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Updated: Feb 19, 2026

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

Kevin M Chambers¹, Bhaskar S Mandavilli², Nick J Dolman³

¹Thermo Fisher Scientific, 29851 Willow Creek Road, Eugene, OR, 97402, USA.

Methods in Molecular Biology (Clifton, N.J.)

|October 31, 2017

Summary

This summary is machine-generated.

High content imaging (HCI) uses fluorescent probes for cell labeling and segmentation in automated microscopy. This guide details standard procedures and troubleshooting for reliable cell demarcation in live and fixed samples.

Keywords:

CellMask CellTracker High content imaging High content screening Nuclear segmentation Segmentation

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

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

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

Published on: December 16, 2014

Area of Science:

Cell biology
Microscopy
Image analysis

Background:

Automated quantitative fluorescence microscopy, or high content imaging (HCI), is increasingly vital in cell biology.
Accurate cell and subcellular region demarcation is crucial for automated image analysis in HCI.
Fluorescent probes targeting DNA or proteins are standard for cell labeling in HCI.

Purpose of the Study:

To describe standard procedures for cell labeling and image segmentation in HCI.
To provide troubleshooting guidelines for common issues in HCI cell segmentation.

Main Methods:

Utilizing fluorescent probes for nuclear (DNA-binding) or whole-cell (protein-reactive) staining.
Applying standard procedures for labeling and image segmentation in both live and fixed cell samples.
Detailing instrument and software settings critical for successful cell segmentation.

Main Results:

Established standard protocols for cell labeling and image segmentation in HCI.
Identified key reagents and settings influencing segmentation accuracy.
Provided practical troubleshooting advice for common HCI workflow challenges.

Conclusions:

Reliable cell labeling and segmentation are fundamental to successful automated quantitative fluorescence microscopy.
Standardized procedures and troubleshooting are essential for robust HCI data acquisition.
This chapter serves as a practical resource for researchers employing HCI in cell biology.