Optimized fragmentation schemes and data analysis strategies for proteome-wide cross-link identification
Fan Liu1,2, Philip Lössl1,2, Richard Scheltema1,2
1Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH Utrecht, The Netherlands.
Nature Communications
|May 20, 2017
Summary
This study introduces advanced methods for identifying protein cross-links, significantly improving the accuracy and depth of protein interaction analysis in whole proteomes. The new techniques enable a deeper understanding of macromolecular assemblies and cellular functions.
Area of Science:
- Proteomics
- Biochemistry
- Molecular Biology
Background:
- Identifying protein-protein interactions is crucial for understanding cellular mechanisms.
- Current methods for mapping protein interactions using cross-linking mass spectrometry (XL-MS) face challenges in depth and accuracy.
- Whole proteome analysis requires robust strategies for comprehensive interaction mapping.
Purpose of the Study:
- To develop and validate optimized fragmentation schemes and data analysis strategies for enhanced protein cross-link identification.
- To improve the depth and accuracy of protein interaction analysis using non-restricted whole proteome databases.
- To provide structural insights into macromolecular assemblies through proteome-wide interaction mapping.
Main Methods:
- Implementation of a novel hybrid data acquisition strategy for sequencing cross-links at both MS2 and MS3 levels.
- Development and application of a new algorithmic design, XlinkX v2.0, for enhanced data analysis.
- Investigation of proteome-wide protein interactions in E. coli and HeLa cell lysates.
Main Results:
- Identification of 1,158 unique cross-links in E. coli proteome.
- Identification of 3,301 unique cross-links in HeLa cell lysate proteome.
- Achieved approximately 1% false discovery rate for identified cross-links, ensuring high confidence.
Conclusions:
- The optimized methods substantially enhance the depth and accuracy of protein cross-link identification.
- The identified protein interaction networks provide valuable structural information on endogenous macromolecular assemblies.
- The study showcases the utility of the developed approach on protein complexes involved in fundamental cellular processes.
