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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and

Hongbin Wang1, Yongqian Zhang2, Shuqi Gui3

  • 1School of Life Science, Beijing Institute of Technology, Beijing, China; Key Lab of Industrial Fermentation Microbiology, Ministry of Education, College of Bioengineering, Tianjin University of Science and Technology, China.

Talanta
|May 29, 2017
PubMed
Summary

A new 18O-reference strategy combined with a decoupled quantitation and identification method improves accuracy and reproducibility in large-scale quantitative proteomics. This approach enhances protein identification across multiple samples, overcoming limitations of previous methods.

Keywords:
(18)O-reference strategyComparative proteomicsLabel-free methodQuantitation and identification-decoupled strategy

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Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Biochemistry

Background:

  • Quantitative proteomics often requires comparing numerous samples, a task challenging for existing methods like stable isotope labeling (e.g., iTRAQ) which are limited in sample capacity.
  • Label-free methods for large-scale comparisons suffer from poor reproducibility and accuracy.
  • A novel 18O-reference strategy, using a pooled reference sample, shows promise but requires validation with known protein mixtures.

Purpose of the Study:

  • To investigate and evaluate a combined strategy using the 18O-reference approach and a quantitation-identification-decoupled method.
  • To assess the accuracy and reliability of this new strategy for large-scale quantitative proteomics using proportion-known protein mixtures.
  • To improve protein identification reproducibility across multiple samples.

Main Methods:

  • Utilized proportion-known protein mixtures to validate the 18O-reference strategy.
  • Implemented a quantitation and identification-decoupled strategy.
  • Combined LC-MS for quantification and LC-MS/MS for identification, correlating data by retention time and accurate mass.

Main Results:

  • The 18O-reference strategy demonstrated superior accuracy and reliability compared to transferring comparison and label-free methods.
  • The decoupled strategy enabled protein identification using a single pooled sample, significantly improving reproducibility across all samples.
  • Optimized peptide identification separately, leading to the identification of a greater number of proteins.

Conclusions:

  • The combined 18O-reference and decoupled strategy offers a robust solution for accurate and reproducible quantitative proteomics in large sample sets.
  • This method overcomes key limitations of previous techniques, enhancing both quantification and identification.
  • The approach facilitates deeper proteomic analysis and improved discovery of differential protein expression.