation periods and elucidate cell dynamics. Parameters such as characteristic cycle shape, beating frequency, duration and regularity can be used to classify stem-cell derived cardiomyocytes according to their health and, potentially, cell type. Unlike classical patch-clamp based electrophysiological characterization of cardiomyocytes, this interferometric approach enables rapid and non-destructive analysis of large populations of cells, with longitudinal follow-up, and applications to tissue regeneration, personalized medicine, and drug testing.

Onset of cellular motion in Taylor-Couette flow

The onset of cellular motion in Taylor-Couette flow is a pitchfork bifurcation under the assumption of periodicity. New experimental data show that an explanation of the observed bifurcation requires the interaction between neighboring states.

High-order positivity-preserving hybrid finite-volume-finite-difference methods for chemotaxis systems

Chemotaxis refers to mechanisms by which cellular motion occurs in response to an external stimulus, usually a chemical one. Chemotaxis phenomenon plays an important role in bacteria/cell aggregation and pattern formation mechanisms, as well as in tumor growth. A common property of all chemotaxis systems is their ability to model a concentration phenomenon that mathematically results in rapid growth of solutions in small neighborhoods of concentration points/curves. The solutions may blow up or may exhibit a very singular, spiky behavior. There is consequently a need for accurate and computationally efficient numerical methods for the chemotaxis models. In this work, we develop and study novel high-order hybrid finite-volume-finite-difference schemes for the Patlak-Keller-Segel chemotaxis system and related models. We demonstrate high-accuracy, stability and computational efficiency of the proposed schemes in a number of numerical examples.

Random blebbing motion: A simple model linking cell structural properties to migration characteristics.

If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.

Guiding cellular activity with polarized light.

Actin, cytoskeleton protein forming microfilaments, play a crucial role in cellular motility. Here we show that exposure to very low levels of polarized light guide their orientation in-vivo within the live cell. Using a simple model to describe the role of actin-filament orientation in directional cellular motion, we demonstrate that the actin polymerization/depolymerization mechanism develops primarily along this direction and, under certain conditions, can lead to guidance of the cell movement. Our results also show a dose dependent increase in actin activity in direct correspondence to the level of laser irradiance. We found that total expression of Tau protein, which stabilize microtubules, was decreased by the irradiance, indicating that exposure to the light may change the activity of kinase, leading to increased cell activity.

Fatty acid synthase reprograms the epigenome in uterine leiomyosarcomas.

SK-UT-1 uterine leiomyosarcomas (Ut-LMS) cells were transduced with a fatty acid synthase (FASN)-containing retroviral vector to recapitulate the “lipogenic phenotype of cancer.” Consistent with this model, forced expression of FASN enhanced SK-UT-1 proliferation, migration, and cellular motion. Further investigation showed FASN promotes trimethylation of H3K9 (H3K9me3) and acetylation of H3K27 (H3K27ac) in SK-UT-1 cells. In contrast, siRNA targeting of FASN in high endogenous FASN expressing SK-LMS-1 Ut-LMS cells inhibits trimethylation of H3K9 and acetylation of H3K27. Palmitate, the predominant fatty acid product of FASN, increased H3K9me3, H3K27ac and H3K27me3 detection in SK-UT-1 cells. FASN promoted histone 3 methylation and acetylation through alteration of histone 3-modifying enzymatic activities (HDAC, HDM, HMT and HAT). ChIP-seq in SK-UT-1-FASN cells with anti-H3K9me3 antibody identified regions of enriched binding compared to vector-only cells. One differentially-enriched gene, CRISP1, was investigated further by ChIP-PCR. The transcriptionally repressive function of H3K9me3 was confirmed in CRISP1. Our results provide mechanistic insight into the pathobiology of the “lipogenic phenotype of cancer.” Here, FASN reprograms the Ut-LMS epigenome through chromatin remodeling to promote the “malignant phenotype.”

Modelling osteoblast adhesion on surface-engineered biomaterials: optimisation of nanophase grain size

A double-layered model is proposed for numerically simulating osteoblast adhesion on surface-engineered biomaterials. The proposed model consists of molecular and cellular motions based on theoretical and experimental evidence and creates predictive simulations from sparse experimental data. The comparison of numerical solutions and experimental data reveals that the proposed model can explain the nonlinear behaviour of osteoblast adhesion on material surfaces in respect to nanophase grain size (0–100 nm). The model further provides insight into the optimisation of nanophase grain size on the surface of the biomaterial.

Streptozotocin is more convenient than Alloxan for the induction of Type 2 diabetes

Alloxan as well as Streptozotocin tend to be toxic glucose analogues which preferentially build up in pancreatic beta tissue via the actual GLUT2 glucose transporter. Alloxan as well as Streptozotocin would be the most notable diabetogenic chemical substances in diabetes investigation. Both tend to be cytotoxic glucose analogues. Even though their cytotoxicity is actually achieved by way of different paths, their systems of beta cellular selective motion are similar. In 1838, Wohler as well as Liebig synthesized the pyrimidine type, which these people later known as alloxan. Within 1943, alloxan grew to become of curiosity about diabetes investigation when Dunn as well as McLetchie reported it could stimulate diabetes within animals due to the particular necrosis from the pancreatic beta tissue. The ensuing insulinopenia causes a situation of fresh diabetes mellitus known as alloxan diabetes. Streptozotocin (STZ) was isolated through Streptomyces achromogenes within 1960, Streptozotocin is definitely an antimicrobial agent and it has also already been used like a chemotherapeutic alkylating agent. In 1963, Rakieteneting. reported which Streptozotocin is actually diabetogenic. Once again, this insulinopenia affliction, called Streptozotocin diabetes is brought on by the particular necrosis from the pancreatic beta tissue and Streptozotocin may be the agent of preference for the actual induction associated with diabetes mellitus within animals since. STZ is actually preferred compared to Alloxan in order to induce diabetic rat because of its higher inductive price and reduce toxicity. STZ is much better especially whenever inducing DM2, STZ as well as nicotinamide may be used within recent functions. The fatality rate associated with alloxan is actually high and result in a high reduction in bodyweight. In this short article we may demonstrates using STZ is actually more security and handy than using Alloxan for that induction associated with diabetes mellitus 2.

Extracellular matrix motion and early morphogenesis.

For over a century, embryologists who studied cellular motion in early amniotes generally assumed that morphogenetic movement reflected migration relative to a static extracellular matrix (ECM) scaffold. However, as we discuss in this Review, recent investigations reveal that the ECM is also moving during morphogenesis. Time-lapse studies show how convective tissue displacement patterns, as visualized by ECM markers, contribute to morphogenesis and organogenesis. Computational image analysis distinguishes between cell-autonomous (active) displacements and convection caused by large-scale (composite) tissue movements. Modern quantification of large-scale 'total' cellular motion and the accompanying ECM motion in the embryo demonstrates that a dynamic ECM is required for generation of the emergent motion patterns that drive amniote morphogenesis.

Cellular Contraction and Polarization Drive Collective Cellular Motion

Coordinated motions of close-packed multicellular systems typically generate cooperative packs, swirls, and clusters. These cooperative motions are driven by active cellular forces, but the physical nature of these forces and how they generate collective cellular motion remain poorly understood. Here, we study forces and motions in a confined epithelial monolayer and make two experimental observations: 1) the direction of local cellular motion deviates systematically from the direction of the local traction exerted by each cell upon its substrate; and 2) oscillating waves of cellular motion arise spontaneously. Based on these observations, we propose a theory that connects forces and motions using two internal state variables, one of which generates an effective cellular polarization, and the other, through contractile forces, an effective cellular inertia. In agreement with theoretical predictions, drugs that inhibit contractility reduce both the cellular effective elastic modulus and the frequency of oscillations. Together, theory and experiment provide evidence suggesting that collective cellular motion is driven by at least two internal variables that serve to sustain waves and to polarize local cellular traction in a direction that deviates systematically from local cellular velocity.