Targeted Quantitation of Phosphotyrosine-Containing Proteins in T-Cell Receptor Signaling Using a SureQuant-Based

Firdous A Bhat1, Husheng Ding1, Dong-Gi Mun1

  • 1Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.

Proteomics
|August 27, 2025
PubMed

Insights

This study developed a targeted mass spectrometry method, SureQuant, to accurately measure low-abundance phosphotyrosine peptides in T-cell receptor (TCR) signaling. The method enables sensitive and reproducible quantification of key signaling molecules upon T-cell activation.

Area of Science:

  • Immunology
  • Proteomics
  • Cell Signaling

Background:

  • T-cell receptor (TCR) signaling is vital for immune responses.
  • Tyrosine phosphorylation is a key regulatory mechanism in TCR signaling.
  • Low abundance of phosphotyrosine peptides challenges conventional detection methods.

Purpose of the Study:

  • To develop and validate a targeted proteomics method for quantifying phosphotyrosine peptides in TCR signaling.
  • To assess the sensitivity and reproducibility of the SureQuant approach for low-abundance peptides.
  • To investigate dynamic changes in phosphotyrosine signaling during T-cell activation.

Main Methods:

  • Development of a SureQuant-based targeted mass spectrometry assay.
  • Utilizing triggered data acquisition with heavy isotope-labeled peptides.
  • Stimulation of primary T-cells with anti-CD3/CD28 antibodies to monitor signaling.

Main Results:

  • Successful quantification of changes in key phosphotyrosine peptides in primary T-cells.
  • Demonstrated high sensitivity and reproducibility of the SureQuant method for low-abundance phosphotyrosine peptides.
  • Provided a systematic view of TCR signaling dynamics with distinct phosphorylation patterns.

Conclusions:

  • The SureQuant approach accurately quantifies low-abundance phosphotyrosine peptides in TCR signaling.
  • This method offers a valuable tool for precise analysis of signaling pathways and post-translational modifications.
  • The framework can be extended to study other signaling networks and immune cell functions.