Polylysine-Coated Surfaces Drive Competition in Chemical Reaction Networks to Enable Molecular Information Processing

A. Hazal Koyuncu, Jacopo Movilli, Sevil Sahin, Dmitrii V. Kriukov, Jurriaan Huskens*, Albert S.Y. Wong*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

This work describes a competing activation network, which is regulated by chemical feedback at the liquid-surface interface. Feedback loops dynamically tune the concentration of chemical components in living systems, thereby controlling regulatory processes in neural, genetic, and metabolic networks. Advances in systems chemistry demonstrate that chemical feedback could be designed based on similar concepts of using activation and inhibition processes. Most efforts, however, are focused on temporal feedback whereas biological networks are maintained by the interplay between temporal and spatial organization. Here, we designed a feedback system comprising a simple acid-base equilibrium that can be perturbed by two opposing activation processes. Crucially, one of the processes is immobilized on the surface of a microfluidic channel using poly-l-lysine (PLL). We measured the capacity of the PLL-coated channels to resist changes in pH in flow using a pH-sensitive indicator, phenol red, and showed that this capacity can be increased by employing polyelectrolyte multilayers. Specifically, we found that the rate of local activation (i. e., the deprotonation of the immobilized lysine residues) could be significantly increased to delay the otherwise fast equilibrium. This effect allowed for encoding read and write operations, providing the potential to bestow CRNs with the capacity of molecular information processing.

Original languageEnglish
Article numbere202300030
JournalChemSystemsChem
Volume6
Issue number1
DOIs
Publication statusPublished - Jan 2024

Keywords

  • UT-Hybrid-D
  • feedback loops
  • microfluidics
  • molecular information processing
  • molecular nanofabrication
  • chemical reaction network

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