Programmable synthetic cell networks regulated by tuneable reaction rates

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Adrian Zambrano - , Max Planck Institute of Molecular Cell Biology and Genetics (Author)
  • Giorgio Fracasso - , Clusters of Excellence PoL: Physics of Life, Chair of Biofunctional Polymer Materials, Max Planck Institute of Molecular Cell Biology and Genetics (Author)
  • Mengfei Gao - , Max Planck Institute of Molecular Cell Biology and Genetics, TUD Dresden University of Technology (Author)
  • Martina Ugrinic - , ETH Zurich (Author)
  • Dishi Wang - , Chair of Organic Chemistry of Polymers, Leibniz Institute of Polymer Research Dresden (Author)
  • Dietmar Appelhans - , Leibniz Institute of Polymer Research Dresden (Author)
  • Andrew deMello - , ETH Zurich (Author)
  • T. Y.Dora Tang - , Max Planck Institute of Molecular Cell Biology and Genetics, TUD Dresden University of Technology (Author)

Abstract

Coupled compartmentalised information processing and communication via molecular diffusion underpin network based population dynamics as observed in biological systems. Understanding how both compartmentalisation and communication can regulate information processes is key to rational design and control of compartmentalised reaction networks. Here, we integrate PEN DNA reactions into semi-permeable proteinosomes and characterise the effect of compartmentalisation on autocatalytic PEN DNA reactions. We observe unique behaviours in the compartmentalised systems which are not accessible under bulk conditions; for example, rates of reaction increase by an order of magnitude and reaction kinetics are more readily tuneable by enzyme concentrations in proteinosomes compared to buffer solution. We exploit these properties to regulate the reaction kinetics in two node compartmentalised reaction networks comprised of linear and autocatalytic reactions which we establish by bottom-up synthetic biology approaches.

Details

Original languageEnglish
Article number3885
JournalNature communications
Volume13
Issue number1
Publication statusPublished - 6 Jul 2022
Peer-reviewedYes

External IDs

PubMed 35794089