4 research outputs found
History Dependence in a Chemical Reaction Network Enables Dynamic Switching
This work describes an enzymatic autocatalytic network capable of dynamic switching under out-of-equilibrium conditions. The network, wherein a molecular fuel (trypsinogen) and an inhibitor (soybean trypsin inhibitor) compete for a catalyst (trypsin), is kept from reaching equilibria using a continuous flow stirred tank reactor. A so-called âlinear inhibition sweepâ is developed (i.e., a molecular analogue of linear sweep voltammetry) to intentionally perturb the competition between autocatalysis and inhibition, and used to demonstrate that a simple molecular system, comprising only three components, is already capable of a variety of essential neuromorphic behaviors (hysteresis, synchronization, resonance, and adaptation). This research provides the first steps in the development of a strategy that uses the principles in systems chemistry to transform chemical reaction networks into platforms capable of neural network computing.</p
PolylysineâCoated Surfaces Drive Competition in Chemical Reaction Networks to Enable Molecular Information Processing
Polylysine-Coated Surfaces Drive Competition in Chemical Reaction Networks to Enable Molecular Information Processing
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.</p
Polylysine-coated surfaces drive competition in chemical reaction networks to enable molecular information processing
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 which consists of a simple acid-base equilibrium that can be perturbed by two opposing activation processes. Crucially, one of the activation processes is immobilized (or localized) 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