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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Simple topological features reflect dynamics and modularity in protein interaction networks.

Yuri Pritykin¹, Mona Singh

¹Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America ; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.

Plos Computational Biology

|October 17, 2013

Summary

Simple protein network properties predict protein roles in cellular organization. Topological features of protein-protein interaction networks reveal protein modularity and are conserved across species.

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Area of Science:

Systems Biology
Network Biology
Bioinformatics

Background:

Protein-protein interaction (PPI) networks are crucial for understanding cellular functions.
Previous studies have explored network modularity using gene expression data, yielding controversial results.
Hub proteins, central to networks, play significant roles in cellular organization.

Purpose of the Study:

To investigate if simple topological properties of proteins in PPI networks predict their functional roles.
To re-examine the dynamic modularity of the Saccharomyces cerevisiae interactome.
To determine the conservation of these properties across different organisms.

Main Methods:

Analysis of PPI networks from five diverse organisms: S. cerevisiae, H. sapiens, D. melanogaster, A. thaliana, and E. coli.
Comparison of hub proteins based on co-expression with their interacting partners.
Correlation analysis between simple topological measures and average co-expression.
Cross-interactomic analysis to assess conservation.

Main Results:

Hub proteins co-expressed with partners differ functionally and structurally from those not co-expressed.
Co-expressed hubs tend to be intramodular, while non-co-expressed hubs are intermodular.
Simple topological measures correlate with average hub co-expression, independent of classification.
These topological characteristics are conserved across the analyzed organisms.
Topological features alone reflect interactome dynamics and modularity.

Conclusions:

Static PPI network topology effectively captures dynamic aspects of cellular organization.
Simple topological measures are powerful predictors of protein roles and modularity.
These findings offer a conserved framework for understanding protein function in diverse species.