High throughput quantification of cells with complex morphology in mixed cultures

Area of Science:

• Neuroscience
• Cell Biology
• Biotechnology

Background:

• Automated assays enhance cell quantification in vitro.
• Counting specific cell types with complex morphologies in mixed cultures remains challenging.

Purpose of the Study:

• To develop a fully automated, fast, accurate, and objective method for quantifying primary human GFAP-positive astrocytes and CD45-positive microglia.
• To address limitations in automated cell counting for complex cell morphologies in mixed populations.

Main Methods:

• Developed the complex cell count (CCC) assay using MetaMorph software.
• Employed a combination of image processing (morphology filters, digital thresholding), integrated morphometry analysis, and object standards.
• Achieved an analysis time of 1.82 seconds per image.

Main Results:

• Demonstrated significant correlations between CCC assay data and manual cell counts.
• Successfully quantified human astrocytes and microglia in mixed cell cultures with high accuracy and speed.
• Validated the assay's ability to handle complex cell morphologies.

Conclusions:

• The CCC assay provides a rapid, accurate, and objective solution for quantifying specific cell types with complex morphologies.
• This method is applicable to various neuroscience research applications involving cell quantification.
• The assay can be adapted for quantifying other complex cells or objects in biological imaging.