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Related Experiment Video

Updated: May 21, 2026

Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT)
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A rapid approach for isobaric peptide termini labeling.

Christian J Koehler1, Magnus O Arntzen, Achim Treumann

  • 1The Biotechnology Centre of Oslo, University of Oslo, Oslo, Norway.

Methods in Molecular Biology (Clifton, N.J.)
|June 6, 2012
PubMed
Summary

A new method for Isobaric Peptide Termini Labeling (IPTL) simplifies quantitative proteomics. This streamlined approach enables rapid, one-pot labeling for accurate peptide quantification across samples.

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Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Biochemistry

Background:

  • Isobaric Peptide Termini Labeling (IPTL) is an advanced chemical labeling technique for quantitative proteomics.
  • The original IPTL method involved multiple steps, including selective lysine modification and C-18 micropurification.

Purpose of the Study:

  • To develop a simplified and more efficient IPTL method.
  • To introduce a one-pot labeling procedure for improved throughput.
  • To present a user-friendly software tool for data analysis.

Main Methods:

  • Developed a novel IPTL approach utilizing selective N-terminal modification with succinic anhydride.
  • Employed reductive amination of C-terminal lysines with formaldehyde and cyanoborohydride.
  • Performed both labeling reactions in a single pot within 10 minutes without C-18 micropurification.

Main Results:

  • Achieved efficient and quantitative labeling of peptide N and C termini.
  • Demonstrated a significant reduction in sample processing time and complexity.
  • Introduced the IsobariQ software for streamlined analysis of IPTL data.

Conclusions:

  • The new IPTL method offers a faster and simpler alternative for quantitative peptide analysis.
  • This optimized approach enhances the accessibility and efficiency of quantitative proteomics workflows.
  • The IsobariQ software facilitates straightforward interpretation of quantitative proteomic data.