Time-lapse microscopy
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Biocompatibility testing of new materials is often performed in vitro by measuring the growth rate of mammalian cancer cells in time-lapse images acquired by phase contrast microscopes. The growth rate is measured by tracking cell coverage, which requires an accurate automatic segmentation method. However, cancer cells have irregular shapes that change over time, the mottled background pattern is partially visible through the cells and the images contain artifacts such as halos. We developed a novel algorithm for cell segmentation that copes with the mentioned challenges. It is based on temporal differences of consecutive images and a combination of thresholding, blurring, and morphological operations. We tested the algorithm on images of four cell types acquired by two different microscopes, evaluated the precision of segmentation against manual segmentation performed by a human operator, and finally provided comparison with other freely available methods. We propose a new, fully automated method for measuring the cell growth rate based on fitting a coverage curve with the Verhulst population model. The algorithm is fast and shows accuracy comparable with manual segmentation. Most notably it can correctly separate live from dead cells.
The analysis of dynamic cellular processes such as plant cytokinesis stands and falls with live-cell time-lapse confocal imaging. Conventional approaches to time-lapse imaging of cell division in Arabidopsis root tips are tedious and have low throughput. Here, we describe a protocol for long-term time-lapse simultaneous imaging of multiple root tips on a vertical-stage confocal microscope with automated root tracking. We also provide modifications of the basic protocol to implement this imaging method in the analysis of genetic, pharmacological or laser ablation wounding-mediated experimental manipulations. Our method dramatically improves the efficiency of cell division time-lapse imaging by increasing the throughput, while reducing the person-hour requirements of such experiments.
- MeSH
- Arabidopsis * MeSH
- buněčné dělení MeSH
- časosběrné zobrazování MeSH
- konfokální mikroskopie MeSH
- lidé MeSH
- meristém MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
We used hybrid detectors (HyDs) to monitor the trajectories and interactions of promyelocytic leukemia (GFP-PML) nuclear bodies (NBs) and mCherry-53BP1-positive DNA lesions. 53BP1 protein accumulates in NBs that occur spontaneously in the genome or in γ-irradiation-induced foci. When we induced local DNA damage by ultraviolet irradiation, we also observed accumulation of 53BP1 proteins into discrete bodies, instead of the expected dispersed pattern. In comparison with photomultiplier tubes, which are used for standard analysis by confocal laser scanning microscopy, HyDs significantly eliminated photobleaching of GFP and mCherry fluorochromes during image acquisition. The low laser intensities used for HyD-based confocal analysis enabled us to observe NBs for the longer time periods, necessary for studies of the trajectories and interactions of PML and 53BP1 NBs. To further characterize protein interactions, we used resonance scanning and a novel bioinformatics approach to register and analyze the movements of individual PML and 53BP1 NBs. The combination of improved HyD-based confocal microscopy with a tailored bioinformatics approach enabled us to reveal damage-specific properties of PML and 53BP1 NBs.
- MeSH
- akutní promyelocytární leukemie metabolismus patologie MeSH
- časosběrné zobrazování MeSH
- DNA chemie metabolismus MeSH
- intracelulární signální peptidy a proteiny metabolismus MeSH
- intranukleární inkluzní tělíska metabolismus ultrastruktura MeSH
- konfokální mikroskopie přístrojové vybavení metody MeSH
- lidé MeSH
- nádorové buněčné linie MeSH
- poškození DNA MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- hodnotící studie MeSH
- práce podpořená grantem MeSH
SIGNIFICANCE: Machine learning is increasingly being applied to the classification of microscopic data. In order to detect some complex and dynamic cellular processes, time-resolved live-cell imaging might be necessary. Incorporating the temporal information into the classification process may allow for a better and more specific classification. AIM: We propose a methodology for cell classification based on the time-lapse quantitative phase images (QPIs) gained by digital holographic microscopy (DHM) with the goal of increasing performance of classification of dynamic cellular processes. APPROACH: The methodology was demonstrated by studying epithelial-mesenchymal transition (EMT) which entails major and distinct time-dependent morphological changes. The time-lapse QPIs of EMT were obtained over a 48-h period and specific novel features representing the dynamic cell behavior were extracted. The two distinct end-state phenotypes were classified by several supervised machine learning algorithms and the results were compared with the classification performed on single-time-point images. RESULTS: In comparison to the single-time-point approach, our data suggest the incorporation of temporal information into the classification of cell phenotypes during EMT improves performance by nearly 9% in terms of accuracy, and further indicate the potential of DHM to monitor cellular morphological changes. CONCLUSIONS: Proposed approach based on the time-lapse images gained by DHM could improve the monitoring of live cell behavior in an automated fashion and could be further developed into a tool for high-throughput automated analysis of unique cell behavior.
Responses of cell populations in vitro to toxic substances are very dynamic and exceed hours or even days. Toxicologists realise that cell-based dynamic assays can acquire important additional information about toxic responses of individual cell within a treated population. In the past, this type of cellular dynamics could have been monitored only with the help of time-lapse microcinematography. In spite of several advantages, the time-lapse approach has been used relatively infrequently in the routine in vitro cytotoxicity assessment. The main reasons were demanding time and work schedules, problems with quantification of visual information, and lack of mechanistic data. Recently, the situation has changed dramatically. The progress in digital imaging technology coincides with enormous development in the field of fluorescence microscopy. With the help of specific fluorochromes or fluorescent proteins we can now analyse practically all sub-cellular and cellular events. Some producers developed large-scale high-throughput systems for live cell imaging. Nevertheless, there has been significant progress in small-scale approach as well. New versions of motorised microscopes are fulfilling principal demands for in vitro assessment of toxic effects: ease of performance, high-throughput of data, quantitative cell-based analysis, simultaneous assessment of several parameters, and control of the environment conditions for cultivation of cells. In this paper, we present our experience with two of these systems designed for long-lasting observation of living cells in phase contrast and fluorescence. Our aim is to draw attention to the suitability of small-scale cell-based assays for determination of cytotoxicity in vitro. We believe that these methods could be considered as a further step towards the replacement of animal testing.
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- audiovizuální záznam metody přístrojové vybavení MeSH
- buněčné kultury MeSH
- časové faktory MeSH
- financování organizované MeSH
- fluorescenční mikroskopie metody MeSH
- fyziologie buňky účinky léků MeSH
- toxikologie metody MeSH
- viabilita buněk účinky léků MeSH
- videomikroskopie MeSH
- xenobiotika toxicita MeSH
- Publikační typ
- srovnávací studie MeSH
The dynamics of nuclear morphology changes during apoptosis remains poorly investigated and understood. Using 3D time-lapse confocal microscopy we performed a study of early-stage apoptotic nuclear morphological changes induced by etoposide in single living HepG2 cells. These observations provide a definitive evidence that nuclear apoptotic volume decrease (AVD) is occurring simultaneously with peripheral chromatin condensation (so called "apoptotic ring"). In order to describe quantitatively the dynamics of nuclear morphological changes in the early stage of apoptosis we suggest a general molecular kinetic model, which fits well the obtained experimental data in our study. Results of this work may clarify molecular mechanisms of nuclear morphology changes during apoptosis.
- MeSH
- analýza jednotlivých buněk metody MeSH
- apoptóza fyziologie MeSH
- buněčné jádro fyziologie ultrastruktura MeSH
- buňky Hep G2 MeSH
- časosběrné zobrazování metody MeSH
- chromatin chemie metabolismus ultrastruktura MeSH
- kinetika MeSH
- konfokální mikroskopie MeSH
- lidé MeSH
- sbalení DNA MeSH
- teoretické modely * MeSH
- velikost organel fyziologie MeSH
- zobrazování trojrozměrné MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
... Kreft (Ljubjana) -- 14.00 -14.20 Rescuing real time three-dimensional scanning electron microscopy (L7 ... ... Cižmár (Brno) -- 15.20-15.30 Visualisation of kidney glomeruli in real time video-rate confocal reflection ... ... microscopy (LI 1) A. ... ... Holecek (Pilsen) -- 9.20 - 9.40 Low-coherence holographic microscope image Characteristics & Time lapse ...
42 s. ; 30 cm
- MeSH
- buňky cytologie MeSH
- fyziologie buňky MeSH
- mikrofilmy přístrojové vybavení trendy MeSH
- mikroskopie metody normy přístrojové vybavení MeSH
- Publikační typ
- přehledy MeSH
Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical. The measure behavior is extensively analyzed based on the tracking results provided by the participants of the first Cell Tracking Challenge hosted by the 2013 IEEE International Symposium on Biomedical Imaging. We demonstrate the robustness and stability of the measure against small changes in the choice of weights for diverse cell tracking algorithms and fluorescence microscopy datasets. As the measure penalizes all possible errors in the tracking results and is easy to compute, it may especially help developers and analysts to tune their algorithms according to their needs.
