SPPUSM: An MS/MS spectra merging strategy for improved low-input and single-cell proteome identification

Area of Science:

• Proteomics
• Mass Spectrometry
• Single-Cell Analysis

Background:

• Bulk measurements mask cellular heterogeneity crucial for understanding biological processes and diseases.
• Proteomic analysis of trace samples or single cells lags behind nucleic acid analysis due to protein non-amplifiability and mass spectrometry sensitivity limits.

Purpose of the Study:

• To develop an MS/MS spectra merging strategy, SPPUSM (same precursor-produced unidentified spectra merging), to enhance low-input and single-cell proteome data analysis.
• To improve protein identification and proteome coverage in challenging sample types.

Main Methods:

• Extracted unidentified MS/MS spectra from multiple test files.
• Matched and merged MS/MS spectra from the same precursor ion across different files based on precursor mass and retention time (RT).
• Searched merged spectra against a database to increase identifications.

Main Results:

• Achieved up to 18.2% improvement in protein identification for 1 ng HeLa peptides using SPPUSM.
• Demonstrated a marginal error rate via an "entrapment database" strategy.
• Showed 28%-61% identification enhancement for proteins in single-cell proteome (SCP) data.
• Identified lower abundance peptides, indicating enhanced sensitivity.

Conclusions:

• SPPUSM effectively improves protein identification and proteome coverage for low-input and single-cell samples.
• The method offers significant potential for more sensitive proteomic analyses in trace amounts of biological material.
• SPPUSM advances the field of single-cell proteome analysis by overcoming current sensitivity limitations.