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Establishing Quality Control Metrics for Large-Scale Plasma Proteomic Sample Preparation.

Nekesa C OliverMin Ji ChoiAlbert B ArulMarsalas D WhitakerRenã A S Robinson
Published in: ACS measurement science au (2024)
Large-scale plasma proteomics studies have been transformed due to the multiplexing and automation of sample preparation workflows. However, these workflows can suffer from reproducibility issues, a lack of standardized quality control (QC) metrics, and the assessment of variation before liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The incorporation of robust QC metrics in sample preparation workflows ensures better reproducibility, lower assay variation, and better-informed decisions for troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of patient samples ( N = 808) using tandem mass tag (TMT) 16-plex batches ( N = 58). The proteomic workflow consisted of protein depletion, protein digestion, TMT labeling, and fractionation. Five QC sample types (QC std , QC dig , QC pool , QC TMT , and QC BSA ) were created to measure the performance of sample preparation prior to the final LC-MS/MS analysis. We measured <10% CV for individual sample preparation steps in the proteomic workflow based on data from various QC sample steps. The establishment of robust measures for QC of sample preparation steps allowed for greater confidence in prepared samples for subsequent LC-MS/MS analysis. This study also provides recommendations for standardized QC metrics that can assist with future large-scale cohort sample preparation workflows.
Keyphrases
  • quality control
  • molecularly imprinted
  • liquid chromatography tandem mass spectrometry
  • machine learning
  • electronic health record
  • solid phase extraction
  • ms ms
  • amino acid