PCoM-DB Update: A Protein Co-Migration Database for Photosynthetic Organisms

Area of Science:

• Proteomics
• Bioinformatics
• Molecular Biology

Background:

• Protein complexes are crucial for cellular processes, protein structure, and function.
• Systematic identification of protein complexes aids in understanding cellular mechanisms.
• Existing databases offer limited tools for predicting and comparing protein complexes.

Purpose of the Study:

• To update and expand the protein co-migration database (PCoM-DB) with new datasets and analytical tools.
• To provide enhanced prediction tools for protein complexes and their interaction partners.
• To facilitate the study of protein complex evolution across different species and cellular compartments.

Main Methods:

• Blue-native PAGE and tandem mass spectrometry were employed for systematic protein complex identification.
• A web database (PCoM-DB) was developed to store and provide access to protein migration profiles.
• Version 2.0 includes new data from various organisms and cellular components, along with enhanced analytical tools.

Main Results:

• PCoM-DB version 2.0 incorporates data from Prochlorococcus marinus, Thermosynechococcus elongatus, Chlamydomonas reinhardtii, and Physcomitrella patens.
• Expanded Arabidopsis thaliana data includes intact mitochondria, chloroplasts, stroma, and envelopes.
• New tools enable multiple protein searches and heat map visualization of migration profiles for comparative analysis.

Conclusions:

• The updated PCoM-DB version 2.0 significantly enhances the ability to identify protein complexes and their interactions.
• The database serves as a valuable resource for researchers investigating protein complex dynamics and evolutionary changes.
• Comparative analysis tools in PCoM-DB aid in understanding protein complex conservation and divergence across species.