Low-Cost Motility Tracking System (LOCOMOTIS) for Time-Lapse Microscopy Applications and Cell Visualisation (original) (raw)
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Automated time-lapse microscopy and high-resolution tracking of cell migration
Cytotechnology, 2006
We describe a novel fully automated high-throughput time-lapse microscopy system and evaluate its performance for precisely tracking the motility of several glioma and osteoblastic cell lines. Use of this system revealed cell motility behavior not discernable with conventional techniques by collecting data (1) from closely spaced time points (minutes), (2) over long periods (hours to days), (3) from multiple areas of interest, (4) in parallel under several different experimental conditions. Quantitation of true individual and average cell velocity and path length was obtained with high spatial and temporal resolution in “scratch” or “wound healing” assays. This revealed unique motility dynamics of drug-treated and adhesion molecule-transfected cells and, thus, this is a considerable improvement over current methods of measurement and analysis. Several fluorescent vital labeling methods commonly used for end-point analyses (GFP expression, DiO lipophilic dye, and Qtracker nanocrystal...
Investigation of Cell Dynamics in Vitro by Time Lapse Microscopy and Image Analysis
Chemical engineering transactions, 2014
Pharmacological research is continuously working on the development of new drugs. This research typically starts from the formulation of new molecules that are first investigated at the cell scale, finally is completed with clinical trials. Investigation on the cell scale requires simple, reproducible and reliable assays, able to simulate physiological conditions in the lab. A wide range of biological processes, such as angiogenesis, inflammation, tissue regeneration, tumour growth and invasion, are strongly linked to cell proliferation and migration mechanisms that govern the dynamic evolution of both individual cells and cell aggregates. In this work we present an experimental methodology for the quantitative investigation of cell dynamics in vitro by live imaging of biological soft matter. Cell motility is observed by means of a Time Lapse Microscopy workstation, consisting of a motorized video-microscope equipped with an incubating system, and quantified by image analysis techniques. We report some preliminary experimental results relative to the migration of a tumour cell line both in random condition and in presence of an external stimulus, such as a chemical concentration gradient. The ultimate goal of this research is the development of a standard assay to be used as a test for drug efficiency, suitable for routine application in the pharmaceutical research.
Automated live cell imaging systems reveal dynamic cell behavior
Biotechnology Progress, 2011
Key features for time-lapsed microscopic imaging technology include robotic stage movement, long-term incubation control, and camera/imaging capabilities with both magnification adjustment and fluorescent capability. Many research labs utilize custom-built systems. More recently, several commercial suppliers have developed systems with a wide range of capabilities.
Scientific Reports, 2019
Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors’ discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the ...
Automated measurement of cell motility and proliferation
BMC Cell Biology, 2005
Background Time-lapse microscopic imaging provides a powerful approach for following changes in cell phenotype over time. Visible responses of whole cells can yield insight into functional changes that underlie physiological processes in health and disease. For example, features of cell motility accompany molecular changes that are central to the immune response, to carcinogenesis and metastasis, to wound healing and tissue regeneration, and to the myriad developmental processes that generate an organism. Previously reported image processing methods for motility analysis required custom viewing devices and manual interactions that may introduce bias, that slow throughput, and that constrain the scope of experiments in terms of the number of treatment variables, time period of observation, replication and statistical options. Here we describe a fully automated system in which images are acquired 24/7 from 384 well plates and are automatically processed to yield high-content motility and morphological data. Results We have applied this technology to study the effects of different extracellular matrix compounds on human osteoblast-like cell lines to explore functional changes that may underlie processes involved in bone formation and maintenance. We show dose-response and kinetic data for induction of increased motility by laminin and collagen type I without significant effects on growth rate. Differential motility response was evident within 4 hours of plating cells; long-term responses differed depending upon cell type and surface coating. Average velocities were increased approximately 0.1 um/min by ten-fold increases in laminin coating concentration in some cases. Comparison with manual tracking demonstrated the accuracy of the automated method and highlighted the comparative imprecision of human tracking for analysis of cell motility data. Quality statistics are reported that associate with stage noise, interference by non-cell objects, and uncertainty in the outlining and positioning of cells by automated image analysis. Exponential growth, as monitored by total cell area, did not linearly correlate with absolute cell number, but proved valuable for selection of reliable tracking data and for disclosing between-experiment variations in cell growth. Conclusion These results demonstrate the applicability of a system that uses fully automated image acquisition and analysis to study cell motility and growth. Cellular motility response is determined in an unbiased and comparatively high throughput manner. Abundant ancillary data provide opportunities for uniform filtering according to criteria that select for biological relevance and for providing insight into features of system performance. Data quality measures have been developed that can serve as a basis for the design and quality control of experiments that are facilitated by automation and the 384 well plate format. This system is applicable to large-scale studies such as drug screening and research into effects of complex combinations of factors and matrices on cell phenotype.
Differential Optical Flow for Automated Cell Motility
1831
Image analysis of time-lapse microscopy images was performed using a temporal differential optical flow algorithm that generated a one-dimensional, time-dependent signal proportional to cellular motion. We found that exposure to the metabolic toxin NaF and chemical fixation with paraformaldehyde resulted in statistically significant decreases in differential optical flow (p<0.001). Additionally, we report the exponential decrease in differential optical flow upon exposure to NaF with a decay time constant that is strongly dependent on toxin concentration (R 2 = 0.43).
Cytometry
Background: Eukaryotic cell motility plays a key role during development, wound healing, and tumour invasion. Computer-assisted image analysis now makes it a realistic task to quantify individual cell motility of a large number of cells. However, the influence of culture conditions before and during measurements has not been investigated systematically. Methods: We have evaluated intraassay and interassay variations in determinations of cellular speed of fibroblastoid L929 cells and investigated the effects of a series of physical and biological parameters on the motile behavior of this cell line. Cellular morphology and organization of filamentous actin were assessed by means of phase-contrast and confocal laser scanning microscopy and compared to the corresponding motility data. Results: Cell dissociation procedure, seeding density, time of cultivation, and substrate concentration were shown to affect cellular speed significantly. pH and temperature of the medium most profoundly influenced cell motility and morphology. Thus, the mean cell speed was 40% lower at pH 7.25 than at pH 7.6; at 29°C, it was approximately four times lower than at 39°C. Conclusion: Of the parameters evaluated, cell motility was most strongly affected by changes in pH and temperature. In general, changes in cell speed were accompanied by alterations in cell morphology and organization of filamentous actin, although no consistent phenotypic characteristics could be demonstrated for cells exhibiting high cell speed.
Scientific Reports, 2017
Cell motility is governed by a complex molecular machinery that converts physico-chemical cues into whole-cell movement. Understanding the underlying biophysical mechanisms requires the ability to measure physical quantities inside the cell in a simple, reproducible and preferably non-invasive manner. To this end, we developed BioFlow, a computational mechano-imaging method and associated software able to extract intracellular measurements including pressure, forces and velocity everywhere inside freely moving cells in two and three dimensions with high spatial resolution in a non-invasive manner. This is achieved by extracting the motion of intracellular material observed using fluorescence microscopy, while simultaneously inferring the parameters of a given theoretical model of the cell interior. We illustrate the power of BioFlow in the context of amoeboid cell migration, by modelling the intracellular actin bulk flow of the parasite Entamoeba histolytica using fluid dynamics, and report unique experimental measures that complement and extend both theoretical estimations and invasive experimental measures. Thanks to its flexibility, BioFlow is easily adaptable to other theoretical models of the cell, and alleviates the need for complex or invasive experimental conditions, thus constituting a powerful tool-kit for mechano-biology studies. BioFlow is open-source and freely available via the Icy software.
Cell_motility: a cross-platform, open source application for the study of cell motion paths
2006
Background: Migration is an important aspect of cellular behaviour and is therefore widely studied in cell biology. Numerous components are known to participate in this process in a highly dynamic manner. In order to obtain a better insight in cell migration, mutants or drugs are used and their motive phenotype is then linked with the disturbing factors. One of the typical approaches to study motion paths of individual cells relies on fitting mean square displacements to a persistent random walk function. Since the numerous calculations involved often rely on diverse commercial software packages, the analysis can be expensive, labour-intensive and error-prone work. Additionally, due to the nature of algorithms employed the calculations involved are not readily reproducible without access to the exact software package(s) used.