Related Experiment Video
Updated: Jul 24, 2025
07:12
A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation
Published on: April 24, 2020
10.1K
A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics
Xiaokang Li1,2,3, Hui Song Pak1,2,3, Florian Huber1,2,3
1Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland.
Cell Reports Methods
|July 10, 2023
Summary
This study introduces a novel, low-volume workflow for mass spectrometry (MS)-based immunopeptidomics, enhancing antigen discovery from limited clinical samples. The streamlined process improves assay sensitivity and identifies thousands of HLA-I-restricted peptides.
Area of Science:
- Immunology
- Analytical Chemistry
- Biochemistry
Background:
- Mass spectrometry (MS)-based immunopeptidomics is crucial for antigen discovery and has clinical relevance.
- Current methods require large sample volumes, limiting clinical specimen analysis.
- Identifying HLA-restricted peptides is key for understanding immune responses.
Purpose of the Study:
- To develop an innovative, low-sample-volume workflow for MS-based immunopeptidomics.
- To enhance the sensitivity and efficiency of HLA-restricted peptide identification.
- To enable immunopeptidome analysis from sparse clinical samples.
Main Methods:
- A single microfluidics platform integrating immunoaffinity purification (IP) and C18 peptide cleanup.
- Automated liquid handling and minimal sample transfers for streamlined processing.
- Data-independent acquisition (DIA) for enhanced tandem MS spectra-based peptide sequencing.
Main Results:
- Identification of over 4,000 and 5,000 HLA-I-restricted peptides from minimal cell and tissue samples (0.2 million RA957 cells, 5 mg melanoma tissue).
- Demonstrated higher assay sensitivity due to the integrated microfluidics workflow.
- Discovery of multiple immunogenic tumor-associated antigens and peptides from non-canonical protein sources.
Conclusions:
- The developed workflow significantly reduces sample volume requirements for immunopeptidomics.
- This method provides a powerful tool for identifying the immunopeptidome in sparse samples.
- The approach enhances antigen discovery capabilities for clinical applications.
