Counting colonies of clonogenic assays by using densitometric software.
Ontology highlight
ABSTRACT:
SUBMITTER: Niyazi M
PROVIDER: S-EPMC1770926 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Precise, objective data on brood and honey levels in honey bee colonies can be obtained through the analysis of hive frame photographs. However, accurate analysis of all the frame photographs from medium- to large-scale experiments is time-consuming. This limits the number of hives than can be practically included in honeybee studies. Faster estimation methods exist but they significantly decrease precision and their use requires a larger sample size to maintain statistical power. To resolve this issue, we created 'CombCount' a python program that automatically detects uncapped cells to speed up measurements of capped brood and capped honey on photos of frames. CombCount does not require programming skills, it was designed to facilitate colony-level research in honeybees and to provide a fast, free, and accurate alternative to older methods based on visual estimations. Six observers measured the same photos of thirty different frames both with CombCount and by manually outlining the entire capped areas with ImageJ. The results obtained were highly similar between both the observers and the two methods, but measurements with CombCount were 3.2 times faster than with ImageJ (4 and 13 min per side of the frame, respectively) and all observers were faster when using CombCount rather than ImageJ. CombCount was used to measure the proportions of capped brood and capped honey on each frame of 16 hives over a year as they developed from packages to full-size colonies over about 60 days. Our data describe the formation of brood and honey stores during the establishment of a new colony.
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Project description:Radiotherapy treatment strategies should be personalized based on the radiosensitivity of individual tumors. Clonogenic assays are the gold standard method for in vitro assessment of radiosensitivity. Reproducibility is the critical factor for scientific rigor; however, this is reduced by insufficient reporting of methodologies. In reality, the reporting standards of methodologies pertaining to clonogenic assays remain unclear. To address this, we performed a literature search and qualitative analysis of the reporting of methodologies pertaining to clonogenic assays. A comprehensive literature review identified 1672 papers that report the radiosensitivity of human cancer cells based on clonogenic assays. From the identified papers, important experimental parameters (i.e. number of biological replicates, technical replicates, radiation source and dose rate) were recorded and analyzed. We found that, among the studies, (i) 30.5% did not report biological or technical replicates; (ii) 47.0% did not use biological or technical replicates; (iii) 3.8% did not report the radiation source; and (iv) 32.3% did not report the dose rate. These data suggest that reporting of methodologies pertaining to clonogenic assays in a considerable number of previously published studies is insufficient, thereby threatening reproducibility. This highlights the need to raise awareness of standardization of the methodologies used to conduct clonogenic assays.
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Project description:Photon radiation therapy is a major curative treatment for cancer. However, the lack of robust predictive biomarkers for radiosensitivity precludes personalized radiation therapy. Clonogenic assays are the gold standard method for measuring the radiosensitivity of cancer cells. Although a large number of publications describe the use of clonogenic assays to measure cancer cell radiosensitivity, the robustness of results from different studies is unclear. To address this, we conducted a comprehensive detailed literature search of 256 common cancer cell lines and identified the eight cell lines most-frequently examined for photon sensitivity using clonogenic assays. Survival endpoints and experimental parameters from all 620 relevant experiments were compiled and analyzed. We found that the coefficients of variation for SF2 (surviving fraction after 2 Gy irradiation) and for D10 (dose that yields a surviving fraction of 10%) were below 30% for all cell lines, indicating that SF2 and D10 have acceptable inter-assay precision. These data support further analysis of published data on clonogenic assays using SF2 and D10 as survival endpoints, which facilitates robust identification of biological profiles representative of cancer cell sensitivity to photons.
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Project description:We report the development and testing of software called QuantiFly: an automated tool to quantify Drosophila egg laying. Many laboratories count Drosophila eggs as a marker of fitness. The existing method requires laboratory researchers to count eggs manually while looking down a microscope. This technique is both time-consuming and tedious, especially when experiments require daily counts of hundreds of vials. The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. The accuracy of the baseline algorithm is additionally increased in this study through correction of bias observed in the algorithm output. The QuantiFly software, which includes the refined algorithm, has been designed to be immediately accessible to scientists through an intuitive and responsive user-friendly graphical interface. The software is also open-source, self-contained, has no dependencies and is easily installed (https://github.com/dwaithe/quantifly). Compared to manual egg counts made from digital images, QuantiFly achieved average accuracies of 94% and 85% for eggs laid on transparent (defined) and opaque (yeast-based) fly media. Thus, the software is capable of detecting experimental differences in most experimental situations. Significantly, the advanced feature recognition capabilities of the software proved to be robust to food surface artefacts like bubbles and crevices. The user experience involves image acquisition, algorithm training by labelling a subset of eggs in images of some of the vials, followed by a batch analysis mode in which new images are automatically assessed for egg numbers. Initial training typically requires approximately 10 minutes, while subsequent image evaluation by the software is performed in just a few seconds. Given the average time per vial for manual counting is approximately 40 seconds, our software introduces a timesaving advantage for experiments starting with as few as 20 vials. We also describe an optional acrylic box to be used as a digital camera mount and to provide controlled lighting during image acquisition which will guarantee the conditions used in this study.
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Project description:The clonogenic or colony formation assay is a widely used method to study the number and size of cancer cell colonies that remain after irradiation or cytotoxic agent administration and serves as a measure for the anti-proliferative effect of these treatments. Alternatively, this assay is used to quantitate the transforming potential of cancer associated genes and chemical agents. Therefore, there is a need for a simplified and standardized analysis of colony formation assays for both routine laboratory use and for parallelized automated analysis. Here we describe the freely available ImageJ-plugin "ColonyArea", which is optimized for rapid and quantitative analysis of focus formation assays conducted in 6- to 24-well dishes. ColonyArea processes image data of multi-well dishes, by separating, concentrically cropping and background correcting well images individually, before colony formation is quantitated. Instead of counting the number of colonies, ColonyArea determines the percentage of area covered by crystal violet stained cell colonies, also taking the intensity of the staining and therefore cell density into account. We demonstrate that these parameters alone or in combination allow for robust quantification of IC50 values of the cytotoxic effect of two staurosporines, UCN-01 and staurosporine (STS) on human glioblastoma cells (T98G). The relation between the potencies of the two compounds compared very well with that obtained from an absorbance based method to quantify colony growth and to published data. The ColonyArea ImageJ plugin provides a simple and efficient analysis routine to quantitate assay data of one of the most commonly used cellular assays. The bundle is freely available for download as supporting information. We expect that ColonyArea will be of broad utility for cancer biologists, as well as clinical radiation scientists.
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Project description:Clonogenic assays are the gold standard for determining radiosensitivity, which governs tumor response to radiation therapy. Although multiple studies of clonogenic assays on cancer cell lines have been published, the robustness of this technique has not been examined by comparative analysis of data from different studies. To address this issue, we investigated the inter-assay precision of clonogenic assays by analyzing in-house and published data on A549, a cell line frequently studied in this context. The coefficients of variation for SF2, the surviving fraction after 2 Gy irradiation, and D10, the radiation dose that reduces survival to 10%, were below 30% for both in-house data obtained from 20 independent experiments performed under consistent experimental settings (i.e., radiation type, dose rate, and timing of cell seeding) and data collected from 192 publications using diverse experimental settings. Multivariate analyses of the published data revealed that timing of cell seeding significantly affected SF2. These data indicate that SF2 and D10 of clonogenic assay have acceptable inter-assay precision, and that timing of cell seeding influences the inter-assay precision of SF2. These results provide a rationale for combined analysis of published clonogenic assay data, which may help to discover robust biological properties associated with tumor radiosensitivity.
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Project description:We describe an information-theory-based method and associated software for computationally identifying sister spores derived from the same meiotic tetrad. The method exploits specific DNA sequence features of tetrads that result from meiotic centromere and allele segregation patterns. Because the method uses only the genomic sequence, it alleviates the need for tetrad-specific barcodes or other genetic modifications to the strains. Using this method, strains derived from randomly arrayed spores can be efficiently grouped back into tetrads.
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Project description:BackgroundHigh-dose synchrotron microbeam radiation therapy (MRT) has shown the potential to deliver improved outcomes over conventional broadbeam (BB) radiation therapy. To implement synchrotron MRT clinically for cancer treatment, it is necessary to undertake dose equivalence studies to identify MRT doses that give similar outcomes to BB treatments.AimTo develop an in vitro approach to determine biological dose equivalence between MRT and BB using two different cell-based assays.MethodsThe acute response of tumour and normal cell lines (EMT6.5, 4T1.2, NMuMG, EMT6.5ch, 4T1ch5, SaOS-2) to MRT (50-560 Gy) and BB (1.5-10 Gy) irradiation was investigated using clonogenic and real time cell impedance sensing (RT-CIS)/xCELLigence assays. MRT was performed using a lattice of 25 or 50 µm-wide planar, polychromatic kilovoltage X-ray microbeams with 200 µm peak separation. BB irradiations were performed using a Co60 teletherapy unit or a synchrotron radiation source. BB doses that would generate biological responses similar to MRT were calculated by data interpolation and verified by clonogenic and RT-CIS assays.ResultsFor a given cell line, MRT equivalent BB doses identified by RT-CIS/xCELLigence were similar to those identified by clonogenic assays. Dose equivalence between MRT and BB were verified in vitro in two cell lines; EMT6.5ch and SaOS-2 by clonogenic assays and RT-CIS/xCELLigence. We found for example, that BB doses of 3.4±0.1 Gy and 4.40±0.04 Gy were radiobiologically equivalent to a peak, microbeam dose of 112 Gy using clonogenic and RT-CIS assays respectively on EMT6.5ch cells.ConclusionOur data provides the first determination of biological dose equivalence between BB and MRT modalities for different cell lines and identifies RT-CIS/xCELLigence assays as a suitable substitute for clonogenic assays. These results will be useful for the safe selection of MRT doses for future veterinary and clinical trials.
| S-EPMC4063937 | biostudies-literature