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Related Experiment Video

Updated: Apr 19, 2026

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
09:57

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

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Workflow for high-content, individual cell quantification of fluorescent markers from universal microscope data,

Simon R Stockwell1, Sibylle Mittnacht2

  • 1Cancer Biology, UCL Cancer Institute; ss2233@MRC-CU.cam.ac.uk.

Journal of Visualized Experiments : Jove
|December 31, 2014
PubMed
Summary

This study presents a universally applicable workflow for quantifying fluorescent markers in individual cells using freely available software. This method overcomes limitations of traditional assays, enabling detailed analysis of cellular heterogeneity in mammalian tissue culture.

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Last Updated: Apr 19, 2026

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Area of Science:

  • Cell Biology
  • Microscopy
  • Bioimaging

Background:

  • Single-cell analysis is crucial for understanding cellular control mechanisms, but traditional methods averaging population data obscure subpopulation dynamics.
  • High-content microscopy offers detailed cellular analysis but is often costly and specialized, limiting accessibility for researchers.
  • Existing methods risk losing critical information about cellular heterogeneity present in mammalian tissue culture models.

Purpose of the Study:

  • To develop and present a universally applicable workflow for quantifying multiple fluorescent marker intensities within specific subcellular regions of individual cells.
  • To enable detailed single-cell analysis using readily available fluorescence microscopy and free software.
  • To provide a accessible method for researchers to analyze cellular heterogeneity and biomarker dynamics.

Main Methods:

  • Utilized the freely available CellProfiler software for image analysis.
  • Developed a workflow to distinguish individual cells, segment them into subcellular regions, and quantify fluorescence marker intensities.
  • Applied the workflow to analyze data from a siRNA screen targeting G1 checkpoint regulators in adherent human cells.

Main Results:

  • Successfully extracted individual cell fluorescence intensity values from specific subcellular regions.
  • Demonstrated the workflow's capability to quantify multiple fluorescent markers per cell.
  • Validated the workflow's utility in analyzing data from a specific cell perturbation screen.

Conclusions:

  • The presented workflow offers a broadly applicable and accessible method for high-content, single-cell fluorescence analysis.
  • This approach overcomes limitations of traditional assays and specialized equipment, facilitating deeper insights into cellular heterogeneity.
  • The workflow is adaptable for various cell perturbation studies and fluorescence-based markers, benefiting a wide range of laboratories.