High throughput quantification of cells with complex morphology in mixed cultures.
Automated image-based and biochemical assays have greatly increased throughput for quantifying cell numbers in in vitro studies. However, it has been more difficult to automate the counting of specific cell types with complex morphologies in mixed cell cultures. We have developed a fully automated, fast, accurate and objective method for the quantification of primary human GFAP-positive astrocytes and CD45-positive microglia from images of mixed cell populations. This method, called the complex cell count (CCC) assay, utilizes a combination of image processing and analysis operations from MetaMorph (Version 6.2.6, Molecular Devices). The CCC assay consists of four main aspects: image processing with a unique combination of morphology filters; digital thresholding; integrated morphometry analysis; and a configuration of object standards. The time needed to analyze each image is 1.82s. Significant correlations have been consistently achieved between the data obtained from CCC analysis and manual cell counts. This assay can quickly and accurately quantify the number of human astrocytes and microglia in mixed cell culture and can be applied to quantifying a range of other cells/objects with complex morphology in neuroscience research.
Narayan
Pritika J
PJ
Department of Pharmacology and Clinical Pharmacology, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
Gibbons
Hannah M
HM
Mee
Edward W
EW
Faull
Richard L
RL
Dragunow
Michael
M
D000328:Adult; D001921:Brain / Q000166:cytology*; D002452:Cell Count / Q000379:methods*; D002478:Cells, Cultured; D003952:Diagnostic Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009474:Neurons / Q000166:cytology* / Q000502:physiology*; D013223:Statistics as Topic