A statistical mechanics investigation of unfolded protein response across organisms

Year: 2024

Authors: Luchetti N., Smith K.M., Matarrese M.A.G., Loppini A., Filippi S., Chiodo L.

Autors Affiliation: Univ Campus Biomed Roma, Dept Engn, Via Alvaro Portillo 21, I-00128 Rome, Italy; Italian Inst Technol, Ctr Life Nano& Neurosci, Viale Regina Elena 291, I-00161 Rome, Italy; Univ Strathclyde, Comp & Informat Sci, 26 Richmond St, Glasgow G1 1XH, Scotland; Univ Campus Biomed Roma, Dept Med & Surg, Via Alvaro Portillo 21, I-00128 Rome, Italy; CNR, Natl Inst Opt, Largo Enr Fermi 6, I-50125 Florence, Italy; Int Ctr Relativist Astrophys Network, Piazza Repubbl 10, I-65122 Pescara, Italy.

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 protein-protein interaction 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.

Journal/Review: SCIENTIFIC REPORTS

Volume: 14 (1)      Pages from: 27658-1  to: 27658-17

More Information: A.L., S.F., and L.C. acknowledge the support of the International Center for Relativistic Astrophysics Network (ICRANet), Italy, and the support of the Italian National Group for Mathematical Physics (GNFM-INdAM).
KeyWords: Endoplasmic reticulum stress; Complex networks; Protein-protein interactions; Network analysis
DOI: 10.1038/s41598-024-79086-8