Effects of fixation method on image cytometric measurement of DNA content and distribution in cells stained for fluorescence with propidium iodide.

Poulin, Neal; Matthews, Jeffrey B.; Skov, Kirsten A.; Palcic, Branko

doi:10.1177/42.8.8027534

Cited by 14 publications

(10 citation statements)

References 9 publications

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“…On the contrary, 50% ethanol fixation has been suggested as the fixation of choice when DNA analysis requires a balance of homogeneity of staining and high resolution of staining (Poulin et al, 1994). Ethanol mechanism of action has not been associated with DNA changes.…”

Section: Discussionmentioning

confidence: 99%

Metamorphosis inXenopus laevisis not associated with large-scale nuclear DNA content variation

Freeman

Rayburn

2004

Journal of Experimental Biology

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presence of nuclei of variable fluorescence intensity within the unfixed nuclei. Upon optimum fixation, which has been speculated to result in more homogeneous chromatin conformation and to reduce staining artifacts, the nuclei were observed to have less fluorescence intensity variation. The differential fluorescence observed in this study is consistent with the hypothesis that large-scale intraindividual DNA variation is not associated with amphibian metamorphosis.

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Section: Discussionmentioning

confidence: 99%

Metamorphosis inXenopus laevisis not associated with large-scale nuclear DNA content variation

Freeman

Rayburn

2004

Journal of Experimental Biology

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“…In contrast, certain phenotypes, like changes in DNA content, are impossible to discern by eye. Unlike whole population-based methods, image cytometry measures individual cell fluorescence intensities so that the DNA content of DNA-stained cells can be determined [46,47]. These measurements are very easily degraded by anomalies in the illumination of the field of view and poor identification algorithms (the most common errors are counting two nearby nuclei as one nucleus with twice the DNA content and incorrectly splitting a nucleus into two half-nuclei).…”

Section: Validation Of Cellprofiler For Many Phenotypesmentioning

confidence: 99%

CellProfiler: image analysis software for identifying and quantifying cell phenotypes

et al. 2006

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This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Cell image analysis software

CellProfiler, the first free, open-source system for flexible and high-throughput cell image analysis is described.

AbstractBiologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining). RationaleExamining cells by microscopy has long been a primary method for studying cellular function. When cells are stained appropriately, visual analysis can reveal biological mechanisms. Advanced microscopes can now, in a single day, easily collect thousands of high resolution images of cells from timelapse experiments and from large-scale screens using chemical compounds, RNA interference (RNAi) reagents, or expression plasmids [1][2][3][4][5]. However, a bottleneck exists at the image analysis stage. Several pioneering large screens have been scored through visual inspection by expert biologists [6,7], whose interpretive ability will not soon be replicated by a computer. Still, for most applications, image cytometry (automated cell image analysis) is strongly preferable to analysis by eye. In fact, in some cases image cytometry is absolutely required to extract the full spectrum of information present in biological images, for reasons we discuss here.First, while human observers typically score one or at most a few cellular features, image cytometry simultaneously yields many informative measures of cells, including the intensity and localization of each fluorescently labeled cellular component (for example, DNA or protein) within each subcellular compartment, as well as the number, size, and shape of those subcellular compartments. Image-based analysis is thus versatile, inherently multiplexed, and high in information content. Like flow cytometry, image cytometry measures the percell amount of protein and DNA, but can more conveniently handle hundreds of thousands of distinct samples and is also compatible with adherent cell types, time-lapse samples, and intact tissues. In addition, image cytometry can accurately

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“…Cell cycle analysis was performed by DNA image cytometry using integrated optical intensity histograms (Poulin et al 1994). The cultures synchronized at G 1 /S transition phase and S phase contained approx.…”

Section: Cell Proliferation and Phase Distributionmentioning

confidence: 99%

Heterogeneity in tumor cell energetic metabolome at different cell cycle phases of human colon cancer cell lines

Maddula

Baumbach

2010

Metabolomics

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In this present study, the efficacy of metabolomics as a tool for tumor cell energetics for in vitro cell cultures was demonstrated with full competence for the first time by elucidating the anabolic and energy-yielding segments of glycolysis and glutaminolysis, which constitute a part of energy metabolism in tumor cells. By synchronizing colon cancer cells SW480 and SW620 in culture, the metabolome specific to cell cycle phases was analyzed using nuclear magnetic resonance spectroscopy. At the G 1 /S transition of the cell cycle (i.e. transition from cell growth to duplication of genetic material), the majority of the energy production was realized by glycolysis through a high channeling of glucose carbons towards lactate. During the late S phase, the majority of energy was produced by glutaminolysis through a high channeling of glutamine carbons towards lactate, while the glucose carbons were channeled towards bio-synthetic pathways. These results indicate that the metabolism of proliferating cells is heterogeneous throughout the cell cycle and can be better interpreted on the basis of different cell cycle phases. These findings could be exploited for the development of a tool for tumor diagnosis as well as for targeting tumors.

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Effects of fixation method on image cytometric measurement of DNA content and distribution in cells stained for fluorescence with propidium iodide.

Cited by 14 publications

References 9 publications

Metamorphosis inXenopus laevisis not associated with large-scale nuclear DNA content variation

Metamorphosis inXenopus laevisis not associated with large-scale nuclear DNA content variation

CellProfiler: image analysis software for identifying and quantifying cell phenotypes

Heterogeneity in tumor cell energetic metabolome at different cell cycle phases of human colon cancer cell lines

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