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Related Concept Videos

Proteomics01:33

Proteomics

8.7K
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...
8.7K

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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A data-independent acquisition-based global phosphoproteomics system enables deep profiling.

Reta Birhanu Kitata1, Wai-Kok Choong2, Chia-Feng Tsai3

  • 1Institute of Chemistry, Academia Sinica, Taipei, 11529, Taiwan.

Nature Communications
|May 6, 2021
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Summary

We developed a sensitive phosphoproteomics method using data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries. This approach enables deep profiling of phosphorylation signaling in lung cancer, identifying key events in drug resistance and tumor progression.

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Mass Spectrometry

Background:

  • Phosphoproteomics reveals cellular signaling dynamics.
  • Accurate profiling of phosphoproteomics is challenging for small samples.

Purpose of the Study:

  • Develop a deep and robust quantitative phosphoproteomics strategy for minute samples.
  • Establish a streamlined workflow for analyzing phosphorylation signaling in lung cancer.

Main Methods:

  • Utilized data-independent acquisition (DIA) mass spectrometry.
  • Created hybrid spectral libraries from data-dependent acquisition (DDA) and DIA data.
  • Benchmarked method sensitivity, site localization, and quantification accuracy using synthetic phosphopeptides.

Main Results:

  • Achieved high sensitivity (<0.1 ng), accurate site localization, and reproducible quantification (~5% CV).
  • Constructed a hybrid phosphoproteome spectral library with 159,524 phosphopeptides.
  • Quantified 36,350 phosphosites in lung cancer cell lines within two hours using a single-shot DIA workflow.
  • Identified site-specific phosphorylation events linked to drug resistance and tumor progression in patient-derived tissues.

Conclusions:

  • The developed phosphoproteomics workflow enables deep coverage and high sensitivity analysis of phosphorylation signaling.
  • The method is effective for characterizing phosphorylation events in complex biological samples like lung cancer.
  • This approach facilitates the study of phosphorylation in disease progression and drug resistance with low between-run missing values.