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Evaluation of Acquisition Modes for the Quantitative Analysis of Cross-Linked Peptides by Targeted and Untargeted Mass Spectrometry

submitted on 16.11.2020, 16:11 and posted on 17.11.2020, 11:10 by Hannah Britt, Tristan Cragnolini, Suniya Khatun, Abubakar Hatimy, Juliette James, Nathanael Page, Jonathan Williams, Christ Hughes, Richard Denny, Konstantinos Thalassinos, Hans Vissers

Cross-linking mass spectrometry (XL-MS) is a structural biology technique that can provide insights into the structure and interactions of proteins and their complexes, especially those that cannot be easily assessed by other methods. Quantitative XL-MS has the potential to probe the structural and temporal dynamics of protein complexes; however, it requires further development. Until recently, quantitative XL-MS has largely relied upon isotopic labeling and data dependent acquisition (DDA) methods, limiting the number of biological samples that can be studied in a single experiment. Here, the acquisition modes available on an ion mobility (IM) enabled QToF mass spectrometer are evaluated for the quantitation of cross-linked peptides, eliminating the need for isotopic labels and thus expanding the number of comparable studies that can be conducted in parallel. Workflows were optimized using metabolite and peptide standards analyzed in biological matrices, facilitating modelling of the data and addressing linearity issues, which allow for significant increases in dynamic range. Evaluation of the DDA acquisition method commonly used in XL-MS studies indicated consistency issues between technical replicates and reduced performance in quantitative metrics. On the contrary, data independent acquisition (DIA) and parallel reaction monitoring (PRM) modes proved more robust for analyte quantitation. Mobility enabled modes exhibited an improvement in sensitivity due to the added dimension of separation, and a simultaneous reduction in dynamic range, which was largely recovered by correction methods. Hi[3] and probabilistic quantitation methods were successfully applied to the DIA data, determining the molar amounts of cross-linked peptides relative to their linear counterparts.


Wellcome Trust Collaborative Award in Science 209250/Z/17/Z.


Email Address of Submitting Author


University College London


United Kingdom

ORCID For Submitting Author


Declaration of Conflict of Interest

The authors declare the following competing interest(s): J.P.W, C.H, R.D., and J.P.C.V are employed by Waters Corporation.

Version Notes

Manuscript version 1 (16/11/20)