Programming Hydrogels with Complex Transient Behaviors via Autocatalytic Cascade Reactions.

It is challenging to design complex synthetic life-like systems that can show both autoevolution and fuel-driven transient behaviors. Here, we report a new class of chemical reaction networks (CRNs) to construct life-like polymer hydrogels. The CRNs are constituted of autocatalytic cascade reactions and fuel-driven reaction networks. The reactions start with only two compounds, that is, thiol of 4-arm-PEG-SH and thiuram disulfides, and undergo thiol oxidation (k1), disulfide metathesis (k2), and thionate hydrolysis-coupling reactions (k3) subsequently, leading to a four-state autonomous transition of sol(I) → soft gel → sol(II) → stiff gel. Moreover, thiuram disulfides can be applied as a fuel to drive the repeated occurrence of metathesis and hydrolysis-coupling reactions, generating dissipative stiff gel → sol(II) → stiff gel cycles. Systematic kinetics studies reveal that the event and lifetime of every transient state could be delicately tailored-up by varying the thiuram disulfide concentration, pH of the system, and thiuram structures. Since the consecutive transient behaviors are precisely predictable, we envision the strategy's potential in guiding the molecular designs of autonomous and adaptive materials for many fields.

Feedback and Communication in Active Hydrogel Spheres with pH Fronts: Facile Approaches to Grow Soft Hydrogel Structures.

Compartmentalized reaction networks regulating signal processing, communication and pattern formation are central to living systems. Towards achieving life-like materials, we compartmentalized urea-urease and more complex urea-urease/ester-esterase pH-feedback reaction networks into hydrogel spheres and investigate how fuel-driven pH fronts can be sent out from these spheres and regulated by internal reaction networks. Membrane characteristics are installed by covering urease spheres with responsive hydrogel shells. We then encapsulate the two networks (urea-urease and ester-esterase) separately into different hydrogel spheres to devise communication, pattern formation and attraction. Moreover, these pH fronts and patterns can be used for self-growing hydrogels, and for developing complex geometries from non-injectable hydrogels without 3D printing tools. This study opens possibilities for compartmentalized feedback reactions and their use in next generation materials fabrication.

Artificial Biosystems by Printing Biology.

The continuous progress of printing technologies over the past 20 years has fueled the development of a plethora of applications in materials sciences, flexible electronics, and biotechnologies. More recently, printing methodologies have started up to explore the world of Artificial Biology, offering new paradigms in the direct assembly of Artificial Biosystems (small condensates, compartments, networks, tissues, and organs) by mimicking the result of the evolution of living systems and also by redesigning natural biological systems, taking inspiration from them. This recent progress is reported in terms of a new field here defined as Printing Biology, resulting from the intersection between the field of printing and the bottom up Synthetic Biology. Printing Biology explores new approaches for the reconfigurable assembly of designed life-like or life-inspired structures. This work presents this emerging field, highlighting its main features, i.e., printing methodologies (from 2D to 3D), molecular ink properties, deposition mechanisms, and finally the applications and future challenges. Printing Biology is expected to show a growing impact on the development of biotechnology and life-inspired fabrication.

Preprogramming Complex Hydrogel Responses using Enzymatic Reaction Networks.

The creation of adaptive matter is heavily inspired by biological systems. However, it remains challenging to design complex material responses that are governed by reaction networks, which lie at the heart of cellular complexity. The main reason for this slow progress is the lack of a general strategy to integrate reaction networks with materials. Herein we use a systematic approach to preprogram the response of a hydrogel to a trigger, in this case the enzyme trypsin, which activates a reaction network embedded within the hydrogel. A full characterization of all the kinetic rate constants in the system enabled the construction of a computational model, which predicted different hydrogel responses depending on the input concentration of the trigger. The results of the simulation are in good agreement with experimental findings. Our methodology can be used to design new, adaptive materials of which the properties are governed by reaction networks of arbitrary complexity.