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Related Experiment Video

Updated: Jan 3, 2026

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Published on: April 14, 2015

High throughput pSTAT signaling profiling by fluorescent cell barcoding and computational analysis.

Wanxia Li Tsai¹, Laura Vian¹, Valentina Giudice²

¹Translational Immunology Section, Office of Science Technology (OST), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health, Bethesda, MD 20892, USA.

Journal of Immunological Methods

|November 15, 2019

Summary

Fluorescent cell barcoding (FCB) offers high-throughput flow cytometry (FCM) with reduced variability. A new method using internal controls minimizes operator differences, enhancing reproducibility for clinical trials.

Keywords:

Computational analysis Fluorescent cell barcoding Phenotyping Phosphoproteins Variability

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Area of Science:

Immunology
Cell Biology
Biotechnology

Background:

Fluorescent cell barcoding (FCB) is a multiplexing technique for high-throughput flow cytometry (FCM).
FCB minimizes staining variability but is limited by inter-operator variability and data analysis subjectivity.
Implementing FCB with phosphoprotein signaling analysis requires robust methods for variability assessment.

Purpose of the Study:

To develop and validate a robust method for measuring intra- and inter-assay variability of FCB.
To assess the reproducibility of FCB data analysis using conventional and semi-automated computational workflows.
To evaluate the feasibility of FCB for phosphoprotein signaling analysis in T/B cells and monocytes.

Main Methods:

FCB was implemented using a two-dye system (DyLight 350 and Pacific Orange) combined with five-color surface marker and intracellular staining.
Intra- and inter-assay variability were measured using a combination of range, ratio, and standard statistical analyses.
Data analysis involved conventional and semi-automated workflows developed with R software, including machine learning methods.
An internal control bridged across matrices was used to minimize inter-operator variability.

Main Results:

Efficient FCB was achieved using specific concentrations of DyLight 350 and Pacific Orange.
High reproducibility of FCB was demonstrated in combination with surface marker and intracellular antibodies.
Computational workflows yielded results comparable to conventional gating strategies.
The addition of bridge internal controls effectively minimized inter-operator variability.

Conclusions:

FCB is a reproducible technique for studying phosphoprotein signaling in T/B cells and monocytes.
The proposed method, incorporating internal controls, significantly minimizes inter-operator variability.
FCB offers high-throughput analysis with low intra- and inter-assay variability, making it suitable for clinical trials.
Computational software provides reliable analysis of FCB data.