Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

Area of Science:

• Proteomics
• Mass Spectrometry
• Biochemistry

Background:

• Data independent acquisition (DIA) mass spectrometry enhances reproducibility and throughput in proteomics.
• Existing methods often rely on data dependent acquisition (DDA) for library generation, limiting DIA utility.
• Chromatogram libraries are crucial for accurate peptide identification and quantification.

Purpose of the Study:

• To develop an experimental workflow for constructing chromatogram libraries using DIA mass spectrometry.
• To introduce EncyclopeDIA, a software tool for generating and searching these libraries.
• To improve peptide detection rates in DIA proteomics by leveraging calibrated retention time and fragmentation data.

Main Methods:

• Utilized data independent acquisition (DIA) mass spectrometry to generate chromatogram libraries.
• Captured fragment ion chromatographic peak shape and retention time for all detectable peptides.
• Developed the EncyclopeDIA software for chromatogram library creation and searching.
• Quantified proteins in human and yeast cell samples.

Main Results:

• The workflow successfully constructed chromatogram libraries capturing peptide-specific chromatographic features.
• EncyclopeDIA facilitates the calibration of protein databases and spectrum libraries for specific instrument setups.
• The EncyclopeDIA workflow detected 20-25% more peptides compared to DDA-based spectrum libraries alone.
• Demonstrated improved peptide quantification in human and yeast proteomes.

Conclusions:

• Chromatogram libraries generated via DIA improve peptide identification and quantification accuracy.
• EncyclopeDIA enables DIA-only proteomics pipelines and the reuse of global resource libraries.
• This approach significantly enhances the performance of DIA mass spectrometry for large-scale proteomics studies.