Rozprawy doktorskie na temat „Systems Biology, Synthetic Biology, Metabolic Engineering”

The field of Synthetic Biology seeks to develop engineering principles for biological systems. Modular biological parts are repurposed and recombined to develop new synthetic biological devices with novel functions. The proper functioning of these devices is dependent on the cellular context provided by the host organism, and the interaction of these devices with host systems. The field of Systems Biology seeks to measure and model the properties of biological phenomena at the network scale. We present the application of systems biology approaches to synthetic biology, with particular emphasis on understanding and remodeling metabolic networks. Chapter 2 demonstrates the use of a Flux Balance Analysis model of the Saccharomyces cerevisiae metabolic network to identify and construct strains of S. cerevisiae that produced increased amounts of formic acid. Chapter 3 describes the development of synthetic metabolic pathways in Escherichia coli for the production of hydrogen, and a directed evolution strategy for hydrogenase enzyme improvement. Chapter 4 introduces the use of metabolomic profiling to investigate the role of circadian regulation in the metabolic network of the photoautotrophic cyanobacterium Synechococcus elongatus PCC 7942. Together, this work demonstrates the utility of network-scale approaches to understanding biological systems, and presents novel strategies for engineering metabolism.

Les chercheurs en biologie de synthèse programment l’ADN pour construire des systèmes biologiques capables de répondre à certaines conditions de manière prédéfinie. Cette capacité pourrait avoir un impact sur plusieurs domaines, de la médecine à la fermentation industrielle. Le traitement de signal par des circuits biologiques synthétiques est en train d’être démontré à large échelle, mais hélas la variété des signaux d’entrée capables de contrôler ces circuits est pour l’instant limitée. Ce manque de diversité est un obstacle majeur au développement de nouvelles applications car en général chaque application requiert une réponse à des signaux de nature particulière qui lui sont spécifiques. Cette thèse cherche à apporter des solutions au manque de signaux d’entrée appropriés contrôlant les circuits biologiques en développant deux nouvelles stratégies d’induction. La première stratégie vise à étendre la diversité chimique des signaux d’entrée. A l’inverse des approches existantes, qui reposent sur la modification des systèmes de détections naturels tels que les riboswitchs ou les facteurs de transcription allostériques, j’ai cherché ici à modifier directement des molécules préalablement non-détectables afin de les rendre détectables par les systèmes de détection actuels. Pour ce faire, la transformation chimique des molécules cibles est réalisée in situ grâce à l’expression de voies métaboliques synthétiques dans la cellule. Afin de pouvoir utiliser cette stratégie de manière systématique, j’ai employé la conception assistée par ordinateur et puisé dans l’ensemble des réactions biochimiques connues afin de prédire des voies de détections pour de nouvelles molécules. J’ai ensuite implémenté in vivo plusieurs prédictions qui ont permis à E. coli de détecter de nouveaux composés. Au-delà de l’intérêt de cette méthode en biotechnologie, cela montre que le métabolisme peut jouer un rôle dans le transfert d’information, en plus de son rôle dans le transfert de matière et d’énergie, ce qui soulève la question de l’utilisation potentielle de cette stratégie de détection par la nature. Un second axe présente une façon d’épargner l’utilisation d’inducteurs chimiques pour les programmes biologiques simples, et propose d’utiliser des inducteurs biologiques à la place. Lorsqu’une seule étape d’induction ou de répression de gènes est nécessaire, comme c’est le cas en fermentation industrielle, je propose de remplacer la coûteuse étape d’induction chimique par l’infection simultanée de toutes les cellules d’une population par des particules virales capables d’injecter en temps réel l’ensemble des informations nécessaires pour déclencher l’activité biologique recherchée. A des fins de fermentation, j’ai développé des particules virales modifiées qui reprogramment dynamiquement le métabolisme d’une large population de bactérie au moment opportun et les forcent à produire des molécules à haute valeur ajoutée
Synthetic biologists program DNA with the aim of building biological systems that react under certain conditions in a predefined way. This ability could have impact in several fields, from medicine to industrial fermentation. While the scalability of synthetic biological circuits in terms of signal processing in now almost demonstrated, the variety of input signals for these circuits is limited. Because each application typically requires a circuit to react to case-specific molecules, the lack of input diversity is a major obstacle to the development of new applications. Two axis are developed over the course of this thesis to try to address input-related problems. The main axis consists in a new strategy aiming at systematically and immediately increasing the chemical diversity of inputs for synthetic circuits. Current approaches to expand the number of potential inputs focus on re-engineering sensing systems such as riboswitches or allosteric transcription factors to make them react to previously non-detectable molecules. On the contrary, here we developed a method to transform the non-detectable molecules themselves into molecules for which sensing systems already exist. These chemical transformations are realized in situ by expressing synthetic metabolic pathways in the cell. In order to systematize this strategy, we leveraged computer-aided design to predict ways of detecting new molecules by digging into all known biochemical reactions. We then implemented several predictions in vivo that successfully enabled E. coli to detect new chemicals. Aside from the interest of the method for biotechnological applications, this shows that in addition to transferring matter and energy, metabolism can also play a role in transferring information, raising the question of potential occurrences of this sensing strategy in nature. A second axis introduce a way to exempt simple programs from the need for a chemical input, and explore the use of a biological input instead. In situations where a single timely induction or repression of multiple genes is required, such as in industrial fermentation processes, we propose to replace expensive chemical induction by simultaneous infection of all the members of a growing population of cells with viral particles inputting in real-time all the necessary information for the task at hand. In the context of fermentation, we developed engineered viral particles that can dynamically reprogram the metabolism of a large population of bacteria at the optimal stage of growth and force them to produce value-added chemicals

The current investigation is aimed at the reconstruction and analysis of genome-scale metabolic models. Specifically, it is focused on the use of mathematical-computational simulations to predict the cellular metabolism behavior towards bio-products production. The photosynthetic cyanobacterium Synechococcus elongatus PCC7942 was studied as biological system. This prokaryotic has been used in several studies as a biological platform for the synthesis of several substances for industrial interest. These studies are based on the advantage of autotrophic systems, which basically requires light and CO2 for growth. The main objective of this thesis is the integration of different types of biological information, whose interaction can be extract applicable knowledge for economic interests. To this end, our study was addressed to the use of methods for modeling, analyzing and predicting the behavior of metabolic phenotypes of cyanobacterium. The work has been divided into chapters organized sequentially, where the starting point was the in silico metabolic reconstruction network. This process intent to join in a metabolic model of all chemical reactions codified in genome. The stoichiometric coefficients of each reactions, can be arranged into a sparse matrix (stoichiometric matrix), where the columns corresponds to reactions and rows to metabolites. As a result of this process the first model was obtained (iSyf646) than later was updated to another (iSyf714). Both were generated from data ¿omics published in databases, scientific reviews as well as textbooks. To validate them, each one of the stoichiometric matrix together with relevant constraints were used by simulation techniques based on linear programming. These reconstructions have to be flexible enough to allow autotrophic growth under which the organism grows in nature. Once the reconstructions were validated, environmental variations can be simulated and we were able to study its effects through changes in outline system parameters. Subsequently, synthetic capabilities were evaluated from the in silico models in order to design metabolic engineering strategies. To do this a genetic variation was simulated in reactions network, where the disturbed stoichiometric matrix was the object of the quadratic optimization methods. As a results sets of optimal solutions were generated to enhanced production of various metabolites of energetic interest such as: ethanol, n-butanol isomers, lipids and hydrogen, as well as lactic acid as the compound which is an interest to the industry. Furthermore, functionally coupled reactions have been studied and have been weighted to the importance in the production of metabolites. Finally, genome-scale metabolic models allow us to establish criteria to integrate different types of data to help of find important points of regulation that may be subject to genetic modification. These regulatory centers have been investigated under drastic changes of illumination and have been inferred operational principles of cyanobacterium metabolism. In general, this thesis presents the metabolic capabilities of photosynthetic cyanobacterium Synechococcus elongatus PCC7942 to produce substances of interest, being a potential biological platform for clean and sustainable production.
Triana Dopico, J. (2014). Model-based analysis and metabolic design of a cyanobacterium for bio-products synthesis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39351
TESIS

Microbial biosynthesis of commodity compounds offers a cheaper, greener and more reliable method of production than does chemical synthesis. However, engineering metabolic pathways within a microbe for biosynthesis of a target compound is a complicated process: levels of gene expression, protein stability, enzyme activity, and metabolic flux must be balanced for high productivity without compromising host cell viability. A major rate-limiting step in engineering microbes for optimum biosynthesis of a target compound is DNA assembly, as current methods can be cumbersome and costly. This study aimed to develop a new, synthetic biology tool for rapid DNA assembly that can be applied to engineering and optimizing metabolic pathways for the microbial biosynthesis of commodity compounds. The potential of using serine site-specific recombinases as synthetic biology tools to assemble DNA was investigated and a new DNA assembly method, Serine Integrase Recombinational Assembly (SIRA), using PhiC31 integrase was established. It was demonstrated that SIRA can clone DNA parts ranging in size from 71 bp to 12.7 kb, assemble as many as five DNA parts in a one-pot reaction, facilitate targeted post-assembly modification of an assembled construct and generate variation between DNA constructs in a single assembly reaction. SIRA was used to generate variation between constructs containing genes of the violacein biosynthesis pathway, the lycopene biosynthesis pathway, or the DXP pathway for isoprenoid biosynthesis in E. coli. By studying the phenotypes and genotypes of the constructs generated, it was possible to identify rate-limiting steps within these pathways. Finally, a lycopene-producing in vivo biosensor screen was developed in E. coli to screen DNA assemblies, made with SIRA, encoding genes from the DXP pathway, for enhanced isoprenoid production. By optimizing the expression conditions for assemblies of DXP pathway genes that enhanced isoprenoid production and genes for lycopene biosynthesis in E. coli, 35.78 mg lycopene per gram dry cell weight was obtained - the highest recorded level of lycopene produced from engineering of the DXP pathway alone in E. coli.

Inexpensive petroleum is the cornerstone of the modern global economy despite its huge environmental costs and its nature as a non-renewable resource. While ninety percent of petroleum is ultimately used as fuel and can in principle be replaced by sources of renewable electricity, ten percent is used as a feedstock to produce societally important chemicals that cannot currently be made at a reasonable cost through alternative processes. In this dissertation, I will discuss my efforts, together with several colleagues, to apply synthetic biology approaches to the challenge of producing renewable petrochemical replacements. In Chapter 2, I discuss our efforts to engineer E. coli to produce fatty acids with a wide range of chain lengths at high yield, thereby providing an alternative platform for the production of diverse petrochemicals. In Chapter 3, I describe a novel method of DNA assembly that we developed to facilitate synthetic biology efforts such as those in Chapter 2. This method is capable of simultaneously assembling multiple DNA pieces with substantial sequence homology, a common challenge in synthetic biology. In Chapter 4, I discuss the development of a "bionic leaf": a hybrid microbial-inorganic catalyst that marries the advantages of photovoltaic-based light capture and microbial carbon fixation to achieve solar biomass yields greater than those observed in terrestrial plants. This technology offers a potentially low-cost alternative to photosynthesis as a source of biomass and derived chemicals and fuels. The work described in this dissertation demonstrates the capacity of synthetic biology to address the problem of renewable chemical production, and offers proof of principle demonstrations that both the scope and efficiency of biological chemical production may be improved.

Systems biology is a rapidly growing field which seeks a refined quantitative understanding of organisms, particularly studying how molecular species such as metabolites, proteins and genes interact in cells to form the complex emerging behaviour exhibited by living systems. Synthetic biology is a related and emerging field which seeks to engineer new organisms for practical purposes. Both fields can benefit from formal languages for modelling, simulation and analysis. In systems biology there is however a trade-off in the landscape of existing formal languages: some are modular but may be difficult for some biologists to understand (e.g. process calculi) while others are more intuitive but monolithic (e.g. rule-based languages). The first major contribution of this thesis is to bridge this gap with a Language for Biochemical Systems (LBS). LBS is based on the modular Calculus of Biochemical Systems and adds e.g. parameterised modules with subtyping and a notion of nondeterminism for handling combinatorial explosion. LBS can also incorporate other rule-based languages such as Kappa, hence adding modularity to these. Modularity is important for a rational structuring of models but can also be exploited in analysis as is shown for the specific case of Petri net flows. On the synthetic biology side, none of the few existing dedicated languages allow for a high-level description of designs that can be automatically translated into DNA sequences for implementation in living cells. The second major contribution of this thesis is exactly such a language for Genetic Engineering of Cells (GEC). GEC exploits the recent advent of standard genetic parts (“biobricks”) and allows for the composition of such parts into genes in a modular and abstract manner using logical constraints. GEC programs can then be translated to DNA sequences using a constraint satisfaction engine based on a given database of genetic parts.

Renewable green alternatives to fossil fuels need to be sought in order to address the challenges of environmental and energy crises. Up until now, ethanol has been the major biofuel. Geobacillus thermoglucosidans is a thermophilic bacterium that is capable of producing bioethanol in an industrial setting at high temperatures and is capable of metabolizing pentoses and hexoses commonly found in lignocellulosic biomass. Due to these attractive properties, the aim of this work has been to construct a toolbox of genetic components to develop G. thermoglucosidans as as the leading thermophile chassis for synthetic biology and metabolic engineering. The toolbox is composed of shuttle vectors that have higher transformation efficiencies than previous existing vectors and are modular, where the presence of restriction sites separating each of the components allows users to exchange parts easily and efficiently. Also included in the toolbox are the fluorescent reporters sfGFP, mCherry and BsFbFP that will permit the characterization of promoters. As a proof-of-principle application to demontrate the effectivity of the toolbox for the production of valuable compounds, this work explores the production of isobutanol by the thermophile bacteria Geobacillus thermoglucosidans. Isobutanol is a higher chain alcohol that is a significantly better fuel molecule than ethanol, both for energy content and infrastructure compatibility. The Geobacillus host was able to produce isobutanol in amounts of around 50 mg/L via the conversion of isobutyryl-CoA to isobutyraldehyde by an (ALDH) and from isobutyraldehyde to isobutanol by an alcohol dehydrogenase (ADH). It was observed that supplementing the growth medium with an intermediate of the valine biosynthesis pathway, 2-ketoisovalerate, resulted in the production of isobutanol and overexpressing ALDH increased the isobutanol titres.

Doctor en Ciencias de la Ingeniería, Mención Química
In the first chapter, this thesis aims to demonstrate the great potential of Constraint-Based Reconstruction and Analysis (COBRA) methods for studying and predicting specific phenotypes in the bacterium Acidithiobacillus ferrooxidans. A genome-scale metabolic reconstruction of Acidithiobacillus ferrooxidans ATCC 23270 (iMC507) is presented and characterized. iMC507 is validated for aerobic chemolithoautotrophic conditions by fixating carbon dioxide and using three different electron donors: ferrous ion, tetrathionate and thiosulfate. Furthermore, the model is utilized for (i) quantitatively studying and analyzing key reactions and pathways involved in the electron transfer metabolism, (ii) describing the central carbon metabolism and (iii) for evaluating the potential to couple the production of extracellular polymeric substances through knock-outs. The second chapter work outlines the effort towards advancing the field of systems metabolic engineering by using COBRA methods in conjunction with chemoinformatic approaches to metabolically engineer the bacterium Escherichia coli. A complete strain design workflow integrating synthetic pathway prediction with growth-coupled designs for the production of non-native compounds in a target organism of interest is outlined. The generated enabling technology is a computational pipeline including chemoinformatics, bioinformatics, constraint-based modeling, and GEMs to aid in the process of metabolic engineering of microbes for industrial bioprocessing purposes. A retrosynthetic based pathway predictor algorithm containing a novel integration with GEMs and reaction promiscuity analysis is developed and demonstrated. Specifically, the production potential of 20 industrially-relevant chemicals in E. coli and feasible designs for production strains generation is outlined. A comprehensive mapping from E. coli s native metabolome to commodity chemicals that are 4 reactions or less away from a natural metabolite is performed. Sets of metabolic interventions, specifically knock-outs and knock-ins that coupled the target chemical production to growth rate were determined. In the third chapter, in order to aid the field of cancer metabolism, potential biomarkers were determined through gain of function oncometabolites predictions. Based on a chemoinformatic approach in conjunction with the global human metabolic network Recon 2, a workflow for predicting potential oncometabolites is constructed. Starting from a list of mutated enzymes genes, described as GoF mutations, a range of promiscuous catalytic activities are inferred. In total 24 chemical substructures of oncometabolites resulting from the GoF analysis are predicted.

Microbial metabolism can be tailored to meet human specifications, but the degree to which these living systems can be repurposed is still unknown. Artificial biological control strategies are being developed with the goal of enabling the predictable implementation of novel biological functions (e.g., engineered metabolism). This dissertation project contributes genetic tools useful for modulating gene expression levels (extending promoters with UP elements) and isolating transcription and translation of engineered DNA from the endogenous cellular network (expression by orthogonal cellular machinery), which have been demonstrated in Escherichia coli for the production of lycopene, a 40-carbon tetraterpene carotenoid with antioxidant activity and a number of other desirable properties.

Biological systems display remarkable complexity that is not properly accounted for in small, reductionistic models. Increasingly, big data approaches using genomics, proteomics, metabolomics etc. are being applied to predicting and modifying the emergent phenotypes produced by complex biological systems. In this research, several novel tools were developed to assist in the acquisition and analysis of biological big data for a variety of applications. In total, two entirely new tools were created and a third, relatively new method, was evaluated by applying it to questions of clinical importance. 1) To assist in the quantification of metabolites at the subcellular level, a strategy for localized in-vivo enzymatic assays was proposed. A proof of concept for this strategy was conducted in which the local availability of acetyl-CoA in the peroxisomes of yeast was quantified by the production of polyhydroxybutyrate (PHB) using three heterologous enzymes. The resulting assay demonstrated the differences in acetyl-CoA availability in the peroxisomes under various culture conditions and genetic alterations. 2) To assist in the design of genetically modified microbe strains that are stable over many generations, software was developed to automate the selection of gene knockouts that would result in coupling cellular growth with production of a desired chemical. This software, called OptQuick, provides advantages over contemporary software for the same purpose. OptQuick can run considerably faster and uses a free optimization solver, GLPK. Knockout strategies generated by OptQuick were compared to case studies of similar strategies produced by contemporary programs. In these comparisons, OptQuick found many of the same gene targets for knockout. 3) To provide an inexpensive and non-invasive alternative for bladder cancer screening, Raman-based urinalysis was performed on clinical urine samples using RametrixTM software. RametrixTM has been previously developed and employed to other urinalysis applications, but this study was the first instance of applying this new technology to bladder cancer screening. Using a pool of 17 bladder cancer positive urine samples and 39 clinical samples exhibiting a range of healthy or other genitourinary disease phenotypes, RametrixTM was able to detect bladder cancer with a sensitivity of 94% and a specificity of 54%. 4) Methods for urine sample preservation were tested with regard to their effect on subsequent analysis with RametrixTM. Specifically, sterile filtration was tested as a potential method for extending the duration at which samples may be kept at room temperature prior to Raman analysis. Sterile filtration was shown to alter the chemical profile initially, but did not prevent further shifts in chemical profile over time. In spite of this, both unfiltered and filtered urine samples alike could be used for screening for chronic kidney disease or bladder cancer even after being stored for 2 weeks at room temperature, making sterile filtration largely unnecessary.
Doctor of Philosophy

Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed June 2, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 251-259).
Across technology industries and particularly at the cutting edge of biotechnology a debate is under way about the proper balance between open and closed - between co-developing products with shared information and open standards, versus using more traditional, closed, proprietary processes. Beyond the relative success of open source software to date, it is not clear how and whether open design processes might be applied generally for complex, assembled technologies. This problem takes on special urgency within the domain of synthetic biology, an emerging discipline in which many practitioners advocate opening design and development through platforms such as the registry of standardized biological parts. Biotechnology is IP intensive in part because commercialization is complicated and capital intensive. How might one develop a sustainable open development process in this context? This thesis addresses these questions from an Engineering Systems perspective. Defining open, collaborative system development (OCSD) specifically as a process in which subsystems are created voluntarily by an unrestricted set of third-party contributors, it makes the following claim: An OCSD process can itself be designed, with the principal objective of creating an environment for third-party innovation. To support this claim the thesis outlines a conceptual framework to guide OCSD design. The framework includes a taxonomy of parameters and constraints relevant to opening design, a list of options within each taxonomic category, and three high level strategies found to recur as a function of sponsor goals and technological constraints. Finally, the thesis proposes a quantitative method, based on multidisciplinary modeling and pareto analysis, to design open standards within the context of one of the three strategies. The research is carried out through a pragmatic blend of case studies and quantitative modeling. First, an in-depth, multi-discipline literature review synthesizes relevant taxonomic categories. Thirteen examples of OCSD spanning nine industries are then analyzed to define options within each taxonomic category. The case studies are also used to identify strategies for opening design based on correlations between OCSD options. The framework is validated and expanded through an in-depth case study of the opening of Very Large Scale Integration (VLSI) in the semi-conductor industry in the late 1970s. Finally, a quantitative method is developed to guide the design of open standards within one of the three strategies. These three contributions - the framework, correlated strategies, and quantitative method - are then applied to a particular biotechnology called microbial fuel cells.
by Matthew Robin Silver.
Ph.D.

Metabolic engineering of microorganisms for chemical production involves the coordination of regulatory, kinetic, and thermodynamic parameters within the context of the entire network, as well as the careful allocation of energetic and structural resources such as ATP, redox potential, and amino acids. The exponential progression of “omics” technologies over the past few decades has transformed our ability to understand these network interactions by generating enormous amounts of data about cell behavior. The great challenge of the new biological era is in processing, integrating, and rationally interpreting all of this information, leading to testable hypotheses. In silico metabolic reconstructions are versatile computational tools for integrating multiple levels of bioinformatics data, facilitating interpretation of that data, and making functional predictions related to the metabolic behavior of the cell. To explore the use of this modeling paradigm as a tool for enabling metabolic engineering in a poorly understood microorganism, an in silico constraint-based metabolic reconstruction for the anaerobic, cellulolytic bacterium Clostridium thermocellum was constructed based on available genome annotations, published phenotypic information, and specific biochemical assays. This dissertation describes the analysis and experimental validation of this model, the integration of transcriptomic data from an RNAseq experiment, and the use of the resulting model for generating novel strain designs for significantly improved production of ethanol from cellulosic biomass. The genome-scale metabolic reconstruction is shown to be a powerful framework for understanding and predicting various metabolic phenotypes, and contributions described here enhance the utility of these models for interpretation of experimental datasets for successful metabolic engineering.

Synthetic Biology is a relatively new and multi-faceted interdisciplinary emergent field of research that combines biology with technology in novel and exciting ways. One of its main branches aims to see living systems engineered in a rational and straightforward bottom-up approach, like in other engineering disciplines. The inherent complex nature of living systems turns them into a difficult and challenging substrate where to apply common engineering principles such as standardization, abstraction and modularity. Efforts to overcome these limitations and adapt such principles for working upon living systems have been devoted, though yet with relative success. The aim of this Thesis is to critically explore what is Synthetic Biology and how far it is from a veritable engineering discipline. In this Thesis, we first present a review that thoroughly explores and discusses this scenario. Then, we present two works that shall contribute to this ambitious and hard goal. First, within the context of standardization, we address the need for better genetic parts characterization by providing an example of a biologically grounded framework inspired by classical enzymology theory. Second, and in relation with the principle of modularity, we provide a theoretical framework, in this case inspired by the Ohm’s law of electric theory, that describes the unintended coupling of the coexisting genetic loads within a given host cell due to sharing a limited common pool of machinery and resources. Together, both works contribute, on one hand, to increase our understanding of the organizing principles of living systems, and on the other hand, to improve how engineering principles are applied to synthetic circuit design. Finally, these works emphasize the need to find better experimentally backed-up theoretical frameworks or models that should allow us to jump from the current time-consuming, trial-error and ad hoc Synthetic Biology to a well-established engineering discipline as fruitful and efficient with the living systems realm as other engineering disciplines are.
La Biologia Sintètica és un camp de recerca emergent relativament nou i multi-facètic que combina la biologia amb la tecnologia de formes innovadores i emocionants. Una de les seves principals branques té com a objectiu aconseguir ingenieritzar els sistemes vius des d’abaix de manera racional i senzilla, tal com passa en altres tipus d’enginyeria. La naturalesa inherentment complexa dels éssers vius els converteix en un substrat difícil sobre el qual aplicar principis d’enginyeria com l’abstracció, l’estandardització i la modularitat. S’han dedicat esforços per superar aquestes limitacions i adaptar aquests principis perquè funcionin sobre sistemes vius, tot i que encara que amb un èxit relatiu. L’objectiu d’aquesta tesi és explorar críticament què és la Biologia Sintètica i quan lluny està de ser una veritable enginyeria. En aquesta tesi, primer presentem un article de revisió que explora i discuteix a fons aquest escenari. Després presentem dos treballs que han de contribuir a aquest ambiciós i difícil objectiu. En primer lloc, en el context de l’estandardització, adrecem la necessitat d’una millor caracterització de les parts genètiques oferint un exemple de marc teòric amb fonaments biològics que esta inspirat en teoria enzimològica clàssica. En segon lloc, i relacionat amb el principi de modularitat, oferim un marc teòric, aquest cop inspirat en la llei de Ohm de la teoria elèctrica, que descriu l’aparellament no intencionat de les carregues genètiques coexistents dins d’una cèl.lula hoste qualssevol degut al fet de compartir un conjunt comú limitat de recursos i maquinària cel•lular. Ambdós treballs contribueixen, per un cantó, a incrementar el nostre coneixement sobre els principis d’organització dels éssers vius, i per l’altre, a millorar com s’apliquen els principis d’enginyeria pel disseny de circuits sintètics. Finalment, aquests treballs emfatitzen la necessitat de trobar millors marcs teòrics o models recolzats experimentalment que haurien de permetre’ns fer un salt des de l’actual Biologia Sintètica ad hoc, farregosa i basada en assaig-error, a un tipus d’enginyeria ben establerta que pugui ser tan profitosa i eficient en el reialme dels éssers vius com ho són les altres enginyeries.

Spider silk is a biodegradable and biocompatible natural material that is stronger than steel and more elastic than nylon. These properties make spider silk a desirable material for many commercial products, ranging from textiles to biomedical materials. Due to spiders’ cannibalistic and territorial nature it is impossible to farm them to produce spider silk at a high enough yield to meet product demands. Therefore, a bioengineered synthetic process is necessary to produce spider silk. Synthetic spider silk has been produced in bacteria, goats, yeast, plants, mammalian cells and silkworms, but none of these processes provided a commercially viable yield or were able to express recombinant spider silk proteins (rSSps) that can mechanically imitate the natural spider silks. The overall goal of this research was to increase the yield and mechanical characteristics, e.g. strength and elasticity, to create a commercially viable spider silk. Three different hosts were used: E. coli, alfalfa and an insect cell line. Each host addresses issues with synthetic protein production in both the short-term and long-term scheme. Through this research yields were increased, while the mechanical properties of the synthetic silks were improved and groundwork for future research into the improvement of synthetic spider silk production were identified.

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.

[EN] Synthetic Biology is an emerging interdisciplinary field that aims to apply the engineering principles of modularity, abstraction and standardization to genetic engineering. The nascent branch of Synthetic Biology devoted to plants, Plant Synthetic Biology (PSB), offers new breeding possibilities for crops, potentially leading to enhanced resistance, higher yield, or increased nutritional quality. To this end, the molecular tools in the PSB toolbox need to be adapted accordingly, to become modular, standardized and more precise. Thus, the overall objective of this Thesis was to adapt, expand and refine DNA assembly tools for PSB to enable the incorporation of functional specifications to the description of standard genetic elements (phytobricks) and to facilitate the construction of increasingly complex and precise multigenic devices, including genome editing tools. The starting point of this Thesis was the modular DNA assembly method known as GoldenBraid (GB), based on type IIS restriction enzymes. To further optimize the GB construct-making process and to better catalog the phytobricks collection, a database and a set of software-tools were developed as described in Chapter 1. The final webbased software package, released as GB2.0, was made publicly available at www.gbcloning.upv.es. A detailed description of the functioning of GB2.0, exemplified with the building of a multigene construct for anthocyanin overproduction was also provided in Chapter 1. As the number and complexity of GB constructs increased, the next step forward consisted in the refinement of the standards with the incorporation of experimental information associated to each genetic element (described in Chapter 2). To this end, the GB package was reshaped into an improved version (GB3.0), which is a self-contained, fully traceable assembly system where the experimental data describing the functionality of each DNA element is displayed in the form of a standard datasheet. The utility of the technical specifications to anticipate the behavior of composite devices was exemplified with the combination of a chemical switch with a prototype of an anthocyanin overproduction module equivalent to the one described in Chapter 1, resulting in a dexamethasone-responsive anthocyanin device. Furthermore, Chapter 3 describes the adaptation and functional characterization of CRISPR/Cas9 genome engineering tools to the GB technology. The performance of the adapted tools for gene editing, transcriptional activation and repression was successfully validated by transient expression in N. benthamiana. Finally, Chapter 4 presents a practical implementation of GB technology for precision plant breeding. An intragenic construct comprising an intragenic selectable marker and a master regulator of the flavonoid biosynthesis was stably transformed in tomato resulting in fruits enhanced in flavonol content. All together, this Thesis shows the implementation of increasingly complex and precise genetic designs in plants using standard elements and modular tools following the principles of Synthetic Biology.
[ES] La Biología Sintética es un campo emergente de carácter interdisciplinar que se fundamenta en la aplicación de los principios ingenieriles de modularidad, abstracción y estandarización a la ingeniería genética. Una nueva vertiente de la Biología Sintética aplicada a las plantas, la Biología Sintética Vegetal (BSV), ofrece nuevas posibilidades de mejora de cultivos que podrían llevar a una mejora de la resistencia, a una mayor productividad, o a un aumento de la calidad nutricional. Sin embargo, para alcanzar este fin las herramientas moleculares disponibles en estos momentos para BSV deben ser adaptadas para convertirse en modulares, estándares y más precisas. Por ello se planteó como objetivo general de esta Tesis adaptar, expandir y refinar las herramientas de ensamblaje de DNA de la BSV para permitir la incorporación de especificaciones funcionales en la descripción de elementos genéticos estándar (fitobricks) y facilitar la construcción de estructuras multigénicas cada vez más complejas y precisas, incluyendo herramientas de editado genético. El punto de partida de esta Tesis fue el método de ensamblaje modular de ADN GoldenBraid (GB) basado en enzimas de restricción tipo IIS. Para optimizar el proceso de ensamblaje y catalogar la colección de fitobricks generados se desarrollaron una base de datos y un conjunto de herramientas software, tal y como se describe en el Capítulo 1. El paquete final de software se presentó en formato web como GB2.0, haciéndolo accesible al público a través de www.gbcloning.upv.es. El Capítulo 1 también proporciona una descripción detallada del funcionamiento de GB2.0 ejemplificando su uso con el ensamblaje de una construcción multigénica para la producción de antocianinas. Con el aumento en número y complejidad de las construcciones GB, el siguiente paso necesario fue el refinamiento de los estándar con la incorporación de la información experimental asociada a cada elemento genético (se describe en el Capítulo 2). Para este fin, el paquete de software de GB se reformuló en una nueva versión (GB3.0), un sistema de ensamblaje auto-contenido y completamente trazable en el que los datos experimentales que describen la funcionalidad de cada elemento genético se muestran en forma de una hoja de datos estándar. La utilidad de las especificaciones técnicas para anticipar el comportamiento de dispositivos biológicos compuestos se ejemplificó con la combinación de un interruptor químico y un prototipo de un módulo de sobreproducción de antocianinas equivalente al descrito en el Capítulo 1, resultando en un dispositivo de producción de antocianinas con respuesta a dexametasona. Además, en el Capítulo 3 se describe la adaptación a la tecnología GB de las herramientas de ingeniería genética CRISPR/Cas9, así como su caracterización funcional. La funcionalidad de estas herramientas para editado génico y activación y represión transcripcional se validó con el sistema de expresión transitoria en N.benthamiana. Finalmente, el Capítulo 4 presenta una implementación práctica del uso de la tecnología GB para hacer mejora vegetal de manera precisa. La transformación estable en tomate de una construcción intragénica que comprendía un marcador de selección intragénico y un regulador de la biosíntesis de flavonoides resultó en frutos con un mayor contenido de flavonoles. En conjunto, esta Tesis muestra la implementación de diseños genéticos cada vez más complejos y precisos en plantas utilizando elementos estándar y herramientas modulares siguiendo los principios de la Biología Sintética.
[CAT] La Biologia Sintètica és un camp emergent de caràcter interdisciplinar que es fonamenta amb l'aplicació a la enginyeria genètica dels principis de modularitat, abstracció i estandarització. Una nova vessant de la Biologia Sintètica aplicada a les plantes, la Biologia Sintètica Vegetal (BSV), ofereix noves possibilitats de millora de cultius que podrien portar a una millora de la resistència, a una major productivitat, o a un augment de la qualitat nutricional. Tanmateix, per poder arribar a este fi les eines moleculars disponibles en estos moments per a la BSV han d'adaptar-se per convertir-se en modulars, estàndards i més precises. Per això es plantejà com objectiu general d'aquesta Tesi adaptar, expandir i refinar les eines d'ensamblatge d'ADN de la BSV per permetre la incorporació d'especificacions funcionals en la descripció d'elements genètics estàndards (fitobricks) i facilitar la construcció d'estructures multigèniques cada vegada més complexes i precises, incloent eines d'edidat genètic. El punt de partida d'aquesta Tesi fou el mètode d'ensamblatge d'ADN modular GoldenBraid (GB) basat en enzims de restricció tipo IIS. Per optimitzar el proces d'ensamblatge i catalogar la col.lecció de fitobricks generats es desenvolupà una base de dades i un conjunt d'eines software, tal i com es descriu al Capítol 1. El paquet final de software es presentà en format web com GB2.0, fent-se accessible al públic mitjançant la pàgina web www.gbcloning.upv.es. El Capítol 1 també proporciona una descripció detallada del funcionament de GB2.0, exemplificant el seu ús amb l'ensamblatge d'una construcció multigènica per a la producció d'antocians. Amb l'augment en nombre i complexitat de les construccions GB, el següent pas fou el refinament dels estàndards amb la incorporació de la informació experimental associada a cada element genètic (es descriu en el Capítol 2). Per a aquest fi, el paquet de software de GB es reformulà amb una nova versió anomenada GB3.0. Aquesta versió consisteix en un sistema d'ensamblatge auto-contingut i complemtament traçable on les dades experimentals que descriuen la funcionalitat de cada element genètic es mostren en forma de fulla de dades estàndard. La utilitat de les especificacions tècniques per anticipar el comportament de dispositius biològics compostos s'exemplificà amb la combinació de un interruptor químic i un prototip d'un mòdul de sobreproducció d'antocians equivalent al descrit al Capítol 1. Aquesta combinació va tindre com a resultat un dispositiu de producció d'antocians que respón a dexametasona. A més a més, al Capítol 3 es descriu l'adaptació a la tecnologia GB de les eines d'enginyeria genètica CRISPR/Cas9, així com la seua caracterització funcional. La funcionalitat d'aquestes eines per a l'editat gènic i activació i repressió transcripcional es validà amb el sistema d'expressió transitòria en N. benthamiana. Finalment, al Capítol 4 es presenta una implementació pràctica de l'ús de la tecnologia GB per fer millora vegetal de mode precís. La transformació estable en tomaca d'una construcció intragènica que comprén un marcador de selecció intragènic i un regulador de la biosíntesi de flavonoïdes resultà en plantes de tomaca amb un major contingut de flavonols en llur fruits. En conjunt, esta Tesi mostra la implementació de dissenys genètics cada vegada més complexos i precisos en plantes utilitzant elements estàndards i eines modulars seguint els principis de la Biologia Sintètica.
Vázquez Vilar, M. (2016). DESIGN OF GENETIC ELEMENTS AND SOFTWARE TOOLS FOR PLANT SYNTHETIC BIOLOGY [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/68483
TESIS
Premiado

This thesis is concerned with large-scale systems of Ordinary Differential Equations that model Biomolecular Reaction Networks (BRNs) in Systems and Synthetic Biology. It addresses the strategies of model reduction and decomposition used to overcome the challenges posed by the high dimension and stiffness typical of these models. A number of developments of these strategies are identified, and their implementation on various BRN models is demonstrated. The goal of model reduction is to construct a simplified ODE system to closely approximate a large-scale system. The error estimation problem seeks to quantify the approximation error; this is an example of the trajectory comparison problem. The first part of this thesis applies semi-definite programming (SDP) and dissipativity theory to this problem, producing a single a priori upper bound on the difference between two models in the presence of parameter uncertainty and for a range of initial conditions, for which exhaustive simulation is impractical. The second part of this thesis is concerned with the BRN decomposition problem of expressing a network as an interconnection of subnetworks. A novel framework, called layered decomposition, is introduced and compared with established modular techniques. Fundamental properties of layered decompositions are investigated, providing basic criteria for choosing an appropriate layered decomposition. Further aspects of the layering framework are considered: we illustrate the relationship between decomposition and scale separation by constructing singularly perturbed BRN models using layered decomposition; and we reveal the inter-layer signal propagation structure by decomposing the steady state response to parametric perturbations. Finally, we consider the large-scale SDP problem, where large scale SDP techniques fail to certify a system’s dissipativity. We describe the framework of Structured Storage Functions (SSF), defined where systems admit a cascaded decomposition, and demonstrate a significant resulting speed-up of large-scale dissipativity problems, with applications to the trajectory comparison technique discussed above.

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 116-127).
Synthetic biology is an emerging field, with a rapidly developing academic-industrial base and the promise of extensive product launches over the next few years. An intense debate over the risks and benefits of synthetic biology has developed even before commercialization. Nongovernmental organizations and official commissions have published over a dozen reports on the potential pitfalls and promise of synthetic biology, with widely varying analytic assumptions, assessment methods, definitions of values, and policy recommendations. How should governments go about developing regulatory policies to govern synthetic biology? This thesis begins by outlining the synthetic biology academic-industrial base, and then describes and critiques official and unofficial assessments of synthetic biology risks and the regulatory policies now in place to regulate risks. It differentiates among risks to security, safety and environment, and ethics, and finds that regulations in each of these areas suffer from significant deficits. Regulations are not well grounded on technical understanding of synthetic biology, lack methodologies for risk assessment of organisms without close natural counterparts, frame risk assessment as a technocratic process without substantial input from stakeholders, and emphasize physical risks to safety and security over non-physical threats to ethics and values. The thesis suggests that the US government and European Union modify existing regulations governing risks associated with synthetic biology and, more fundamentally, processes for developing such regulations to mitigate some of the deficits identified above.
by Pernilla C. Regårdh.
S.M.in Technology and Policy

Cyanobacteria are solar-powered cell factories that can be engineered to supply us with renewable fuels and chemicals. To do so robust and well-working biological parts and tools are necessary. Parts for controlling gene expression are of special importance in living systems, and specifically promoters are needed for enabling and simplifying rational design. Synthetic biology is an engineering science that incorporates principles such as decoupling, standardization and modularity to enable the design and construction of more advanced systems from simpler parts and the re-use of parts in new contexts. For these principles to work, cross-talk must be avoided and therefore orthogonal parts and systems are important as they are decoupled by definition. This work concerns the design and development of biological parts and tools that can enable synthetic biology in cyanobacteria. This encompasses parts necessary for the development of other systems, such as vectors and translational elements, but with a focus on transcriptional regulation. First, to enable the development and characterization of promoters in different cyanobacterial chassis, a broad-host-range BioBrick plasmid, pPMQAK1, was constructed and confirmed to function in several cyanobacterial strains. Then, ribosome binding sites, protease degradation tags and constitutive, orthogonal promoters were characterized in the model strain Synechocystis PCC 6803. These tools were then used to design LacI-regulated promoter libraries for studying DNA-looping and the behaviour of LacI-mediated loops in Synechocystis. Ultimately, this lead to the design of completely repressed LacI-regulated promoters that could be used for e.g. cyanobacterial genetic switches, and was used to design a destabilized version of the repressed promoter that could be induced to higher levels. Further, this promoter was used to implement an orthogonal transcriptional system based on T7 RNAP that was shown to drive different levels of T7 promoter transcription depending on regulation. Also, Gal4-repressed promoters for bacteria were engineered and examined in Escherichia coli as an initial step towards transferring them to cyanobacteria. Attempts were also made to implement a light-regulated one-component transcription factor based on Gal4. This work provides a background for engineering transcription and provides suggestions for how to develop the parts further.

In metabolic engineering of prokaryotes, combinatorial approaches have developed recently that induce random genetic perturbations to achieve a desired cell phenotype. A screening strategy follows the randomized genetic manipulations to select strain(s) with the more optimal phenotype of interest. This screening strategy is often divided into two categories: (i) a growth competition assay and (ii) selection by high-throughput screening. The growth competition assay involves culturing strains together. The strain with the highest growth rate will ultimately dominate the culture. This strategy is ideal for selecting strain with cellular fitness (e.g., solvent tolerance), but it does not work for selecting a strain that can over-produce a product (e.g., an amino acid). For the case of selecting highly productive phenotypes, high-throughput screening is used. This method analyzes strains individually and is costly and time-consuming. In this research, a synthetic genetic circuit was developed to select highly productive phenotypes using a growth competition assay rather than high-throughput screening. This novel system is called Feed-back Inhibition of Transcription for Growth Selection (FITSelect), and it uses a natural feedback inhibition mechanism in the L-arginine production pathway to select strains (transformed with a random genomic library) that can over-produce L-arginine in E. coli DH10B. With FITSelect, the cell can thrive in the growth competition assay when L-arginine is over-produced (i.e., growth is tied to L-arginine production). Cell death or reduced growth results if L-arginine is not over-produced by the cell. This system was created by including an L-arginine concentration responsive argF promoter to control a ccdB cell death gene in the FITSelect system. The effects of ccdB were modulated by the antidote ccdA gene under control of an L-tryptophan responsive trp promoter. Several insights and construction strategies were required to build a system that ties the growth rate of the cell to L-arginine concentrations.
Master of Science

The goal of Synthetic Biology is to engineer systems from biological parts. One class of systems are those whose purpose is to process information. My work seeks to build transcription-based devices for use in combinational digital logic. Preliminary characterization experiments show that existing devices fall short of desired device behavior. I propose to develop a novel implementation of transcription-based logic by designing synthetic transcription factors from well-characterized DNA binding and dimerization domains. Initial modeling work serves to inform design of these devices.
Poster presented at the 2005 ICSB meeting, held at Harvard Medical School in Boston, MA.

Bacteria use Two Component Systems (TCS) to sense and respond to changes in their external environment. TCS are used to navigate to nutrients or away from toxins (chemotaxis) and to adapt to changes in osmolarity (osomosensing). TCS are composed of a histidine protein kinase (HPK) which trans-autophosphorylates in response to environmental change, transferring the phosphoryl group to a cognate response regulator (RR). Phosphorylated RRs modulate an output response such as protein-protein interaction for chemotaxis, and transcription for osmosensing. RRs are composed of a conserved amino terminal REC domain, and where present a variable effector domain. CheY, the chemotaxis RR, contains only a REC domain, whilst OmpR, the osmosensing RR, also contains a DNA binding effector domain. Recently, TCS have been used in synthetic biology applications due to their modularity and conserved signalling mechanism. This thesis aimed to investigate whether it was possible to design a synthetic TCS composed of fused chemotaxis and osmosensing components. Synthetic RRs were designed, fusing the highly conserved REC domains of CheY and OmpR upstream of the OmpR effector domain. REC domains were fused across the α₄-β₅-α₅ region, a region which transmits REC domain phosphorylation into effector domain activation. Synthetic RRs were designed to undergo phosphotransfer to their fused REC domains from the chemotaxis HPK, CheA, activate the attached OmpR effector domain and bind promoter DNA. Four chimeric RRs were created, although only three were structurally viable; F2, F3 and F4. Each fusion bound CheA, and F3 and F4 bound CheA with a significantly higher affinity than CheY. The chimeric RRs could all be phosphorylated byCheA-P; F4 and F3 were phosphorylated to wild-type levels. DNA binding affinitywas investigated with fluorescence anisotropy, hosphorylated and unphosphorylated F3 could not bind promoter DNA. F2 bound promoter DNA regardless of phosphorylation state. These data indicate that phosphorylation of the F2 REC domain does not lead to activation of the effector domain. F2 is likely to be constitutively active suggesting a previously unknown role for OmpR α₅ as a mediator of effector domain activation. Furthermore, using a simple fusion approach to design RRs is not a viable method to create a synthetic TCS with a controllable output.

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 84-90).
On the surface, the emerging field of synthetic biology looks highly similar to that of genetic engineering. However, the two fields are based upon divergent underlying logic structures. Whereas genetic engineering affects change through localized modifications of existing organisms, synthetic biology attempts to fuse independent component parts to create wholly novel applications. While legacy regulatory systems were adequate for monitoring biosafety in the early days of the emerging field, as synthetic biology advances, the fundamental differences in its logic structure are creating fissures in the oversight system. A continued reliance on increasingly incompatible mechanisms squanders the limited present opportunity for proactive risk management, and generates increasing potential for significant future risk exposure in the field. This thesis will describe the current state of domestic and international oversight systems relevant to synthetic biology, and characterize their limits and vulnerabilities. It will argue that the current approach of relying on prescriptive, sequence-based controls creates growing gaps in oversight for a field moving toward amalgam organisms, and that the soft methods intended to bridge these gaps, predominantly in the form of institutional biosafety committees, are instead points of additional significant vulnerability. This thesis will also illustrate the challenges that have arisen because of these gaps, both in theory and in practice, through an examination of the International Genetically Engineered Machine competition (iGEM). iGEM, a university-level synthetic biology contest, first served as a valuable case study for illuminating challenges associated with the current system. Later, the Massachusetts Institute of Technology's Program on Emerging Technologies collaborated with iGEM to establish the competition as a policy testbed for demonstrating innovative approaches to biosafety oversight. This thesis will conclude by proposing recommendations for improving biosafety oversight based on lessons learned from the iGEM testbed. First, it is not enough for scientists to recognize that risks exist in their field; as the first line of defense in risk management, they must also be able to identify, understand, and engage with the risks inherent in their own work. Second, in light of the limits imposed on policy revisions due to political gridlock, it is necessary to understand what can be realistically accomplished within the existing federal system, and what instead needs to be achieved outside it. Here, a fuller, more invigorated approach to engagement support is coupled with a mix of improved, adaptive interpretations of the existing oversight system.
by Julie H. McNamara.
S.M. in Technology and Policy

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 99-101).
Synthetic biology is an emerging technology field within the realm of genetic engineering, differing from traditional genetic engineering in that it focuses on the modularization of genetic parts and the creation of de novo organisms. Significant concerns over safety have been expressed. This research explores traditional engineering and biotechnology practices for overarching principles of design, testing and demonstration that address safety concerns. The information is used to assess the current state of design, testing and demonstration in current synthetic biology projects addressing safety. Component and system design literature provide an engineering backbone of safety systems however, biological attributes such as mutation, growth, and multiplication create safety gaps, where biological engineering practices are needed. These principles are organized into categories of design and testing, and testing and demonstration to gain greater insight on where gaps in the literature might lie. Retrospective cases of traditional engineering and current cases of biotechnologies provide external validation and further illustrate which practices address which design, testing and demonstration needs. While most of the traditional engineering cases addressed safety through design and testing, when they were faced with questions of safety, they presented specific efforts to gain public confidence. The pro-biotics case was different in that the safety concerns came from the scientific community since history is being used as the convincing demonstration of safety. The three synthetic biology research projects cross the divide between traditional engineering and biotechnologies, but theses efforts are firmly in the area of design and testing. These efforts begin to show the tradeoff between implementing safety and faster technical results. Strategies for further research are explored.
by Neelima Yeddanapudi.
S.M.in Technology and Policy

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2014.
260
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 52-64).
The emerging field of synthetic biology is developing rapidly and promises diverse applications. Many anticipated applications, particularly those involving release of engineered microbes into the environment or human bodies, have potential environmental and health implications. These implications, which present design challenges to engineers, stem from organisms' potential for competitiveness with natural strains upon entering an environment, their tendency to evolve new characteristics after leaving the lab, and their propensity to exchange genetic material with other organisms they encounter. The field's rapid evolution and the substantial uncertainties in the technology and relevant sciences present challenges to regulators seeking to ensure health and environmental wellbeing. Regulations exhibiting planned adaptation are especially suited to such contexts of uncertainty. However, the synthetic biology applications first nearing commercialization are regulated by the EPA under the Toxic Substances Control Act (TSCA), which was not written to be adaptive. EPA regulators appear to be using TSCA adaptively even though it was not written this way. An examination of characteristics of planned adaptation using the EPA program for ambient air standards as a case study suggests more that the regulators may be able to do to regulate synthetic biology effectively by using TSCA adaptively. Due to statutory language and court history, TSCA is essentially incapable of imposing restrictions or setting standards. Examination of the emerging algal biofuels industry as a case study suggests that concepts of industry-favored regulation may be useful to the EPA for fashioning strong regulations that would promote real health and environmental wellbeing.
by Shlomiya Lightfoot.
S.M. in Technology and Policy

The objective of the field of Synthetic Biology is to implement novel functionalities in a biological context or redesign existing biological systems. To achieve this, it employs tried and tested engineering principles, such as standardisation and the design-build-test cycle. A crucial part of this process is the convergence of modelling and experiment. The aim of this thesis is to improve the design principles employed by Synthetic Biology in the context of Gene Regulatory Networks (GRNs). Small Ribonucleic Acids (sRNAs), in particular, are focussed on as a mechanism for post-transcriptional expression regulation, as they present great potential as a tool to be harnessed in GRNs. Modelling sRNA regulation and its interaction with its associated chaperone Host-Factor of Bacteriophage Qβ (Hfq) is investigated. Inclusion of Hfq is found to be necessary in stochastic models, but not in deterministic models. Secondly, feedback is core to the thesis, as it presents a means to scale-up designed systems. A linear design framework for GRNs is then presented, focussing on Transcription Factor (TF) interactions. Such frameworks are powerful as they facilitate the design of feedback. The framework supplies a block diagram methodology for visualisation and analysis of the designed circuit. In this context, phase lead and lag controllers, well-known in the context of Control Engineering, are presented as genetic motifs. A design example, employing the genetic phase lag controller, is then presented, demonstrating how the developed framework can be used to design a genetic circuit. The framework is then extended to include sRNA regulation. Four GRNs, demonstrating the simplest forms of genetic feedback, are then modelled and implemented. The feedback occurs at three different levels: autoregulation, through an sRNA and through another TF. The models of these GRNs are inspired by the implemented biological topologies, focussing on steady state behaviour and various setups. Both deterministic and stochastic models are studied. Dynamic responses of the circuits are also briefly compared. Data is presented, showing good qualitative agreement between models and experiment. Both culture level data and cell population data is presented. The latter of these is particularly useful as the moments of the distributions can be calculated and compared to results from stochastic simulation. The fit of a deterministic model to data is attempted, which results in a suggested extension of the model. The conclusion summarises the thesis, stating that modelling and experiment are in good qualitative agreement. The required next step is to be able to predict behaviour quantitatively.

Recientemente, el uso de técnicas de manipulación genética ha abierto la puerta a la obtención de microorganismos con fenotipos mejorados, lo que a su vez ha llevado a unas mejoras significativas en la síntesis de algunos productos bioquímicos. Sin embargo, la mutación y selección de estos nuevos organismos se ha llevado a cabo, en la mayoría de casos, por ensayo y error. Es de esperar que estos procesos puedan ser mejorados si se usan principios de diseño cuantitativos para guiar la búsqueda hacia el perfil enzimático ideal. Esta tesis está dedicada al desarrollo de un conjunto de herramientas de optimización avanzadas para asesorar en problemas de ingeniería metabólica y otras cuestiones emergentes en biología de sistemas. Concretamente, nos centramos en problemas en qué se modelan las redes metabólicas usando expresiones cinéticas. La utilidad de los algoritmos desarrollados para resolver tales problemas es demostrada por medio de varios casos de estudio.
In recent years, the use of genetic manipulation techniques has opened the door for obtaining microorganisms with enhanced phenotypes, which has in turn led to significant improvements in the synthesis of certain biochemical products. However, mutation and selection of these new organisms has been performed, in most cases, in a trial-and-error basis. It is expected that these processes could be further improved if quantitative design principles were used to guide the search towards the ideal enzymatic profiles. This thesis is devoted to developing a set of advanced global optimization tools to assess metabolic engineering problems and other questions arising in systems biology. In particular, we focus on problems where metabolic networks are modeled making use of kinetic expressions. The usefulness of the algorithms developed to solve such problems is demonstrated by means of several case studies.

La biología sintética se define como la ingeniería de la biología: el (re)diseño y construcción de nuevas partes, dispositivos y sistemas biológicos para realizar nuevas funciones con fines útiles, que se basan en principios elucidados de la biología y la ingeniería. Para facilitar la construcción rápida, reproducible y predecible de estos sistemas biológicos a partir de conjuntos de componentes es necesario desarrollar nuevos métodos y herramientas. La tesis plantea la optimización multiobjetivo como el marco adecuado para tratar los problemas comunes que surgen en el diseño racional y el ajuste óptimo de los circuitos genéticos sintéticos. Utilizando un enfoque clásico de ingeniería de sistemas, la tesis se centra principalmente en: i) el modelado de circuitos genéticos sintéticos basado en los primeros principios, ii) la estimación de parámetros de modelos a partir de datos experimentales y iii) el ajuste basado en modelos para lograr el desempeño deseado de los circuitos. Se han utilizado dos circuitos genéticos sintéticos de diferente naturaleza y con diferentes objetivos y problemas: un circuito de realimentación de tipo 1 incoherente (I1-FFL) que exhibe la importante propiedad biológica de adaptación, y un circuito de detección de quorum sensing y realimentación (QS/Fb) que comprende dos bucles de realimentación entrelazados -uno intracelular y uno basado en la comunicación de célula a célula- diseñado para regular el nivel medio de expresión de una proteína de interés mientras se minimiza su varianza a través de la población de células. Ambos circuitos han sido analizados in silico e implementados in vivo. En ambos casos, se han desarrollado modelos de estos circuitos basado en primeros principios. Se presta especial atención a ilustrar cómo obtener modelos de orden reducido susceptibles de estimación de parámetros, pero manteniendo el significado biológico. La estimación de los parámetros del modelo a partir de los datos experimentales se considera en diferentes escenarios, tanto utilizando modelos determinísticos como estocásticos. Para el circuito I1-FFL se consideran modelos determinísticos. Aquí, la tesis plantea la utilización de modelos locales utilizando la optimización multiobjetivo para realizar la estimación de parámetros del modelo bajo escenarios con estructura de modelo incompleta. Para el circuito QS/Fb, una estructura controlada por realimentación, el problema tratado es la falta de excitabilidad de las señales. La tesis propone una metodología de estimación en dos etapas utilizando modelos estocásticos. La metodología permite utilizar datos de curso temporal promediados de la población y mediciones de distribución en estado estacionario para una sola célula. El ajuste de circuitos basado en modelos para lograr un desempeño deseado también se aborda mediante la optimización multiobjetivo. Para el circuito QS/Fb se realiza un análisis estocástico completo. La tesis aborda cómo tener en cuenta correctamente tanto el ruido intrínseco como el extrínseco, las dos principales fuentes de ruido en los circuitos genéticos. Se analiza el equilibrio entre ambas fuentes de ruido y el papel que desempeñan en el bucle de realimentación intracelular, y en la realimentación extracelular de toda la población. La principal conclusión es que la compleja interacción entre ambos canales de realimentación obliga al uso de la optimización multiobjetivo para el adecuado ajuste del circuito. En esta tesis además del uso adecuado de herramientas de optimización multiobjetivo, la principal preocupación es cómo derivar directrices para el ajuste in silico de parámetros de circuitos que puedan aplicarse de forma realista in vivo en un laboratorio estándar. Como alternativa al análisis de sensibilidad de parámetros clásico, la tesis propone el uso de técnicas de clustering a lo largo de los frentes de Pareto, relacionando el compr
La biologia sintètica es defineix com l'enginyeria de la biologia: el (re) disseny i construcció de noves parts, dispositius i sistemes biològics per a realitzar noves funcions útils que es basen a principis elucidats de la biologia i l'enginyeria. Per facilitar la construcció ràpida, reproduïble i predictible de aquests sistemes biològics a partir de conjunts de components és necessari desenvolupar nous mètodes i eines. La tesi planteja la optimització multiobjectiu com el marc adequat per a tractar els problemes comuns que apareixen en el disseny racional i l' ajust òptim dels circuits genètics sintètics. Utilitzant un enfocament clàssic d'enginyeria de sistemes, la tesi es centra principalment en: i) el modelatge de circuits genètics sintètics basat en primers principis, ii) l' estimació de paràmetres de models a partir de dades experimentals i iii) l' ajust basat en models per aconseguir el rendiment desitjat dels circuits. S'han utilitzat dos circuits genètics sintètics de diferent naturalesa i amb diferents objectius i problemes: un circuit de prealimentació de tipus 1 incoherent (I1-FFL) que exhibeix la important propietat biològica d'adaptació, i un circuit de quorum sensing i realimentació (QS/Fb) que comprèn dos bucles de realimentació entrellaçats -un intracel·lular i un basat en la comunicació de cèl·lula a cèl·lula- dis-senyat per regular el nivell mitjà d'expressió normal d'una proteïna d'interès mentre es minimitza la seua variació al llarg de la població de cèl·lules. Els dos circuits han estat analitzats in silico i implementats in vivo. En tots dos casos, s'han desenvolupat models basats en primers principis d'aquests circuits. Després es presta especial atenció a delinear com obtenir models d'ordre reduït susceptibles de estimació de paràmetres, però mantenint el significat biològic. L' estimació dels paràmetres del model a partir de les dades experimentals es considera en diferents escenaris, tant utilitzant models determinístics com estocàstics. Per al circuit I1-FFL es consideren models determinístics. La tesi planteja la utilització de models locals utilitzant la optimització multiobjectiu per realitzar l'estimació de parametres del model sota escenaris amb estructura de model incompleta (dinàmica no modelada). Per al circuit de QS/Fb, una estructura controlada per realimentació, el problema tractat és la manca d'excitabilitat dels senyals. La tesi proposa una metodologia de estimació en dues etapes utilitzant models estocàstics. La metodologia permet utilitzar dades de curs temporal promediats de la població i mesures de distribució en estat estacionari d'una sola una cèl·lula. L' ajust de circuits basat en models per aconseguir el rendiment desitjat dels circuits també s' aborda mitjançant la optimització multiobjectiu. Per al circuit QS/Fb, es fa un anàlisi estocàstic complet. La tesi aborda com tenir en compte correctament tant el soroll intrínsec com l' extrínsec, les dues principals fonts de soroll en els circuits genètics sintètics. S' analitza l'equilibri entre dues fonts de soroll i el paper que exerceixen en el bucle de realimentació intracel·lular, les i en la realimentació extracel·lular de tota la població. La principal conclusió es que la complexa interacció entre els dos canals de realimentació fa necessari l' ús de la optimització multiobjectiu per al adequat ajust del circuit. En aquesta tesi, a més de l'ús adequat d'eines d'optimització multiobjectiu, la principal preocupació és com derivar directives per al ajust in silico de paràmetres de circuits que puguin aplicar-se de forma realista en viu en un laboratori estàndard. Així, com a alternativa a l'anàlisi de sensibilitat de paràmetres clàssic, la tesi proposa l'ús de l' tècniques de l'agrupació al llarg dels fronts de Pareto, relacionant el compromís de dessempeny amb les regions en l'espai d'paràmetres.
Synthetic biology is defined as the engineering of biology: the deliberate (re)design and construction of novel biological and biologically based parts, devices and systems to perform new functions for useful purposes, that draws on principles elucidated from biology and engineering. Methods and tools are needed to facilitate fast, reproducible and predictable construction of biological systems from sets of biological components. This thesis raises multi-objective optimization as the proper framework to deal with common problems arising in rational design and optimal tuning of synthetic gene circuits. Using a classical systems engineering approach, the thesis mainly addresses: i) synthetic gene circuit modeling based on first principles, ii) model parameters estimation from experimental data and iii) model-based tuning to achieve desired circuit performance. Two gene synthetic circuits of different nature and with different goals and inherent problems have been used throughout the thesis: an Incoherent type 1 feedforward circuit (I1-FFL) that exhibits the important biological property of adaptation, and a Quorum sensing/Feedback circuit (QS/Fb) comprising two intertwined feedback loops -an intracellular one and a cell-to-cell communication-based one-- designed to regulate the mean expression level of a protein of interest while minimizing its variance across the population of cells. Both circuits have been analyzed in silico and implemented in vivo. In both cases, circuit modeling based on first principles has been carried out. Then, special attention is paid to illustrate how to obtain reduced order models amenable for parameters estimation yet keeping biological significance. Model parameters estimation from experimental data is considered in different scenarios, both using deterministic and stochastic models. For the I1-FFL circuit, deterministic models are considered. In this case, the thesis raises ensemble modeling using multi-objective optimization to perform model parameters estimation under scenarios with incomplete model structure (unmodeled dynamics). For the QS/Fb gene circuit, a feedback controlled structure, the lack of excitability of the signals is the problem addressed. The thesis proposes a two-stage estimation methodology using stochastic models. The methodology allows using population averaged time-course data and steady state distribution measurements at the single-cell level. Model-based circuit tuning to achieve desired circuit performance is also addressed using multi-objective optimization. First, for the QS/Fb feedback control circuit, a complete stochastic analysis is performed. Here, the thesis addresses how to correctly take into account both intrinsic and extrinsic noise, the two main sources of noise in gene synthetic circuits. The trade-off between both sources of noise, and the role played by in the intracellular single-cell feedback loop and the extracellular population-wide feedback is analyzed. The main conclusion being that the complex interplay between both feedback channels compel the use of multi-objective optimization for proper tuning of the circuit to achieve desired performance. Thus, the thesis wraps up all the previous results and uses them to address circuit tuning for desired performance. Here, besides the proper use of multi-objective optimization tools, the main concern is how to derive guidelines for circuit parameters tuning in silico that can realistically be applied in vivo in a standard laboratory. Thus, as an alternative to classical parameters sensitivity analysis, the thesis proposes the use of clustering techniques along the optimal Pareto fronts relating the performance trade-offs with regions in the circuits parameters space.
This work has been partially supported by the Spanish Government (CICYT DPI2014- 55276-C5-1) and the European Union (FEDER). The author was recipient of the grant Formación de Personal Investigador by the Universitat Politècnica de València, subprogram 1 (FPI/2013-3242). She was also recipient of the competitive grants for pre-doctoral stays Erasmus Student Placement-European Programme 2015, and FPI Mobility program 2016 of the Universitat Politècnica de València. She also received the competitive grant for a pre-doctoral stay Becas de movilidad para Jóvenes Profesores e Investigadores 2016, Programa de Becas Iberoamérica of the Santander Bank.
Boada Acosta, YF. (2018). A systems engineering approach to model, tune and test synthetic gene circuits [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/112725
TESIS

Application of bioengineering technologies for enhanced biological hydrogen production is a promising approach that may play a vital role in sustainable energy. Due to the ability of several naturally occurring microorganisms to generate hydrogen through varying metabolic processes, biological hydrogen has become an attractive alternative energy and fuel source. One area of particular interest is the production of biological hydrogen in organically-rich engineered systems, such as those associated with waste treatment. Despite the potential for high energy yields, hydrogen yields generated by bacteria in waste systems are often limited due to a focus on microbial utilization of organic material towards cellular growth rather than production of biogas. To address this concern and to improve upon current technological applications, metabolic engineering approaches may be applied to known hydrogen producing organisms. However, to successfully modify metabolic pathways, full understanding of metabolic networks involved in expression of microbial traits in hydrogen producing organisms is necessary. Because microbial communities associated with hydrogen production are capable of exhibiting a number of phenotypes, attempts to apply metabolic engineering concepts have been restricted due to limited information regarding complex metabolic processes and regulatory networks involved in expression of microbial traits associated with biohydrogen production. To bridge this gap, this dissertation focuses on identification of phenotype-related biochemical processes within sets of phenotype-expressing organisms. Specifically, through co-development and application of evolutionary genome-scale phenotype-centric comparative network analysis tools, metabolic and cellular components related to three phenotypes (i.e., dark fermentative, hydrogen production and acid tolerance) were identified. The computational tools employed for the systematic elucidation of key phenotype-related genes and subsystems consisted of two complementary methods. The first method, the Network Instance-Based Biased Subgraph Search (NIBBS) algorithm, identified phenotype-related metabolic genes and subsystems through comparative analysis of multiple genome-scale metabolic networks. The second method was the multiple alignments of metabolic pathways for identification of conserved metabolic sub-systems in small sets of phenotype-expressing microorganisms. For both methodologies, key metabolic genes and sub-systems that are likely to be related to hydrogen production and acid-tolerance were identified and hypotheses regarding their role in phenotype expression were generated. In addition, analysis of hydrogen producing enzymes generated by NIBBS revealed the potential interplay, or cross-talk, between metabolic pathways. To identify phenotype-related subnetworks, three complementary approaches were applied to individual, and sets of phenotype-expressing microorganisms. In the first method, the Dense ENriched Subgraph Enumeration (DENSE) algorithm, partial "prior knowledge" about the proteins involved in phenotype-related processes are utilized to identify dense, enriched sets of known phenotype-related proteins in Clostridium acetobutylicum. The second approach utilized a bi-clustering algorithm to identify phenotype-related functional association modules associated with metabolic controls of phenotype-related pathways. Last, through comparison of hundreds of genome-scale networks of functionally associated proteins, the á, â-motifs approach, was applied to identify phenotype-related subsystems. Application of methodologies for identification of subnetworks resulted in detection of regulatory proteins, transporters, and signaling proteins predicted to be related to phenotype-expression. Through analysis of protein interactions, clues to the functional roles and associations of previously uncharacterized proteins were identified (DENSE) and hypotheses regarding potentially important acid-tolerant mechanisms were generated (á, â-motifs). Similar to the NIBBS algorithm, analysis of functional modules predicted by the bi-clustering algorithm suggest cross-talk is occurring between pathways associated with hydrogen production. The ability of these phenotype-centric comparative network analysis tools to identify both known and potentially new biochemical process is important for providing further understanding and insights into metabolic networks and system controls involved in the expression of microbial traits. In particular, identification of phenotype-related metabolic components through a systems approach provides the underlying foundation for the development of improved bioengineering technologies and experimental design for enhanced biological hydrogen production.

Enhancing productivity in bioprocesses, especially for biofuel production, is crucial for achieving an environmentally and economically sustainable biotechnology industry.Metabolic channelling occurs in nature when the intermediate between two consecutive enzymes in a pathway is directed from the first enzyme to the second avoiding diffusion in the cytosol. This would be very advantageous in bioprocesses as it would increase efficiency of a particular pathway, reducing side products and protecting the cells from potential toxic intermediates. In recent years different strategies for emulating channelling effect wereproposed and used with very promising results. Clustering of enzymes seems to be the simplest way to create metabolic channelling. In this master thesis, four different strategies to co-localize enzymes in clusters are compared. The metabolic pathway chosen as a model was ethanol production by pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh). Chimeric proteins were genetically engineered and transformed in E. coli creating different strains. Ethanol production by the different strains was measured to compare production efficiency. Cell growth and protein expression were used for further understanding of the results. Strengths and weaknesses of each strategy and proposals for further improvement were discussed.

I lantibiotici sono molecole peptidiche prodotte da un gran numero di batteri Gram-positivi, posseggono attività antibatterica contro un ampio spettro di germi, e rappresentano una potenziale soluzione alla crescente problematica dei patogeni multi-resistenti. La loro attività consiste nel legame alla membrana del bersaglio, che viene quindi destabilizzata mediante l’induzione di pori che determinano la morte del patogeno. Tipicamente i lantibiotici sono formati da un “leader-peptide” e da un “core-peptide”. Il primo è necessario per il riconoscimento della molecola da parte di enzimi che effettuano modifiche post-traduzionali del secondo - che sarà la regione con attività battericida una volta scissa dal “leader-peptide”. Le modifiche post-traduzionali anticipate determinano il contenuto di amminoacidi lantionina (Lan) e metil-lantionina (MeLan), caratterizzati dalla presenza di ponti-tioetere che conferiscono maggior resistenza contro le proteasi, e permettono di aggirare la principale limitazione all’uso dei peptidi in ambito terapeutico. La nisina è il lantibiotico più studiato e caratterizzato, prodotto dal batterio L. lactis che è stato utilizzato per oltre venti anni nell’industria alimentare. La nisina è un peptide lungo 34 amminoacidi, che contiene anelli di lantionina e metil-lantionina, introdotti dall’azione degli enzimi nisB e nisC, mentre il taglio del “leader-peptide” è svolto dall’enzima nisP. Questo elaborato affronta l’ingegnerizzazione della sintesi e della modifica di lantibiotici nel batterio E.coli. In particolare si affronta l’implementazione dell’espressione eterologa in E.coli del lantibiotico cinnamicina, prodotto in natura dal batterio Streptomyces cinnamoneus. Questo particolare lantibiotico, lungo diciannove amminoacidi dopo il taglio del leader, subisce modifiche da parte dell’enzima CinM, responsabile dell’introduzione degli aminoacidi Lan e MeLan, dell’enzima CinX responsabile dell’idrossilazione dell’acido aspartico (Asp), e infine dell’enzima cinorf7 deputato all’introduzione del ponte di lisinoalanina (Lal). Una volta confermata l’attività della cinnamicina e di conseguenza quella dell’enzima CinM, si è deciso di tentare la modifica della nisina da parte di CinM. A tal proposito è stato necessario progettare un gene sintetico che codifica nisina con un leader chimerico, formato cioè dalla fusione del leader della cinnamicina e del leader della nisina. Il prodotto finale, dopo il taglio del leader da parte di nisP, è una nisina completamente modificata. Questo risultato ne permette però la modifica utilizzando un solo enzima invece di due, riducendo il carico metabolico sul batterio che la produce, e inoltre apre la strada all’utilizzo di CinM per la modifica di altri lantibiotici seguendo lo stesso approccio, nonché all’introduzione del ponte di lisinoalanina, in quanto l’enzima cinorf7 necessita della presenza di CinM per svolgere la sua funzione.

In silico analysis of biological systems represents a valuable alternative and complementary approach to experimental research. Computational methodologies, indeed, allow to mimic some conditions of cellular processes that might be difficult to dissect by exploiting traditional laboratory techniques, therefore potentially achieving a thorough comprehension of the molecular mechanisms that rule the functioning of cells and organisms. In spite of the benefits that it can bring about in biology, the computational approach still has two main limitations: first, there is often a lack of adequate knowledge on the biological system of interest, which prevents the creation of a proper mathematical model able to produce faithful and quantitative predictions; second, the analysis of the model can require a massive number of simulations and calculations, which are computationally burdensome. The goal of the present thesis is to develop novel computational methodologies to efficiently tackle these two issues, at multiple scales of biological complexity (from single molecular structures to networks of biochemical reactions). The inference of the missing data — related to the three-dimensional structures of proteins, the number and type of chemical species and their mutual interactions, the kinetic parameters — is performed by means of novel methods based on Evolutionary Computation and Swarm Intelligence techniques. General purpose GPU computing has been adopted to reduce the computational time, achieving a relevant speedup with respect to the sequential execution of the same algorithms. The results presented in this thesis show that these novel evolutionary-based and GPU-accelerated methodologies are indeed feasible and advantageous from both the points of view of inference quality and computational performances.

Clostridium thermocellum is a thermophilic anaerobe that is capable of producing ethanol directly from lignocellulosic compounds, however this organism suffers from low ethanol tolerance and low ethanol yields. In vivo mathematical modeling studies based on steady state traditional metabolic flux analysis, metabolic control analysis, transient and steady states’ flux spectrum analysis (FSA) were conducted on C. thermocellum’s central metabolism. The models were developed in Matrix Laboratory software ( MATLAB® (The Language of Technical Computing), R2008b, Version 7.7.0.471)) based on known stoichiometry from C. thermocellum pathway and known physical constraints. Growth on cellobiose from Metabolic flux analysis (MFA) and Metabolic control analysis (MCA) of wild type (WT) and ethanol adapted (EA) cells showed that, at lower than optimum exogenous ethanol levels, ethanol to acetate (E/A) ratios increased by approximately 29% in WT cells and 7% in EA cells. Sensitivity analyses of the MFA and MCA models indicated that the effects of variability in experimental data on model predictions were minimal (within ±5% differences in predictions if the experimental data varied up to ±20%). Steady state FSA model predictions showed that, an optimum hydrogen flux of ~5mM/hr in the presence of pressure equal to or above 7MPa inhibits ferrodoxin hydrogenase which causes NAD re-oxidation in the system to increase ethanol yields to about 3.5 mol ethanol/mol cellobiose.

Les promesses de la médecine de précision dépendent de nouvelles solutions technologiques pour le diagnostic. Dans l’aire post-génomique, les approches de biologie synthétique pour la médecine apportent de nouvelles façon de sonder, monitorer et interfacer la physiopathologie humaine. Émergeant en tant que champ scientifique mature dont la transition clinique s’accélère, la biologie synthétique peut être utilisée pour appliquer des principes d’ingénierie afin de concevoir et construire des systèmes biologiques comprenant des spécifications cliniques. Une application particulièrement intéressante est de développer des outils diagnostiques polyvalents, programmables et intelligents étroitement interconnectés avec la thérapie. Cette thèse présente de nouveaux concepts et approches d’ingénierie pour concevoir des dispositifs biosynthétiques capable d’interfacer les maladies humaines dans des échantillons cliniques en exploitant du traitement de signal au niveau biomoléculaire, à la lumière d’un besoin croissant en termes de capacités et de robustesse. Cette thèse s’intéresse en premier lieu à l’ingénierie de circuits synthétiques de gènes, reposant sur les portes logiques à integrases, pour intégrer des opérations modulaires et programmables de biodétéction de biomarqueur associées à des algorithmes de décisions au sein de population de bactéries. Elle s’intéresse ensuite à des méthodologies systématiques dites bottom-up, pour programmer des protocellules synthétiques microscopiques, capables d’exécuter des opérations de biodétéction médicale et de biocomputation. Nous décrivons le développement de méthodes simples de fabrications microfluidique associées à des solutions pour implémenter des opérations Booléenne complexes en utilisant de circuits biochimiques synthétiques. Cette contribution s’élargit aussi à la caractérisation de l’espace de conception de protocellules à l’aide d’approches de design assisté par ordinateur, ainsi que à l’analyse de preuves mathématiques et biologiques pour l’utilisation de protocellules comme des dispositifs universels de calcul. L’articulation des principes biologiques fondamentaux avec les implications médicales concernant les dispositifs biosynthétiques développés dans ce travail, a été jusqu’à la validation clinique, et initie de nouveaux modèles pour le développement de diagnostics de nouvelle génération. Ce travail prévoit que la biologie synthétique est en train de préparer le future de la médecine, en supportant et accélérant le développement de diagnostics avec de nouvelles capacités, apportant un progrès biotechnologique direct depuis le laboratoire de biologie clinique jusqu’au patient
The promise for real precision medicine is contingent on novel technological solutions to diagnosis. In the post-genomic era, synthetic biology approaches to medicine provide new ways to probe, monitor and interface human pathophysiology. Emerging as a mature field increasingly transitioning to the clinics, synthetic biology can be used to apply engineering principles to design and build biological systems with clinical specifications. A particularly tantalizing application is to develop versatile, programmable and intelligent diagnostic devices closely interconnected with therapy. This thesis presents novel engineering concepts and approaches to design synthetic biological devices interfacing human diseases in clinical samples through biomolecular digital signal processing, in light of a need for dramatic improvements in capabilities and robustness. It addresses primarily the engineering of synthetic gene circuits through integrase based digital genetic amplifiers and logic gates, to integrate modular and programmable biosensing of biomarkers and diagnostic decision algorithms into bacteria. It then investigates systematic bottom-up methodologies to program microscale synthetic protocells performing medical biosensing and biocomputing operations. We demonstrate streamlined microfluidic fabrication methods and solutions to implement complex Boolean operation using integrated synthetic biochemical circuits. This contribution also extends to the characterization of protocell design space through novel computer assisted design frameworks, as well as the analysis of mathematical and biological evidence for universal protocellular biocomputing devices. The articulation of biological governing principles and medical implications for the synthetic devices developed in this work was further validated in the clinic, and initiates new models towards next-generation diagnostics. This work envisions that synthetic biology is preparing the future of medicine, supporting and speeding up the development of diagnostics with novel capabilities to bring direct improvement in biotechnologies from the clinical lab to the patient

The idea of Terraformation comes from the science fiction literature, where humans have the capability of changing a non-habitable planet to an Earth-like one. Nowadays, Nature is changing rapidly, the poles are melting, oceans biodiversity is vanishing due to plastic pollution, and the deserts are advancing at an unstoppable rhythm. This thesis is a first step towards the exploration of new strategies that could serve to change this pernicious tendencies jeopardising ecosystems. We suggest it may not only be possible by adding new species (alien species), but also engineering autochthonous microbial species that are already adapted to the environment. Such engineering may improve their functions and capabilities allowing them to recover the (host) ecosystem upon their re-introduction. These new functionalities should make the microbes be able to induce a bottom-up change in the ecosystem: from the micro-scale (microenvironment) to the macro-scale (even changing the composition of species in the entire the ecosystem). To make this possible, the so-called Terraformation strategy needs to fuse many different fields of knowledge. The focus of this thesis relies on studying the outcome of the interactions between species and their environment (Ecology), on making the desired modifications by means of genetic engineering of the wild-type species (Synthetic Biology), and on monitoring the evaluation of the current ecosystems’ states, testing the possible changes, and predicting the future development of possible interventions (Dynamical Systems). In order to do so, in this thesis, we have gathered the tools provided by these different fields of knowledge. The methodology is based on loops between observation, designing, and prediction. For example, if there is a lack of humidity in semiarid ecosystems, we then propose to engineer e.g. Nostoc sp. to enhace its capability to produce extracellular matrix (increasing water retention). With this framework, we perform a model to understand the different possible dynamics, by means of dynamical equations to evaluate e.g. when a synthetic strain will remain in the ecosystem and the effects it will produce. We have also studied spatial models to predict their ability to modify the spatial organization of vegetation. Transient dynamics depend on the kind of transition underlying the occurring tipping point. For this reason, we have studied different systems: vegetation dynamics with facilitation (typical from drylands), a cooperator-parasite system, and a trophic chain model where different human interventions can be tested (i.e. hunting, deforestation, soil degradation, habitat destruction). All of these systems are shown to promote different types of transitions (i.e. smooth and catastrophic transitions). Each transition has its own dynamical fingerprint and thus knowing them can help monitoring and anticipating these transitions even before they happen, taking advantage of the so-called early warning signals. In this travel, we have found that transients can be an important phenomena in the current changing world. The ecosystems that we observe can be trapped into a seemingly stable regime, but be indeed in an unstable situation driving to a future sudden collapse (Fig 1) For this reason, we need to investigate novel intervention methods able to sustain the current ecosystems, for instance: Terraformation.

Background Cancer is one of the leading causes of death in Sweden. In order to develop better treatments against cancer we need to better understand it. One area of special interest is cancer metabolism and the metabolic fluxes. As these fluxes cannot be directly measured, modeling is required to determine them. Due to the complexity of cell metabolism, some limitations in the metabolism model are required. As the TCA-cycle (TriCarboxylic Acid cycle) is one of the most important parts of cell metabolism, it was chosen as a starting point. The primary goal of this project has been to evaluate the previously constructed TCA-cycle model. The first step of the evaluation was to determine the CI (Confidence Interval) of the model parameters, to determine the parameters’ identifiability. The second step was to validate the model to see if the model could predict data for which the model had not been trained for. The last step of the evaluation was to determine the uncertainty of the model simulation. Method The TCA-cycle model was created using Isotopicaly labeled data and EMUs (ElementaryMetabolic Units) in OpenFlux, an open source toolbox. The CIs of the TCA-cycle model parameters were determined using both OpenFlux’s inbuilt functionality for it as well as using amethod called PL (Profile Likelihood). The model validation was done using a leave one out method. In conjunction with using the leave on out method, a method called PPL (Prediction Profile Likelihood) was used to determine the CIs of the TCA-cycle model simulation. Results and Discussion Using PL to determine CIs had mixed success. The failures of PL are most likely caused by poor choice of settings. However, in the cases in which PL succeeded it gave comparable results to those of OpenFLux. However, the settings in OpenFlux are important, and the wrong settings can severely underestimate the confidence intervals. The confidence intervals from OpenFlux suggests that approximately 30% of the model parameters are identifiable. Results from the validation says that the model is able to predict certain parts of the data for which it has not been trained. The results from the PPL yields a small confidence interval of the simulation. These two results regarding the model simulation suggests that even though the identifiability of the parameters could be better, that the model structure as a whole is sound. Conclusion The majority of the model parameters in the TCA-cycle model are not identifiable, which is something future studies needs to address. However, the model is able to to predict data for which it has not been trained and the model has low simulation uncertainty.

La biologie synthétique des mammifères a le potentiel de permettre la mise au point de nouvelles stratégies thérapeutiques, la découverte de nouvelles méthodes d'identification de médicaments et la facilitation de synthèse de nouvelles molécules à haute valeur ajoutée. Toutefois, notre capacité à programmer les cellules est extrêmement limitée à la fois par un manque de technologies adaptées au design, la construction et le screening des circuits génétiques, mais aussi par la complexité des systèmes mammifères. Pour répondre à ces problèmes, j'ai travaillé sur la mise au point de nouvelles approches pendant mon doctorat. Tout d'abord, j'ai créée une nouvelle plateforme 1) d'assemblage modulaire et combinatoire de circuits génétiques mammifères comprenant plusieurs unités de transcription et 2) d'intégration de ces circuits dans un locus spécifique des chromosomes mammifères. Ensuite, j'ai développé une autre plateforme pour identifier et caractériser de nouvelles sérine-recombinases à partir dE génomes séquencés de Mycobactériophages afin d'étendre le spectre des outils disponibles pour l'ingénierie des génomes mammifères. Enfin, j'ai développé deux nouveaux systèmes artificiels de communication intercellulaire pour les systèmes mammifères afin de faciliter le découplage spatial des différents modules d'un circuit génétique synthétique
Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to program cells is currently hampered both by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks, and also by the complexity of mammalian systems and our poor understanding of cellular processes context¬dependencies. To address these problems, I proposed and validated a number of concepts and approaches during my PhD. First, I created a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. Second, I developed a platform to identify and characterize new serine reconnbinase systems from Mycobacteriophage genomes in order to extend the toolbox of genome engineering techniques available for mammalian cells progranning. To overcome the apparent limitations in our single-tell rational engineering capacity, I also engineered two new artificial intercellular communication systems for mammalian cells, in order to facilitate the spatial decoupling of different modules of a synthetic circuit. Even though we are still years away from therapies using engineered cells carrying synthetic circuits to repair damaged or non-functional organs or to create de-novo tissues, I believe the contributions developed during the course of my PhD could potentially be used to help fasten the development of therapeutically relevant DNA circuits or to provide new means to understand mechanisms of cellular processes.

Esta Tesis Doctoral recoge el trabajo de investigación que se ha realizado en dos líneas desarrolladas de forma paralela sobre Escherichia coli. Por un lado, la optimización de un proceso de biotransformación para mejorar la síntesis de L( )-carnitina mediante técnicas de ingeniería metabólica. Y por otro, la determinación de los principales efectos que provoca la exposición prolongada a altas concentraciones de sal y su respuesta de adaptación, principalmente cuando las fuentes de carbono pueden contener altas concentraciones de sal y tanto el sustrato como el producto son osmoprotectores. Para ello, se han aplicado técnicas utilizadas por la biología de sistemas y la ingeniería metabólica. La importancia de L( )-carnitina viene determinada por el papel que desempeña en el metabolismo energético, de hecho su deficiencia está asociada a diversas patologías. Varios trabajos centrados en la aplicación terapéutica de L( )-carnitina han demostrado que su administración puede ayudar a suplir dicha carencia. A partir de este punto, comienza una creciente actividad investigadora centrada en la producción de L( )-carnitina. Este trabajo presenta un método alternativo basado en la utilización de E. coli para llevar a cabo la biotransformación de compuestos de bajo valor añadido como puede ser D(+)-carnitina y/o crotonobetaína en L( )-carnitina. Por medio de técnicas de biología molecular se ha modificado genéticamente una cepa de E. coli, consiguiendo la sobreexpresión de caiC y mejorando el rendimiento de la cepa silvestre. Además, para optimizar la producción de L( )-carnitina se han estudiado aspectos relacionados con el metabolismo de carnitina como la disponibilidad de coenzima A o la inhibición de una ruta metabólica que favorezca la transformación del sustrato en L( )-carnitina. Posteriormente, se obtuvo una cepa modificada más estable y con una alta capacidad para la producción de L( )-carnitina, para ello se han implementado diversas estrategias de ingeniería metabólica. Las mutaciones implicadas en la mejora de esta cepa fueron: a) la deleción del gen aceK para incrementar el flujo hacia el ciclo de los ácidos tricarboxílicos, b) la deleción del gen caiA para impedir la síntesis de γ-butyrobetaína (productos del metabolismo de carnitina), y c) la sustitución del promotor natural altamente regulado del operón cai por un promotor artificial constitutivo. Con dichas mutaciones implementadas en una misma cepa, no sólo se consiguió aproximadamente un 100 % de conversión de crotonobetaína en L( )-carnitina en las condiciones de ensayo, sino que también la limitación impuesta por la presencia de oxígeno fue superada por este mutante, lo que indica la importancia de la ingeniería metabólica en la mejora de procesos biotecnológicos. L(-)-carnitina o compuestos similares son utilizados como osmoprotectores, acumulándolos en el interior celular, para evitar la deshidratación cuando la osmolaridad del medio se incrementa. Ante estas situaciones, los microorganismos pueden adaptarse y dar una respuesta pasajera, o realizar un proceso de adaptación para mantener su supervivencia mientras el estrés está presente. En este trabajo, se observó la evolución y la respuesta generada de una cepa de E. coli cultivada en un reactor continuo y sometida a tres concentraciones crecientes de sal (moderada, alta y muy alta). La medida de las actividades enzimáticas de las principales rutas metabólicas, así como la determinación de los metabolitos fermentativos producidos, resaltaron el importante papel ejercido por el metabolismo central en la adaptación y en la supervivencia celular tras una larga exposición a estrés salino, así como la necesidad de disponer de precursores biosintéticos y de energía en forma de ATP. Además, se profundizó en el estudio del comportamiento celular realizando una aproximación desde la biología de sistemas, integrando los niveles metabolómico, flujómico y transcriptómico. Se debe destacar que se observaron dos conjuntos de respuestas consecuencia de la concentración de sal presente en el medio. Uno dirigido a mantener unos niveles energéticos umbrales en la célula, basado tanto en el incremento de los flujos metabólicos hacia rutas que permitían la generación de energía, como en la reducción de procesos no esenciales para la supervivencia. Y otro, una respuesta característica en las células expuestas a alta o a muy alta concentración de sal, que estuvo caracterizada no sólo por cambios en los patrones de fermentación metabólica sino también por una alteración significativa del estado redox celular. Así, con el uso de técnicas apropiadas se han podido detectar un gran número de cambios en la fisiología y el metabolismo de E. coli. Además, la aproximación de la biología de sistemas ofrece una forma de obtener e integrar gran cantidad de información, que de otra forma se perdería por la cantidad de información que se obtiene. Finalmente, la ingeniería metabólica y la biología de sistemas han aportado una excelente manera de mejorar y conocer las características de los microorganismos involucrados en los procesos biotecnológicos relacionados con la producción de L( )-carnitina.
Two parallel research aims addressed on Escherichia coli are shown in this PhD thesis. On one hand, the optimization of a biotransformation process in order to improve L( )-carnitine synthesis by using metabolic engineering techniques is explained within the first chapters. On the other hand, in the following chapters, the main effects provoked by long-term high salt concentrations and the adaptative response to osmotic stress were determined using different techniques related to systems biology. L( )-carnitine is an important trimethylammonium compound because of its role in the energetic metabolism, in humans, several pathologies are related with deficiencies of carnitine level. Several works focused on the therapeutic application of L( )-carnitine, showed that administration of this compound could be a solution as opposed to its absence. Once different carnitine production ways were revised, this work shows an alternative method using Escherichia coli to carry out the biotransformation from D(+)-carnitine and/or crotonobetaine into L( )-carnitine. By using molecular biology techniques a strain of E. coli was engineered, obtaining caiC overexpression and enhancing the production yield respect to the wild type strain. Moreover, several aspects related with carnitine metabolism, such as coenzyme A availability and the inhibition of specific metabolic pathways were studied to optimize the carnitine production. Afterwards, various metabolic engineering strategies were implemented, obtaining a stable engineered strain with high capacity to produce L( )-carnitine. The modifications carried out were: a) deletion of the aceK gene (encoding a bifunctional protein phosphatase/kinase which performs post-translational control of isocitrate dehydrogenase) in order to increase the metabolic flux towards TCA cycle, b) deletion of the caiA gene (encoding the crotonobetainyl-CoA reductase) to avoid synthesis of γ-butyrobetaine (byproduct of the carnitine metabolism), and c) replacement of the highly regulated natural promoter of the cai operon by a constitutive promoter. These mutations implemented in the same strain led to obtaining almost 100% conversion from crotonobetaine to L( )-carnitine in the assay conditions. Moreover, the main restrictions impossed to the aerobic expression of the carnitine metabolism were eliminated producing L( ) carnitine in the presence of oxygen. Therefore, this work emphasizes the important role of metabolic engineering to improve any biotechnological process. On the other hand, L( )-carnitine and similar compounds are used as osmoprotectors, which are accumulated in high concentrations, either through the uptake from the medium or through de novo synthesis inside the cells, to avoid dehydratation when the osmolarity of the culture medium increases. Under these conditions, microorganisms have different response to an environmental stress, short-term or shock and long-term adaptation. In this work, evolution and response to long-term adaptation were analyzed in a E. coli strain growing in continuous reactors supplemented with a gradually increasing concentration of NaCl (moderate, high and very high). Enzyme activities from the main metabolic pathways and fermentative metabolites were analyzed, highlighting important role of central metabolism on adaptation and cellular survival after salt stress exposition. Furthermore, the need of biosynthetic precursors and energy as ATP were shown. In addition, a systems biology approach was conducted to study cellular behavior. In order to estimate the critical modifications undergone to overcome stress and to develop tolerance to salt, the metabolism was examined at several levels using different techniques (metabolomics, fluxomics and transcriptomics). Under salt stress conditions two set of responses were shown. One of them was focused to maintain the energetic threshold in cells, thus, either an increment of the metabolic pathways which could produce energy or a decrease of no-essential processes to survive were shown. On the other hand, cells under high or very high salt concentrations showed another similar response characterized by both changing on pattern of fermentative pathways and redox state. Therefore, using suitable techniques many changes in the physiology and metabolism of the E. coli strain in use were detected. Moreover, the systems biology approach offered a way to obtain and integrate a large amount of information, preventing some of the information being overlooked by the massive amount of data. Both the metabolic engineering and systems biology approaches have provided excellent ways to improve and know features of microorganisms involved in biotechnological processes related with the L( )-carnitine production.

Esta tesis se centra en la construcción y usos de los modelos metabólicos a escala genómica para obtener biocombustibles de manera eficiente, como etanol e hidrógeno. Como organismo objetivo, se ha elegido a la cianobacteria Synechocystis sp. PCC6803. Este organismo ha sido estudiado como una potencial plataforma de producción alimentada por fotones, dada su capacidad de crecer solamente a partir de dióxido de carbono y fotones. Esta tesis versa acerca de los métodos para modelar, analizar, estimar y predecir el comportamiento del metabolismo de las células. La principal meta es extraer conocimiento de los diferentes aspectos biológicos de un organismo con el fin de utilizarlo para un objetivo industrial pertinente. Esta tesis ha sido estructurada en capítulos organizados de acuerdo con las sucesivas tareas que terminan con la construcción de una célula in silico que se comporta, idealmente, como la que está basada en el carbono. Este proceso suele comenzar con los archivos de anotación del genoma y termina con un modelo metabólico a escala genómica capaz de integrar datos -ómicos. El primer objetivo de la presente tesis es la reconstrucción de un modelo del metabolismo de esta cianobacteria que tenga en cuenta todas las reacciones presentes en la misma. Esta reconstrucción tenía que ser lo suficientemente flexible como para permitir el crecimiento en las distintas condiciones ambientales bajo las cuales este organismo crece en la naturaleza, así como permitir la integración de diferentes niveles de información biológica. Una vez que se cumplió este requisito, se pudieron simular variaciones ambientales y estudiar sus efectos desde una perspectiva de sistema. Se han estudiado hasta cinco diferentes condiciones de crecimiento en este modelo metabólico y sus diferencias han sido evaluadas. La siguiente tarea fue definir estrategias de producción para sopesar la viabilidad de este organismo como una plataforma de producción. Se simularon perturbaciones genéticas para e
This thesis is focused on the construction and uses of genome-scale metabolic models to efficiently obtain biofuels, such as ethanol and hydrogen. As a target organism, cyanobacterium Synechocystis sp. PCC6803 was chosen. This organism has been studied as a potential photon-fuelled production platform, for its ability to grow only from carbon dioxide, water and photons. This dissertation verses about methods to model, analyse, estimate and predict the metabolic behaviour of cells. Principal goal is to extract knowledge from the different biological aspects of an organism in order to use it for an industrial relevant objective. This dissertation has been structured in chapters accordingly organized as the successive tasks that end up building an in silico cell that behaves as the carbon-based one. This process usually starts with the genome annotation files and ends up with a genome-scale metabolic model able to integrate ¿omics data. First objective of present thesis is to reconstruct a model of this cyanobacteria¿s metabolism that accounts for all the reactions present in it. This reconstruction had to be flexible enough as to allow growth under the different environmental conditions under which this organism grows in nature as well as to allow the integration of different levels of biological information. Once this requisite was met, environmental variations could be simulated and their effect studied under a system-wide perspective. Up to five different growth conditions were simulated on this metabolic model and differences were evaluated. Following assignment was to define production strategies to weigh this organism¿s viability as a production platform. Genetic perturbations were simulated to design strains with an enhanced production of three industrially-relevant metabolites: succinate, ethanol and hydrogen. Resulting sets of genetic modifications for the overproduction of those metabolites are, thus, proposed. Moreover, functional reactions couplings were studied and weighted to their metabolite production importance. Finally, genome-scale metabolic models allow establishing integrative approaches to include different types of data that help to find regulatory hotspots that can be targets of genetic modification. Such regulatory hubs were identified upon light/dark shifts and general metabolism operational principles inferred. All along this process, blind spots in Synechocystis sp. PCC6803 metabolism, and more importantly, blind spots in our understanding of it, are revealed. Overall, the work presented in this thesis unveils the industrial capabilities of cyanobacterium Synechocystis sp. PCC6803 to evolve interesting metabolites as a clean production platform.
Esta tesis es centra en la construcció i els usos del models metabòlics a escala genòmica per a obtenir eficientment biocombustibles, com etanol i hidrogen. Com a organisme diana, s¿elegí el cianobacteri Synechocystis sp. PCC6803. Aquest organisme ha segut estudiat com una plataforma de producció nodrida per fotons, per la seva habilitat per créixer a partir únicament de diòxid de carboni, aigua i fotons. Aquesta tesi versa sobre mètodes per a modelitzar, analitzar, estimar i predir el comportament metabòlic de cèl¿lules. La principal meta és extreure coneixement del diferents aspectes biològics d¿un organisme de manera que s¿usen per a un objectiu industrial rellevant. La tesi ha segut estructurada en capítols organitzats d¿acord a les successives tasques que acaben construint una cèl¿lula in silico que es comporta, idealment, com la que està basada en carboni. Aquest procés generalment comença amb els arxius de l¿anotació del genoma i acaba amb un model metabòlic a escala genòmica capaç d¿integrar dades ¿òmiques. El primer objectiu de la present tesi és la reconstrucció d¿un model del metabolisme d¿aquest cianobacteri que tinga en compte totes les reaccions que hi estan presents. Esta reconstrucció havia de ser prou flexible com per permetre la simulació del creixement en les diferents condicions ambientals en les quals aquest cianobacteri creix en la natura, així com permetre la integració de diferents nivells d¿informació biològica. Una vegada que aquest requisit fou assolit, es pogueren simular variacions ambientals i estudiar els seus efectes amb una perspectiva de sistema. S¿han simulat fins a cinc condicions de creixement en este model metabòlic i les seves diferències han segut avaluades. La següent tasca fou definir estratègies de producció per a valorar la viabilitat d¿aquest organisme com a plataforma de producció. Es simularen pertorbacions genètiques per al disseny de soques amb producció millorada de metabòlits de rellevància industrial: succinat, etanol i hidrogen. Així, es proposen conjunts de modificacions genètiques per a la sobreproducció d¿aquests metabòlits. També s'han estudiat reaccions acoblades funcionalment i s¿ha ponderat la seva importància en la producció de metabòlits. Finalment, els models metabòlics a escala genòmica permeten establir criteris per integrar diferents tipus de dades que ens ajuden a trobar punts importants de regulació. Eixos centres reguladors, que poden ser objecte de modificacions genètiques, han segut investigats baix canvis dràstics d¿il¿luminació i s¿han inferit principis operacionals del metabolisme. Al llarg d'aquest procés, s¿han revelat punts cecs al metabolisme de Synechocystis sp. PCC6803 i, el més important, punts cecs en la nostra comprensió d'aquest metabolisme. En general, el treball presentat en aquesta tesi dona a conèixer les capacitats industrials del cianobacteri Synechocystis sp. PCC6803 per a produir metabòlits d'interès, tot sent una plataforma de producció neta i sostenible.
Montagud Aquino, A. (2012). Modelling and analysis of biological systems to obtain biofuels [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17319
Palancia

Les huiles microbiennes sont considérées comme des alternatives prometteuses aux combustibles fossiles qui suscitent de plus en plus de préoccupations environnementales et énergétiques. Les acides gras à chaîne impaires (AGI), un type de lipide inhabituel, sont des composés d’intérêt ayant diverses applications biotechnologiques. L’objectif de cette thèse est de développer Yarrowia lipolytica comme souche plateforme, par l’ingénierie métabolique, pour la production d’AGI.Pour développer Y. lipolytca, l'identification et la caractérisation d’une nouvelle série de promoteurs érythritol-hybrides-inductible (pEYK1, pEYD1, et dérivés) ont été réalisées. La série de promoteurs hybrides a montré des forces variables, l'induction à base d'érythritol a augmenté de 2,2 à 32,3 fois dans la souche WT et de 2,9 à 896,1 fois dans la souche eyk1Δ. Ces promoteurs amélioreront la capacité de moduler l'expression de gènes chez Y. lipolytica.Pour la production d’AGI, la tolérance au propionate a été étudiée. Deux gènes, RTS1 et MFS1, améliorant la résistance au propionate ont été identifiés par le criblage d’une banque d’ADN génomique. Par des stratégies d’ingénierie métabolique, comme l’inhibition de la voie compétitive, l’augmentation les pools de précurseurs, et l’amélioration de l’accumulation de lipides totale, la production d'AGI a été augmentée de 0,14 g/L à 1,87 g/L. La production de novo des AGI sans supplémentation de propionate a également été explorée. Par surexpression des gènes dans la voie de synthèse de la thréonine, la production d’AGI été augmentée de 12 fois par rapport à la souche sauvage (0,36 versus 0,03 g/L).En résumé, des souches de Y. lipolytica ont été développées pour produire efficacement des AGI, principalement l’acide heptadécénoïque. Ce travail ouvre la voie à la production microbienne d'AGI et de ses dérivés à plus grande échelle
Microbial oils are regarded as promising alternatives to fossil fuels with growing environmental and energy concerns. Odd-chain fatty acids (OCFAs), a type of unusual lipids, are value-added compounds with various biotechnological applications. The objective of the thesis was to develop Yarrowia lipolytica as a platform strain for the production of OCFAs by metabolic engineering.For developing Y. lipolytica, the identification and characterization of a new series of erythritol-hybrid-inducible promoters (pEYK1, pEYD1, and derivatives) were explored. The hybrid promoter series showed variable strengths, erythritol-based induction increased 2.2 to 32.3 times in the WT strain and 2.9 to 896.1 times in the eyk1Δ strain, which will improve the modulation of gene expression for metabolic engineering of Y. lipolytica.For OCFA production, tolerance to propionate was studied. Two genes, RTS1 and MFS1, were identified as propionate-tolerant genes by screening a genomic DNA library. Through metabolic engineering strategies, such as inhibiting competitive pathways, increasing precursor pools, and enhancement of total lipid accumulation, OCFA production was increased from 0.14 g/L to 1.87 g/L. De novo production of OCFAs without propionate supplementation was also explored by overexpression of the threonine synthesis pathway. OCFAs production was increased by 12-times; 0.36 versus 0.03 g/L for WT.In summary, Y. lipolytica strains were developed to produce high-amount of OCFAs, mainly heptadecenoic acid. This work paves the way for the microbial production of OCFAs and their derivatives at the industrial scale

The development of shape in multicellular organisms has intrigued human minds for millenia. Empowered by modern genetic techniques, molecular biologists are now striving to not only dissect developmental processes, but to exploit their modularity for the design of custom living systems used in bioproduction, remediation, and regenerative medicine. Currently, our capacity to harness this potential is fundamentally limited by a lack of spatiotemporal control over gene expression in multicellular systems. While several synthetic genetic circuits for control of multicellular patterning have been reported, hierarchical induction of gene expression domains has received little attention from synthetic biologists, despite its fundamental role in biological self-organization. In this thesis, I introduce the first synthetic genetic system implementing population-based AND logic for programmed hierarchical patterning of bacterial populations of Escherichia coli, and address fundamental prerequisites for implementation of an analogous genetic circuit into the emergent multicellular plant model Marchantia polymorpha. In both model systems, I explore the use of bacteriophage T7 RNA polymerase as a gene expression engine to control synthetic patterning across populations of cells. In E. coli, I developed a ratiometric assay of bacteriophage T7 RNA polymerase activity, which I used to systematically characterize different intact and split enzyme variants. I utilized the best-performing variant to build a three-color patterning system responsive to two different homoserine lactones. I validated the AND gate-like behavior of this system both in cell suspension and in surface culture. Then, I used the synthetic circuit in a membrane-based spatial assay to demonstrate programmed hierarchical patterning of gene expression across bacterial populations. To prepare the adaption of bacteriophage T7 RNA polymerase-driven synthetic patterning from the prokaryote E. coli to the eukaryote M. polymorpha, I developed a toolbox of genetic elements for spatial gene expression control in the liverwort: I analyzed codon usage across the transcriptome of M. polymorpha, and used insights gained to design codon-optimized fluorescent reporters successfully expressed from its nuclear and chloroplast genomes. For targeting of bacteriophage T7 RNA polymerase to these cellular compartments, I functionally validated nuclear localization signals and chloroplast transit peptides. For spatiotemporal control of bacteriophage T7 RNA polymerase in M. polymorpha, I characterized spatially restricted and inducible promoters. For facilitated posttranscriptional processing of target transcripts, I functionally validated viral enhancer sequences in M. polymorpha. Taking advantage of this genetic toolbox, I introduced inducible nuclear-targeted bacteriophage T7 RNA polymerase into M. polymorpha. I showed implementation of the bacteriophage T7 RNA polymerase/PT7 expression system accompanied by hypermethylation of its target nuclear transgene. My observations suggest operation of efficient epigenetic gene silencing in M. polymorpha, and guide future efforts in chassis engineering of this multicellular plant model. Furthermore, my results encourage utilization of spatiotemporally controlled bacteriophage T7 RNA polymerase as a targeted silencing system for functional genomic studies and morphogenetic engineering in the liverwort. Taken together, the work presented enhances our capacity for spatiotemporal gene expression control in bacterial populations and plants, facilitating future efforts in synthetic morphogenesis for applications in synthetic biology and metabolic engineering.

La biologie de synthèse permet désormais la production de nouvelles molécules n’existant pas dans la nature. Au cours de cette thèse, nous nous sommes focalisés sur la diversification de produits issus du (+)-epi-α-bisabolol. Cette molécule issue de la plante Lippia dulcis appartient à la vaste famille des sesquiterpènes qui recèle de nombreuses activités biologiques. En particulier, le (+)-epi-α-bisabolol est le précurseur de l’hernandulcine, un édulcorant intense. Cependant, la dernière étape d’oxydation conduisant à ce composé demeure inconnue.Plutôt que de rechercher la (ou les enzymes) intervenant dans la voie de biosynthèse de l’hernandulcine chez L. dulcis, nous avons choisi de mettre à profit la promiscuité connue de cytochromes P450 pour diversifier les molécules issues du (+)-epi-α-bisabolol ou de reproduire la voie de synthèse naturelle. Tout d’abord, une souche châssis adaptée au criblage in vivo a été construite en exprimant la (+)-epi-α-bisabolol synthase (BBS) et une NADPH cytochrome P450 réductase. Puis, le criblage in vivo chez la levure a montré que des cytochromes P450 (CYPs) parmi notre banque de 25 enzymes impliquées dans le métabolisme des xénobiotiques (CYPs animaux) oxydaient le (+)-epi-α-bisabolol. Parmi ces produits, le 14-hydroxy-(+)-epi-α-bisabolol a été purifié et caractérisé par RMN tandis que la structure probable d’un second produit a été obtenue (9-hydroxy-(+)-epi-α-bisabolol). En parallèle, la production de produits hydroxylés (+)-epi-α-bisabolol a été optimisée notamment par l’addition d’une copie génomique supplémentaire de BBS, avec un titre de de produit hydroxylé de 64 mg/L. Ainsi, nous avons démontré le potentiel des CYPs du métabolisme des xénobiotiques dans la synthèse de nouvelles molécules issues des sesquiterpènes.Parmi les enzymes identifiées, deux enzymes homologues, CYP2B6 et CYP2B11 ont catalysé la formation de produits différents à partir du (-)-α-bisabolol et du trans,trans-farnésol. Pour identifier les possibles déterminants moléculaires responsables de la spécificité de chacune de ces deux enzymes, des chimères échangeant divers éléments de structure secondaire de CYP2B6 dans CYP2B11 ont été comparées. Ainsi, la spécificité ne peut pas être expliquée par un seul élément de la structure secondaire mais plus probablement par des déterminants disséminés en divers endroits des séquences protéiques des deux enzymes.Afin d’étendre la diversité de molécules produites à partir de l’α-bisabolol et de l’hernandulcine et de produire des composés aux propriétés physico-chimiques améliorées (solubilité, pouvoir sucrant…) des essais de glycosylation par une glucosyltransférase de plante (UGT93B16) et par des glucuronosyltransférases humaines ont été menés. UGT93B16 a démontré son potentiel en glucosylant l’α-bisabolol et l’hernandulcine. La bioconversion de ces molécules en utilisant E. coli and S. cerevisiae a également montré une meilleure conversion chez la levure. Concernant les UDP-glucuronosyltransférases, des essais enzymatiques ont mis en évidence une activité d’UGT1A9, d’UGT2B4 et d’UGT2B7 pour l’α-bisabolol et l’hernandulcine. Toutefois, l’introduction de ces enzymes dans la levure n’a pas été permis la production de sesquiterpènes glucuronylés à un niveau détectable. Pour résumer, nous avons prouvé la faisabilité de la production de nouveaux sesquiterpènes glycosylés soit par voie enzymatique soit par bioconversion chez deux microorganismes couramment utilisés en biotechnologie.En conclusion, les approches utilisées au cours de cette thèse ont montré l’intérêt du criblage d’enzymes promiscuitaires pour l’α-bisabolol et la production de nouvelles molécules. Nous avons exploré les limites de notre souche châssis et une régulation plus fine du métabolisme de S. cerevisiae pourrait améliorer les titres obtenus. Enfin, le couplage des étapes impliquant un cytochrome P450 et une glucosyltransférase est désormais envisageable afin de créer une voie encore plus orthogonale
The rise of synthetic biology now enables the production of new to nature molecules. In the frame of this thesis we focused on the diversification of the (+)-epi-α-bisabolol scaffold. This molecule coming from the plant Lippia dulcis belongs to the vast family of sesquiterpenes. While sesquiterpenes possess diverse biological activities, (+)-epi-α-bisabolol is the precursor of hernandulcin, an intense sweetener. However, the last oxidative step(s) of the hernandulcin biosynthetic pathway remain elusive.Rather than seeking the native oxidase responsible for hernandulcin synthesis among L. dulcis enzymes we selected oxidative enzymes known to be promiscuous and that could functionalize (+)-epi-α-bisabolol in order to i) generate diversity from (+)-epi-α-bisabolol; ii) hopefully identify an oxidative enzyme catalyzing hernandulcin synthesis. First, a yeast chassis strain enabling the in vivo screening of cytochromes P450 (CYPs) was constructed by coexpressing two key enzymes: the (+)-epi-α-bisabolol synthase (BBS) and the NADPH cytochrome P450 reductase. Then, the in vivo screening assays revealed that 5 CYPs out of our library of 25 animal CYPs involved in xenobiotic metabolism oxidized (+)-epi-α-bisabolol and produced new hydroxylated regioisomers. Of the oxidized products, the structure of one compound, 14-hydroxy-(+)-epi-α-bisabolol, was fully elucidated by NMR while the probable structure of a second one was determined (9-hydroxy-(+)-epi-α-bisabolol). In parallel, the production of (+)-epi-α-bisabolol derivatives was enhanced through addition of a supplementary genomic copy of BBS that augmented the final titer of hydroxylated product to 64 mg/L. We thus demonstrate that promiscuous drug metabolism CYPs can be used to produce novel compounds from a sesquiterpene scaffold.Furthermore, different products were obtained with two homologous enzymes i.e. CYP2B6 and CYP2B11. This prompted us to study the molecular determinants putatively responsible for enzyme regiospecificity. From chimeric enzymes composed of secondary structure elements originating from CYP2B6 and CYP2B11 we were not able to identify specific motifs that could explain the CYPs regiospecificity. This approach suggests that the molecular determinants cannot be attributed to specific structural elements of the two enzymes but are rather widespread in the protein sequences.In order to generate a wider molecular diversity from α-bisabolol or hernandulcin, and synthesize molecules with different physico-chemical and biological properties (i.e. solubility, sweetening power etc.), we attempted the glycosylation of these compounds using a plant glucosyltransferase (UGT93B16) or human glucuronosyltransferases. UGT93B16 was found to glucosylate both (-)-α-bisabolol and hernandulcin. In addition, we carried out whole cell catalysis using E. coli and S. cerevisiae as recombinant producers of UGT93B16. Comparison of the two microbial hosts showed that glycosylation using yeast cells was more efficient. In parallel, we investigated α-bisabolol glucosylation by human UDP-glucuronosyltransferases involved in the xenobiotic metabolism. In vitro enzymatic assays demonstrated a weak activity of UGT1A9, UGT2B4 and UGT2B7 towards α-bisabolol and hernandulcin. However, their introduction in yeast failed to produce detectable amounts of glucuronide products. In summary, we proved the feasibility of producing new to nature sesquiterpene glucosides using either enzyme-based assay or bioconversion in two different hosts that are widely used in biotechnology.To conclude, the approaches used in this thesis highlight the assets of screening promiscuous enzymes for the production of new molecules from α-bisabolol. We also explored the limits of our chassis strain and a tighter regulation of S. cerevisiae metabolism could improve the production (+)-epi-α-bisabolol oxidized products. Finally, the coupling in yeast of cytochrome P450 and glucosyltransferase steps can now be envisioned

Le métabolisme définit l’ensemble des réactions biochimiques au sein d’un organisme, lui permettant de survivre et de s’adapter dans différents environnements. La régulation de ces réactions requiert un processus complexe impliquant de nombreux effecteurs interagissant ensemble à différentes échelles.Développer des modèles de ces réseaux de régulation est ainsi une étape indispensable pour mieux comprendre les mécanismes précis régissant les systèmes vivants et permettre, à terme, la conception de systèmes synthétiques, autorégulés et adaptatifs, à l'échelle du génome. Dans le cadre de ces travaux interdisciplinaires, nous proposons d’utiliser une approche itérative d’inférence de réseau et d’interrogation afin de guider l’ingénierie du métabolisme de la levure d’intérêt industriel Yarrowia lipolytica.À partir de données transcriptomiques, le premier réseau de régulation de l’adaptation à la limitation en azote et de la production de lipides a été inféré pour cette levure. L’interrogation de ce réseau a ensuite permis de mettre en avant et valider expérimentalement l’impact de régulateurs sur l'accumulation lipidique.Afin d’explorer davantage les liens entre régulation et métabolisme, une nouvelle méthode, CoRegFlux, a été proposée pour la prédiction de phénotype métabolique à partir des profils d’activités des régulateurs dans les conditions étudiées.Ce package R, disponible sur la plateforme Bioconductor, a ensuite été utilisé pour mieux comprendre l’adaptation à la limitation en azote et identifier des phénotypes d’intérêts en vue de l’ingénierie de cette levure, notamment pour la production de lipides et de violacéine.Ainsi, par une approche itérative, ces travaux apportent de nouvelles connaissances sur les interactions entre la régulation et le métabolisme chez Y. lipolytica, l’identification de motifs de régulation chez cette levure et contribue au développement de méthodes intégratives pour la conception de souches assistée par ordinateur
Metabolism defines the set of biochemical reactions within an organism, allowing it to survive and adapt to different environments. Regulating these reactions requires complex processes involving many effectors interacting together at different scales.Developing models of these regulatory networks is therefore an essential step in better understanding the precise mechanisms governing living systems and ultimately enabling the design of synthetic, self-regulating and adaptive systems at the genome level. As part of this interdisciplinary work, we propose to use an iterative network inference and interrogation approach to guide the engineering of the metabolism of the yeast of industrial interest Yarrowia lipolytica.Based on transcriptomic data, the first network for the regulation of adaptation to nitrogen limitation and lipid production in this yeast was inferred.The interrogation of this network has then allowed to to highlight and experimentally validate the impact of several regulators on lipid accumulation. In order to further explore the relationships between regulation and metabolism, a new method, CoRegFlux, has been proposed for the prediction of metabolic phenotype based on the influence profiles of regulators in the studied conditions. This R package, available on the Bioconductor platform, was then used to better understand adaptation to nitrogen limitation and to identify phenotypes of interest for strain engineering, particularly for the production of lipids and amino acid derivatives such as violacein.Thus, through an iterative approach, this work provides new insights into the interactions between regulation and metabolism in Y. lipolytica, conserved regulatory module in this yeast and contributes to the development of innovative integrative methods for computer-assisted strain design

The interconnection of molecular machines with different functionalities to form molecular communication systems can increase the number of design possibilities and overcome the limited reliability of the individual molecular machines. Artificial information exchange using molecular signals would also expand the capabilities of single engineered cell populations by providing them a way to cooperate across heterogeneous cell populations for the applications of synthetic biology and lab-on-a-chip systems. The realization of molecular communication systems necessitates analysis and design of the communication channel, where the information carrying molecular signal is transported from the transmitter to the receiver. In this thesis, significant progress towards the use of microfluidic channels to interconnect molecular transmitter and receiver pairs is presented. System-theoretic analysis of the microfluidic channels are performed, and a finite-impulse response filter is designed using microfluidic channels. The spectral density of the propagation noise is studied and the additive white Gaussian noise channel model is developed. Memory due to inter-diffusion of the transmitted molecular signals is also modeled. Furthermore, the interference modeling is performed for multiple transmitters and its impact on the communication capacity is shown. Finally, the efficient sampling of the signal transduction by engineered bacterial receivers connected to a microfluidic channel is investigated for the detection of the pulse-amplitude modulated molecular signals. This work lays the foundation for molecular communication over microfluidic channels that will enable interconnection of engineered molecular machines.

Cette thèse consiste à étudier l'organisation du système de contrôle des voies métaboliques des bactéries afin de dégager des propriétés systémiques révélant son fonctionnement. Dans un premier temps, nous montrons que le contrôle des voies métaboliques est hautement structuré et peut se décomposer en modules fortement découplés en régime stationnaire. Ces modules possèdent des propriétés mathématiques remarquables ayant des conséquences importantes en biologie. Cette décomposition, basée intrinsèquement sur la vision système de l'Automatique, offre un cadre théorique formel général d'analyse du contrôle des voies métaboliques qui s'est révélé effectif pour analyser des données expérimentales. dans un deuxième temps, nous nous intéressons aux raisons possibles de l'émergence de cette structure de contrôle similaire. Nous identifions un ensemble de contraintes structurelles agissant au niveau de la répartition d'une ressource commune, les protéines, entre les processus cellulaires. Respecter ces contraintes pour un taux de croissance donné conduit à formaliser et résoudre un problème d'optimisation convexe non différentiable, que nous appelons Resource balance Analysis. Ce problème d'optimisation se résout numériquement à l'échelle de la bactérie grâce à un problème de Programmation Linéaire équivalent. plusieurs propriétés sont déduites de l'analyse théorique du critère obtenu. Tout d'abord, le taux de croissance est structurellement limité par la répartition d'une quantité finie de protéines entre les voies métaboliques et les ribosomes. Ensuite, l'émergence des modules dans les voies métaboliques provient d'une politique générale d'économie en protéines chez la bactérie pour gagner du taux de croissance. Certaines stratégies de transport bien connues comme la répression catabolique ou la substitution de transporteurs haute/basse affinités sont prédites par notre méthode et peuvent alors être interprétées comme le moyen de maximiser la croissance tout en minimisant l'investissement en protéines.

Elevated expression of proteins, such as those involved in native antibiotic resistance pathways or introduced to enable biosynthesis of a metabolic engineering target, frequently leads to increased fitness cost. This can result in reduced growth and places selective pressure on cells. In conditions where there is diversity in expression within the population, this can result in cells with higher fitness out-competing their low-fitness counterparts. In the antibiotic resistance context, differential fitness costs caused by antibiotic resistance machinery can be exploited to select against resistant bacteria. However, in biotechnology applications, introducing burdensome synthetic constructs often requires additional engineering to increase genetic stability and maintain production. In this thesis, we investigate the origin of fitness costs and strategies for either exploiting or reducing it, focusing on specific examples related to antibiotic resistance and metabolic engineering. In the resistance work, we study the multiple antibiotic resistance activator MarA and related proteins in Escherichia coli. We quantify the differential fitness cost impacts of salicylate on E. coli antibiotic resistance variants. We demonstrate that salicylate, the natural inducer of MarA, imposes a higher fitness cost on resistant cells compared to the susceptible counterparts, making it possible to bias bacterial population membership towards those cells that are susceptible. In a second study, we focus on the role of salicylate in antibiotic tolerant persister cell formation, finding that salicylate induces reactive oxygen species and consequently persistence. In the metabolic engineering parts of the thesis we first review the mechanisms of fitness cost and existing strategies to ameliorate cost and cell-to-cell variation. Next, we present a technique for reducing fitness cost while maintaining production that takes advantage of transcription factor decoy sites to regulate biosynthesis in E. coli. Using arginine production as a model system, the transcription factor decoy is able to increase production by 16-fold without detectable growth differences. Together, the thesis provides an understanding of the origins and mechanisms of fitness cost in the context of antibiotic resistance and metabolic engineering. It also introduces strategies to exploit fitness costs to select against resistant bacteria and engineering strategies to ameliorate cost while increasing production and genetic stability.

abstract: This dissertation focuses on the biosynthetic production of aromatic fine chemicals in engineered Escherichia coli from renewable resources. The discussed metabolic pathways take advantage of key metabolites in the shikimic acid pathway, which is responsible for the production of the aromatic amino acids phenylalanine, tyrosine, and tryptophan. For the first time, the renewable production of benzaldehyde and benzyl alcohol has been achieved in recombinant E. coli with a maximum titer of 114 mg/L of benzyl alcohol. Further strain development to knockout endogenous alcohol dehydrogenase has reduced the in vivo degradation of benzaldehyde by 9-fold, representing an improved host for the future production of benzaldehyde as a sole product. In addition, a novel alternative pathway for the production of protocatechuate (PCA) and catechol from the endogenous metabolite chorismate is demonstrated. Titers for PCA and catechol were achieved at 454 mg/L and 630 mg/L, respectively. To explore potential routes for improved aromatic product yields, an in silico model using elementary mode analysis was developed. From the model, stoichiometric optimums maximizing both product-to-substrate and biomass-to-substrate yields were discovered in a co-fed model using glycerol and D-xylose as the carbon substrates for the biosynthetic production of catechol. Overall, the work presented in this dissertation highlights contributions to the field of metabolic engineering through novel pathway design for the biosynthesis of industrially relevant aromatic fine chemicals and the use of in silico modelling to identify novel approaches to increasing aromatic product yields.
Dissertation/Thesis
Doctoral Dissertation Chemical Engineering 2016