Investigating automated chemical evolution of oil-in-water droplets

One of the main unresolved questions in science is how non-living matter became alive in a process known as abiognesis, which aims to explain how from a primordial soup scenario containing simple molecules, by following a ``bottom up'' approach, complex biomolecules emerged forming the first living system, known as a protocell. A protocell is defined by the interplay of three sub-systems which are considered requirements for life: information molecules, metabolism, and compartmentalization. This thesis investigates the role of compartmentalization during the emergence of life, and how simple membrane aggregates could evolve into entities that were able to develop ``life-like'' behaviours, and in particular how such evolution could happen without the presence of information molecules. Our ultimate objective is to create an autonomous evolvable system, and in order tp do so we will try to engineer life following a ``top-down'' approach, where an initial platform capable of evolving chemistry will be constructed, but the chemistry being dependent on the robotic adjunct, and how then this platform can be de-constructed in iterative operations until it is fully disconnected from the evolvable system, the system then being inherently autonomous. The first project of this thesis describes how the initial platform was designed and built. The platform was based on the model of a standard liquid handling robot, with the main difference with respect to other similar robots being that we used a 3D-printer in order to prototype the robot and build its main equipment, like a liquid dispensing system, tool movement mechanism, and washing procedures. The robot was able to mix different components and create populations of droplets in a Petri dish filled with aqueous phase. The Petri dish was then observed by a camera, which analysed the behaviours described by the droplets and fed this information back to the robot. Using this loop, the robot was then able to implement an evolutionary algorithm, where populations of droplets were evolved towards defined life-like behaviours. The second project of this thesis aimed to remove as many mechanical parts as possible from the robot while keeping the evolvable chemistry intact. In order to do so, we encapsulated the functionalities of the previous liquid handling robot into a single monolithic 3D-printed device. This device was able to mix different components, generate populations of droplets in an aqueous phase, and was also equipped with a camera in order to analyse the experiments. Moreover, because the full fabrication process of the devices happened in a 3D-printer, we were also able to alter its experimental arena by adding different obstacles where to evolve the droplets, enabling us to study how environmental changes can shape evolution. By doing so, we were able to embody evolutionary characteristics into our device, removing constraints from the physical platform, and taking one step forward to a possible autonomous evolvable system.

Engineering the transition from non-living to living matter

Re-creating and understanding the origin of life represents one of the major challenges facing the scientific community. We will never know exactly how life started on planet Earth, however, we can reconstruct the most likely chemical pathways that could have contributed to the formation of the first living systems. Traditionally, prebiotic chemistry has investigated the formation of modern life’s precursors and their self-organisation under very specific conditions thought to be ‘plausible’. So far, this approach has failed to produce a living system from the bottom-up. In the work presented herein, two different approaches are employed to explore the transition from inanimate to living matter. The development of microfluidic technology during the last decades has changed the way traditional chemical and biological experiments are performed. Microfluidics allows the handling of low volumes of reagents with very precise control. The use of micro-droplets generated within microfluidic devices is of particular interest to the field of Origins of Life and Artificial Life. Whilst many efforts have been made aiming to construct cell-like compartments from modern biological constituents, these are usually very difficult to handle. However, microdroplets can be easily generated and manipulated at kHz rates, making it suitable for high-throughput experimentation and analysis of compartmentalised chemical reactions. Therefore, we decided to develop a microfluidic device capable of manipulating microdroplets in such a way that they could be efficiently mixed, split and sorted within iterative cycles. Since no microfluidic technology had been developed before in the Cronin Group, the first chapter of this thesis describes the soft lithographic methods and techniques developed to fabricate microfluidic devices. Also, special attention is placed on the generation of water-in-oil microdroplets, and the subsequent modules required for the manipulation of the droplets such as: droplet fusers, splitters, sorters and single/multi-layer micromechanical valves. Whilst the first part of this thesis describes the development of a microfluidic platform to assist chemical evolution, finding a compatible set of chemical building blocks capable of reacting to form complex molecules with endowed replicating or catalytic activity was challenging. Abstract 10 Hence, the second part of this thesis focuses on potential chemistry that will ultimately possess the properties mentioned above. A special focus is placed on the formation of peptide bonds from unactivated amino acids, despite being one of the greatest challenges in prebiotic chemistry. As opposed to classic prebiotic experiments, in which a specific set of conditions is studied to fit a particular hypothesis, we took a different approach: we explored the effects of several parameters at once on a model polymerisation reaction, without constraints on hypotheses on the nature of optimum conditions or plausibility. This was facilitated by development of a new high-throughput automated platform, allowing the exploration of a much larger number of parameters. This led us to discover that peptide bond formation is less challenging than previously imagined. Having established the right set of conditions under which peptide bond formation was enhanced, we then explored the co-oligomerisation between different amino acids, aiming for the formation of heteropeptides with different structure or function. Finally, we studied the effect of various environmental conditions (rate of evaporation, presence of salts or minerals) in the final product distribution of our oligomeric products.

Exploring complex chemical systems: insights from mass spectrometry, electrochemistry and continuous cell culture

The work presented herein covers a broad range of research topics and so, in the interest of clarity, has been presented in a portfolio format. Accordingly, each chapter consists of its own introductory material prior to presentation of the key results garnered, this is then proceeded by a short discussion on their significance. In the first chapter, a methodology to facilitate the resolution and qualitative assessment of very large inorganic polyoxometalates was designed and implemented employing ion-mobility mass spectrometry. Furthermore, the potential of this technique for ‘mapping’ the conformational space occupied by this class of materials was demonstrated. These claims are then substantiated by the development of a tuneable, polyoxometalate-based calibration protocol that provided the necessary platform for quantitative assessments of similarly large, but unknown, polyoxometalate species. In addition, whilst addressing a major limitation of travelling wave ion mobility, this result also highlighted the potential of this technique for solution-phase cluster discovery. The second chapter reports on the application of a biophotovoltaic electrochemical cell for characterising the electrogenic activity inherent to a number of mutant Synechocystis strains. The intention was to determine the key components in the photosynthetic electron transport chain responsible for extracellular electron transfer. This would help to address the significant lack of mechanistic understanding in this field. Finally, in the third chapter, the design and fabrication of a low-cost, highly modular, continuous cell culture system is presented. To demonstrate the advantages and suitability of this platform for experimental evolution investigations, an exploration into the photophysiological response to gradual iron limitation, in both the ancestral wild type and a randomly generated mutant library population, was undertaken. Furthermore, coupling random mutagenesis to continuous culture in this way is shown to constitute a novel source of genetic variation that is open to further investigation.

Applied evolution: An integrated approach to studying life history traits in response to drug selection

The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.

Physicochemical complexity in complex chemical systems

Self-replication and compartmentalization are two central properties thought to be essential for minimal life, and understanding how such processes interact in the emergence of complex reaction networks is crucial to exploring the development of complexity in chemistry and biology. Autocatalysis can emerge from multiple different mechanisms such as formation of an initiator, template self-replication and physical autocatalysis (where micelles formed from the reaction product solubilize the reactants, leading to higher local concentrations and therefore higher rates). Amphiphiles are also used in artificial life studies to create protocell models such as micelles, vesicles and oil-in-water droplets, and can increase reaction rates by encapsulation of reactants. So far, no template self-replicator exists which is capable of compartmentalization, or transferring this molecular scale phenomenon to micro or macro-scale assemblies. Here a system is demonstrated where an amphiphilic imine catalyses its own formation by joining a non-polar alkyl tail group with a polar carboxylic acid head group to form a template, which was shown to form reverse micelles by Dynamic Light Scattering (DLS). The kinetics of this system were investigated by 1H NMR spectroscopy, showing clearly that a template self-replication mechanism operates, though there was no evidence that the reverse micelles participated in physical autocatalysis. Active oil droplets, composed from a mixture of insoluble organic compounds in an aqueous sub-phase, can undergo processes such as division, self-propulsion and chemotaxis, and are studied as models for minimal cells, or protocells. Although in most cases the Marangoni effect is responsible for the forces on the droplet, the behaviour of the droplet depends heavily on the exact composition. Though theoretical models are able to calculate the forces on a droplet, to model a mixture of oils on an aqueous surface where compounds from the oil phase are dissolving and diffusing through the aqueous phase is beyond current computational capability. The behaviour of a droplet in an aqueous phase can only be discovered through experiment, though it is determined by the droplet's composition. By using an evolutionary algorithm and a liquid handling robot to conduct droplet experiments and decide which compositions to test next, entirely autonomously, the composition of the droplet becomes a chemical genome capable of evolution. The selection is carried out according to a fitness function, which ranks the formulation based on how well it conforms to the chosen fitness criteria (e.g. movement or division). Over successive generations, significant increases in fitness are achieved, and this increase is higher with more components (i.e. greater complexity). Other chemical processes such as chemiluminescence and gelation were investigated in active oil droplets, demonstrating the possibility of controlling chemical reactions by selective droplet fusion. Potential future applications for this might include combinatorial chemistry, or additional fitness goals for the genetic algorithm. Combining the self-replication and the droplet protocells research, it was demonstrated that the presence of the amphiphilic replicator lowers the interfacial tension between droplets of a reaction mixture in organic solution and the alkaline aqueous phase, causing them to divide. Periodic sampling by a liquid handling robot revealed that the extent of droplet fission increased as the reaction progressed, producing more individual protocells with increased self-replication. This demonstrates coupling of the molecular scale phenomenon of template self-replication to a macroscale physicochemical effect.