Structural controllability to unveil hidden regulation mechanisms in Unfolded Protein Response: The role of network models
Year: 2023
Authors: Luchetti N., Loppini A., Matarrese MAG., Chiodo L., Filippi S.
Autors Affiliation: Univ Campus Biomed Roma, Dept Engn, Via Alvaro Portillo 21, I-00128 Rome, Italy; Ist Italiano Tecnol, Ctr Life Nano & Neurosci, Viale Regina Elena 291, I-00161 Rome, Italy; Jane & John Justin Inst Mind Hlth Neurosci Ctr, Cook Children Hlth Care Syst, 1500 Cooper St, Ft Worth, TX 76104 USA; Univ Texas Arlington, Dept Bioengn, 701 Nedderman Dr St, Arlington, TX 76019 USA; Ist Nazl Ott Consiglio Nazl Ric CNR INO, Largo Enrico Fermi 6, I-50125 Florence, Italy; ICRANet Int Ctr Relativist Astrophys Network, Piazza Repubbl 10, I-65122 Pescara, Italy.
Abstract: The Unfolded Protein Response is the cell mechanism for maintaining the balance of properly folded proteins in the endoplasmic reticulum, the specialized cellular compart-ment. Although it is largely studied from a biological point of view, much of the literature lacks a quantitative analysis of such a central signaling pathway. In this work, we aim to fill this gap by applying structural controllability analysis of complex networks to several Unfolded Protein Response networks to identify crucial nodes in the signaling flow. In particular, we first build different network models of the Unfolded Protein Response mechanism, relying on data contained in various protein-protein interaction databases. Then, we identify the driver nodes, essential for overall network control, i.e., the key proteins on which external stimulation may be optimally delivered to control network behavior. Our structural controllability analysis results show that the driver nodes commonly identified across databases match with known endoplasmic reticulum stress sensors. This potentially confirms that the theoretically identified drivers correspond to the biological key proteins associated with fundamental cellular activities and diseases. In conclusion, we prove that structural controllability is a reliable quantitative tool to investigate biological signaling pathways, and it can be potentially applied to networks more complex and less explored than Unfolded Protein Response.& COPY; 2023 Elsevier B.V. All rights reserved.
Journal/Review: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume: 617 Pages from: 128671-1 to: 128671-23
More Information: A.L., L.C. and S.F. acknowledge the support of the International Center for Relativistic Astrophysics Network (ICRANet) , Italy. All the authors acknowledge the support of the Italian National Group for Mathematical Physics (GNFM-INdAM) . All the authors acknowledge the support from the European Commission’s Horizon Europe Framework Programme under the Research and Innovation Action GA n. 101070546-MUQUABIS and the IR0000011-EBRAINS-Italy PNRR research infrastructure. We thank Dr. Alberto Luini for useful scientific discussions. All authors have read and agreed to the published version of the manuscript.KeyWords: Minimum driver nodes; Protein-protein interactions; Complex networks; Endoplasmic reticulum stress; Biological networksDOI: 10.1016/j.physa.2023.128671