A statistical mechanics investigation of Unfolded Protein Response across organisms

TL;DR

This study applies statistical mechanics and network theory to analyze protein interaction networks involved in the Unfolded Protein Response across twelve organisms, revealing phylogenetic relationships and key pathways.

Contribution

It introduces a novel approach using network robustness and controllability to identify critical proteins and pathways in the UPR across diverse species.

Findings

Network measures correlate with phylogenetic relationships.

Advanced network methods identify main UPR pathways.

Protein interaction networks exhibit varying robustness across organisms.

Abstract

Living systems rely on coordinated molecular interactions, especially those related to gene expression and protein activity. The Unfolded Protein Response is a crucial mechanism in eukaryotic cells, activated when unfolded proteins exceed a critical threshold. It maintains cell homeostasis by enhancing protein folding, initiating quality control, and activating degradation pathways when damage is irreversible. This response functions as a dynamic signaling network, with proteins as nodes and their interactions as edges. We analyze these protein-protein networks across different organisms to understand their intricate intra-cellular interactions and behaviors. In this work, analyzing twelve organisms, we assess how fundamental measures in network theory can individuate seed-proteins and specific pathways across organisms. We employ network robustness to evaluate and compare the strength of the investigated PPI networks, and the structural controllability of complex networks to find and compare the sets of driver nodes necessary to control the overall networks. We find that network measures are related to phylogenetics, and advanced network methods can identify main pathways of significance in the complete Unfolded Protein Response mechanism.