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Related Experiment Video

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Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry
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Technical advances in proteomics: new developments in data-independent acquisition.

Alex Hu1, William S Noble1, Alejandro Wolf-Yadlin1

  • 1Department of Genome Sciences, University of Washington, Seattle, WA, 98109, USA.

F1000Research
|April 20, 2016
PubMed
Summary
This summary is machine-generated.

Data-independent acquisition (DIA) offers broad protein identification and reproducible quantification in proteomics. While still developing, DIA shows promise for sensitive, precise analysis comparable to targeted methods.

Keywords:
data-independent acquisitionmass spectrometryproteomics

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) has been standard for broad proteomics discovery.
  • Multiple reaction monitoring (MRM) LC-MS/MS is the standard for targeted proteomics requiring precise quantification and reproducibility.
  • Data-independent acquisition (DIA) is a rediscovered sampling method with potential for both breadth and reproducibility.

Purpose of the Study:

  • To evaluate the performance of data-independent acquisition (DIA) in proteomics.
  • To compare DIA with established methods like DDA and MRM/PRM for protein identification and quantification.
  • To assess the current capabilities and future potential of DIA in complex biological samples.

Main Methods:

  • Utilized data-independent acquisition (DIA) mass spectrometry for comprehensive peptide sampling.
  • Performed comparative de novo identification and quantification studies on human cell lysates.
  • Employed spectral libraries derived from prior DIA or DDA experiments to aid analysis.

Main Results:

  • DIA identified up to 89% of proteins detected by DDA in human cell lysates.
  • DIA provided reproducible quantification for over 85% of identified proteins.
  • DIA achieved quantification reproducibility and precision comparable to MRM/PRM, with limitations for low-abundance peptides.

Conclusions:

  • DIA approaches the identification breadth of DDA and the quantification reproducibility of MRM/PRM.
  • Spectral libraries are currently crucial for optimal DIA performance, especially for complex spectra interpretation.
  • Ongoing development in bioinformatics tools is expected to enhance DIA's sensitivity, reproducibility, and identification breadth without external libraries.