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Updated: Feb 4, 2026

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry
Published on: January 5, 2021
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.
Abstract:
In most proteome mass spectrometry experiments, more than half of the mass spectra cannot be identified, mainly because of various modifications. The open search strategy allows for a larger precursor tolerance to utilize more spectra, especially those with post-translational modifications; however, thorough quality control based on independent information is lacking. Here, we used the "Suspicious Discovery Rate (SDR)" based on translatome sequencing (RNC-seq) as an independent source to reference the proteome open search results in steady-state cells. We found that the open search strategy increased the spectra utilization with the cost of increased suspicious identifications that lack translation evidence. We further found that restricting the peptide FDR below 0.1% efficiently controlled the suspicious identifications of open search methods and thus enhanced the confidence of the peptide identification with modifications comparable to the level of the traditional narrow window search. We then demonstrated the successful and validated identification of 27 single amino acid variations from the spectra of two cell lines using the open search strategy without a predefined database. These results validated the proper use of open search methods for higher-quality proteome identifications with information on post-translational modifications and single amino acid polymorphisms.
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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