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Related Experiment Video

Updated: Jul 31, 2025

A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation
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Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses.

Khiry L Patterson1, Albert B Arul1, Min Ji Choi1

  • 1Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States.

Journal of the American Society for Mass Spectrometry
|May 10, 2023
PubMed
Summary
This summary is machine-generated.

Robust quality control (QC) for large-scale plasma proteomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is crucial. This study evaluated QC metrics for a 335-patient cohort, developing a workflow for reliable, reproducible results.

Keywords:
liquid chromatographymass spectrometryplasmaproteinsproteomicsquality control

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Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Biotechnology

Background:

  • High-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) has advanced proteomics.
  • Scaling proteomics to large cohorts necessitates stringent quality control (QC) for reproducibility and accuracy.

Purpose of the Study:

  • To evaluate analytical variability metrics for designing a robust LC-MS/MS QC workflow.
  • To establish general tips for real-time troubleshooting of LC-MS/MS performance issues using daily QC checks.

Main Methods:

  • A plasma proteomics study of 335 patients using tandem mass tag (TMTpro) 16-plex batches.
  • Collected 271 pooled QC LC-MS/MS result files from a patient-derived pooled plasma sample over 10 months.
  • Evaluated instrumental and data analysis metrics including protein/peptide identifications, PSMs, MS/MS spectra, peptide abundance, and retention times.

Main Results:

  • Identified key metrics for assessing LC-MS/MS instrument performance and data quality.
  • Demonstrated the utility of pooled QC samples for daily performance monitoring and batch normalization.
  • Provided insights into analytical variability across a large-scale proteomics study.

Conclusions:

  • A robust LC-MS/MS QC workflow is essential for large-scale proteomics cohort studies.
  • Daily QC checks using specific metrics enable effective troubleshooting and ensure data reliability.
  • The developed QC strategy supports reproducible and accurate plasma proteomics research.