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Related Experiment Video

Updated: May 9, 2026

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue
11:49

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

2-Mercaptoethanol/DMSO Workflow Enables Highly Reproducible Quantitative Proteomics.

Arisa Suto1, Yoshihiro Ishikawa1, Toshihide Matsumoto2

  • 1Department of Physics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa 252-0373, Japan.

Journal of Proteome Research
|May 8, 2026
PubMed
Summary

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This summary is machine-generated.

A new 2-mercaptoethanol (2-ME)/dimethyl sulfoxide (DMSO) workflow improves quantitative proteomics accuracy and reproducibility. This method enhances cysteine modification detection and peptide coverage, crucial for understanding cellular functions and disease mechanisms.

Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Biochemistry

Background:

  • Proteomics offers insights into cellular functions and disease mechanisms.
  • Conventional iodoacetamide (IAA) carbamidomethylation for cysteine alkylation introduces nonspecific modifications, increasing spectral complexity and reducing quantitative accuracy in mass spectrometry.
  • There is a need for improved, reproducible proteomics workflows for accurate quantitative analysis.

Purpose of the Study:

  • To establish and evaluate a reproducibility-focused 2-mercaptoethanol (2-ME)/dimethyl sulfoxide (DMSO) workflow for quantitative proteomics.
  • To systematically assess the quantitative performance of the 2-ME/DMSO workflow at the proteome-wide level compared to conventional IAA treatment.
  • To demonstrate the utility of the new workflow in detecting biologically relevant alterations in disease models.
Keywords:
2-mercaptoethanolDMSOcysteine modification

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Main Methods:

  • Mouse liver proteomes were processed using either the optimized 2-ME/DMSO workflow or conventional IAA treatment.
  • Samples were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS).
  • Quantitative performance was evaluated based on the number of cysteine-modified peptides, protein sequence coverage, and quantitative reproducibility (coefficient of variation, CV).

Main Results:

  • The optimized 2-ME treatment increased the identification of cysteine-modified peptides by 1.6- to 1.9-fold.
  • While total protein identifications remained comparable, 77% of proteins showed improved sequence coverage with the 2-ME/DMSO workflow.
  • Quantitative reproducibility significantly improved: peptide CV ≤ 20% increased from 61.4% (IAA) to 86.1% (2-ME/DMSO), and protein CV ≤ 20% increased from 80.6% (IAA) to 93.5% (2-ME/DMSO).
  • The workflow successfully detected cisplatin-induced alterations in ovarian clear cell carcinoma.

Conclusions:

  • The 2-ME/DMSO workflow provides a simple, highly reproducible strategy for accurate quantitative proteomics.
  • This method enhances cysteine modification detection and improves quantitative accuracy, enabling more reliable insights into biological systems.
  • The workflow is suitable for various applications, including disease mechanism studies and biomarker discovery.