LC separation optimization for XL-MS Analysis

Importance of Topic

Cross-linking mass spectrometry (XL-MS) has become an essential approach for mapping protein interactions and elucidating higher-order structures on a proteome-wide scale. Reliable liquid chromatography (LC) separation is critical for XL-MS workflows, as crosslinked peptides are present at low abundance and their complexity demands optimal chromatographic resolution and minimal carryover. Enhanced LC separation directly contributes to improved identification rates and deeper structural insights.

Objectives and Overview

This study aimed to optimize LC conditions for XL-MS analysis on Thermo Scientific Orbitrap Ascend and Astral instruments. Key goals included:

• Comparing performance of three reverse-phase columns (EASY-Spray PepMap RSLC C18, µPAC Neo, IonOpticks Aurora Ultimate) using standard BSA DSSO spiked into HeLa digest.
• Assessing overall peptide carryover, peak widths, and identification metrics.
• Developing and validating an MS2-MS3 acquisition method to improve accuracy for a novel cleavable crosslinker (DizSEC).

Použitá instrumentace

Chromatography:

• Thermo Scientific Vanquish Neo UHPLC system
• Columns: PepMap RSLC C18 (75 µm×25 cm, 2 µm), µPAC Neo HPLC (50 cm, 2.5 µm pillars), IonOpticks Aurora Ultimate (75 µm×25 cm, 1.7 µm)

Mass Spectrometry:

• Orbitrap Ascend (MS1 at 60 K, MS2 at 30 K)
• Orbitrap Astral (MS1 at 180 K, MS2 in Astral detector)

Data Analysis:

• Proteome Discoverer 3.0 with XlinkX node and SEQUEST HT
• Scout v1.4.14

Methodology

Amine-reactive crosslinkers (DizSEC, DSSO, DSBU) were used to crosslink bovine serum albumin, standard proteins, and E. coli lysate. Crosslinked samples were digested and spiked into HeLa digest at defined ratios. Peptides were separated over a 60 min, 6–50% ACN gradient at 300 nL/min and analyzed in data-dependent acquisition mode. For DizSEC, a stepped collision energy MS2-MS3 method was optimized to enhance cleavable fragment detection and reduce false positives.

Main Results and Discussion

• PepMap columns delivered the narrowest peak widths, lowest carryover (0.33%), and highest crosslinked peptide identifications compared to µPAC and Aurora.
• µPAC and Aurora columns provided increased HeLa protein coverage (2797 and 3255 proteins vs. 2545 for PepMap) but suffered higher carryover, especially Aurora (2.5%).
• Venn diagram analysis showed substantial overlap in crosslinks between PepMap and alternative columns, with unique identifications attributable to each stationary phase.
• The novel MS2-MS3 protocol for DizSEC improved confidence in crosslink assignments by leveraging characteristic reporter ions and optimized collision energies.

Benefits and Practical Applications

• Optimized workflows allow sensitive detection of low-abundance crosslinked peptides, enabling deeper structural proteomics studies.
• PepMap RSLC columns offer a robust choice for routine XL-MS due to balanced resolution and minimal carryover.
• Enhanced MS2-MS3 strategies for cleavable crosslinkers broaden the toolkit for residue-level mapping in complex samples.

Future Trends and Opportunities

Advancements in column chemistries (e.g., novel pillar architectures), faster gradients, and further refinement of MSn acquisition schemes promise even higher throughput and sensitivity. Integration of machine-learning algorithms for real-time method optimization and the development of next-generation cleavable reagents will further expand XL-MS capabilities.

Conclusion

This work establishes an optimized LC-MS platform for cross-linking studies on Orbitrap Ascend and Astral instruments. The PepMap column emerged as the top performer for crosslinked peptide detection, while µPAC and Aurora highlight trade-offs between protein coverage and carryover. The bespoke MS2-MS3 method for DizSEC crosslinker enhances confidence in structural analyses and sets the stage for more reliable proteome-wide interaction mapping.

References

1. Faustino AM, Sharma P, Manriquez-Sandoval E, Yadav D, Fried SD. Progress toward Proteome-Wide Photo-Cross-Linking to Enable Residue-Level Visualization of Protein Structures and Networks In Vivo. Anal Chem. 2023 Jul 18;95(28):10670–10685.
2. Avila Clasen M, Ruwolt M, Kurt LU, Gozzo FC, Wang S, Chen T, Carvalho PC, Lima DB, Liu F. Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics. bioRxiv. 2023.11.30.569448.