Optimal Settings of Mass Spectrometry Open Search Strategy for Higher Confidence

Dehua Li1, Shaohua Lu1, Wanting Liu1

  • 1Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Institute of Life and Health Engineering, College of Life Science and Technology , Jinan University , Guangzhou 510632 , China.

Journal of Proteome Research
|September 29, 2018
PubMed

Insights

The open search strategy in mass spectrometry improves spectrum identification, especially for modified peptides. Using translatome sequencing (RNC-seq) for quality control and a peptide false discovery rate (FDR) below 0.1% enhances confidence in identifying post-translational modifications and single amino acid variations.

Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Molecular Biology

Background:

  • Most mass spectrometry data remains unidentified due to peptide modifications.
  • Current open search strategies lack robust quality control for identified spectra.

Purpose of the Study:

  • To establish a quality control method for open search proteome data using translatome sequencing.
  • To evaluate the impact of open search on identifying modified peptides and single amino acid variations.

Main Methods:

  • Utilized "Suspicious Discovery Rate (SDR)" based on RNC-seq data for quality control.
  • Applied open search with a strict peptide false discovery rate (FDR) < 0.1% to proteomic data.
  • Validated findings by identifying single amino acid variations without a predefined database.

Main Results:

  • Open search increased spectra utilization but also introduced more unidentified spectra.
  • Restricting peptide FDR below 0.1% effectively controlled suspicious identifications in open search.
  • Achieved confident identification of post-translational modifications and 27 single amino acid variations.

Conclusions:

  • RNC-seq provides an independent reference for open search quality control.
  • Strict FDR control enhances the reliability of open search for proteome identification.
  • Open search is a valuable tool for discovering post-translational modifications and genetic variations.

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