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Related Experiment Video

Updated: May 23, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

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Isobaric labeling and data normalization without requiring protein quantitation.

Phillip D Kim1, Bhavinkumar B Patel, Anthony T Yeung

  • 1Developmental Therapeutics Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111-2497, USA.

Journal of Biomolecular Techniques : JBT
|April 3, 2012
PubMed
Summary
This summary is machine-generated.

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A new method called exponentially modified protein abundance index (emPAI)-MW deconvolution (EMMOL) normalizes isobaric tag for relative and absolute quantification (iTRAQ) data. This allows comparing many samples, even with minute protein amounts, without a reference standard.

Area of Science:

  • Proteomics
  • Quantitative Mass Spectrometry

Background:

  • Isobaric multiplexed quantitative proteomics is valuable for high-resolution sample isolation.
  • Accurate normalization of isobaric reporter ratios is crucial for reliable quantitative proteomics, especially when dealing with limited sample quantities.

Purpose of the Study:

  • To introduce a novel workflow, exponentially modified protein abundance index (emPAI)-MW deconvolution (EMMOL), for normalizing isobaric reporter ratios.
  • To enable quantitative comparison of multiple samples without a reference standard, particularly when using small or unknown protein amounts.
  • To optimize sample preparation for minute protein quantities in quantitative proteomics experiments.

Main Methods:

  • Developed and applied the EMMOL workflow for deconvolution of isobaric tags for relative and absolute quantification (iTRAQ) data.
Keywords:
EMMOLLCMiTRAQoptimizationproteome

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  • Utilized emPAI, target protein molecular weight (MW), and iTRAQ reporter ratios to calculate protein quantities.
  • Implemented an optimized iTRAQ labeling protocol starting with as little as 5 microg of protein.
  • Main Results:

    • EMMOL successfully normalized iTRAQ data, yielding protein quantities for each sample without prior knowledge or a reference standard.
    • Demonstrated EMMOL's capability by comparing four pooled samples with 20-fold differences in protein abundance, showing no compression of expression ratios.
    • Validated the analysis of minute samples with an optimized iTRAQ labeling protocol.

    Conclusions:

    • EMMOL provides a robust method for normalizing isobaric quantitative proteomics data, enabling accurate comparisons across experiments and samples.
    • The workflow facilitates the analysis of limited biological samples, expanding the applicability of quantitative proteomics.
    • EMMOL allows for the comparison of proteomes from separate iTRAQ experiments without the need for a common reference sample.