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Sample multiplexing in CyTOF: Path to optimize single-cell proteomic profiling.

Muharrem Muftuoglu1, Michael Andreeff1

  • 1Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Cell Signaling
|April 4, 2025
PubMed
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Sample multiplexing in Cytometry by Time-Of-Flight (CyTOF) boosts proteomic analysis depth. New chelators improve metal isotope tagging for simultaneous multi-sample analysis, enhancing data accuracy and discovery potential.

Area of Science:

  • Biotechnology
  • Proteomics
  • Analytical Chemistry

Background:

  • Single-cell proteomic analysis is crucial for understanding cellular heterogeneity.
  • Cytometry by Time-Of-Flight (CyTOF) is a powerful technique for high-dimensional single-cell analysis.
  • Limitations in sample throughput and batch effects can hinder deep proteomic studies.

Purpose of the Study:

  • To enhance the depth and efficiency of single-cell proteomic analysis using CyTOF.
  • To introduce and evaluate novel polymer-based chelators for metal isotope tagging.
  • To demonstrate the benefits of sample multiplexing in CyTOF experiments.

Main Methods:

  • Development of new polymer-based chelators for metal isotope conjugation.
  • Implementation of sample multiplexing strategies in CyTOF workflows.

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Last Updated: May 16, 2025

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  • Comparative analysis of multiplexed versus single-sample CyTOF experiments.
  • Main Results:

    • Sample multiplexing significantly increased the depth of single-cell proteomic analysis.
    • Novel chelators enabled robust tagging and simultaneous analysis of multiple samples.
    • Multiplexing minimized batch effects and conserved sample material.

    Conclusions:

    • Sample multiplexing is a key strategy for advancing CyTOF-based single-cell proteomic research.
    • The developed chelators expand the utility of metal isotopes in multi-sample analyses.
    • These advancements facilitate more accurate biological discoveries through streamlined, cost-effective experiments.