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Related Experiment Video

Updated: Jun 11, 2025

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Interrogating data-independent acquisition LC-MS/MS for affinity proteomics.

David L Tabb1, Mohammed Hanzala Kaniyar1, Omar G Rosas Bringas1

  • 1European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen, The Netherlands.

Journal of Proteins and Proteomics
|October 7, 2024
PubMed
Summary
This summary is machine-generated.

Data-Independent Acquisition (DIA) coupled with mass spectrometry (LC-MS/MS) offers improved protein quantification for affinity proteomics. DIA workflows, particularly when using FragPipe, enhance protein detection and reduce variability compared to Data-Dependent Acquisition (DDA).

Keywords:
Affinity enrichmentBioinformaticsCo-immunoprecipitationData-independent acquisitionLabel-free quantitation

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Area of Science:

  • Proteomics
  • Biochemistry
  • Analytical Chemistry

Background:

  • Data-Independent Acquisition (DIA) LC-MS/MS is a powerful technique for affinity proteomics and co-immunoprecipitation (co-IP).
  • Reducing quantitation variability in DIA can improve the detection of specific protein interactors compared to Data-Dependent Acquisition (DDA).

Purpose of the Study:

  • To evaluate spectral libraries, protein quantity missingness, and coefficient of variation (CV) in DIA experiments across different instrument manufacturers and bioinformatics workflows.
  • To compare the performance of DIA against DDA for affinity proteomics applications.

Main Methods:

  • Interrogation of affinity proteomes from six studies using both DDA and DIA experiments.
  • Analysis of four contemporary DIA bioinformatics workflows: FragPipe, DIA-NN, Spectronaut, and MaxQuant.
  • Assessment of spectral library generation, protein quantification, and CV values.

Main Results:

  • Spectral libraries generated directly from DIA experiments are effective, comparable to those from DDA with equivalent instrument time.
  • Contemporary software may struggle to quantify indistinct signals in experiments with mock pull-downs or IgG controls.
  • Spectronaut, DIA-NN, and FragPipe demonstrated well-controlled CV values for protein quantification.
  • Using FragPipe for both spectral library building and quantification in DIA outperformed DDA, yielding more quantified proteins and lower CVs.

Conclusions:

  • DIA-LC-MS/MS is a robust method for affinity proteomics, offering advantages over DDA in protein quantification and detection.
  • Optimized DIA bioinformatics workflows, such as FragPipe, can significantly enhance the depth and reliability of proteomic analyses.
  • Careful experimental design is needed to manage indistinct signals in control experiments for accurate proteomic profiling.