This work examines azolium catalysis of the small molecules formaldehyde and glyoxylic acid to yield product sugars as the starting point for synthesis of new azolium catalysts. It is broken into two projects: the first focusing on developing a proof of concept process to couple the two reactions, and the second expanding the reaction space using different solvents and catalyst. From these projects, a model for chemical evolution of small molecule catalysts was proposed. Reaction stoichiometry suggests that the process displays autocatalysis; however, the reactions were conducted separately so that kinetic enhancement was not observed. Even without kinetic enhancement, the findings indicate that synthesis of new catalyst from formaldehyde as the sole carbon source is possible, and that the process is robust due to effects such as catalyst deactivation or other loss pathways over time. Alternative work using glyoxylic acid demonstrated that the kinetics for carbohydrate synthesis are much slower.

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Dynamic Kinetic Selection (DKS) suggests that kinetic, rather than thermodynamic, stability will dictate the composition of a replicating population of biomolecules. Here, the results obtained from a series of five related reactions involving gradually increasing percentages of randomly-mutated substrate fragments to generate variants of full-length Azoarcus group I intron through an autocatalytic self-assembly reaction involving a series of recombination events, showed DKS as a driving factor in dictating the population composition of full-length product assembled from substrates that had fewer positions available to randomization. In trying to elucidate a plausible scheme for the origins of complex biomolecules on the prebiotic Earth, the suggestion that networks comprised of interacting molecules were more likely to evolve into biomolecules capable of obtaining and sustaining characteristics attributed to living molecules has gained traction within the past few years. Of specific interest is the catalytic efficacy of ribozymes whose genotypes require that they interact with molecules of the same genotype (selfish systems) to be effective catalysts versus those that are more effective when accomplishing catalysis by cooperating with ribozymes of a different genotype (cooperative systems). Here, the Azoarcus I ribozyme was used to compare these two types of system. Both systems were shown to robustly produce full-length product. Two different methods of introducing random mutations into substrate fragments for the reactions described in this thesis were employed. The differences in the preparation methods for the substrates was not expected to have an impact on the nature of the full-length product. However, there was no correlation between the positions that tended to be more tolerant of accepting random mutations between the products arising from the two preparation methods. One preparation method yielded full-length ribozymes more consistent with the secondary structure of the wild-type ribozyme and followed substitution patterns found in in vivo nucleic acid substitutions, whereas the other method provided full-length ribozymes that tolerated mutations that would be expected to greatly affect the secondary structure of the ribozyme and those positions tended to mutate evenly to any of the three possible alternative nucleobases. Point mutations introduced into ribozyme substrate fragments may have a deleterious, neutral, or beneficial effect, depending on their impact on the catalytic capability of the molecule vis-á-vis the effect, if any, the change has to the secondary and tertiary structure of the ribozyme. In this dissertation, the results of two series of point mutation reactions are addressed. The first set showed a point mutation to have a deleterious effect, whereas concerted mutations did not significantly affect activity of the ribozyme. The second series of reactions involved point mutations at a position that had previously been determined to be highly tolerant of random mutations. Results suggested that substitutions at this position had a minimal impact on ribozyme activity.

Les réseaux de molécules interdépendantes sont depuis quelque temps considérés comme de potentiels candidats pour avoir amorcé la transition de la biologie à la chimie. Bien qu'ils aient été intensivement examinés en théorie, il n'existe toujours aucune preuve expérimentale pour confirmer ou infirmer leur supposé rôle crucial dans les origines de la vie. En particulier, il nous manque encore une démonstration empirique des trois ingrédients habituellement présentés comme requis pour l'évolution darwinienne: l'hérédité, la variation et la sélection. Un système qui posséderait les trois tout en étant couplé à un processus de réplication en compartiments serait théoriquement capable d’évoluer au sens darwinien du terme. Par exemple, cela a été montré théoriquement pour les Ensembles Collectivement Autocatalytiques (CAS pour Collectively Aucatalytic Sets en anglais) où chaque molécule de l'ensemble est formée catalytiquement par un autre membre de l'ensemble. Ici, nous utilisons le système de ribozyme Azoarcus, qui catalysent des réactions de recombinaisons, pour former expérimentalement des CASs structurellement divers afin d’explorer leurs propriétés évolutives. Dans ce système, les ribozymes peuvent catalyser la formation d'autres ribozymes à partir de fragments plus petits, présents dans l'environnement. Nous utilisons un dispositif de microfluidique en gouttes associé au séquençage haut-débit pour mener une étude à grande échelle sur des milliers de CASs Azoarcus. Nous développons une approche perturbative pour identifier les paramètres topologiques importants contrôlant les variations observées dans les CAS à la suite de perturbations de l’environnement, ici l'ajout d'une nouvelle espèce. Nous déterminons ensuite l’ensemble restreint de caractéristiques du réseau régissant la mémoire des conditions initiales dans les CASs Azoarcus, un prérequis pour l'hérédité, en utilisant un modèle théorique validé par des données expérimentales. Enfin, nous démontrons qu’il existe dans les CASs Azoarcus des processus cataboliques qui les rendent robustes aux perturbations des fragments qui composent leur substrat et donc plus pertinent d’un point de vue prébiotique. Ces résultats démontrent le rôle crucial des CASs à base d’ARN dans les origines de la vie et illustrent comment la structure de leur réseau peut être adaptée pour obtenir des CASs avec des propriétés intéressantes d’un point de vue évolutif, ouvrant la voie à une démonstration expérimentale de l'évolution darwinienne avec système purement moléculaire. / Networks of interdependent molecules are considered plausible candidates for initiating the transition from biology to chemistry. Though they have been intensively scrutinized theoretically, there is still no experimental evidence for confirming or denying their supposed crucial role in the origins of life. In particular, we are still lacking experimental proofs of any of the three ingredients usually presented as required for Darwinian evolution: heredity, variation and selection. A system that would possess the three while being coupled to some sort of encapsulated replication process would theoretically be able to undergo Darwinian evolution. As a matter of fact, this has been shown theoretically for Collectively Autocatalytic Sets (CAS) where each molecule of the set is catalytically formed by another member of the ensemble. Here we use the Azoarcus recombination ribozyme system to experimentally form structurally diverse CASs to explore their evolutionary properties. In this system, the ribozymes can catalyze the assembly of other ribozymes from smaller fragments, present in the food set. We first use a droplet microfluidics set-up coupled with next-generation sequencing to conduct a large scale study on thousands of Azoarcus CASs. We develop a perturbative approach to identify the important topological parameters that control variations in CASs as a result of environmental perturbations, here the addition of a new species. We then determine the small set of network features governing memory of the initial conditions in Azoarcus CAS, a pre-requisite for heredity, by using a computational model validated by experimental data. Finally, we demonstrate that Azoarcus CAS possess catabolic processes which make them robust to perturbations in the food set and thus more prebiotic relevant. These results provide evidence for the crucial role of RNA CASs in the origins of life and illustrate how the network structure can be tailored to obtain CASs with properties interesting from an evolutionary point of view, paving the way to an experimental demonstration of Darwinian evolution with a purely molecular system.

Thesis advisor: Jeffery A. Byers / Thesis advisor: Chia-Kuang (Frank) Tsung / Biological systems have evolved over time to favor structures beneficial for the efficient transformation of simple feedstocks to sophisticated products. In particular, enzymes have evolved such that cooperative and geometrically controlled interactions between active sites and substrates enhance catalytic activity and selectivity. Separation of these active sites from other incompatible catalytic components allows for chemical transformation in a stepwise fashion, circumventing the inherent limitations to performing reactions in a single step. This dissertation describes the use of porous crystalline materials called metal-organic frameworks (MOFs) as hosts to mimic the component separation and precise active site control observed in nature. The first phase of these efforts explores the use of dissociative “aperture-opening” linker exchange pathways in a MOF to encapsulate transition metal complexes for carbon dioxide hydrogenation to formate. This strategy is then used to separate two incompatible complexes and perform the cascade conversion of carbon dioxide to methanol, resulting in unique and previously unobserved network autocatalytic behavior. Finally, the modularity of the MOF host is leveraged to install beneficial functionality in close proximity to the encapsulated transition metal complex, leading to activity exceeding that of any reported homogeneous system for carbon dioxide reduction. The insights gained through these studies can inform the development of composites for other reactions, allowing for access to new and unique reaction manifolds. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Chemistry.

For life to arise from non-life, a metabolism must emerge and maintain itself, distinct from its environment. One line of research seeking to understand this emergence has focused on models of autocatalytic reaction networks (ARNs) and the conditions that allow them to approximate metabolic behavior. These models have identified reaction parameters from which a proto-metabolism might emerge given an adequate matter-energy flow through the system. This dissertation extends that research by answering the question: can dynamically structured interactions with the environment promote the emergence of ARNs? This question was inspired by theories that place the origin of life in contexts such as diurnal or tidal cycles. To answer it, an artificial chemistry system with ARN potential was implemented in the dissipative particle dynamics (DPD) modeling paradigm. Unlike differential equation (DE) models favored in prior ARN research, the DPD model is able to simulate environmental dynamics interacting with discrete particles, spatial heterogeneity, and rare events. This dissertation first presents a comparison of the DPD model to published DE results, showing qualitative similarity with some interesting differences. Multiple examples are then provided of dynamically changing flows from the environment that promote emergent ARNs more than constant flows. These include specific cycles of energy and mass flux that consistently increase metrics for ARN concentration and mass focusing. The results also demonstrate interesting nonlinear interactions between the system and cycle amplitude and period. These findings demonstrate the relevance that environmental dynamics has to ARN research and the potential for broader application as well.

In biochemical networks, complex dynamical features such as superlinear growth and oscillations are classically considered a consequence of autocatalysis. For the large class of parameter-rich kinetic models, which includes Generalized Mass Ac- tion kinetics and Michaelis-Menten kinetics, we show that certain submatrices of the stoichiometric matrix, so-called unstable cores, are sufficient for a reaction network to admit instability and potentially give rise to such complex dynami- cal behavior. The determinant of the submatrix distinguishes unstable-positive feedbacks, with a single real-positive eigenvalue, and unstable-negative feedbacks without real-positive eigenvalues. Autocatalytic cores turn out to be exactly the unstable-positive feedbacks that are Metzler matrices. Thus there are sources of dynamical instability in chemical networks that are unrelated to autocatalysis. We use such intuition to design non-autocatalytic biochemical networks with su- perlinear growth and oscillations.

Généralement, diagnostiquer une pathologie donnée à un stade de développement précoce favorise le pronostic vital du patient atteint. Une telle performance nécessite de détecter des marqueurs présents à des seuils de concentrations bas dans des fluides biologiques souvent complexes. Pour détecter ces concentrations extrêmement faibles en analyte donné, la stratégie employée au cours de ce travail est l’amplification moléculaire du signal. Pour cela, différentes approches sont possibles (i) amplifier le signal issu de l’évènement de reconnaissance cible/sonde, (ii et iii) amplifier le signal par régénération ou réplication de la cible. Les stratégies conçues au cours de ce travail de thèse se focalisent principalement sur la détection de petites molécules, telles que l’eau oxygénée ou encore l’anion fluorure, mais avec à terme l’idée de les étendre à la détection indirecte de biomarqueurs ou protéines d’intérêts. La première partie de cette thèse se focalise sur l’amplification moléculaire d’un signal par une catalyse allostérique en utilisant la réaction de reconstitution d’une apoenzyme donnée avec son cofacteur tandis que la seconde partie de cette thèse repose sur la mise en place de systèmes d’amplification catalytique et auto-catalytique pour la détection d’H2O2, grâce à des dérivés pro-quinoniques porteurs de groupement acide/ester boronique. La distinction entre les systèmes catalytique et auto-catalytique se fait selon qu’H2O2 est régénéré ou amplifié au cours de la réaction. / Generally, diagnosing a given pathology at an early stage of development promotes the patient's prognosis. Such a performance requires the detection of specific markers which are present in complex biological fluids at low concentration level. To detect these extremely low analyte concentrations, the strategy employed in this work is the molecular amplification of the signal. To this end, different approaches are possible (i) amplifying the signal resulting from the target / probe recognition event, (ii and iii) amplifying the signal by regeneration or replication of the target. The strategies conceived during this thesis work mainly focus on the detection of small molecules, such as hydrogen peroxide or fluoride anion, but with the idea of extending them to the indirect detection of biomarkers or proteins of interest. The first part of this thesis focuses on the molecular amplification of a signal by allosteric catalysis using the reconstitution reaction of a given apoenzyme with its cofactor. The second part of this thesis is based on the implementation of catalytic and auto-catalytic amplification systems for the detection of H2O2, thanks to pro-quinonic derivatives bearing boronic acid/ester group. The distinction between catalytic and auto-catalytic systems is based on whether H2O2 is regenerated or amplified during the reaction.

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