AI Article Synopsis

  • Cross-linking mass spectrometry (XL-MS) is a crucial method for studying protein interactions, and this study improves its capabilities by using Parallel Accumulation-Serial Fragmentation (PASEF) on timsTOF instruments.
  • The research addresses challenges in XL-MS data interpretation, particularly for low abundant cross-linked peptides and complex spectra, by proposing a peptide-centric analysis method and integrating data-independent acquisition (DIA) into the XL-MS framework.
  • A new workflow is developed for processing PASEF-derived data with Bruker Daltonics software, facilitating compatibility with MeroX and Skyline tools, ultimately enhancing the identification of cross-linked proteins in complex mixtures.

Article Abstract

Cross-linking mass spectrometry (XL-MS) has evolved into a pivotal technique for probing protein interactions. This study describes the implementation of Parallel Accumulation-Serial Fragmentation (PASEF) on timsTOF instruments, enhancing the detection and analysis of protein interactions by XL-MS. Addressing the challenges in XL-MS, such as the interpretation of complex spectra, low abundant cross-linked peptides, and a data acquisition bias, our current study integrates a peptide-centric approach for the analysis of XL-MS data and presents the foundation for integrating data-independent acquisition (DIA) in XL-MS with a vendor-neutral and open-source platform. A novel workflow is described for processing data-dependent acquisition (DDA) of PASEF-derived information. For this, software by Bruker Daltonics is used, enabling the conversion of these data into a format that is compatible with MeroX and Skyline software tools. Our approach significantly improves the identification of cross-linked products from complex mixtures, allowing the XL-MS community to overcome current analytical limitations.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11099889PMC
http://dx.doi.org/10.1021/acs.analchem.4c00829DOI Listing

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