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Peptide Identification Using Tandem Mass Spectrometry

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Sample Preparation and Relative Quantitation using Reductive Methylation of Amines for Peptidomics Studies

Sample Preparation and Relative Quantitation using Reductive Methylation of Amines for Peptidomics Studies

Published on: November 4, 2021

An efficient, amine-specific iTRAQ labeling method improves the peptide and protein identification rates.

Ruomeng Chang¹, Chenchen Chang¹, Yan Cai¹

¹Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China.

Journal of Proteomics

|June 28, 2024

Summary

A new method improves isotope tags for relative and absolute quantification (iTRAQ) labeling by minimizing overlabeling on hydroxyl groups. This enhances peptide and protein identification rates for more accurate proteome quantification.

Keywords:

Identification rate Isobaric labeling Labeling specificity Overlabeling Proteomics iTRAQ

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Area of Science:

Proteomics
Analytical Chemistry
Biochemistry

Background:

Isotope tags for relative and absolute quantification (iTRAQ) are widely used for proteomics quantification.
Standard iTRAQ labeling can react with hydroxyl groups (serine, threonine, tyrosine), especially near histidine, causing biases and reducing identification rates.

Purpose of the Study:

To develop a novel iTRAQ labeling method that overcomes detrimental overlabeling while maintaining high amine labeling efficiency.
To optimize reaction conditions including temperature, concentration, time, buffer, and pH.

Main Methods:

Investigated the impact of various reaction parameters on iTRAQ labeling performance.
Compared the novel method against the standard iTRAQ manufacturer's method.

Main Results:

The novel method reduced overlabeled peptides by 55-fold compared to the standard method.
Achieved comparable amine labeling efficiency.
Eliminated systematic bias against histidyl- and hydroxyl-containing peptides.
Increased peptide identification by 23.9% and protein identification by 9.8%.

Conclusions:

The developed iTRAQ labeling method significantly enhances proteome quantification accuracy and sensitivity.
This method offers superior performance by mitigating overlabeling issues inherent in standard iTRAQ protocols.