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Identification-Free Control over the Precursor Isotopic Mass Misassignment in Orbitrap-Based Proteomics.

Elizaveta M Solovyeva1,2, Sergei A Moshkovskii3,4, Mikhail V Gorshkov2

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Precursor ion selection in Orbitrap mass spectrometry can misassign isotopic masses, impacting proteome analysis reliability. We propose a new metric for quality control software to predict and mitigate this issue.

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Computational Biology

Background:

  • Data-dependent acquisition in Orbitrap FTMS relies on accurate precursor ion selection.
  • Monoisotopic mass assignment errors are a common challenge in proteomic data analysis.
  • Existing solutions for isotopic errors increase data processing time and search space.

Purpose of the Study:

  • To quantify the rate of precursor isotope misassignment in Orbitrap-based LC-MS/MS data.
  • To evaluate the impact of accounting for isotopic errors on peptide identification rates.
  • To develop an identification-free metric for predicting precursor mass assignment issues.

Main Methods:

  • Analysis of 100 Orbitrap LC-MS/MS runs from 10 public datasets.
  • Examination of precursor isotope misassignment rates.
  • Development and validation of a novel identification-free quality metric.

Main Results:

  • Precursor isotope misassignment rates varied significantly across datasets.
  • Accounting for isotopic errors impacted peptide identification by 0-33%.
  • The proposed metric can predict these issues prior to data search.

Conclusions:

  • Precursor mass assignment errors are a notable issue in Orbitrap proteomics.
  • An identification-free metric offers a faster, more reliable quality control approach.
  • The proposed metric is integrated into the viQC software for practical application.