Detecting and dissecting signaling crosstalk via the multilayer network integration of signaling and regulatory interactions

• Published in: Nucleic acids research 2024-01, Vol.52 (1), p.e5-e5
• Main Authors: Martini, Leonardo, Baek, Seung Han, Lo, Ian, Raby, Benjamin A, Silverman, Edwin K, Weiss, Scott T, Glass, Kimberly, Halu, Arda
• Format: Article
• Language: English
• Subjects: Databases, Factual; Gene Expression Regulation; Gene Regulatory Networks; Methods; Signal Transduction - genetics
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkad1035

Abstract The versatility of cellular response arises from the communication, or crosstalk, of signaling pathways in a complex network of signaling and transcriptional regulatory interactions. Understanding the various mechanisms underlying crosstalk on a global scale requires untargeted computational approaches. We present a network-based statistical approach, MuXTalk, that uses high-dimensional edges called multilinks to model the unique ways in which signaling and regulatory interactions can interface. We demonstrate that the signaling-regulatory interface is located primarily in the intermediary region between signaling pathways where crosstalk occurs, and that multilinks can differentiate between distinct signaling-transcriptional mechanisms. Using statistically over-represented multilinks as proxies of crosstalk, we infer crosstalk among 60 signaling pathways, expanding currently available crosstalk databases by more than five-fold. MuXTalk surpasses existing methods in terms of model performance metrics, identifies additions to manual curation efforts, and pinpoints potential mediators of crosstalk. Moreover, it accommodates the inherent context-dependence of crosstalk, allowing future applications to cell type- and disease-specific crosstalk. Graphical Abstract Graphical Abstract