Improving photofermentative hydrogen production through metabolic engineering and DOE (Design of Experiments)

A l’heure actuelle, les biocarburants renouvelables et qui ne nuit pas à l'environnement sont à l'étude intensive en raison de l'augmentation des problèmes de santé et de la diminution des combustibles fossiles. H2 est l'un des candidats les plus prometteurs en raison de ses caractéristiques uniques, telles que la densité d'énergie élevée et la génération faible ou inexistante de polluants. Une façon attrayante pour produire la H2 est par les bactéries photosynthétiques qui peuvent capter l'énergie lumineuse pour actionner la production H2 avec leur système de nitrogénase. L'objectif principal de cette étude était d'améliorer le rendement de H2 des bactéries photosynthétiques pourpres non sulfureuses utilisant une combinaison de génie métabolique et le plan des expériences. Une hypothèse est que le rendement en H2 pourrait être améliorée par la redirection de flux de cycle du Calvin-Benson-Bassham envers du système de nitrogénase qui catalyse la réduction des protons en H2. Ainsi, un PRK, phosphoribulose kinase, mutant « knock-out » de Rhodobacter capsulatus JP91 a été créé. L’analyse de la croissance sur des différentes sources de carbone a montré que ce mutant ne peut croître qu’avec l’acétate, sans toutefois produire d' H2. Un mutant spontané, YL1, a été récupéré qui a retenu l'cbbP (codant pour PRK) mutation d'origine, mais qui avait acquis la capacité de se développer sur le glucose et produire H2. Une étude de la production H2 sous différents niveaux d'éclairage a montré que le rendement d’YL1 était de 20-40% supérieure à la souche type sauvage JP91. Cependant, il n'y avait pas d'amélioration notable du taux de production de H2. Une étude cinétique a montré que la croissance et la production d'hydrogène sont fortement liées avec des électrons à partir du glucose principalement dirigés vers la production de H2 et la formation de la biomasse. Sous des intensités lumineuses faibles à intermédiaires, la production d'acides organiques est importante, ce qui suggère une nouvelle amélioration additionnel du rendement H2 pourrait être possible grâce à l'optimisation des processus. Dans une série d'expériences associées, un autre mutant spontané, YL2, qui a un phénotype similaire à YL1, a été testé pour la croissance dans un milieu contenant de l'ammonium. Les résultats ont montré que YL2 ne peut croître que avec de l'acétate comme source de carbone, encore une fois, sans produire de H2. Une incubation prolongée dans les milieux qui ne supportent pas la croissance de YL2 a permis l'isolement de deux mutants spontanés secondaires intéressants, YL3 et YL4. L'analyse par empreint du pied Western a montré que les deux souches ont, dans une gamme de concentrations d'ammonium, l'expression constitutive de la nitrogénase. Les génomes d’YL2, YL3 et YL4 ont été séquencés afin de trouver les mutations responsables de ce phénomène. Fait intéressant, les mutations de nifA1 et nifA2 ont été trouvés dans les deux YL3 et YL4. Il est probable qu'un changement conformationnel de NifA modifie l'interaction protéine-protéine entre NifA et PII protéines (telles que GlnB ou GlnK), lui permettant d'échapper à la régulation par l'ammonium, et donc d'être capable d'activer la transcription de la nitrogénase en présence d'ammonium. On ignore comment le nitrogénase synthétisé est capable de maintenir son activité parce qu’en théorie, il devrait également être soumis à une régulation post-traductionnelle par ammonium. Une autre preuve pourrait être obtenue par l'étude du transcriptome d’YL3 et YL4. Une première étude sur la production d’ H2 par YL3 et YL4 ont montré qu'ils sont capables d’une beaucoup plus grande production d'hydrogène que JP91 en milieu d'ammonium, qui ouvre la porte pour les études futures avec ces souches en utilisant des déchets contenant de l'ammonium en tant que substrats. Enfin, le reformage biologique de l'éthanol à H2 avec la bactérie photosynthétique, Rhodopseudomonas palustris CGA009 a été examiné. La production d'éthanol avec fermentation utilisant des ressources renouvelables microbiennes a été traitée comme une technique mature. Cependant, la plupart des études du reformage de l'éthanol à H2 se sont concentrés sur le reformage chimique à la vapeur, ce qui nécessite généralement une haute charge énergetique et résultats dans les émissions de gaz toxiques. Ainsi le reformage biologique de l'éthanol à H2 avec des bactéries photosynthétiques, qui peuvent capturer la lumière pour répondre aux besoins énergétiques de cette réaction, semble d’être plus prometteuse. Une étude précédente a démontré la production d'hydrogène à partir d'éthanol, toutefois, le rendement ou la durée de cette réaction n'a pas été examiné. Une analyse RSM (méthode de surface de réponse) a été réalisée dans laquelle les concentrations de trois facteurs principaux, l'intensité lumineuse, de l'éthanol et du glutamate ont été variés. Nos résultats ont montré que près de 2 moles de H2 peuvent être obtenus à partir d'une mole d'éthanol, 33% de ce qui est théoriquement possible.

Engineering of fatty acid production and secretion in Saccharomyces cerevisiae

Tese de Doutoramento em Ciências - Especialidade em Biologia

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

CHO cell engineering to prevent polypeptide aggregation and improve therapeutic protein secretion.

The ability to efficiently produce recombinant proteins in a secreted form is highly desirable and cultured mammalian cells such as CHO cells have become the preferred host as they secrete proteins with human-like post-translational modifications. However, attempts to express high levels of particular proteins in CHO cells may consistently result in low yields, even for non-engineered proteins such as immunoglobulins. In this study, we identified the responsible faulty step at the stage of translational arrest, translocation and early processing for such a "difficult-to-express" immunoglobulin, resulting in improper cleavage of the light chain and its precipitation in an insoluble cellular fraction unable to contribute to immunoglobulin assembly. We further show that proper processing and secretion were restored by over-expressing human signal receptor protein SRP14 and other components of the secretion pathway. This allowed the expression of the difficult-to-express protein to high yields, and it also increased the production of an easy-to-express protein. Our results demonstrate that components of the secretory and processing pathways can be limiting, and that engineering of the secretory pathway may be used to improve the secretion efficiency of therapeutic proteins from CHO cells.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Metabolic, biochemical and molecular profiling of Catharanthus roseus flower cultivars and transformed hairy roots for monoterpenoid indole alkaloid accumulation /

Catharanthlls rosellS (L.) G Don is a commercially significant flower species and in addition is the only source of the monoterpenoid indole alkaloids (MIA) vinblastine and vincristine, which are key pharmaceutical compounds that are used to combat a number of different cancers. Therefore, procurement of the antineoplastic agents is difficult but essential procedure. Alternatively, CatharanthllS tissue cultures have been investigated as a source of these agents; however they do not produce vindoline, which is an obligate precursor to vinblastine and vincristine. The interest in developing high MIA cultivars of Catharantlws rosellS has prompted metabolic profiling studies to determine the variability of MIA accumulation of existing flowering cultivars, with particular focus on the vindoline component ofthe pathway. Metabolic profiling studies that used high performance liquid chromatography of MIAs from seedlings and young leaf extracts from 50 different flowering cultivars showed that, except for a single low vindoline cultivar (Vinca Mediterranean DP Orchid), they all accumulate similar levels of MIAs. Further enzymatic studies with extracts from young leaves and from developing seedlings showed that the low vindoline cultivar has a IO-fold lower tabersonine-16-hydroxylase activity than those of CatharanthllS rosellS cv Little Delicata. Additionally, studies aimed at metabolic engineering ofvindoline bios}l1thesis in Catharanthus rosellS hairy root cultures have been performed by expressing the last step in vindoline biosynthesis [Dcacetylvindoline-4-0- acetyltransferase (DAT)]. Enzymatic profiling studies with transformed hairy roots have confirmed that over-expressing DAT leads to lines with high levels of O-acetyltransferase activity when compared to non-expressing hairy roots. One particular DA T over111 expressing hairy root culture (line 7) contained 200 times the OAT activity than leaves of control lines. Additional MIA analyses revealed that DAT over-expressing hairy roots have an altered alkaloid profile with significant variation in the accumulation of h6rhammericine. Further analysis of transformed hairy root line 7 suggests a correlation between the expression of OAT activity and h6rhammericine accumulation with root maturation. These studies show that metabolic and selective enzymatic profiling can enhance our ability to search for relevant MIA pathway mutants and that genetic engineering with appropriate pathway genes shows promise as a tool to modify the MIA profile of Catharanthus roseus.

In silico metabolic modelling of Saccharomyces cerevisiae for the overproduction of succinate using OptKnock and OptGene

Succinate is a naturally occurring metabolite in organism’s cell and is industrially important chemical with various applications in food and pharmaceutical industry. It is also widely used to produce bio-degradable plastics, surfactants, detergents etc. In last decades, emphasis has been given to bio-based chemical production using industrial biotechnology route rather than fossil-based production considering sustainability and environment friendly economy. In this thesis I am presenting a computational model for silico metabolic engineering of Saccharomyces cerevisiae for large scale production of succinate. For metabolic modelling, I have used OptKnock and OptGene optimization algorithms to identify the reactions to delete from the genome-scale metabolic model of S. cerevisiae to overproduce succinate by coupling with organism’s growth. Both OptKnock and OptGene proposed numerous straightforward and non-intuitive deletion strategies when number of constraints including growth constraint to the model were applied. The most interesting strategy identified by both algorithms was deletion combination of pyruvate decarboxylase and Ubiquinol:ferricytochrome c reductase(respiratory enzyme) reactions thereby also suggesting anaerobic fermentation of the organism in glucose medium. Such strategy was never reported earlier for growth-coupled succinate production in S.cerevisiae.

The Penicillium chrysogenum aclA gene encodes a broad-substrate-specificity acyl-coenzyme A ligase involved in activation of adipic acid, a side-chain precursor for cephem antibiotics

Activation of the cephalosporin side-chain precursor to the corresponding CoA-thioester is an essential step for its incorporation into the P-lactam backbone. To identify an acyl-CoA ligase involved in activation of adipate, we searched in the genome database of Penicillium chrysogenum for putative structural genes encoding acyl-CoA ligases. Chemostat-based transcriptome analysis was used to identify the one presenting the highest expression level when cells were grown in the presence of adipate. Deletion of the gene renamed aclA, led to a 32% decreased specific rate of adipate consumption and a threefold reduction of adipoyl-6-aminopenicillanic acid levels, but did not affect penicillin V production. After overexpression in Escherichia coli, the purified protein was shown to have a broad substrate range including adipate. Finally, protein-fusion with cyan-fluorescent protein showed co-localization with microbody-borne acyl-transferase. Identification and functional characterization of aclA may aid in developing future metabolic engineering strategies for improving the production of different cephalosporins. (C) 2009 Elsevier Inc. All rights reserved.

Functional characterization of the oxaloacetase encoding gene and elimination of oxalate formation in the beta-lactam producer Penicillium chrysogenum

Penicillium chrysogenum is widely used as an industrial antibiotic producer, in particular in the synthesis of g-lactam antibiotics such as penicillins and cephalosporins. In industrial processes, oxalic acid formation leads to reduced product yields. Moreover, precipitation of calcium oxalate complicates product recovery. We observed oxalate production in glucose-limited chemostat cultures of P. chrysogenum grown with or without addition of adipic acid, side-chain of the cephalosporin precursor adipoyl-6-aminopenicillinic acid (ad-6-APA). Oxalate accounted for up to 5% of the consumed carbon source. In filamentous fungi, oxaloacetate hydrolase (OAH; EC3.7.1.1) is generally responsible for oxalate production. The P. chrysogenum genome harbours four orthologs of the A. niger oahA gene. Chemostat-based transcriptome analyses revealed a significant correlation between extracellular oxalate titers and expression level of the genes Pc18g05100 and Pc22g24830. To assess their possible involvement in oxalate production, both genes were cloned in Saccharomyces cerevisiae, yeast that does not produce oxalate. Only the expression of Pc22g24830 led to production of oxalic acid in S. cerevisiae. Subsequent deletion of Pc22g28430 in P. chrysogenum led to complete elimination of oxalate production, whilst improving yields of the cephalosporin precursor ad-6-APA. (C) 2011 Elsevier Inc. All rights reserved.

Identification of cellular changes associated with increased production of human growth hormone in a recombinant Chinese hamster ovary cell line

A proteomics approach was used to identify the proteins potentially implicated in the cellular response concomitant with elevated production levels of human growth hormone in a recombinant Chinese hamster ovary (CHO) cell line following exposure to 0.5 mM butyrate and 80 muM zinc sulphate in the production media. This involved incorporation of two-dimensional (2-D) gel electrophoresis and protein identification by a combination of N-terminal sequencing, matrix-assisted laser desorption/ionisation-time of flight mass spectrometry, amino acid analysis and cross species database matching. From these identifications a CHO 2-D reference,map and annotated database have been established. Metabolic labelling and subsequent autoradiography showed the induction of a number of cellular proteins in response to the media additives butyrate and zinc sulphate. These were identified as GRP75, enolase and thioredoxin. The chaperone proteins GRP78, HSP90, GRP94 and HSP70 were not up-regulated under these conditions.

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.