Relevant bibliographies by topics / Systems Biology, Synthetic Biology, Metabolic Engineering

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Systems Biology, Synthetic Biology, Metabolic Engineering'

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Published: 6 September 2023

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Journal articles on the topic "Systems Biology, Synthetic Biology, Metabolic Engineering"

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Nielsen, Jens, and Jack T. Pronk. "Metabolic engineering, synthetic biology and systems biology." FEMS Yeast Research 12, no. 2 (January 4, 2012): 103. http://dx.doi.org/10.1111/j.1567-1364.2011.00783.x.

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He, Fei, Ettore Murabito, and Hans V. Westerhoff. "Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering." Journal of The Royal Society Interface 13, no. 117 (April 2016): 20151046. http://dx.doi.org/10.1098/rsif.2015.1046.

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Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo , not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways.
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Choi, Kyeong Rok, Woo Dae Jang, Dongsoo Yang, Jae Sung Cho, Dahyeon Park, and Sang Yup Lee. "Systems Metabolic Engineering Strategies: Integrating Systems and Synthetic Biology with Metabolic Engineering." Trends in Biotechnology 37, no. 8 (August 2019): 817–37. http://dx.doi.org/10.1016/j.tibtech.2019.01.003.

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Lee, Hyang-Mi, Phuong Vo, and Dokyun Na. "Advancement of Metabolic Engineering Assisted by Synthetic Biology." Catalysts 8, no. 12 (December 4, 2018): 619. http://dx.doi.org/10.3390/catal8120619.

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Synthetic biology has undergone dramatic advancements for over a decade, during which it has expanded our understanding on the systems of life and opened new avenues for microbial engineering. Many biotechnological and computational methods have been developed for the construction of synthetic systems. Achievements in synthetic biology have been widely adopted in metabolic engineering, a field aimed at engineering micro-organisms to produce substances of interest. However, the engineering of metabolic systems requires dynamic redistribution of cellular resources, the creation of novel metabolic pathways, and optimal regulation of the pathways to achieve higher production titers. Thus, the design principles and tools developed in synthetic biology have been employed to create novel and flexible metabolic pathways and to optimize metabolic fluxes to increase the cells’ capability to act as production factories. In this review, we introduce synthetic biology tools and their applications to microbial cell factory constructions.
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Fong, Stephen S. "Computational approaches to metabolic engineering utilizing systems biology and synthetic biology." Computational and Structural Biotechnology Journal 11, no. 18 (August 2014): 28–34. http://dx.doi.org/10.1016/j.csbj.2014.08.005.

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King, Jason R., Steven Edgar, Kangjian Qiao, and Gregory Stephanopoulos. "Accessing Nature’s diversity through metabolic engineering and synthetic biology." F1000Research 5 (March 24, 2016): 397. http://dx.doi.org/10.12688/f1000research.7311.1.

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In this perspective, we highlight recent examples and trends in metabolic engineering and synthetic biology that demonstrate the synthetic potential of enzyme and pathway engineering for natural product discovery. In doing so, we introduce natural paradigms of secondary metabolism whereby simple carbon substrates are combined into complex molecules through “scaffold diversification”, and subsequent “derivatization” of these scaffolds is used to synthesize distinct complex natural products. We provide examples in which modern pathway engineering efforts including combinatorial biosynthesis and biological retrosynthesis can be coupled to directed enzyme evolution and rational enzyme engineering to allow access to the “privileged” chemical space of natural products in industry-proven microbes. Finally, we forecast the potential to produce natural product-like discovery platforms in biological systems that are amenable to single-step discovery, validation, and synthesis for streamlined discovery and production of biologically active agents.
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Chen, Bor-Sen, and Chia-Chou Wu. "Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering." Cells 2, no. 4 (October 11, 2013): 635–88. http://dx.doi.org/10.3390/cells2040635.

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McArthur, George H., and Stephen S. Fong. "Toward Engineering Synthetic Microbial Metabolism." Journal of Biomedicine and Biotechnology 2010 (2010): 1–10. http://dx.doi.org/10.1155/2010/459760.

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The generation of well-characterized parts and the formulation of biological design principles in synthetic biology are laying the foundation for more complex and advanced microbial metabolic engineering. Improvements inde novoDNA synthesis and codon-optimization alone are already contributing to the manufacturing of pathway enzymes with improved or novel function. Further development of analytical and computer-aided design tools should accelerate the forward engineering of precisely regulated synthetic pathways by providing a standard framework for the predictable design of biological systems from well-characterized parts. In this review we discuss the current state of synthetic biology within a four-stage framework (design, modeling, synthesis, analysis) and highlight areas requiring further advancement to facilitate true engineering of synthetic microbial metabolism.
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Ma, Jingbo, Yang Gu, Monireh Marsafari, and Peng Xu. "Synthetic biology, systems biology, and metabolic engineering of Yarrowia lipolytica toward a sustainable biorefinery platform." Journal of Industrial Microbiology & Biotechnology 47, no. 9-10 (July 4, 2020): 845–62. http://dx.doi.org/10.1007/s10295-020-02290-8.

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Jeong, Yujin, Sang-Hyeok Cho, Hookeun Lee, Hyung-Kyoon Choi, Dong-Myung Kim, Choul-Gyun Lee, Suhyung Cho, and Byung-Kwan Cho. "Current Status and Future Strategies to Increase Secondary Metabolite Production from Cyanobacteria." Microorganisms 8, no. 12 (November 24, 2020): 1849. http://dx.doi.org/10.3390/microorganisms8121849.

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Cyanobacteria, given their ability to produce various secondary metabolites utilizing solar energy and carbon dioxide, are a potential platform for sustainable production of biochemicals. Until now, conventional metabolic engineering approaches have been applied to various cyanobacterial species for enhanced production of industrially valued compounds, including secondary metabolites and non-natural biochemicals. However, the shortage of understanding of cyanobacterial metabolic and regulatory networks for atmospheric carbon fixation to biochemical production and the lack of available engineering tools limit the potential of cyanobacteria for industrial applications. Recently, to overcome the limitations, synthetic biology tools and systems biology approaches such as genome-scale modeling based on diverse omics data have been applied to cyanobacteria. This review covers the synthetic and systems biology approaches for advanced metabolic engineering of cyanobacteria.
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Dissertations / Theses on the topic "Systems Biology, Synthetic Biology, Metabolic Engineering"

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Boyle, Patrick M. "Network-Scale Engineering: Systems Approaches to Synthetic Biology." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10298.

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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.
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Libis, Vincent. "New inputs for synthetic biological systems." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCC127/document.

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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
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Triana, Dopico Julián. "Model-based analysis and metabolic design of a cyanobacterium for bio-products synthesis." Doctoral thesis, Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/39351.

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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
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Merrick, Christine. "A synthetic biology approach to metabolic pathway engineering." Thesis, University of Glasgow, 2015. http://theses.gla.ac.uk/6383/.

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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.
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Torella, Joseph Peter. "Synthetic biology approaches to bio-based chemical production." Thesis, Harvard University, 2014. http://nrs.harvard.edu/urn-3:HUL.InstRepos:13088835.

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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.
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Pedersen, Michael. "Modular languages for systems and synthetic biology." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4602.

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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.
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Martínez-Klimova, Elena. "Synthetic biology approaches to the metabolic engineering of Geobacillus thermoglucosidans for isobutanol production." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/45409.

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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.
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Campodonico, Alt Miguel Ángel. "Systems biology and chemoinformatics methods for biomining and systems metabolic engineering applications." Tesis, Universidad de Chile, 2014. http://repositorio.uchile.cl/handle/2250/132047.

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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.
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McArthur, George Howard IV. "Orthogonal Expression of Metabolic Pathways." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3087.

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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.
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Huttanus, Herbert M. "Screening and Engineering Phenotypes using Big Data Systems Biology." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/102706.

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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
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Books on the topic "Systems Biology, Synthetic Biology, Metabolic Engineering"

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Zhao, Huimin, and An-Ping Zeng, eds. Synthetic Biology – Metabolic Engineering. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-55318-4.

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Pengcheng, Fu, and Panke Sven, eds. Systems biology and synthetic biology. Hoboken, N.J: John Wiley & Sons, 2009.

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Selvarajoo, Kumar, ed. Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-2617-7.

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Wittmann, Christoph. Systems Metabolic Engineering. Dordrecht: Springer Netherlands, 2012.

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Alper, Hal S. Systems metabolic engineering: Methods and protocols. New York: Humana Press, 2013.

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Clay, Sylvia M. Developing Biofuel Bioprocesses Using Systems and Synthetic Biology. New York, NY: Springer New York, 2013.

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Pray, Leslie A. The science and applications of synthetic and systems biology: Workshop summary. Washington, D.C: National Academies Press, 2011.

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Metabolic flux analysis: Methods and protocols. New York: Humana Press, 2014.

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Chen, Bor-Sen, and Chia-Chou Wu. Systems Biology: An Integrated Platform for Bioinformatics, Systems Synthetic Biology and Systems Metabolic Engineering. Nova Science Publishers, Incorporated, 2014.

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Zeng, An-Ping, and Huimin Zhao. Synthetic Biology – Metabolic Engineering. Springer, 2018.

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Book chapters on the topic "Systems Biology, Synthetic Biology, Metabolic Engineering"

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Yan, Qiang, and Stephen S. Fong. "Biosensors for Metabolic Engineering." In Systems Biology Application in Synthetic Biology, 53–70. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-2809-7_5.

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Becker, Judith, Gideon Gießelmann, Sarah Lisa Hoffmann, and Christoph Wittmann. "Corynebacterium glutamicum for Sustainable Bioproduction: From Metabolic Physiology to Systems Metabolic Engineering." In Synthetic Biology – Metabolic Engineering, 217–63. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/10_2016_21.

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Singh, Vijai, Indra Mani, and Dharmendra Kumar Chaudhary. "Metabolic Engineering of Microorganisms for Biosynthesis of Antibiotics." In Systems and Synthetic Biology, 341–56. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9514-2_18.

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Roldão, António, Il-Kwon Kim, and Jens Nielsen. "Bridging Omics Technologies with Synthetic Biology in Yeast Industrial Biotechnology." In Systems Metabolic Engineering, 271–327. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4534-6_9.

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Pei, Lei, and Markus Schmidt. "Sustainable Assessment on Using Bacterial Platform to Produce High-Added-Value Products from Berries through Metabolic Engineering." In Systems Biology Application in Synthetic Biology, 71–78. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-2809-7_6.

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Nikel, Pablo I. "Systems and Synthetic Biology Approaches for Metabolic Engineering of Pseudomonas putida." In Microbial Models: From Environmental to Industrial Sustainability, 3–22. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2555-6_1.

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Papoutsakis, Eleftherios T., and Keith V. Alsaker. "Towards a Synthetic Biology of the Stress-Response and the Tolerance Phenotype: Systems Understanding and Engineering of the Clostridium acetobutylicum Stress-Response and Tolerance to Toxic Metabolites." In Systems Metabolic Engineering, 193–219. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4534-6_7.

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Zhu, Qinlong, and Yao-Guang Liu. "TransGene Stacking II Vector System for Plant Metabolic Engineering and Synthetic Biology." In Methods in Molecular Biology, 19–35. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1068-8_2.

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Marx, Hans, Stefan Pflügl, Diethard Mattanovich, and Michael Sauer. "Synthetic Biology Assisting Metabolic Pathway Engineering." In Synthetic Biology, 255–80. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-22708-5_7.

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Guo, Weihua, Jiayuan Sheng, and Xueyang Feng. "Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production." In Synthetic Biology – Metabolic Engineering, 265–99. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/10_2017_2.

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Conference papers on the topic "Systems Biology, Synthetic Biology, Metabolic Engineering"

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Malcata, F. Xavier. "Engineering of microalgae toward biodiesel: Facts and prospects." In 2022 AOCS Annual Meeting & Expo. American Oil Chemists' Society (AOCS), 2022. http://dx.doi.org/10.21748/jeul5047.

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Excessive release to the atmosphere of greenhouse-effect gases—arising from combustion of fossil fuels, has urged a worldwide search for alternative sources of environment-friendly fuels; microalgae constitute an interesting possibility, owing to their widespread presence in most habitats and unique ability to synthesize oil. Microalgae require indeed only sunlight and water to grow—both freely available; together with CO2 as source of carbon—which concomitantly conveys a path for its direct sequestering from the atmosphere; and low-cost inorganic sources of phosphorus and nitrogen. However, the efficiency of the associated metabolic processes is still poor—and this has so far hampered economic feasibility of such microbial factories for eventual manufacture of biodiesel. Recent advances in genetic engineering tools, systems and synthetic biology, and bioinformatics and omics have widened the portfolio of possibilities for tailor-made genome engineering of microalgae. A holistic approach is needed to metabolic engineering, in which various aspects of cellular metabolism—including transcription factors, transporters, competing pathways, and balance between growth and proliferation are to be taken into account. In attempts to harness the potential of genetic engineering upon microalga-mediated oil production, a realistic assessment of risks and opportunities is a must. The current state-of-the-art of metabolic engineering approaches will accordingly be presented, aimed at enhancing lipid productivity by microalgal strains; technical issues will be critically discussed as well. An overview of the challenges and prospects for technical applicability of such techniques will be tackled, focused on oil for esterification downstream as biodiesel—along with ethical concerns associated to large-scale utilization of such tools.
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"Metabolic engineering of corynebacteria to create a producer of L-valine." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-317.

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Jensen, P. A., and J. A. Papin. "A scalable systems analysis approach for regulated metabolic networks." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2009. http://dx.doi.org/10.1109/iembs.2009.5334060.

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Egan, Paul F., Jonathan Cagan, Christian Schunn, and Philip R. LeDuc. "Utilizing Emergent Levels to Facilitate Complex Systems Design: Demonstrated in a Synthetic Biology Domain." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12072.

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Designing complex systems often requires consideration of many components interacting across vast scales of space and time, thus producing highly challenging design spaces to search. In particular, nano-based technologies may require considerations of how nanoscale (10−9) embodiments affect macroscale (∼100) systems and typically have multiple layers of emergent behavior. It is frequently cited that counter-intuitive properties of emergence complicates design tasks; however, we investigate whether some multiscale emergent systems have organizational levels that may inform more effective design methods and searches. Investigations are conducted by extending an agent-based simulation that predicts the emergent interactions of myosin motors interacting with a motile actin filament. Both the behaviors of individual motors and an ensemble of motors are stochastic, therefore analytical methods are often unable to form accurate design evaluations and computationally intensive simulations are required for investigation. Our modification of the simulation enables the prediction of the duration of time that motors will carry an actin filament before system dissociation (termed its processive life-time), which is a vital performance metric for future nanotechnology designs such as molecular sorters. Virtual experiments were conducted that determines how perturbations of synthetic myosin design configurations, and the number of myosins present, affects emergent ensemble performance with respect to run-length and energy usage. It is found that all systems have nearly identical average processive life-times for a given input energy regardless of how much energy individual myosins utilize. Such a finding reduces the total information that a designer must consider, since it is a fundamental relationship that holds regardless of lower level component configurations. Such relationships may occur in complex systems in additional domains, and knowledge of these emergent relationships could greatly facilitate the efficiencies of design methods and automated searches for future technologies.
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Bay, Brian, and Mike Bailey. "Pre-Programmed Failure Behavior Using Biology-Inspired Structures." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34685.

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Core (filler) materials are key components of the sandwich panel and box-beams that are used in the design of lightweight structures. They perform a variety of elastic-range functions such as transferring and supporting working stresses and energy and collapse management. There is an increasing demand, however, for post-yield performance characteristics such as buckling control, impact toughness, and maintenance of component strength after damage. Low density is also an important consideration, as overall component mass is critical in most applications. These cellular solids need to perform well under normal working stress conditions, yet still resist damage from simple and unavoidable low velocity impacts. A new design approach is suggested by biological systems that have evolved for toughness and damage tolerance (bones, trees, plants, corals, etc.). These systems share the relatively low density cellular arrangements of common synthetic core materials, but also exhibit variable density gradients within the core. (Figures 1 and 2) This paper describes engineering design methods that are inspired by such biology. The result is that a design’s failure modes can be more effectively “designed-in”, controlling locations and amounts of failure.
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Reports on the topic "Systems Biology, Synthetic Biology, Metabolic Engineering"

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Gupta, Shweta. Synthetic Biology: The Gateway to Future Biotechnological Industry. Science Repository OÜ, May 2021. http://dx.doi.org/10.31487/sr.blog.34.

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Synthetic biology has come up as a new interdisciplinary area involving the application of engineering principles in the field of biology aiming at fabricating and redesigning biological systems and components that are not naturally found in the world.
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Jung, Carina, Karl Indest, Matthew Carr, Richard Lance, Lyndsay Carrigee, and Kayla Clark. Properties and detectability of rogue synthetic biology (SynBio) products in complex matrices. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45345.

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Synthetic biology (SynBio) aims to rationally engineer or modify traits of an organism or integrate the behaviors of multiple organisms into a singular functional organism through advanced genetic engineering techniques. One objective of this research was to determine the environmental persistence of engineered DNA in the environment. To accomplish this goal, the environmental persistence of legacy engineered DNA building blocks were targeted that laid the foundation for SynBio product development and application giving rise to “post-use products.” These building blocks include genetic constructs such as cloning and expression vectors, promoter/terminator elements, selectable markers, reporter genes, and multi-cloning sites. Shotgun sequencing of total DNA from water samples of pristine sites was performed and resultant sequence data mined for frequency of legacy recombinant DNA signatures. Another objective was to understand the fate of a standardized contemporary synthetic genetic construct (SC) in the context of various chassis systems/genetic configurations representing different degrees of “genetic bioavailability” to the environmental landscape. These studies were carried out using microcosms representing different environmental matrices (soils, waters, wastewater treatment plant (WWTP) liquor) and employed a novel genetic reporter system based on volatile organic compounds (VOC) detection to assess proliferation and persistence of the SC in the matrix over time.
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