La biologie synthétique est une discipline en pleine expansion visant à concevoir et construire des systèmes biologiques possédant des fonctions qui n'existent pas dans la nature. Elle se fonde sur des principes d'ingénierie pour rationnaliser la conception de tels systèmes. Le projet CompuBioTic a pour objectif le développement d'un nouveau type de diagnostic du cancer colorectal, se fondant sur une approche de biologie synthétique. Un choix stratégique a été fait et consiste à vouloir développer un système non vivant, ne nécessitant pas de cellule hôte et fondé sur l'utilisation de réseaux protéiques plutôt que génétiques. Très peu de méthodologies et d'outils ont été développés pour faciliter la conception de ce type de système. Cette thèse propose une méthodologie en trois points : conception, simulation et validation expérimentale ainsi que deux outils bioinformatiques, développés pour aider à la conception de réseaux biochimiques synthétiques. Tout d'abord, CompuBioTicDB est une base de données qui regroupe et annote des dispositifs fonctionnels et des molécules réalisant des processus (protéines et petites molécules) pouvant être exploités dans un contexte de biologie synthétique. Deuxièmement, BioNetCAD est un outil permettant de concevoir un réseau biochimique composé de molécules réelles à partir d'un réseau abstrait. BioNetCAD facilite également la simulation spatio-temporelle du système conçu grâce à un lien vers le logiciel HSim. Des portes logiques moléculaires et un dispositif de détection du glucose ont ainsi été conçus, modélisés et validés expérimentalement. Les principes d'un système pour le diagnostic du cancer colorectal sont également proposés. / Synthetic biology is a growing discipline which aims to design and construct biological systems with functions that do not exist in nature. It is based on engineering principles to rationalize the design such systems. The CompuBioTic project aims at the development of a new system for the diagnosis of the colorectal cancer, based on a synthetic biology approach. A strategic choice has been done and consists in wanting to develop a non-living system, which does not require a host cell and which is based on the use of protein rather than genetic networks. Very few methodologies and tools have been developed to facilitate the design of such systems. This thesis proposes a methodology in three steps: design, simulation and experimental validation, as well as two bioinformatics tools, developed to assist the design of synthetic biochemical networks. Firstly, CompuBioTicDB is a database that registers and annotates functional devices and molecules carrying processes (proteins and small molecules) that can be exploited in a context of synthetic biology. Secondly, BioNetCAD is a tool for designing a biochemical network composed of real molecules from an abstract network. BioNetCAD also facilitates spatiotemporal simulation of the designed system with a link to the HSim software. Molecular logic gates and a device for detecting glucose have been designed, modeled and then validated experimentally. The principles of a system for the diagnosis of colorectal cancer are also proposed.

Two major roadblocks in synthetic biology are the difficulties associated with the physical assembly of gene regulatory networks (GRNs) and the lack of characterized biological parts. In this work we aimed to address both of these issues. We developed a novel method for the assembly of GRNs called Brick- Mason assembly. We have shown that the method can assemble a 6 part network in a single day and provides significant advancements over traditional cloning methods. We used BrickMason to assemble GRNs that would allow us to compare natural yeast mechanisms of repression to the steric hindrance based mechanisms that are commonly used in synthetic GRNs in yeast. Our results show that the two mechansisms of repression are not equivalent. This finding opens possibilities for using a new class of repressor in a synthetic context in yeast.

Oncolytic viruses (OVs) are emerging as a potent therapeutic platform for the treatment of malignant disease. The tumor cells inability to induce antiviral defences in response to a small cytokine known as interferon (IFN) is a common defect exploited by OVs. Heterogeneity in IFN signalling across tumors is therefore a pillar element of resistance to these therapies. I have generated a mathematical model and simulation platform to study the impact of IFN on OV dynamics in normal and cancerous tissues. In the first part of my thesis, I used this model to identify novel OV engineering strategies which could be implemented to overcome IFN based resistance in tumor tissues. From these simulations, it appears that a positive feedback loop, established by virus-mediated expression of an interferon-binding decoy receptor, could increase tumor cytotoxicity without compromising normal cells. The predictions set forth by this model have been validated both qualitatively and quantitatively in in-vitro and in-vivo models using two independent OV strains. This model has subsequently been used to investigate OV attenuation mechanisms, the impact of tumor cell heterogeneity, as well as drug-OV interactions. Following these results, it became apparent that selectivity should equally be observed when overwhelming the cell with a non replicating virus. While normal tissues will clear this pseudo-infection rapidly, owing to their high baseline in antiviral products at the onset of infection, tumor cells with defective anti-viral pathways should not have readily available biomachinery required to degrade this pro-apoptotic signal. Recapitulated by the mathematical model, non-replicating virus-derived particles generated by means of UV irradiation selectively kill tumor cells in cultured cell lines and patient samples, leading to long term cures in murine models. Taken together, this thesis uses a novel mathematical model and simulation platform to understand, design & improve oncolytic virus-based therapeutics.

Synthetic biology is an emergent field incorporating aspects of computer science molecular biology-based methodologies in a systems biology context, taking naturally occurring cellular systems, pathways, and molecules, and selectively engineering them for the generation of novel or beneficial synthetic behaviour. This study described the construction of a novel synthetic gene circuit, which utilises the inducible downstream transcriptional activation properties of the pheromone-response pathway in the budding yeast Saccharomyces cerevisiae as the basis for initiation. The circuit was composed of three novel yeast expression plasmids; (1) a reporter plasmid in which the luciferase reporter gene was fused to the iron response element (IRE), and expressed under the control of the pheromone-inducible FUS1 promoter, (2) a repressor plasmid which constitutively expressed the mammalian iron response protein (IRP), which can bind to the IRE in the luciferase mRNA transcript, blocking translation, and (3) a de-repressor plasmid which also utilised the pheromone-inducible FUS1 promoter to express the bacterial LexA protein that represses transcription of the IRP gene, and thereby de-represses luciferase translation. Yeast cultures were propagated in media that selected for cells containing all three plasmid components of the gene circuit. In these cells, during vegetative growth conditions, reporter gene translation is constitutively repressed by IRP until addition of pheromone. Upon pheromone-induction, the pheromone response pathway up-regulated the expression of the LexA protein which represses transcription of IRP, enabling the translation of luciferase, which is itself up-regulated by the pheromone response pathway. The combination of the repressors functioned to increase the ratio of induction of the reporter gene between pheromone-induced and un-induced states. Proteins and mRNA species expressed by each plasmid were semi-quantified using SDS-PAGE, Western blot, and RT-qPCR. Luciferase expression was measured using an in vitro whole cell luminescence assay, and the data used to define the circuit 'output'. Metabolic control analysis was used prior to building the circuit in silico, and identified the transcription of IRP, as well as the IRP protein half-life as significant control points for increasing the expression of luciferase in vivo. Modelling resulted in the development of multiple variations of the circuit, incorporating strong and weak constitutive promoters for the IRP. For the degradation rate, the IRP was fused with a degradation tag from the PEST rich C-terminal residue of the Cln2 protein, forming IRPPEST , with approximately a 10-fold reduced half-life compared to wild type. By varying the promoter strength and half-life of the IRP, the circuit could be tuned in terms of the amplitude and period of luciferase expression during pheromone induction. Simulated annealing and Hooke-Jeeves algorithms were used to estimate model parameter values from the experimental luminescence data, refining the modelling such that it produced accurate time course simulation of the circuit output. While further characterisation of the individual components would be advantageous, the construction of the system represents a completed cycle of extensive modelling, experimentation, and further model refinement.

Synthetic biology has been defined as: “the design and construction of new biological parts, devices, and systems, and the re-design of existing, natural biological systems for useful purposes” (syntheticbiology.org). The convergence of scientific fields such as molecular biology, computer science and others have rendered it a natural progression, based on existing knowledge.The fact that humanity has reached a stage of development where it seems feasible to “create” life, or design it to a high degree of specificity, is a significant milestone in its history. It generates important ethical questions: Is synthetic biology something good, a natural use of humanity’s talents, or is it a step towards megalomania, playing God, a usurpation of his role? Is it really a natural progression, nature advancing to a state where its products can, in turn, improve nature itself; or does it challenge the dignity of nature by virtue of its “unnaturalness”? Is it an expression of the creative talent of humanity, thus enhancing human dignity, and perhaps that of all life, or does it challenge the dignity of life itself? Regarding its potential consequences, it may, if it succeeds, lead humanity to a new level of development, a paradigm shift comparable with the scientific or industrial revolutions, through a vast increase in scientific knowledge, and subsequent technological developments in all relevant areas, including medicine, food production and fuel development. However, there is potential for serious accidents if synthetic organisms interact with naturally occurring ones, possibly affecting the future course of evolution. Synthetic biology also offers the possibility of creating ever more powerful weapons, more easily than ever before; the technology is reaching a stage where any interested members of the public may be able to create weapons of mass destruction. Synbio is a dual use technology, offering potential for both good and evil. Its potential for either appears to be greater than any other technology that has existed.In this thesis I evaluate the ethics of synthetic biology from the following ethical perspectives – deontology, consequentialism and theology. I am approaching it from several viewpoints so as to give as wide an analysis of the issues as possible. I also evaluate the effectiveness of these standard ethical tools for evaluating synbio ethics. In addition, I examine whether ethics should be more deeply integrated into the day-to-day scientific research in synbio. As a secondary study, I discuss regulation, the main legal issue that synthetic biology generates.

abstract: The CRISPR/Cas9 gene-editing tool is currently in clinical trials as the excitement about its therapeutic potential is exponentially growing. However, many of the developed CRISPR based genome engineering methods cannot be broadly translated in clinical settings due to their unintended consequences. These consequences, such as immune reactions to CRISPR, immunogenic adverse events following receiving of adeno-associated virus (AAV) as one of the clinically relevant delivery agents, and CRISPR off-target activity in the genome, reinforces the necessity for improving the safety of CRISPR and the gene therapy vehicles. Research into designing more advanced CRISPR systems will allow for the increased ability of editing efficiency and safety for human applications. This work 1- develops strategies for decreasing the immunogenicity of CRISPR/Cas9 system components and improving the safety of CRISPR-based gene therapies for human subjects, 2- demonstrates the utility of this system in vivo for transient repression of components of innate and adaptive immunity, and 3- examines an inducible all-in-one CRISPR-based control switch to pave the way for controllable CRISPR-based therapies. / Dissertation/Thesis / Doctoral Dissertation Biological Design 2020

Besides helping us advance the understanding of the physicochemical principles governing the three-dimensional folding of proteins and their mechanisms of action, the ability to build, evaluate, and optimize reliable 3D protein models has provided valuable tools for the development of different applications in the fields of biotechnology, medicine, and synthetic biology. The development of automated algorithms has made many of the current methodologies for protein modelling and visualization available to researchers from all backgrounds, without the need to be familiarized with the inner workings of their statistical and biophysical principles. However, there is still a lack in some areas where the learning curves are too steep for the methods to be widely used by the average non-programmer molecular biologist, or the implementation of the methods lacks key features to improve the interpretability and impact of their results. Throughout this work, I will focus on two different applications in the field of structural biology where computational methods provide useful tools to aid in synthetic biology or medical research. The first application is the implementation of a pipeline to build models of protein complexes by joining structured domains with disordered linkers, in individual or multiple chains, and with the possibility of building symmetric structures. Its capabilities and performance for the generation of complex constructs are evaluated, and possible areas of improvement described. The second application, but not less important, involves the structural analysis of patient-derived protein mutants using protein modelling techniques and visualization tools, to elucidate the potential molecular basis for the patient’s phenotype. The methodology for these analyses is described, along with the results and observations from 22 such cases in 13 different proteins. Finally, the need for a dedicated pipeline for the structure-based prediction of the effect of different types of mutations on the stability and function of proteins, complementary to available sequence-based approaches, is highlighted.

abstract: Fusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than deoxyribose nucleic acid (DNA) sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones, which are bound to DNA in eukaryotic nuclei and regulate gene expression states. In 2011, Haynes et al. showed that a synthetic regulator called the Polycomb chromatin Transcription Factor (PcTF), a fusion protein that binds methylated histones, reactivated an artificially-silenced luciferase reporter gene. These synthetic transcription activators are derived from the polycomb repressive complex (PRC) and associate with the epigenetic silencing mark H3K27me3 to reactivate the expression of silenced genes. It is demonstrated here that the duration of epigenetic silencing does not perturb reactivation via PcTF fusion proteins. After 96 hours PcTF shows the strongest reactivation activity. A variant called Pc2TF, which has roughly double the affinity for H3K27me3 in vitro, reactivated the silenced luciferase gene by at least 2-fold in living cells. / Dissertation/Thesis / Masters Thesis Biological Design 2019

This study focuses on engineering whole cell-based biosensors for heavy metal detection. Through the exploitation of metalloregulatory proteins, fabrication of metal ion-responsive biosensors is achieved. Metalloregulatory proteins of the SmtB/ArsR family including arsenite-responsive ArsR, cadmium-responsive CadC, zinc-responsive CzrA, and nickel-responsive NmtR were evaluated as biosensor sensing modules. Characterization of these four metal sensing modules was accomplished through quantification of a reporter green fluorescence protein (gfp) gene. As such, biosensors pCTYC-r34ArsR-pL(ArsOvN)GFP and pCTYC-r34CadC-pL(CadOv1)GFP displayed excellent gfp expression and sensitivity to As(III) and Cd (II), respectively. These two biosensors were consequently selected and successfully implemented in soil bacterium Pseudomonas putida. Lastly, a proof of concept arsenite-responsive genetic toggle switch is proposed utilizing PurRcelR467 (PC47), a cellobiose-responsive gene, and an LAA degradation tag. Overall, this study expands the bank of metalloregulatory bioparts for heavy metal sensing in the aim of constructing an optimized water monitoring system.

Synthetic biology is a rapidly growing discipline that aims to rationally design the behavior of living organisms for an array of applications, ranging from environmental monitoring to one of particular interest –medicine. For instance, given bacteria’s inherent ability to passively localize to tumor sites and previous work of engineering bacteria to sense compounds of interest utilizing genetic circuits, synthetic biologists can engineer bacteria to proactively sense the tumor for various applications. In this dissertation, we will discuss two such critical applications; one is ensuring safety of living therapeutics by having bacteria limit their growth to disease sites in order to prevent off-target toxicity. The other is a novel method of diagnostic readout, using bacterial production of a volatile compound. The aim of this thesis is to develop safe and robust bacteria-based technologies as living therapies. To confine bacterial growth within defined regions of interest, we engineer enhanced bacterial tropism with genetic circuits that couple bacterial sensing and growth in response to physiological signatures in vivo. Specifically, we construct oxygen, pH, and lactate biosensors with tunable features for activation at distinct physiological concentrations. We use these biosensors to control the expression of essential genes, which results in significant bacterial growth differences in permissive vs non-permissive conditions. Using pH and oxygen sensors, we demonstrate preferential growth in physiologically-relevant acidic and oxygen conditions. Upon oral delivery in mice, these engineered strains lowered bacteria numbers outside of the host. Multiplexing hypoxia and lactate biosensors with an AND logic-gate architecture resulted in improved performance, reducing bacterial off-target colonization in a syngeneic mouse tumor model. Taken together, these results demonstrate a synthetic biology approach to enhance precision localization of bacteria to specified organ niches. In additional to engineering bacteria localization, we also want to take advantage of E. coli’s programmable nature to produce diagnostic molecules. The engineering of microbial metabolic pathways over the last two decades has led to numerous examples of cell factories used for the production of small molecules. These molecules have an array of utility in commercial industries and as in-situ expressed biomarkers or therapeutics in microbial applications. While most efforts have focused on the production of molecules in the liquid phase, there has been increasing interest in harnessing microbes’ inherent ability to generate volatile compounds. Here, we optimized and characterized the production of methyl salicylate, an aromatic compound found mainly in plants, using a common lab strain of E. coli. We utilized genetic components from both microbes and plants to construct the volatile metabolite circuit cassette. In order to maximize production, we explored expressing methyl salicylate precursors, upregulating expression by increasing ribosomal binding strength and codon optimizing methyl transferase gene obtain from plant Petunia x hybrida. Lastly, we validated and quantified the production of methyl salicylate with liquid chromatography and gas chromatography mass spectrometry (LC-MS or GC-MS) and found that the codon optimized strain with precursor supplementation yield the highest production compared to the other strains. This work characterizes an optimized metabolite producing-genetic circuit and sets the stage for creation of an engineered bacteria diagnostic to be used in volatile assays.Finally we conclude by discussing the current efforts to adapt technology described in this thesis dissertation for clinical research and applying them in genetic mouse models for further validation. This underlying work contributes to rapidly growing field in synthetic biology to engineer microbial based living therapy.