Open Prebiotic Environments Drive Emergent Phenomena and Complex Behavior

Artificial Homeostasis Systems Based on Feedback Reaction Networks: Design Principles and Future Promises

Feedback-controlled chemical reaction networks (FCRNs) are indispensable for various biological processes, such as cellular mechanisms, patterns, and signaling pathways. Through the intricate interplay of many feedback loops (FLs), FCRNs maintain a stable internal cellular environment. Currently, creating minimalistic synthetic cells is the long-term objective of systems chemistry, which is motivated by such natural integrity. The design, kinetic optimization, and analysis of FCRNs to exhibit functions akin to those of a cell still pose significant challenges. Indeed, reaching synthetic homeostasis is essential for engineering synthetic cell components. However, maintaining homeostasis in artificial systems against various agitations is a difficult task. Several biological events can provide us with guidelines for a conceptual understanding of homeostasis, which can be further applicable in designing artificial synthetic systems. In this regard, we organize our review with artificial homeostasis systems driven by FCRNs at different length scales, including homogeneous, compartmentalized, and soft material systems. First, we stretch a quick overview of FCRNs in different molecular and supramolecular systems, which are the essential toolbox for engineering different nonlinear functions and homeostatic systems. Moreover, the existing history of synthetic homeostasis in chemical and material systems and their advanced functions with self-correcting, and regulating properties are also emphasized.

Light-driven eco-evolutionary dynamics in a synthetic replicator system

Darwinian evolution involves the inheritance and selection of variations in reproducing entities. Selection can be based on, among others, interactions with the environment. Conversely, the replicating entities can also affect their environment generating a reciprocal feedback on evolutionary dynamics. The onset of such eco-evolutionary dynamics marks a stepping stone in the transition from chemistry to biology. Yet the bottom-up creation of a molecular system that exhibits eco-evolutionary dynamics has remained elusive. Here we describe the onset of such dynamics in a minimal system containing two synthetic self-replicators. The replicators are capable of binding and activating a co-factor, enabling them to change the oxidation state of their environment through photoredox catalysis. The replicator distribution adapts to this change and, depending on light intensity, one or the other replicator becomes dominant. This study shows how behaviour analogous to eco-evolutionary dynamics-which until now has been restricted to biology-can be created using an artificial minimal replicator system.

Design of oscillatory dynamics in numerical simulations of compartment-based enzyme systems

Enzymatic reactions that yield non-neutral products are known to involve feedback due to the bell-shaped pH-rate curve of the enzyme. Compartmentalizing the reaction has been shown to lead to transport-driven oscillations in theory; however, there have been few reproducible experimental examples. Our objective was to determine how the conditions could be optimized to achieve pH oscillations. We employed numerical simulations to investigate the hydrolysis of ethyl acetate in a confined esterase enzyme system, examining the influence of key factors on its behavior. Specific parameter ranges that lead to bistability and self-sustained pH oscillations and the importance of fast base transport for oscillations in this acid-producing system are highlighted. Suggestions are made to expand the parameter space for the occurrence of oscillations, including modifying the maximum of the enzyme pH-rate curve and increasing the negative feedback rate. This research not only sheds light on the programmable nature of enzyme-driven pH regulation but also furthers knowledge on the optimal design of such feedback systems for experimentalists.

Enhancement of Prebiotic Peptide Formation in Cyclic Environments

The dynamic behaviors of prebiotic reaction networks may be critically important to understanding how larger biopolymers could emerge, despite being unfavorable to form in water. We focus on understanding the dynamics of simple systems, prior to the emergence of replication mechanisms, and what role they may have played in biopolymer formation. We specifically consider the dynamics in cyclic environments using both model and experimental data. Cyclic environmental conditions prevent a system from reaching thermodynamic equilibrium, improving the chance of observing interesting kinetic behaviors. We used an approximate kinetic model to simulate the dynamics of trimetaphosphate (TP)-activated peptide formation from glycine in cyclic wet-dry conditions. The model predicts that environmental cycling allows trimer and tetramer peptides to sustain concentrations above the predicted fixed points of the model due to overshoot, a dynamic phenomenon. Our experiments demonstrate that oscillatory environments can shift product distributions in favor of longer peptides. However, experimental validation of certain behaviors in the kinetic model is challenging, considering that open systems with cyclic environmental conditions break many of the common assumptions in classical chemical kinetics. Overall, our results suggest that the dynamics of simple peptide reaction networks in cyclic environments may have been important for the formation of longer polymers on the early Earth. Similar phenomena may have also contributed to the emergence of reaction networks with product distributions determined not by thermodynamics, but rather by kinetics.

pH-feedback systems to program autonomous self-assembly and material lifecycles

pH-responsive systems have gained importance for the development of smart materials and for biomedical applications because they can switch between different states by simple acid/base triggers. However, such equilibrium systems lack the autonomous behaviour that is so ubiquitous in living systems that self-regulate out of equilibrium. As a contribution to the emerging field of autonomous chemical systems, we have developed pH-feedback systems (pH-FS) based on the coupling of acid- and base-producing steps in chemical reaction networks. The resulting autonomous nonlinear pH curves can be coupled with a variety of pH-sensitive building blocks to program the lifecycles of the associated transient state at the level of self-assemblies and material systems. In this article, we discuss the different generations of such pH-feedback systems, the principles of their coupling to self-assemblies with lifecycles and highlight emerging concepts for the design of autonomous functional materials. The specificity, robustness, and flexible operation of such pH-FS can also be used to realize chemo-structural and chemo-mechanical feedbacks that extend the behaviour of such materials systems toward complex and functional life-like systems.

Dynamic properties of a self-replicating peptide network with inhibition

In this paper, we report an open system consisting of three self-replicating peptides, in which peptide 1 inhibits the duplex template of peptide 2, peptide 2 inhibits duplex 3, and peptide 3 inhibits duplex 1 to complete the negative feedback loop. This interacting chemical network yields oscillations in the concentrations of all species over time and establishes a possible mechanism for pre-biotic chemical systems organization. The first focus of our analysis is the effect of altering rates of duplex formation and inhibition on oscillations. We then examine the autocatalytic rate constant in the symmetric and asymmetric cases.

Spontaneous Emergence of Transient Chirality in Closed, Reversible Frank-like Deterministic Models

To explore abiotic theories related to the origin of biomolecular homochirality, we analyze two entirely reversible kinetic models composed of an enantioselective autocatalysis with limited stereoselectivity that is coupled to an enantiomeric mutual inhibition (Frank-like models). The two models differ in their autocatalytic steps in respect to the formation of monomer species in one model and of dimer species in the other. While fully reversible and running in a closed system, spontaneous mirror symmetry breaking (SMSB) gives rise to transient chiral excursions, even when starting from a strictly achiral situation. Before the SMSB, the two models differ in the main dissipative processes. At the SMSB, the entropy production rate reaches its maximum in both models. Here it is the enantioselective autocatalysis with retention of the winner enantiomer that dominates. During the terminal phase, the enantioselective autocatalysis with inversion prevails, while the entropy production rate vanishes, thus fulfilling the conditions of microscopic reversibility. SMSB does not occur if the autocatalytic rate constant is too strong or too weak. However, when the autocatalysis is relatively weak, the temporary chiral excursions last for long periods of time and could be the starting point of a cascade of asymmetric reactions. The realism of such Frank-like models is discussed from the viewpoint of their relevance to prebiotic chemistry.

An Approach to the De Novo Synthesis of Life

As the remit of chemistry expands beyond molecules to systems, new synthetic targets appear on the horizon. Among these, life represents perhaps the ultimate synthetic challenge. Building on an increasingly detailed understanding of the inner workings of living systems and advances in organic synthesis and supramolecular chemistry, the de novo synthesis of life (i.e., the construction of a new form of life based on completely synthetic components) is coming within reach. This Account presents our first steps in the journey toward this long-term goal. The synthesis of life requires the functional integration of different subsystems that harbor the different characteristics that are deemed essential to life. The most important of these are self-replication, metabolism, and compartmentalization. Integrating these features into a single system, maintaining this system out of equilibrium, and allowing it to undergo Darwinian evolution should ideally result in the emergence of life. Our journey toward de novo life started with the serendipitous discovery of a new mechanism of self-replication. We found that self-assembly in a mixture of interconverting oligomers is a general way of achieving self-replication, where the assembly process drives the synthesis of the very molecules that assemble. Mechanically induced breakage of the growing replicating assemblies resulted in their exponential growth, which is an important enabler for achieving Darwinian evolution. Through this mechanism, the self-replication of compounds containing peptides, nucleobases, and fully synthetic molecules was achieved. Several examples of evolutionary dynamics have been observed in these systems, including the spontaneous diversification of replicators allowing them to specialize on different food sets, history dependence of replicator composition, and the spontaneous emergence of parasitic behavior. Peptide-based replicator assemblies were found to organize their peptide units in space in a manner that, inadvertently, gives rise to microenvironments that are capable of catalysis of chemical reactions or binding-induced activation of cofactors. Among the reactions that can be catalyzed by the replicators are ones that produce the precursors from which these replicators grow, amounting to the first examples of the assimilation of a proto-metabolism. Operating these replicators in a chemically fueled out-of-equilibrium replication-destruction regime was found to promote an increase in their molecular complexity. Fueling counteracts the inherent tendency of replicators to evolve toward lower complexity (caused by the fact that smaller replicators tend to replicate faster). Among the remaining steps on the road to de novo life are now to assimilate compartmentalization and achieve open-ended evolution of the resulting system. Success in the synthesis of de novo life, once obtained, will have far-reaching implications for our understanding of what life is, for the search for extraterrestrial life, for how life may have originated on earth, and for every-day life by opening up new vistas in the form living technology and materials.

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.

Signaling in Systems Chemistry: Programing Gold Nanoparticles Formation and Assembly Using a Dynamic Bistable Network

Living cells exploit bistable and oscillatory behaviors as memory mechanisms, facilitating the integration of transient stimuli into sustained molecular responses that control downstream functions. Synthetic bistable networks have also been studied as memory entities, but have rarely been utilized to control orthogonal functions in coupled dynamic systems. We herein present a new cascade pathway, for which we have exploited a well-characterized switchable peptide-based replicating network, operating far from equilibrium, that yields two alternative steady-state outputs, which in turn serve as the input signals for consecutive processes that regulate various features of Au nanoparticle shape and assembly. This study further sheds light on how bridging together the fields of systems chemistry and nanotechnology may open up new opportunities for the dynamically controlled design of functional materials.

Entropic analysis of bistability and the general evolution criterion

An open flow bistable Schlögl model in a well-stirred isothermal reaction volume V showing the balance of the entropy production and the exchange entropy on the non-equilibrium stationary states.

An ecological framework for the analysis of prebiotic chemical reaction networks

It is becoming widely accepted that very early in life's origin, even before the emergence of genetic encoding, reaction networks of diverse small chemicals might have manifested key properties of life, namely self-propagation and adaptive evolution. To explore this possibility, we formalize the dynamics of chemical reaction networks within the framework of chemical ecosystem ecology. To capture the idea that life-like chemical systems are maintained out of equilibrium by fluxes of energy-rich food chemicals, we model chemical ecosystems in well-mixed compartments that are subject to constant dilution by a solution with a fixed concentration of input chemicals. Modelling all chemical reactions as fully reversible, we show that seeding an autocatalytic cycle with tiny amounts of one or more of its member chemicals results in logistic growth of all member chemicals in the cycle. This finding justifies drawing an instructive analogy between an autocatalytic cycle and a biological species. We extend this finding to show that pairs of autocatalytic cycles can exhibit competitive, predator-prey, or mutualistic associations just like biological species. Furthermore, when there is stochasticity in the environment, particularly in the seeding of autocatalytic cycles, chemical ecosystems can show complex dynamics that can resemble evolution. The evolutionary character is especially clear when the network architecture results in ecological precedence, which makes a system's trajectory historically contingent on the order in which cycles are seeded. For all its simplicity, the framework developed here helps explain the onset of adaptive evolution in prebiotic chemical reaction networks, and can shed light on the origin of key biological attributes such as thermodynamic irreversibility and genetic encoding.

Compositional Persistence in a Multicyclic Network of Synthetic Replicators

The emergence of collections of simple chemical entities that create self-sustaining reaction networks, embedding replication and catalysis, is cited as a potential mechanism for the appearance on the early Earth of systems that satisfy minimal definitions of life. In this work, a functional reaction network that creates and maintains a set of privileged replicator structures through auto- and cross-catalyzed reaction cycles is created from the pairwise combinations of four reagents. We show that the addition of individual preformed templates to this network, representing instructions to synthesize a specific replicator, induces changes in the output composition of the system that represent a network-level response. Further, we establish through sets of serial transfer experiments that the catalytic connections that exist between the four replicators in this network and the system-level behavior thereby encoded impose limits on the compositional variability that can be induced by repeated exposure to instructional inputs, in the form of preformed templates, to the system. The origin of this persistence is traced through kinetic simulations to the properties and inter-relationships between the critical ternary complexes formed by the auto- and crosscatalytic templates. These results demonstrate that in an environment where there is no continuous selection pressure the network connectivity, described by the catalytic relationships and system-level interactions between the replicators, is persistent, thereby limiting the ability of this network to adapt and evolve.