Environmental conditions drive self-organization of reaction pathways in a prebiotic reaction network

A selective non-enzymatic synthesis of ribose simply from formaldehyde, metal salts and clays

This study demonstrates that metal-doped-clay (MDC) can be a selective platform for ribose produced from formaldehyde under abiotic conditions. Ribose exhibits superior retention compared with other carbohydrates on naturally occurring minerals on the early Earth in the presence of divalent cations. This finding offers an insight into the necessity of the emergence of ribose as the backbone of extant RNA.

From Bayes to Darwin: Evolutionary search as an exaptation from sampling-based Bayesian inference

Building on the algorithmic equivalence between finite population replicator dynamics and particle filtering based approximation of Bayesian inference, we design a computational model to demonstrate the emergence of Darwinian evolution over representational units when collectives of units are selected to infer statistics of high-dimensional combinatorial environments. The non-Darwinian starting point is two units undergoing a few cycles of noisy, selection-dependent information transmission, corresponding to a serial (one comparison per cycle), non-cumulative process without heredity. Selection for accurate Bayesian inference at the collective level induces an adaptive path to the emergence of Darwinian evolution within the collectives, capable of maintaining and iteratively improving upon complex combinatorial information. When collectives are themselves Darwinian, this mechanism amounts to a top-down (filial) transition in individuality. We suggest that such a selection mechanism can explain the hypothesized emergence of fast timescale Darwinian dynamics over a population of neural representations within animal and human brains, endowing them with combinatorial planning capabilities. Further possible physical implementations include prebiotic collectives of non-replicating molecules and reinforcement learning agents with parallel policy search.

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.

Multi-Stimuli-Responsive Network of Multicatalytic Reactions using a Single Palladium/Platinum Catalyst

Given her unrivalled proficiency in the synthesis of all molecules of life, nature has been an endless source of inspiration for developing new strategies in organic chemistry and catalysis. However, one feature that remains thus far beyond chemists' grasp is her unique ability to adapt the productivity of metabolic processes in response to triggers that indicate the temporary need for specific metabolites. To demonstrate the remarkable potential of such stimuli-responsive systems, we present a metabolism-inspired network of multicatalytic processes capable of selectively synthesising a range of products from simple starting materials. Specifically, the network is built of four classes of distinct catalytic reactions-cross-couplings, substitutions, additions, and reductions, involving three organic starting materials-terminal alkyne, aryl iodide, and hydrosilane. All starting materials are either introduced sequentially or added to the system at the same time, with no continuous influx of reagents or efflux of products. All processes in the system are catalysed by a multifunctional heteronuclear PdII/PtII complex, whose performance can be controlled by specific additives and external stimuli. The reaction network exhibits a substantial degree of orthogonality between different pathways, enabling the controllable synthesis of ten distinct products with high efficiency and selectivity through simultaneous triggering and suppression mechanisms.

Self-organization in computation and chemistry: Return to AlChemy

How do complex adaptive systems, such as life, emerge from simple constituent parts? In the 1990s, Walter Fontana and Leo Buss proposed a novel modeling approach to this question, based on a formal model of computation known as the λ calculus. The model demonstrated how simple rules, embedded in a combinatorially large space of possibilities, could yield complex, dynamically stable organizations, reminiscent of biochemical reaction networks. Here, we revisit this classic model, called AlChemy, which has been understudied over the past 30 years. We reproduce the original results and study the robustness of those results using the greater computing resources available today. Our analysis reveals several unanticipated features of the system, demonstrating a surprising mix of dynamical robustness and fragility. Specifically, we find that complex, stable organizations emerge more frequently than previously expected, that these organizations are robust against collapse into trivial fixed points, but that these stable organizations cannot be easily combined into higher order entities. We also study the role played by the random generators used in the model, characterizing the initial distribution of objects produced by two random expression generators, and their consequences on the results. Finally, we provide a constructive proof that shows how an extension of the model, based on the typed λ calculus, could simulate transitions between arbitrary states in any possible chemical reaction network, thus indicating a concrete connection between AlChemy and chemical reaction networks. We conclude with a discussion of possible applications of AlChemy to self-organization in modern programming languages and quantitative approaches to the origin of life.

Alternative Pathways in Astrobiology: Reviewing and Synthesizing Contingency and Non-Biomolecular Origins of Terrestrial and Extraterrestrial Life

The pursuit of understanding the origins of life (OoL) on and off Earth and the search for extraterrestrial life (ET) are central aspects of astrobiology. Despite the considerable efforts in both areas, more novel and multifaceted approaches are needed to address these profound questions with greater detail and with certainty. The complexity of the chemical milieu within ancient geological environments presents a diverse landscape where biomolecules and non-biomolecules interact. This interaction could lead to life as we know it, dominated by biomolecules, or to alternative forms of life where non-biomolecules could play a pivotal role. Such alternative forms of life could be found beyond Earth, i.e., on exoplanets and the moons of Jupiter and Saturn. Challenging the notion that all life, including ET life, must use the same building blocks as life on Earth, the concept of contingency-when expanded beyond its macroevolution interpretation-suggests that non-biomolecules may have played essential roles at the OoL. Here, we review the possible role of contingency and non-biomolecules at the OoL and synthesize a conceptual model formally linking contingency with non-biomolecular OoL theories. This model emphasizes the significance of considering the role of non-biomolecules both at the OoL on Earth or beyond, as well as their potential as agnostic biosignatures indicative of ET Life.

Living cells and biological mechanisms as prototypes for developing chemical artificial intelligence

Artificial Intelligence (AI) is having a revolutionary impact on our societies. It is helping humans in facing the global challenges of this century. Traditionally, AI is developed in software or through neuromorphic engineering in hardware. More recently, a brand-new strategy has been proposed. It is the so-called Chemical AI (CAI), which exploits molecular, supramolecular, and systems chemistry in wetware to mimic human intelligence. In this work, two promising approaches for boosting CAI are described. One regards designing and implementing neural surrogates that can communicate through optical or chemical signals and give rise to networks for computational purposes and to develop micro/nanorobotics. The other approach concerns "bottom-up synthetic cells" that can be exploited for applications in various scenarios, including future nano-medicine. Both topics are presented at a basic level, mainly to inform the broader audience of non-specialists, and so favour the rise of interest in these frontier subjects.

Exploring the Core Formose Cycle: Catalysis and Competition

The core autocatalytic cycle of the formose reaction may be enhanced or eroded by the presence of simple molecules at life's origin. Utilizing quantum chemistry, we calculate the thermodynamics and kinetics of reactions both within the core cycle and those that deplete the reactants and intermediates, such as the Cannizzaro reaction. We find that via disproportionation of aldehydes into carboxylic acids and alcohols, the Cannizzaro reaction furnishes simple catalysts for a variety of reactions. We also find that ammonia can catalyze both in-cycle and Cannizzaro reactions while hydrogen sulfide does not; both, however, play a role in sequestering reactants and intermediates in the web of potential reactions.

Chemical reservoir computation in a self-organizing reaction network

Chemical reaction networks, such as those found in metabolism and signalling pathways, enable cells to process information from their environment1,2. Current approaches to molecular information processing and computation typically pursue digital computation models and require extensive molecular-level engineering3. Despite considerable advances, these approaches have not reached the level of information processing capabilities seen in living systems. Here we report on the discovery and implementation of a chemical reservoir computer based on the formose reaction4. We demonstrate how this complex, self-organizing chemical reaction network can perform several nonlinear classification tasks in parallel, predict the dynamics of other complex systems and achieve time-series forecasting. This in chemico information processing system provides proof of principle for the emergent computational capabilities of complex chemical reaction networks, paving the way for a new class of biomimetic information processing systems.

Emergence of a short peptide based reductase via activation of the model hydride rich cofactor

In extant biology, large and complex enzymes employ low molecular weight cofactors such as dihydronicotinamides as efficient hydride transfer agents and electron carriers for the regulation of critical metabolic processes. In absence of complex contemporary enzymes, these molecular cofactors are generally inefficient to facilitate any reactions on their own. Herein, we report short peptide-based amyloid nanotubes featuring exposed arrays of cationic and hydrophobic residues that can bind small molecular weak hydride transfer agents (NaBH4) to facilitate efficient reduction of ester substrates in water. In addition, the paracrystalline amyloid phases loaded with borohydrides demonstrate recyclability, substrate selectivity and controlled reduction and surpass the capabilities of standard reducing agent such as LiAlH4. The amyloid microphases and their collaboration with small molecular cofactors foreshadow the important roles that short peptide-based assemblies might have played in the emergence of protometabolism and biopolymer evolution in prebiotic earth.

Triple Adaptation of Constitutional Dynamic Networks of Imines in Response to Micellar Agents: Internal Uptake-Interfacial Localization-Shape Transition

Understanding the behavior of complex chemical reaction networks and how environmental conditions can modulate their organization as well as the associated outcomes may take advantage of the design of related artificial systems. Microenvironments with defined boundaries are of particular interest for their unique properties and prebiotic significance. Dynamic covalent libraries (DCvLs) and their underlying constitutional dynamic networks (CDNs) have been shown to be appropriate for studying adaptation to several processes, including compartmentalization. However, microcompartments (e.g., micelles) provide specific environments for the selective protection from interfering reactions such as hydrolysis and an enhanced chemical promiscuity due to the interface, governing different processes of network modulation. Different interactions between the micelles and the library constituents lead to dynamic sensing, resulting in different expressions of the network through pattern generation. The constituents integrated into the micelles are protected from hydrolysis and hence preferentially expressed in the network composition at the cost of constitutionally linked members. In the present work, micellar integration was observed for two processes: internal uptake based on hydrophobic forces and interfacial localization relying on attractive electrostatic interactions. The latter drives a complex triple adaptation of the network with feedback on the shape of the self-assembled entity. Our results demonstrate how microcompartments can enforce the expression of constituents of CDNs by reducing the hydrolysis of uptaken members, unravelling processes that govern the response of reactions networks. Such studies open the way toward using DCvLs and CDNs to understand the emergence of complexity within reaction networks by their interactions with microenvironments.

Distilling dynamical knowledge from stochastic reaction networks

Stochastic reaction networks are widely used in the modeling of stochastic systems across diverse domains such as biology, chemistry, physics, and ecology. However, the comprehension of the dynamic behaviors inherent in stochastic reaction networks is a formidable undertaking, primarily due to the exponential growth in the number of possible states or trajectories as the state space dimension increases. In this study, we introduce a knowledge distillation method based on reinforcement learning principles, aimed at compressing the dynamical knowledge encoded in stochastic reaction networks into a singular neural network construct. The trained neural network possesses the capability to accurately predict the state conditional joint probability distribution that corresponds to the given query contexts, when prompted with rate parameters, initial conditions, and time values. This obviates the need to track the dynamical process, enabling the direct estimation of normalized state and trajectory probabilities, without necessitating the integration over the complete state space. By applying our method to representative examples, we have observed a high degree of accuracy in both multimodal and high-dimensional systems. Additionally, the trained neural network can serve as a foundational model for developing efficient algorithms for parameter inference and trajectory ensemble generation. These results collectively underscore the efficacy of our approach as a universal means of distilling knowledge from stochastic reaction networks. Importantly, our methodology also spotlights the potential utility in harnessing a singular, pretrained, large-scale model to encapsulate the solution space underpinning a wide spectrum of stochastic dynamical systems.

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Disaccharides are composed of two monosaccharide subunits joined by a glycosidic linkage in an α or β configuration. Different combinations of isomeric monosaccharide subunits and different glycosidic linkages result in different isomeric disaccharide products. Thus, direct discrimination of these disaccharide isomers from a mixture is extremely difficult. In this paper, a hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore conjugated with a phenylboronic acid (PBA) adapter was applied for disaccharide sensing, with which three most widely known disaccharides in nature, including sucrose, lactose and maltose, were clearly discriminated. Besides, all six isomeric α-D-glucopyranosyl-D-fructoses, differing only in their glycosidic linkages, were also well resolved. Assisted by a custom machine learning algorithm, a 0.99 discrimination accuracy is achieved. Nanopore discrimination of disaccharide isomers with different glycosidic linkages, which has never been previously demonstrated, is inspiring for nanopore saccharide sequencing. This sensing capacity was also applied in direct identification of isomaltulose additives in a commercial sucrose-free yogurt, from which isomaltulose, lactose and L-lactic acid were simultaneously detected.

Direct Analysis of Complex Reaction Mixtures: Formose Reaction

Complex reaction mixtures, like those postulated on early Earth, present an analytical challenge because of the number of components, their similarity, and vastly different concentrations. Interpreting the reaction networks is typically based on simplified or partial data, limiting our insight. We present a new approach based on online monitoring of reaction mixtures formed by the formose reaction by ion-mobility-separation mass-spectrometry. Monitoring the reaction mixtures led to large data sets that we analyzed by non-negative matrix factorization, thereby identifying ion-signal groups capturing the time evolution of the network. The groups comprised ≈300 major ion signals corresponding to sugar-calcium complexes formed during the formose reaction. Multivariate analysis of the kinetic profiles of these complexes provided an overview of the interconnected kinetic processes in the solution, highlighting different pathways for sugar growth and the effects of different initiators on the initial kinetics. Reconstructing the network's topology further, we revealed so far unnoticed fast retro-aldol reaction of ketoses, which significantly affects the initial reaction dynamics. We also detected the onset of sugar-backbone branching for C6  sugars and cyclization reactions starting for C5  sugars. This top-down analytical approach opens a new way to analyze complex dynamic mixtures online with unprecedented coverage and time resolution.

Chemical Information Processing by a Responsive Chemical System

Nature has an extraordinary capacity to precisely regulate the chemical reactivity in a highly complex mixture of molecules that is present in the cell. External stimuli lead to transient up- and downregulation of chemical reactions and provide a means for a cell to process information arriving from the environment. The development of synthetic chemical systems with life-like properties requires strategies that allow likewise control over chemical reactivity in a complex environment. Here, we show a synthetic system that mimics the initial steps that take place when a natural signal transduction pathway is activated. Monophosphate nucleosides act as chemical triggers for the self-assembly of nanoreactors that upregulate chemical reactions between reagents present at low micromolar concentrations. Different nucleotides template different assemblies and hence activate different pathways, thus establishing a distinct connection between input and output molecules. Trigger-induced upregulation of chemical reactivity occurs for only a limited amount of time because the chemical triggers are gradually removed from the system by enzymes. It is shown that the same system transiently produces different output molecules depending on the chemical input that is provided.

Microbial Biomanufacturing Using Chemically Synthesized Non-Natural Sugars as the Substrate

The bioproduction of valuable materials using biomass sugars is attracting attention as an environmentally friendly technology. However, its ability to fulfil the enormous demand to produce fuels and chemical products is limited. With a view towards the future development of a novel bioproduction process that addresses these concerns, this study investigated the feasibility of bioproduction of valuable substances using Corynebacterium glutamicum (C. glutamicum) with a chemically synthesized non-natural sugar solution. Cells were grown using the synthesized sugar solution as the sole carbon source and they produced lactate under oxygen-limited conditions. It was also found that some of the sugars produced by the series of chemical reactions inhibited cell growth since prior removal of these sugars increased the cell growth rate. The results obtained in this study indicate that chemically synthesized sugars have the potential to resolve the concerns regarding future biomass sugar supply in microbial biomanufacturing.

Small-molecule autocatalysis drives compartment growth, competition and reproduction

Sustained autocatalysis coupled to compartment growth and division is a key step in the origin of life, but an experimental demonstration of this phenomenon in an artificial system has previously proven elusive. We show that autocatalytic reactions within compartments-when autocatalysis, and reactant and solvent exchange outpace product exchange-drive osmosis and diffusion, resulting in compartment growth. We demonstrate, using the formose reaction compartmentalized in aqueous droplets in an emulsion, that compartment volume can more than double. Competition for a common reactant (formaldehyde) causes variation in droplet growth rate based on the composition of the surrounding droplets. These growth rate variations are partially transmitted after selective division of the largest droplets by shearing, which converts growth-rate differences into differences in droplet frequency. This shows how a combination of properties of living systems (growth, division, variation, competition, rudimentary heredity and selection) can arise from simple physical-chemical processes and may have paved the way for the emergence of evolution by natural selection.

Construction of an autocatalytic reaction cycle in neutral medium for synthesis of life-sustaining sugars

Autocatalytic mechanisms in carbon metabolism, such as the Calvin cycle, are responsible for the biological assimilation of CO2 to form organic compounds with complex structures, including sugars. Compounds that form C-C bonds with CO2 are regenerated in these autocatalytic reaction cycles, and the products are concurrently released. The formose reaction in basic aqueous solution has attracted attention as a nonbiological reaction involving an autocatalytic reaction cycle that non-enzymatically synthesizes sugars from the C1 compound formaldehyde. However, formaldehyde and sugars, which are the substrate and products of the formose reaction, respectively, are consumed in Cannizzaro reactions, particularly under basic aqueous conditions, which makes the formose reaction a fragile sugar-production system. Here, we constructed an autocatalytic reaction cycle for sugar synthesis under neutral conditions. We focused on the weak Brønsted basicity of oxometalate anions such as tungstates and molybdates as catalysts, thereby enabling the aldol reaction, retro-aldol reaction, and aldose-ketose transformation, which collectively constitute the autocatalytic reaction cycle. These bases acted on sugar molecules of substrates together with sodium ions of a Lewis acid to promote deprotonation under neutral conditions, which is the initiation step of the reactions forming an autocatalytic cycle, whereas the Cannizzaro reaction was inhibited. The autocatalytic reaction cycle established using this abiotic approach is a robust sugar production system. Furthermore, we found that the synthesized sugars work as energy storage substances that sustain microbial growth despite their absence in nature.

The protometabolic nature of prebiotic chemistry

The field of prebiotic chemistry has been dedicated over decades to finding abiotic routes towards the molecular components of life. There is nowadays a handful of prebiotically plausible scenarios that enable the laboratory synthesis of most amino acids, fatty acids, simple sugars, nucleotides and core metabolites of extant living organisms. The major bottleneck then seems to be the self-organization of those building blocks into systems that can self-sustain. The purpose of this tutorial review is having a close look, guided by experimental research, into the main synthetic pathways of prebiotic chemistry, suggesting how they could be wired through common intermediates and catalytic cycles, as well as how recursively changing conditions could help them engage in self-organized and dissipative networks/assemblies (i.e., systems that consume chemical or physical energy from their environment to maintain their internal organization in a dynamic steady state out of equilibrium). In the article we also pay attention to the implications of this view for the emergence of homochirality. The revealed connectivity between those prebiotic routes should constitute the basis for a robust research program towards the bottom-up implementation of protometabolic systems, taken as a central part of the origins-of-life problem. In addition, this approach should foster further exploration of control mechanisms to tame the combinatorial explosion that typically occurs in mixtures of various reactive precursors, thus regulating the functional integration of their respective chemistries into self-sustaining protocellular assemblies.

(Photoredox) Organocatalysis in the Emergence of Life: Discovery, Applications, and Molecular Evolution

ConspectusLife as we know it is built on complex and perfectly interlocking processes that have evolved over millions of years through evolutionary optimization processes. The emergence of life from nonliving matter and the evolution of such highly efficient systems therefore constitute an enormous synthetic and systems chemistry challenge. Advances in supramolecular and systems chemistry are opening new perspectives that provide insights into living and self-sustaining reaction networks as precursors for life. However, the ab initio synthesis of such a system requires the possibility of autonomous optimization of catalytic properties and, consequently, of an evolutionary system at the molecular level. In this Account, we present our discovery of the formation of substituted imidazolidine-4-thiones (photoredox) organocatalysts from simple prebiotic building blocks such as aldehydes and ketones under Strecker reaction conditions with ammonia and cyanides in the presence of hydrogen sulfide. The necessary aldehydes are formed from CO2 and hydrogen under prebiotically plausible meteoritic or volcanic iron-particle catalysis in the atmosphere of the early Earth. Remarkably, the investigated imidazolidine-4-thiones undergo spontaneous resolution by conglomerate crystallization, opening a pathway for symmetry breaking, chiral amplification, and enantioselective organocatalysis. These imidazolidine-4-thiones enable α-alkylations of aldehydes and ketones by photoredox organocatalysis. Therefore, these photoredox organocatalysts are able to modify their aldehyde building blocks, which leads in an evolutionary process to mutated second-generation and third-generation catalysts. In our experimental studies, we found that this mutation can occur not only by new formation of the imidazolidine core structure of the catalyst from modified aldehyde building blocks or by continuous supply from a pool of available building blocks but also by a dynamic exchange of the carbonyl moiety in ring position 2 of the imidazolidine moiety. Remarkably, it can be shown that by incorporating aldehyde building blocks from their environment, the imidazolidine-4-thiones are able to change and adapt to altering environmental conditions without undergoing the entire formation process. The selection of the mutated catalysts is then based on the different catalytic activities in the modification of the aldehyde building blocks and on the catalysis of subsequent processes that can lead to the formation of molecular reaction networks as progenitors for cellular processes. We were able to show that these imidazolidine-4-thiones not only enable α-alkylations but also facilitate other important transformations, such as the selective phosphorylation of nucleosides to nucleotides as a key step leading to the oligomerization to RNA and DNA. It can therefore be expected that evolutionary processes have already taken place on a small molecular level and have thus developed chemical tools that change over time, representing a hidden layer on the path to enzymatically catalyzed biochemical processes.

Towards a prebiotic chemoton - nucleotide precursor synthesis driven by the autocatalytic formose reaction

The formose reaction is often cited as a prebiotic source of sugars and remains one of the most plausible forms of autocatalysis on the early Earth. Herein, we investigated how cyanamide and 2-aminooxazole, molecules proposed to be present on early Earth and precursors for nonenzymatic ribonucleotide synthesis, mediate the formose reaction using HPLC, LC-MS and 1H NMR spectroscopy. Cyanamide was shown to delay the exponential phase of the formose reaction by reacting with formose sugars to form 2-aminooxazole and 2-aminooxazolines thereby diverting some of these sugars from the autocatalytic cycle, which nonetheless remains intact. Masses for tetrose and pentose aminooxazolines, precursors for nucleotide synthesis including TNA and RNA, were also observed. The results of this work in the context of the chemoton model are further discussed. Additionally, we highlight other prebiotically plausible molecules that could have mediated the formose reaction and alternative prebiotic autocatalytic systems.

Dynamic Environmental Conditions Affect the Composition of a Model Prebiotic Reaction Network

Prebiotic environments are dynamic, containing a range of periodic and aperiodic variations in reaction conditions. However, the impact of the temporal dynamics of environmental conditions upon prebiotic chemical reaction networks has not been investigated. Here, we demonstrate how the magnitude and rate of temporal fluctuations of the catalysts Ca²⁺ and hydroxide control the product distributions of the formose reaction. Surprisingly, the product compositions of the formose reaction under dynamic conditions deviate significantly from those under steady state conditions. We attribute these compositional changes to the non-uniform propagation of fluctuations through the network, thereby shaping reaction outcomes. An examination of temporal concentration patterns showed that collections of compounds responded collectively to perturbations, indicating that key gating reactions branching from the Breslow cycle may be important responsive features of the formose reaction. Our findings show how the compositions of prebiotic reaction networks were shaped by sequential environmental events, illustrating the necessity for considering the temporal traits of prebiotic environments that supported the origin of life.

Chemically Driven Multimodal Locomotion of Active, Flexible Sheets

The inhibitor-promoter feedback loop is a vital component in regulatory pathways that controls functionality in living systems. In this loop, the production of chemical A at one site promotes the production of chemical B at another site, but B inhibits the production of A. In solution, differences in the volumes of the reactants and products of this reaction can generate buoyancy-driven fluid flows, which will deform neighboring soft material. To probe the intrinsic interrelationship among chemistry, hydrodynamics, and fluid-structure interactions, we model a bio-inspired system where a flexible sheet immersed in solution encompasses two spatially separated catalytic patches, which drive the A-B inhibitor-promotor reaction. The convective rolls of fluid generated above the patches can circulate inward or outward depending on the chemical environment. Within the regime displaying chemical oscillations, the dynamic fluid-structure interactions morph the shape of the sheet to periodically "fly", "crawl", or "swim" along the bottom of the confining chamber, revealing an intimate coupling between form and function in this system. The oscillations in the sheet's motion in turn affect the chemical oscillations in the solution. In the regime with non-oscillatory chemistry, the induced flow still morphs the shape of the sheet, but now, the fluid simply translates the sheet along the length of the chamber. The findings reveal the potential for enzymatic reactions in the body to generate hydrodynamic behavior that modifies the shape of neighboring soft tissue, which in turn modifies both the fluid dynamics and the enzymatic reaction. The findings indicate that this non-linear dynamic behavior can be playing a critical role in the functioning of regulatory pathways in living systems.

Nucleobases in Meteorites to Nucleobases in RNA and DNA?

Nucleic acids likely played a foundational role in the origin of life. However, the prebiotic chemistry of nucleoside and nucleotide synthesis has proved challenging on a number of fronts. The recent discovery of both pyrimidine and purine nucleobases in carbonaceous chondrite meteorites has garnered much attention from both the popular press and the scientific community. Here, we discuss these findings in the context of nucleoside/nucleotide prebiotic chemistry. We consider that the main challenge of prebiotic nucleoside synthesis, that of nucleosidic bond formation, is not addressed by the identification nucleobases in meteorites. We further discuss issues of selection that arise from the observation that such meteorites contain both canonical and non-canonical nucleobases. In sum, we argue that, despite the major analytical achievement of identifying and characterizing nucleobases in meteorites, this observation does little to advance our understanding of the prebiotic chemistry that could have led to the first genetic molecules that gave rise to us.