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Quantitation of fibroblast population growth rate in situ using computerized image analysis

✍ Scribed by Michael A. Perricone; Veronica Saldate; Dallas M. Hyde


Publisher
John Wiley and Sons
Year
1995
Tongue
English
Weight
899 KB
Volume
31
Category
Article
ISSN
1059-910X

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✦ Synopsis


The development of computer-assisted image analysis has provided the technology to rapidly determine the population size of cultured cell monolayers in situ. We have adapted this technology to determine the population growth rate of cultured fibroblasts for use in a highreplicate format. Human lung fibroblasts were seeded into 112 A 96-well plates that had one-half the culture area of standard 96-well plates. The cells were cultured in medium supplemented with different concentrations of FBS and on days 0,1, 2,3,5, and 7, and their nuclei were stained with propidium iodide. A microscopic field representing one-quarter of a well of fluorescent nuclear images was captured onto a Macintosh computer, and the number of nuclei were counted using an image analysis software program. There were no significant differences between the number of nuclei counted manually and the number counted using computer-assisted software, until day 7 where the cells were multilayered (P < 0.05). This image analysis method was compared to other assays typically used to estimate cell proliferation or population size, namely hemocytometer counting, a rapid colorimetric staining assay using naphthol blue-black, and [3H]-thymidine incorporation. The growth rates derived using image analysis were in close agreement with results derived from hemocytometer counts and r3H1-thymidine incorporation. However, the growth rates of cells grown in high concentrations of FBS as determined using naphthol blue-black were substantially lower than results from image analysis. We conclude that this adaptation of computer-assisted image analysis provides a method to derive accurate growth curves by directly counting the number of cells in a large number of replicates.

Cell count, Cell division, Computer-assisted image processing o 1995 Wiley-Liss, Inc.