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Enzyme sequestration as a tuning point in controlling response dynamics of signalling networks
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Feng, Song, Ollivier, Julien F. and Soyer, Orkun S. (2016) Enzyme sequestration as a tuning point in controlling response dynamics of signalling networks. PLoS Computational Biology, 12 (5). e1004918. doi:10.1371/journal.pcbi.1004918
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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1004918
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.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QH Natural history > QH426 Genetics | ||||||||
| Divisions: | Faculty of Science > Life Sciences (2010- ) | ||||||||
| Library of Congress Subject Headings (LCSH): | Cells -- Decision making -- Research, Enzyme kinetics, Biochemical engineering, Synthetic biology | ||||||||
| Journal or Publication Title: | PLoS Computational Biology | ||||||||
| Publisher: | Public Library of Science | ||||||||
| ISSN: | 1553-7358 | ||||||||
| Official Date: | 10 May 2016 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 11 May 2016 | ||||||||
| Volume: | 12 | ||||||||
| Number: | 5 | ||||||||
| Article Number: | e1004918 | ||||||||
| DOI: | 10.1371/journal.pcbi.1004918 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| Funder: | Engineering and Physical Sciences Research Council (EPSRC), University of Warwick. School of Life Sciences | ||||||||
| Grant number: | EP/H04986X/1 |
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