Cross-ID: Analysis and Visualization of Complex XL-MS-Driven Protein Interaction Networks

Area of Science:

• Proteomics
• Structural Biology
• Bioinformatics

Background:

• Protein interactions are fundamental to cellular processes, exhibiting complexity beyond individual protein functions.
• Cross-linking mass spectrometry (XL-MS) is a powerful technique for mapping protein-protein interactions (PPIs).
• Analyzing the large datasets generated by XL-MS presents significant challenges due to data complexity and varied software input formats.

Purpose of the Study:

• To introduce Cross-ID, an interactive visualization platform for analyzing XL-MS data.
• To provide a versatile tool that integrates with existing software and offers a user-friendly data import option.
• To facilitate the comprehensive analysis and validation of identified cross-links.

Main Methods:

• Development of the Cross-ID visualization platform.
• Integration with XlinkX for Proteome Discoverer output.
• Implementation of a user-controllable text-file importer for broad compatibility.
• Inclusion of features such as spectral viewing, Gene Ontology (GO) enrichment, post-translational modification (PTM) visualization, domain mapping, and dataset comparison.
• Integration with the DisVis online platform for structural validation.

Main Results:

• Cross-ID offers a unified platform for visualizing and analyzing complex XL-MS data.
• The platform supports direct integration with common XL-MS analysis software and provides flexible data import.
• Advanced features enable in-depth analysis, including structural mapping and PTM visualization.
• Export options for graphs (PDF) and data (tab-separated text) facilitate further evaluation and dissemination.

Conclusions:

• Cross-ID significantly enhances the interpretability and utility of XL-MS data.
• The platform streamlines the workflow for researchers studying protein interactions and cellular complexity.
• Cross-ID serves as a valuable tool for validating and understanding protein interaction networks.