Network Effects Lead to Self-Organization in Metabolic Cycles of Self-Repelling Catalysts
Vincent Ouazan-Reboul, Ramin Golestanian, Jaime Agudo‐Canalejo
Abstract
Mixtures of particles that interact through phoretic effects are known to aggregate if they belong to species that exhibit attractive self-interactions. We study self-organization in a model metabolic cycle composed of three species of catalytically active particles that are chemotactic toward the chemicals that define their connectivity network. We find that the self-organization can be controlled by the network properties, as exemplified by a case where a collapse instability is achieved by design for self-repelling species. Our findings highlight a possibility for controlling the intricate functions of metabolic networks by taking advantage of the physics of phoretic active matter.Received 18 April 2023Accepted 27 July 2023DOI:https://doi.org/10.1103/PhysRevLett.131.128301Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the Max Planck Society.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasBiological self-organizationClusteringDiffusiophoresisEmergence of patternsPhase separationPhysical SystemsColloidsEnzymesLiving matter & active matterMulticomponent systemsNonequilibrium systemsTechniquesBrownian dynamicsPattern formationPhysics of Living SystemsPolymers & Soft MatterStatistical Physics & Thermodynamics