An optimized enrichment strategy for improved mass spec analysis of chemically crosslinked peptides

Importance of the Topic

This study addresses the critical challenge of low yield in crosslinked peptide identification by mass spectrometry. Chemical crosslinking coupled with LC-MS offers detailed insights into protein structures and interactions, but typical crosslink yields are below 1% of total peptides. Improving enrichment and sample preparation workflows enhances sensitivity and throughput for proteome‐wide interaction studies.

Objectives and Study Overview

The primary goal was to develop and validate an optimized workflow using the acid‐cleavable crosslinker aaDSBSO for enriched analysis of crosslinked peptides. Key aims included comparing crosslinking efficiency of aaDSBSO versus conventional reagents, evaluating biotinylation probes, selecting the best avidin‐based resins and acid‐cleavage conditions, and integrating efficient fractionation to maximize crosslink identifications while reducing total protocol time.

Methodology and Instrumentation

Samples of bovine serum albumin (BSA) and HeLa cell lysates were crosslinked with DSSO or aaDSBSO at optimized molar ratios (100–300×). Crosslinks were quenched, reduced, alkylated, and digested with trypsin/LysC. For azido‐tagged samples, four copper‐free click reagents were tested, with sDIBO showing the highest labeling efficiency. Biotinylated peptides were enriched on six avidin resins to compare capacity and elution. Acid cleavage was screened across various acids, temperatures, and durations. Enriched samples underwent reversed‐phase chromatography on a Thermo Scientific UltiMate 3000 UHPLC with EASY-Spray column and were analyzed on an Orbitrap Fusion Tribrid mass spectrometer. Data processing employed Proteome Discoverer 2.2 with the XlinkX node.

Instrumental Setup

• UHPLC: Thermo Scientific UltiMate 3000 system with Acclaim PepMap 100 C18 trap and EASY-Spray analytical column (15 cm×75 µm).
• Mass Spectrometry: Orbitrap Fusion Tribrid MS with high‐resolution MS1 (120 K), data‐dependent MS2 and MS3 CID scans.
• Data Analysis: Proteome Discoverer 2.2, XlinkX for crosslink searches, SEQUEST HT for linear peptides.

Main Results and Discussion

aaDSBSO and DSSO displayed comparable crosslinking efficiency, though both were ~30% less efficient than BS3. sDIBO provided superior biotinylation at low probe concentrations. NeutrAvidin Plus Ultralink and Streptavidin POROS resins achieved the highest crosslink peptide identifications and sample recovery. Optimal acid cleavage used 5% TFA at 50 °C for 4 h, improving MS3 triggering and doubling crosslink spectral matches. Incorporating strong cation exchange or reversed‐phase fractionation further increased crosslink identifications by 14–50% while reducing unmodified peptides. The refined protocol cut total sample preparation time from 3.5 days to under 2 days, a 60% improvement. In complex HeLa digest backgrounds, aaDSBSO enrichment retained ~37–50% of crosslinked identifications, outperforming DSSO under identical conditions.

Benefits and Practical Applications

The optimized aaDSBSO workflow offers:

• Higher crosslink peptide identification rates and specificity.
• Reduced protocol time for faster turnaround.
• Robust performance in complex biological matrices.
• Compatibility with standard LC‐MS platforms for structural proteomics and interaction mapping.

Future Trends and Opportunities

Emerging prospects include integration of automated fractionation, novel cleavable crosslinkers with improved cell permeability, and high‐throughput platforms for in vivo interaction mapping. Combining crosslinking MS with cryo‐EM or computational modeling will advance structural systems biology. Continuous development of data analysis tools and AI‐driven spectral interpretation will further enhance depth and accuracy.

Conclusion

This study establishes a streamlined, high‐efficiency aaDSBSO enrichment workflow that significantly boosts crosslinked peptide discovery while halving preparation time. The approach is readily adoptable for global protein‐protein interaction studies and paves the way for more comprehensive structural proteomics applications.

References

1. Kao A, Chiu CL, Vellucci D, et al. Development of a novel cross-linking strategy for fast and accurate identification of cross-linked peptides of protein complexes. Mol Cell Proteomics. 2011;10(1):M110.002212.
2. Kaake RM, et al. A new in vivo cross-linking mass spectrometry platform to define protein-protein interactions in living cells. Mol Cell Proteomics. 2014;13(12):3533–3543.
3. Liu F, Rijkers D, Post H, Heck AJ. Proteome-wide profiling of protein assemblies by cross-linking mass spectrometry. Nat Methods. 2015;12(12):1179-84.