APM_GUI: analyzing particle movement on the cell membrane and determining confinement

<p>Abstract</p> <p>Background</p> <p>Single-particle tracking is a powerful tool for tracking individual particles with high precision. It provides useful information that allows the study of diffusion properties as well as the dynamics of movement. Changes in particle movement behavior, such as transitions between Brownian motion and temporary confinement, can reveal interesting biophysical interactions. Although useful applications exist to determine the paths of individual particles, only a few software implementations are available to analyze these data, and these implementations are generally not user-friendly and do not have a graphical interface,.</p> <p>Results</p> <p>Here, we present APM_GUI (Analyzing Particle Movement), which is a MatLab-implemented application with a Graphical User Interface. This user-friendly application detects confined movement considering non-random confinement when a particle remains in a region longer than a Brownian diffusant would remain. In addition, APM_GUI exports the results, which allows users to analyze this information using software that they are familiar with.</p> <p>Conclusions</p> <p>APM_GUI provides an open-source tool that quantifies diffusion coefficients and determines whether trajectories have non-random confinements. It also offers a simple and user-friendly tool that can be used by individuals without programming skills.</p

A random cell motility gradient downstream of FGF controls elongation of amniote embryos

Vertebrate embryos are characterized by an elongated antero-posterior (AP) body axis, which forms by progressive cell deposition from a posterior growth zone in the embryo. Here, we used tissue ablation in the chicken embryo to demonstrate that the caudal presomitic mesoderm (PSM) has a key role in axis elongation. Using time-lapse microscopy, we analysed the movements of fluorescently labelled cells in the PSM during embryo elongation, which revealed a clear posterior-to-anterior gradient of cell motility and directionality in the PSM. We tracked the movement of the PSM extracellular matrix in parallel with the labelled cells and subtracted the extracellular matrix movement from the global motion of cells. After subtraction, cell motility remained graded but lacked directionality, indicating that the posterior cell movements associated with axis elongation in the PSM are not intrinsic but reflect tissue deformation. The gradient of cell motion along the PSM parallels the fibroblast growth factor (FGF)/mitogen-activated protein kinase (MAPK) gradient1, which has been implicated in the control of cell motility in this tissue2. Both FGF signalling gain- and loss-of-function experiments lead to disruption of the motility gradient and a slowing down of axis elongation. Furthermore, embryos treated with cell movement inhibitors (blebbistatin or RhoK inhibitor), but not cell cycle inhibitors, show a slower axis elongation rate. We propose that the gradient of random cell motility downstream of FGF signalling in the PSM controls posterior elongation in the amniote embryo. Our data indicate that tissue elongation is an emergent property that arises from the collective regulation of graded, random cell motion rather than by the regulation of directionality of individual cellular movements

Parameter identification problems in the modelling of cell motility

We present a novel parameter identification algorithm for the estimation of parameters in models of cell motility using imaging data of migrating cells. Two alternative formulations of the objective functional that measures the difference between the computed and observed data are proposed and the parameter identification problem is formulated as a minimisation problem of nonlinear least squares type. A Levenberg–Marquardt based optimisation method is applied to the solution of the minimisation problem and the details of the implementation are discussed. A number of numerical experiments are presented which illustrate the robustness of the algorithm to parameter identification in the presence of large deformations and noisy data and parameter identification in three dimensional models of cell motility. An application to experimental data is also presented in which we seek to identify parameters in a model for the monopolar growth of fission yeast cells using experimental imaging data. Our numerical tests allow us to compare the method with the two different formulations of the objective functional and we conclude that the results with both objective functionals seem to agree

Anomalous Diffusion Induced by Cristae Geometry in the Inner Mitochondrial Membrane

Diffusion of inner membrane proteins is a prerequisite for correct functionality of mitochondria. The complicated structure of tubular, vesicular or flat cristae and their small connections to the inner boundary membrane impose constraints on the mobility of proteins making their diffusion a very complicated process. Therefore we investigate the molecular transport along the main mitochondrial axis using highly accurate computational methods. Diffusion is modeled on a curvilinear surface reproducing the shape of mitochondrial inner membrane (IM). Monte Carlo simulations are carried out for topologies resembling both tubular and lamellar cristae, for a range of physiologically viable crista sizes and densities. Geometrical confinement induces up to several-fold reduction in apparent mobility. IM surface curvature per se generates transient anomalous diffusion (TAD), while finite and stable values of projected diffusion coefficients are recovered in a quasi-normal regime for short- and long-time limits. In both these cases, a simple area-scaling law is found sufficient to explain limiting diffusion coefficients for permeable cristae junctions, while asymmetric reduction of the junction permeability leads to strong but predictable variations in molecular motion rate. A geometry-based model is given as an illustration for the time-dependence of diffusivity when IM has tubular topology. Implications for experimental observations of diffusion along mitochondria using methods of optical microscopy are drawn out: a non-homogenous power law is proposed as a suitable approach to TAD. The data demonstrate that if not taken into account appropriately, geometrical effects lead to significant misinterpretation of molecular mobility measurements in cellular curvilinear membranes

53BP1 promotes non-homologous end joining of telomeres by increasing chromatin mobility

Double-strand breaks activate the ataxia telangiectasia mutated (ATM) kinase, which promotes the accumulation of DNA damage factors in the chromatin surrounding the break. The functional significance of the resulting DNA damage foci is poorly understood. Here we show that 53BP1 (also known as TRP53BP1), a component of DNA damage foci, changes the dynamic behaviour of chromatin to promote DNA repair. We used conditional deletion of the shelterin component TRF2 (also known as TERF2) from mouse cells (TRF2fl/-) to deprotect telomeres, which, like double-strand breaks, activate the ATM kinase, accumulate 53BP1 and are processed by non-homologous end joining (NHEJ). Deletion of TRF2 from 53BP1-deficient cells established that NHEJ of dysfunctional telomeres is strongly dependent on the binding of 53BP1 to damaged chromosome ends. To address the mechanism by which 53BP1 promotes NHEJ, we used time-lapse microscopy to measure telomere dynamics before and after their deprotection. Imaging showed that deprotected telomeres are more mobile and sample larger territories within the nucleus. This change in chromatin dynamics was dependent on 53BP1 and ATM but did not require a functional NHEJ pathway. We propose that the binding of 53BP1 near DNA breaks changes the dynamic behaviour of the local chromatin, thereby facilitating NHEJ repair reactions that involve distant sites, including joining of dysfunctional telomeres and AID (also known as AICDA)-induced breaks in immunoglobulin class-switch recombination

Protein Diffusion in Mammalian Cell Cytoplasm

We introduce a new method for mesoscopic modeling of protein diffusion in an entire cell. This method is based on the construction of a three-dimensional digital model cell from confocal microscopy data. The model cell is segmented into the cytoplasm, nucleus, plasma membrane, and nuclear envelope, in which environment protein motion is modeled by fully numerical mesoscopic methods. Finer cellular structures that cannot be resolved with the imaging technique, which significantly affect protein motion, are accounted for in this method by assigning an effective, position-dependent porosity to the cell. This porosity can also be determined by confocal microscopy using the equilibrium distribution of a non-binding fluorescent protein. Distinction can now be made within this method between diffusion in the liquid phase of the cell (cytosol/nucleosol) and the cytoplasm/nucleoplasm. Here we applied the method to analyze fluorescence recovery after photobleach (FRAP) experiments in which the diffusion coefficient of a freely-diffusing model protein was determined for two different cell lines, and to explain the clear difference typically observed between conventional FRAP results and those of fluorescence correlation spectroscopy (FCS). A large difference was found in the FRAP experiments between diffusion in the cytoplasm/nucleoplasm and in the cytosol/nucleosol, for all of which the diffusion coefficients were determined. The cytosol results were found to be in very good agreement with those by FCS

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images

<p>Abstract</p> <p>Background</p> <p>Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed.</p> <p>Results</p> <p>To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies.</p> <p>Conclusions</p> <p>These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.</p

A Stochastic Model for Microtubule Motors Describes the In Vivo Cytoplasmic Transport of Human Adenovirus

Cytoplasmic transport of organelles, nucleic acids and proteins on microtubules is usually bidirectional with dynein and kinesin motors mediating the delivery of cargoes in the cytoplasm. Here we combine live cell microscopy, single virus tracking and trajectory segmentation to systematically identify the parameters of a stochastic computational model of cargo transport by molecular motors on microtubules. The model parameters are identified using an evolutionary optimization algorithm to minimize the Kullback-Leibler divergence between the in silico and the in vivo run length and velocity distributions of the viruses on microtubules. The present stochastic model suggests that bidirectional transport of human adenoviruses can be explained without explicit motor coordination. The model enables the prediction of the number of motors active on the viral cargo during microtubule-dependent motions as well as the number of motor binding sites, with the protein hexon as the binding site for the motors

PhagoSight: an open-source MATLAB® package for the analysis of fluorescent neutrophil and macrophage migration in a zebrafish model

Neutrophil migration in zebrafish larvae is increasingly used as a model to study the response of these leukocytes to different determinants of the cellular inflammatory response. However, it remains challenging to extract comprehensive information describing the behaviour of neutrophils from the multi-dimensional data sets acquired with widefield or confocal microscopes. Here, we describe PhagoSight, an open-source software package for the segmentation, tracking and visualisation of migrating phagocytes in three dimensions. The algorithms in PhagoSight extract a large number of measurements that summarise the behaviour of neutrophils, but that could potentially be applied to any moving fluorescent cells. To derive a useful panel of variables quantifying aspects of neutrophil migratory behaviour, and to demonstrate the utility of PhagoSight, we evaluated changes in the volume of migrating neutrophils. Cell volume increased as neutrophils migrated towards the wound region of injured zebrafish. PhagoSight is openly available as MATLAB® m-files under the GNU General Public License. Synthetic data sets and a comprehensive user manual are available from http://www.phagosight.org