Protein Complex Identification and quantitative complexome by CN-PAGE

Area of Science:

• Proteomics
• Molecular Biology
• Plant Science

Background:

• Protein complexes are crucial for cellular processes.
• Existing methods for identifying protein complexes lack quantitative data.
• Understanding quantitative changes in protein complexes is vital for metabolic flux analysis.

Purpose of the Study:

• To present a proof-of-concept quantitative approach for studying the plant complexome.
• To enable the analysis of protein complex abundance and composition changes.
• To improve the understanding of how complexome alterations affect metabolic pathways.

Main Methods:

• Size-fractionation of native protein complexes using Clear-Native-PAGE (CN-PAGE).
• Coupling CN-PAGE with mass spectrometry to generate abundance profiles across a molecular weight gradient.
• Deconvoluting protein abundance profiles and calculating Euclidean distance for interaction partner identification.
• Utilizing Receiver-Operator Characteristic (ROC) curve analysis to optimize threshold values for complex identification.

Main Results:

• Established a quantitative method to profile the complexome in Arabidopsis thaliana at different time points (end of day and end of night).
• Demonstrated improved clustering of protein profiles through deconvolution of abundance data.
• Successfully identified putative interaction partners and protein complexes with low technical variation.
• Validated the robustness of the approach for complexome analysis.

Conclusions:

• The developed CN-PAGE coupled with mass spectrometry approach provides essential quantitative data for complexome studies.
• This method significantly enhances the ability to identify and characterize protein complexes and their interactions.
• The approach is adaptable to various biological systems for comprehensive complexome analysis and understanding metabolic regulation.