title: Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks.
abstract: Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications.
authors.affiliation: School of Life Sciences, University of Warwick, Coventry, United Kingdom.
authors.forename: Song
authors.identifier: 0000-0003-3983-9009
authors.initials: S
authors.lastname: Feng
authors.affiliation: Biojazz Research, Montreal, Quebec, Canada.
authors.forename: Julien F
authors.initials: JF
authors.lastname: Ollivier
authors.affiliation: School of Life Sciences, University of Warwick, Coventry, United Kingdom.
authors.forename: Orkun S
authors.initials: OS
authors.lastname: Soyer
mesh_terms: D000465:Algorithms; D000494:Allosteric Regulation; D005075:Biological Evolution; D019295:Computational Biology; D003198:Computer Simulation; D004798:Enzymes / Q000378:metabolism*; D007700:Kinetics; D008954:Models, Biological; D011506:Proteins / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*; D058615:Synthetic Biology
chemical_list: D004798:Enzymes; D011506:Proteins