Autocatalytic Reaction Networks Research Articles

Exploring the programmability of autocatalytic chemical reaction networks

Networks of chemical reactions exhibit emergent properties under out-of-equilibrium conditions. Recent advances in systems chemistry demonstrate that networks with sufficient chemical complexity can be harnessed to emulate properties important for neuromorphic computing. In all examples, autocatalysis appears an essential element for facilitating the nonlinear integration of the input and self-regulatory abilities in the output. How this chemical analogue of a positive feedback mechanism can be controlled in a programmable manner is, however, unexplored. Here, we develop a strategy that uses metal ions (Ca2+, La3+, and Nd3+) to control the rate of a trypsin-catalysed autocatalytic reaction network. We demonstrate that this type of control allows for tuning the kinetics in the network, thereby changing the nature of the positive feedback. The simulations and experiments reveal that an input with one or more metal ions allow for temporal and history-dependent outputs that can be mapped onto a variety of mathematical functions.

Coupling DNA Origami Filament Growth to an Autocatalytic Production of Fuel

AbstractIn this study, the hierarchical assembly of DNA origami filaments (DOF) initiated by an autocatalytic DNA reaction network (DRN) is investigated. The so‐formed filaments are subsequently disassembled by toehold‐mediated strand displacement mechanisms. Using fluorescence resonance energy transfer, the kinetics of DOF growth after direct addition of fuel and compared it to the polymerization process triggered by the release of fuel from the DRN is monitored. Optimization of design and experimental conditions enabled to fine‐tune the kinetics of the two processes, ensuring that the release of fuel from the DRN outpaced the consumption of fuel by the downstream polymerization reaction. This resulted in a sustained and controlled DOF growth leading to micrometer‐long filament structures. Finally, although the presence of a toehold in the fuel strand reduced the efficiency of monomer association in the polymerization process, a 10‐fold excess of the anti‐fuel strand is efficient in dissociating the filament structures, permitting a potential reset for new reactions. The study shows that the kinetics of DNA origami filaments growth can be finely manipulated by a cascade of upstream reactions, suggesting alternative approaches for the creation of programmable DNA‐based nanomaterials that can sense and respond to more complex and distant events.

Structural constraints limit the regime of optimal flux in autocatalytic reaction networks

Autocatalytic chemical networks play a predominant role in a large number of natural systems such as in metabolic pathways and in ecological networks. Despite recent efforts, the precise impact of thermodynamic constraints on these networks remains elusive. In this work, we present a theoretical framework that allows specific bounds on the thermodynamic affinity and on the concentrations of autocatalysts in mass-action autocatalytic networks. These bounds can be obtained solely from the stoichiometry of the underlying chemical reaction network, and are independent from the numerical values of kinetic parameters. This property holds in the specific regime where all the fluxes of the network are tightly coupled and maximal. Our method is applicable to large networks, and can be used to complement constraints-based modeling methods of metabolic networks, which typically do not provide predictions about thermodynamic properties or concentration ranges of metabolites.

Demonstrating Prebiotic Peptide Evolution by Nitrogen Isotope Discrimination in an Autocatalytic Chemical Reaction Network

Demonstrating Prebiotic Peptide Evolution by Nitrogen Isotope Discrimination in an Autocatalytic Chemical Reaction Network

Theoretical perspective on synthetic man‐made life: Learning from the origin of life

AbstractCreating a man‐made life in the laboratory is one of life science’s most intriguing yet challenging problems. Advances in synthetic biology and related theories, particularly those related to the origin of life, have laid the groundwork for further exploration and understanding in this field of artificial life or man‐made life. But there remains a wealth of quantitative mathematical models and tools that have yet to be applied to this area. In this paper, we review the two main approaches often employed in the field of man‐made life: the top‐down approach that reduces the complexity of extant and existing living systems and the bottom‐up approach that integrates well‐defined components, by introducing the theoretical basis, recent advances, and their limitations. We then argue for another possible approach, namely “bottom‐up from the origin of life”: Starting with the establishment of autocatalytic chemical reaction networks that employ physical boundaries as the initial compartments, then designing directed evolutionary systems, with the expectation that independent compartments will eventually emerge so that the system becomes free‐living. This approach is actually analogous to the process of how life originated. With this paper, we aim to stimulate the interest of synthetic biologists and experimentalists to consider a more theoretical perspective, and to promote the communication between the origin of life community and the synthetic man‐made life community.

Oscillatory dynamics in a reaction network based on imine hydrolysis.

We have built an autocatalytic reaction network, based on the hydrolysis of certain imines, which exhibits bistability in an open system. The positive feedback originates from the interplay of fast acid-base equilibria, leading to hydroxide ion production, and pH-dependent hydrolysis rates. The addition of a first-order removal of the autocatalyst can result in sustained pH oscillations close to physiological conditions. The unit-amplitude pH oscillations are accompanied by the stoichiometric conversion of imine into amine back and forth. A systematic parameter search is carried out to characterize the rich observable dynamics and identify the evolving bifurcations.

Autocatalytic flow chemistry

Autocatalysis is a crucial process of nonequilibrium self-organization in nature and is assumed to play a role in the origin of life. The essential dynamical phenomena of an autocatalytic reaction network are bistability and the development of propagating front when combined with diffusion. The presence of bulk fluid motion may widen the range of emerging behavior in those systems. Many aspects of the dynamics of autocatalytic reactions in a continuous flow have already been studied, especially the shape and dynamics of the chemical front and the influence of the chemical reactions on hydrodynamic instabilities. This paper aims to provide experimental evidence of bistability and related dynamical phenomena, such as excitability and oscillations in autocatalytic reactions performed in a tubular flow reactor, where the flow is laminar and advection is the dominating transport process. We show that the linear residence time ramp may result in the simultaneous appearance of different dynamic states along the length of the pipe. Therefore, long tubular reactors offer a unique opportunity to quickly explore the dynamics of reaction networks. These findings enhance our understanding of nonlinear flow chemistry and its role in natural pattern formation.

Multispecies autocatalytic RNA reaction networks in coacervates

Robust localization of self-reproducing autocatalytic chemistries is a key step in the realization of heritable and evolvable chemical systems. While autocatalytic chemical reaction networks already possess attributes such as heritable self-reproduction and evolvability, localizing functional multispecies networks within complex primitive phases, such as coacervates, has remained unexplored. Here, we show the self-reproduction of the Azoarcus ribozyme system within charge-rich coacervates where catalytic ribozymes are produced by the autocatalytic assembly of constituent smaller RNA fragments. We systematically demonstrate the catalytic assembly of active ribozymes within phase-separated coacervates—both in micron-sized droplets as well as in a coalesced macrophase, underscoring the facility of the complex, charge-rich phase to support these reactions in multiple configurations. By constructing multispecies reaction networks, we show that these newly assembled molecules are active, participating both in self- and cross-catalysis within the coacervates. Finally, due to differential molecular transport, these phase-separated compartments endow robustness to the composition of the collectively autocatalytic networks against external perturbations. Altogether, our results establish the formation of multispecies self-reproducing reaction networks in phase-separated compartments which in turn render transient robustness to the network composition.

Semigroup models for biochemical reaction networks

The catalytic reaction system (CRS) formalism by Hordijk and Steel is a versatile method to model autocatalytic biochemical reaction networks. It is particularly suited, and has been widely used, to study self-sustainment and self-generation properties. Its distinguishing feature is the explicit assignment of a catalytic function to chemicals that are part of the system. In this work, it is shown that the subsequent and simultaneous catalytic functions give rise to an algebraic structure of a semigroup with the additional compatible operation of idempotent addition and a partial order. The aim of this article is to demonstrate that such semigroup models are a natural setup to describe and analyze self-sustaining CRS. The basic algebraic properties of the models are established and the notion of the function of any set of chemicals on the whole CRS is made precise. This leads to a natural discrete dynamical system on the power set of chemicals, which is obtained by iteratively considering the self-action on a set of chemicals by its own function. The fixed points of this dynamical system are proven to correspond to self-sustaining sets of chemicals, which are functionally closed. Finally, as the main application, a theorem on the maximal self-sustaining set and a structure theorem on the set of functionally closed self-sustaining sets of chemicals are proven.

The hierarchical organization of autocatalytic reaction networks and its relevance to the origin of life.

Prior work on abiogenesis, the emergence of life from non-life, suggests that it requires chemical reaction networks that contain self-amplifying motifs, namely, autocatalytic cores. However, little is known about how the presence of multiple autocatalytic cores might allow for the gradual accretion of complexity on the path to life. To explore this problem, we develop the concept of a seed-dependent autocatalytic system (SDAS), which is a subnetwork that can autocatalytically self-maintain given a flux of food, but cannot be initiated by food alone. Rather, initiation of SDASs requires the transient introduction of chemical "seeds." We show that, depending on the topological relationship of SDASs in a chemical reaction network, a food-driven system can accrete complexity in a historically contingent manner, governed by rare seeding events. We develop new algorithms for detecting and analyzing SDASs in chemical reaction databases and describe parallels between multi-SDAS networks and biological ecosystems. Applying our algorithms to both an abiotic reaction network and a biochemical one, each driven by a set of simple food chemicals, we detect SDASs that are organized as trophic tiers, of which the higher tier can be seeded by relatively simple chemicals if the lower tier is already activated. This indicates that sequential activation of trophically organized SDASs by seed chemicals that are not much more complex than what already exist could be a mechanism of gradual complexification from relatively simple abiotic reactions to more complex life-like systems. Interestingly, in both reaction networks, higher-tier SDASs include chemicals that might alter emergent features of chemical systems and could serve as early targets of selection. Our analysis provides computational tools for analyzing very large chemical/biochemical reaction networks and suggests new approaches to studying abiogenesis in the lab.

Spatiotemporal Regulation of Hydrogel Actuators by Autocatalytic Reaction Networks.

Regulating hydrogel actuators with chemical reaction networks is instrumental for constructing life-inspired smart materials. Herein, hydrogel actuators are engineered that are regulated by the autocatalytic front of thiols. The actuators consist of two layers. The first layer, which is regular polyacrylamide hydrogel, is in a strained conformation. The second layer, which is polyacrylamide hydrogel with disulfide crosslinks, maintains strain in the first layer. When thiols released by the autocatalytic front reduce disulfide crosslinks, the hydrogel actuates by releasing the mechanical strain in the first layer. The autocatalytic front is sustained by the reaction network, which uses thiouronium salts, disulfides of β-aminothiols, and maleimide as starting components. The gradual actuation by the autocatalytic front enables movements such as gradual unrolling, screwing, and sequential closing of "fingers." This actuation also allows the transmission of chemical signals in a relay fashion and the conversion of a chemical signal to an electrical signal. Locations and times of spontaneous initiation of autocatalytic fronts can be preprogrammed in the spatial distribution of the reactants in the hydrogel. To approach the functionality of living matter, the actuators triggered by an autocatalytic front can be integrated into smart materials regulated by chemical circuits.

Linear response in large deviations theory: a method to compute non-equilibrium distributions

We consider thermodynamically consistent autonomous Markov jump processes displaying a macroscopic limit in which the logarithm of the probability distribution is proportional to a scale-independent rate function (i.e. a large deviations principle is satisfied). In order to provide an explicit expression for the probability distribution valid away from equilibrium, we propose a linear response theory performed at the level of the rate function. We show that the first order non-equilibrium contribution to the steady state rate function, g( x ), satisfies where the vector field u ( x ) defines the macroscopic deterministic dynamics, and the scalar field equals the rate at which work is performed on the system in a given state x . This equation provides a practical way to determine g( x ), significantly outperforms standard linear response theory applied at the level of the probability distribution, and approximates the rate function surprisingly well in some far-from-equilibrium conditions. The method applies to a wealth of physical and chemical systems, that we exemplify by two analytically tractable models—an electrical circuit and an autocatalytic chemical reaction network—both undergoing a non-equilibrium transition from a monostable phase to a bistable phase. Our approach can be easily generalized to transient probabilities and non-autonomous dynamics. Moreover, its recursive application generates a virtual flow in the probability space which allows to determine the steady state rate function arbitrarily far from equilibrium.

Molecular Routes of Dynamic Autocatalysis for Methanol-to-Hydrocarbons Reaction

The industrially important methanol-to-hydrocarbons (MTH) reaction is driven and sustained by autocatalysis in a dynamic and complex manner. Hitherto, the entire molecular routes and chemical nature of the autocatalytic network have not been well understood. Herein, with a multitechnique approach and multiscale analysis, we have obtained a full theoretical picture of the domino cascade of autocatalytic reaction network taking place on HZSM-5 zeolite. The autocatalytic reaction is demonstrated to be plausibly initiated by reacting dimethyl ether (DME) with the surface methoxy species (SMS) to generate the initial olefins, as evidenced by combining the kinetic analysis, in situ DRIFT spectroscopy, 2D 13C-13C MAS NMR, electronic states, and projected density of state (PDOS) analysis. This process is operando tracked and visualized at the picosecond time scale by advanced ab initio molecular dynamics (AIMD) simulations. The initial olefins ignite autocatalysis by building the first autocatalytic cycle-olefins-based cycle-followed by the speciation of methylcyclopentenyl (MCP) and aromatic cyclic active species. In doing so, the active sites accomplish the dynamic evolution from proton acid sites to supramolecular active centers that are experimentally identified with an ever-evolving and fluid feature. The olefins-guided and cyclic-species-guided catalytic cycles are interdependently linked to forge a previously unidentified hypercycle, being composed of one "selfish" autocatalytic cycle (i.e., olefins-based cycle with lighter olefins as autocatalysts for catalyzing the formation of olefins) and three cross-catalysis cycles (with olefinic, MCP, and aromatic species as autocatalysts for catalyzing each other's formation). The unraveled dynamic autocatalytic cycles/network would facilitate the catalyst design and process control for MTH technology.

Kinetic Selection in the Out‐of‐Equilibrium Autocatalytic Reaction Networks that Produce Macrocyclic Peptides

AbstractAutocatalytic reaction networks are instrumental for validating scenarios for the emergence of life on Earth and for synthesizing life de novo. Here, we demonstrate that dimeric thioesters of tripeptides with the general structure (Cys‐Xxx‐Gly‐SEt)2 form strongly interconnected autocatalytic reaction networks that predominantly generate macrocyclic peptides up to 69 amino acids long. Some macrocycles of 6–12 amino acids were isolated from the product pool and were characterized by NMR spectroscopy and single‐crystal X‐ray analysis. We studied the autocatalytic formation of macrocycles in a flow reactor in the presence of acrylamide, whose conjugate addition to thiols served as a model “removal” reaction. These results indicate that even not template‐assisted autocatalytic production combined with competing removal of molecular species in an open compartment could be a feasible route for selecting functional molecules during the pre‐Darwinian stages of molecular evolution.

Kinetic Selection in the Out-of-Equilibrium Autocatalytic Reaction Networks that Produce Macrocyclic Peptides.

Autocatalytic reaction networks are instrumental for validating scenarios for the emergence of life on Earth and for synthesizing life de novo. Here, we demonstrate that dimeric thioesters of tripeptides with the general structure (Cys-Xxx-Gly-SEt)2 form strongly interconnected autocatalytic reaction networks that predominantly generate macrocyclic peptides up to 69 amino acids long. Some macrocycles of 6-12 amino acids were isolated from the product pool and were characterized by NMR spectroscopy and single-crystal X-ray analysis. We studied the autocatalytic formation of macrocycles in a flow reactor in the presence of acrylamide, whose conjugate addition to thiols served as a model "removal" reaction. These results indicate that even not template-assisted autocatalytic production combined with competing removal of molecular species in an open compartment could be a feasible route for selecting functional molecules during the pre-Darwinian stages of molecular evolution.

Autocatalytic and oscillatory reaction networks that form guanidines and products of their cyclization

Autocatalytic and oscillatory networks of organic reactions are important for designing life-inspired materials and for better understanding the emergence of life on Earth; however, the diversity of the chemistries of these reactions is limited. In this work, we present the thiol-assisted formation of guanidines, which has a mechanism analogous to that of native chemical ligation. Using this reaction, we designed autocatalytic and oscillatory reaction networks that form substituted guanidines from thiouronium salts. The thiouronium salt-based oscillator show good stability of oscillations within a broad range of experimental conditions. By using nitrile-containing starting materials, we constructed an oscillator where the concentration of a bicyclic derivative of dihydropyrimidine oscillates. Moreover, the mixed thioester and thiouronium salt-based oscillator show unique responsiveness to chemical cues. The reactions developed in this work expand our toolbox for designing out-of-equilibrium chemical systems and link autocatalytic and oscillatory chemistry to the synthesis of guanidinium derivatives and the products of their transformations including analogs of nucleobases.

Self-Reproduction and Darwinian Evolution in Autocatalytic Chemical Reaction Systems.

Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as “a self-sustaining chemical system capable of Darwinian evolution”. It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.

Darwinian properties and their trade-offs in autocatalytic RNA reaction networks

Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, differential reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that growth increases with global connectivity. These rules imply trade-offs between reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution.

An autocatalytic organic reaction network based on cross-catalysis.

Here we report a simple autocatalytic organic reaction network based on the redox chemistry of quinones and reactive oxygen species. Autocatalysis arises from the cross-activation between the H2O2-catalyzed deprotection of a pro-benzoquinone arylboronic ester probe and the benzoquinone-catalyzed H2O2 production through redox cyling with ascorbate in an aerated buffered solution.

Autocatalysis: Kinetics, Mechanisms and Design

AbstractThe importance of autocatalysis spans from practical applications such as in chemically amplified photoresists, to autocatalysis playing a fundamental role in evolution as well as a plausible key role in the origin of life. The phenomenon of autocatalysis is characterized by its kinetic signature rather than by its mechanistic aspects. The molecules that form autocatalytic systems and the mechanisms underlying autocatalytic reactions are very diverse. This chemical diversity, combined with the strong involvement of chemical kinetics, creates a formidable barrier for entrance to the field. Understanding these challenges, we wrote this Review with three main goals in mind: (i) To provide a basic introduction to the kinetics of autocatalytic systems and its relation to the role of autocatalysis in evolution, (ii) To provide a comprehensive overview, including tables, of synthetic chemical autocatalytic systems, and (iii) To provide an in‐depth analysis of the concept of autocatalytic reaction networks, their design, and perspectives for their development.