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Related Experiment Videos

Analysis of quantitative proteomic data generated via multidimensional protein identification technology.

Michael P Washburn1, Ryan Ulaszek, Cosmin Deciu

  • 1Proteomics, Torrey Mesa Research Institute, San Diego, California 92121, USA. michael.washburn@syngenta.com

Analytical Chemistry
|June 5, 2002
PubMed
Summary

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This study introduces a quantitative proteomic analysis method using Multidimensional Protein Identification Technology (MudPIT). The technique accurately measures protein ratios in yeast samples, enabling large-scale quantitative proteomic studies.

Area of Science:

  • Proteomics
  • Yeast Molecular Biology
  • Mass Spectrometry

Background:

  • Quantitative proteomic analysis is crucial for understanding cellular processes.
  • Accurate measurement of protein abundance changes is essential for biological research.
  • Existing methods may have limitations in dynamic range and scalability.

Purpose of the Study:

  • To describe and validate a quantitative proteomic analysis method using MudPIT.
  • To demonstrate the dynamic range and accuracy of the developed method.
  • To provide a robust approach for large-scale quantitative proteomic studies.

Main Methods:

  • Quantitative proteomic analysis of Saccharomyces cerevisiae (yeast) using Multidimensional Protein Identification Technology (MudPIT).
  • Stable isotope labeling of yeast proteome with 15N-enriched minimal media.

Related Experiment Videos

  • Analysis of peptide mixtures with varying 14N:15N ratios (1:1, 5:1, 10:1) using MudPIT.

    • Main Results:

    • Successful incorporation of 15N into the yeast proteome was confirmed.
    • The MudPIT method demonstrated accurate quantification across a dynamic range of 1:1, 5:1, and 10:1 ratios.
    • The analysis of soluble yeast proteome provided reliable quantitative data.

    Conclusions:

    • The described MudPIT-based method offers an accurate approach for large-scale quantitative proteomic studies.
    • This technique is suitable for analyzing relative protein abundance in complex biological samples.
    • The study validates the utility of MudPIT for quantitative proteomic investigations.