Metabolic Engineering Platform Research Articles

Functional Characterization of a 28-Kilobase Catabolic Island from Pseudomonas sp. Strain M1 Involved in Biotransformation of β-Myrcene and Related Plant-Derived Volatiles.

Pseudomonas sp. strain M1 is able to mineralize highly hydrophobic and recalcitrant compounds, such as benzene, phenol, and their methylated/halogenated derivatives, as well as the backbone of several monoterpenes. The ability to use such a spectrum of compounds as the sole carbon source is, most probably, associated with a genetic background evolved under different environmental constraints. The outstanding performance of strain M1 regarding β-myrcene catabolism was elucidated in this work, with a focus on the biocatalytical potential of the β-myrcene-associated core code, comprised in a 28-kb genomic island (GI), predicted to be organized in 8 transcriptional units. Functional characterization of this locus with promoter probes and analytical approaches validated the genetic organization predicted in silico and associated the β-myrcene-induced promoter activity to the production of β-myrcene derivatives. Notably, by using a whole-genome mutagenesis strategy, different genotypes of the 28-kb GI were generated, resulting in the identification of a novel putative β-myrcene hydroxylase, responsible for the initial oxidation of β-myrcene into myrcen-8-ol, and a sensor-like regulatory protein, whose inactivation abolished the myr+ trait of M1 cells. Moreover, it was demonstrated that the range of monoterpene substrates of the M1 enzymatic repertoire, besides β-myrcene, also includes other acyclic (e.g., β-linalool) and cyclic [e.g., R-(+)-limonene and (-)-β-pinene] molecules. Our findings are the cornerstone for following metabolic engineering approaches and hint at a major role of the 28-kb GI in the biotransformation of a broad monoterpene backbone spectrum for its future biotechnological applications.IMPORTANCE Information regarding microbial systems able to biotransform monoterpenes, especially β-myrcene, is limited and focused mainly on nonsystematic metabolite identification. Complete and detailed knowledge at the genetic, protein, metabolite, and regulatory levels is essential in order to set a model organism or a catabolic system as a biotechnology tool. Moreover, molecular characterization of reported systems is scarce, almost nonexistent, limiting advances in the development of optimized cell factories with strategies based on the new generation of metabolic engineering platforms. This study provides new insights into the intricate molecular functionalities associated with β-myrcene catabolism in Pseudomonas, envisaging the production of a molecular knowledge base about the underlying catalytic and regulatory mechanisms of plant-derived volatile catabolic pathways.

Development of a Framework for Metabolic Pathway Analysis-Driven Strain Optimization Methods.

Genome-scale metabolic models (GSMMs) have become important assets for rational design of compound overproduction using microbial cell factories. Most computational strain optimization methods (CSOM) using GSMMs, while useful in metabolic engineering, rely on the definition of questionable cell objectives, leading to some bias. Metabolic pathway analysis approaches do not require an objective function. Though their use brings immediate advantages, it has mostly been restricted to small scale models due to computational demands. Additionally, their complex parameterization and lack of intuitive tools pose an important challenge towards making these widely available to the community. Recently, MCSEnumerator has extended the scale of these methods, namely regarding enumeration of minimal cut sets, now able to handle GSMMs. This work proposes a tool implementing this method as a Java library and a plugin within the OptFlux metabolic engineering platform providing a friendly user interface. A standard enumeration problem and pipeline applicable to GSMMs is proposed, making use by the community simpler. To highlight the potential of these approaches, we devised a case study for overproduction of succinate, providing a phenotype analysis of a selected strategy and comparing robustness with a selected solution from a bi-level CSOM.

Exploring complex cellular phenotypes and model-guided strain design with a novel genome-scale metabolic model of Clostridium thermocellum DSM 1313 implementing an adjustable cellulosome.

BackgroundClostridium thermocellum is a gram-positive thermophile that can directly convert lignocellulosic material into biofuels. The metabolism of C. thermocellum contains many branches and redundancies which limit biofuel production, and typical genetic techniques are time-consuming. Further, the genome sequence of a genetically tractable strain C. thermocellum DSM 1313 has been recently sequenced and annotated. Therefore, developing a comprehensive, predictive, genome-scale metabolic model of DSM 1313 is desired for elucidating its complex phenotypes and facilitating model-guided metabolic engineering.ResultsWe constructed a genome-scale metabolic model iAT601 for DSM 1313 using the KEGG database as a scaffold and an extensive literature review and bioinformatic analysis for model refinement. Next, we used several sets of experimental data to train the model, e.g., estimation of the ATP requirement for growth-associated maintenance (13.5 mmol ATP/g DCW/h) and cellulosome synthesis (57 mmol ATP/g cellulosome/h). Using our tuned model, we investigated the effect of cellodextrin lengths on cell yields, and could predict in silico experimentally observed differences in cell yield based on which cellodextrin species is assimilated. We further employed our tuned model to analyze the experimentally observed differences in fermentation profiles (i.e., the ethanol to acetate ratio) between cellobiose- and cellulose-grown cultures and infer regulatory mechanisms to explain the phenotypic differences. Finally, we used the model to design over 250 genetic modification strategies with the potential to optimize ethanol production, 6155 for hydrogen production, and 28 for isobutanol production.ConclusionsOur developed genome-scale model iAT601 is capable of accurately predicting complex cellular phenotypes under a variety of conditions and serves as a high-quality platform for model-guided strain design and metabolic engineering to produce industrial biofuels and chemicals of interest.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-016-0607-x) contains supplementary material, which is available to authorized users.

Engineering Saccharomyces cerevisiae with the deletion of endogenous glucosidases for the production of flavonoid glucosides.

BackgroundGlycosylation of flavonoids is a promising approach to improve the pharmacokinetic properties and biological activities of flavonoids. Recently, many efforts such as enzymatic biocatalysis and the engineered Escherichia coli biotransformation have increased the production of flavonoid glucosides. However, the low yield of flavonoid glucosides can not meet the increasing demand for human medical and dietary needs. Saccharomyces cerevisiae is a generally regarded as safe (GRAS) organism that has several attractive characteristics as a metabolic engineering platform for the production of flavonoid glucosides. However, endogenous glucosidases of S.cerevisiae as a whole-cell biocatalyst reversibly hydrolyse the glucosidic bond and hinder the biosynthesis of the desired products. In this study, a model flavonoid, scutellarein, was used to exploit how to enhance the production of flavonoid glucosides in the engineered S.cerevisiae.ResultsTo produce flavonoid glucosides, three flavonoid glucosyltransferases (SbGTs) from Scutellaria baicalensis Georgi were successfully expressed in E. coli, and their biochemical characterizations were identified. In addition, to synthesize the flavonoid glucosides in whole-cell S. cerevisiae, SbGT34 was selected for constructing the engineering yeast. Three glucosidase genes (EXG1, SPR1, YIR007W) were knocked out using homologous integration, and the EXG1 gene was determined to be the decisive gene of S. cerevisiae in the process of hydrolysing flavonoid glucosides. To further enhance the potential glycosylation activity of S. cerevisiae, two genes encoding phosphoglucomutase and UTP-glucose-1-phosphate uridylyltransferase involved in the synthetic system of uridine diphosphate glucose were over-expressed in S. cerevisiae. Consequently, approximately 4.8 g (1.2 g/L) of scutellarein 7-O-glucoside (S7G) was produced in 4 L of medium after 54 h of incubation in a 10-L fermenter while being supplied with ~3.5 g of scutellarein.ConclusionsThe engineered yeast harbouring SbGT with a deletion of glucosidases produced more flavonoid glucosides than strains without a deletion of glucosidases. This platform without glucosidase activity could be used to modify a wide range of valued plant secondary metabolites and to explore of their biological functions using whole-cell S. cerevisiae as a biocatalyst.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-016-0535-2) contains supplementary material, which is available to authorized users.

Dedicated Industrial Oilseed Crops as Metabolic Engineering Platforms for Sustainable Industrial Feedstock Production.

Feedstocks for industrial applications ranging from polymers to lubricants are largely derived from petroleum, a non-renewable resource. Vegetable oils with fatty acid structures and storage forms tailored for specific industrial uses offer renewable and potentially sustainable sources of petrochemical-type functionalities. A wide array of industrial vegetable oils can be generated through biotechnology, but will likely require non-commodity oilseed platforms dedicated to specialty oil production for commercial acceptance. Here we show the feasibility of three Brassicaceae oilseeds crambe, camelina, and carinata, none of which are widely cultivated for food use, as hosts for complex metabolic engineering of wax esters for lubricant applications. Lines producing wax esters >20% of total seed oil were generated for each crop and further improved for high temperature oxidative stability by down-regulation of fatty acid polyunsaturation. Field cultivation of optimized wax ester-producing crambe demonstrated commercial utility of these engineered crops and a path for sustainable production of other industrial oils in dedicated specialty oilseeds.

Efficient Agrobacterium-mediated transformation of Artemisia annua L. using young inflorescence

Artemisia annua L. is currently the only practical source of artemisinin, an effective antimalarial agent. Development of an efficient gene delivery system is crucial for genetic manipulation of this medicinal plant to enhance artemisinin production. Here, we report a protocol for efficient Agrobacterium-mediated transformation and plant regeneration of A. annua using young inflorescence as explants. We evaluated the influence of explant types and Agrobacterium strains on transformation and regeneration efficiency. Young inflorescence and leaf explants were co-cultivated with Agrobacterium tumefaciens strains, EHA105 or LBA4404, carrying the pCAMBIA2301 binary vector containing a s-glucuronidase reporter. Shoot regeneration was observed when explants were incubated on modified Murashige and Skoog (MS) medium supplemented with 0.5 mg L−1 6-benzylaminopurine and 0.3 mg L−1 α-naphthalene acetic acid. Shoot bud development from young inflorescence explants was observed within 7 wk of culture whereas those from the leaf explants regenerated after 9 wk. PCR and Southern blot analyses showed that 95% of the putative transgenic lines were positive for the GUS reporter gene. The maximum transformation frequency of 17% was achieved by co-cultivation of A. tumefaciens strain EHA105 with young inflorescence, representing a twofold improvement compared to using leaf explants. Molecular and genetic analysis of T1 progeny further confirmed the inheritance of the introduced gene. The transformation protocol using young inflorescence of A. annua reduces the transformation time and increases the efficiency; hence, this represents a practical platform for metabolic engineering of this important medicinal plant.

Extremely thermophilic microorganisms as metabolic engineering platforms for production of fuels and industrial chemicals

Enzymes from extremely thermophilic microorganisms have been of technological interest for some time because of their ability to catalyze reactions of industrial significance at elevated temperatures. Thermophilic enzymes are now routinely produced in recombinant mesophilic hosts for use as discrete biocatalysts. Genome and metagenome sequence data for extreme thermophiles provide useful information for putative biocatalysts for a wide range of biotransformations, albeit involving at most a few enzymatic steps. However, in the past several years, unprecedented progress has been made in establishing molecular genetics tools for extreme thermophiles to the point that the use of these microorganisms as metabolic engineering platforms has become possible. While in its early days, complex metabolic pathways have been altered or engineered into recombinant extreme thermophiles, such that the production of fuels and chemicals at elevated temperatures has become possible. Not only does this expand the thermal range for industrial biotechnology, it also potentially provides biodiverse options for specific biotransformations unique to these microorganisms. The list of extreme thermophiles growing optimally between 70 and 100°C with genetic toolkits currently available includes archaea and bacteria, aerobes and anaerobes, coming from genera such as Caldicellulosiruptor, Sulfolobus, Thermotoga, Thermococcus, and Pyrococcus. These organisms exhibit unusual and potentially useful native metabolic capabilities, including cellulose degradation, metal solubilization, and RuBisCO-free carbon fixation. Those looking to design a thermal bioprocess now have a host of potential candidates to choose from, each with its own advantages and challenges that will influence its appropriateness for specific applications. Here, the issues and opportunities for extremely thermophilic metabolic engineering platforms are considered with an eye toward potential technological advantages for high temperature industrial biotechnology.

Construction of new synthetic biology tools for the control of gene expression in the cyanobacterium Synechococcus sp. strain PCC 7002.

Predictive control of gene expression is an essential tool for developing synthetic biological systems. The current toolbox for controlling gene expression in cyanobacteria is a barrier to more in-depth genetic analysis and manipulation. Towards relieving this bottleneck, this work describes the use of synthetic biology to construct an anhydrotetracycline-based induction system and adapt a trans-acting small RNA (sRNA) system for use in the cyanobacterium Synechococcus sp. strain PCC 7002. An anhydrotetracycline-inducible promoter was developed to maximize intrinsic strength and dynamic range. The resulting construct, PEZtet , exhibited tight repression and a maximum 32-fold induction upon addition of anhydrotetracycline. Additionally, a sRNA system based on the Escherichia coli IS10 RNA-IN/OUT regulator was adapted for use in Synechococcus sp. strain PCC 7002. This system exhibited 70% attenuation of target gene expression, providing a demonstration of the use of sRNAs for differential gene expression in cyanobacteria. These systems were combined to produce an inducible sRNA system, which demonstrated 59% attenuation of target gene expression. Lastly, the role of Hfq, a critical component of sRNA systems in E. coli, was investigated. Genetic studies showed that the Hfq homolog in Synechococcus sp. strain PCC 7002 did not impact repression by the engineered sRNA system. In summary, this work describes new synthetic biology tools that can be applied to physiological studies, metabolic engineering, or sRNA platforms in Synechococcus sp. strain PCC 7002.

Tn7-Based Device for Calibrated Heterologous Gene Expression in Pseudomonas putida.

The soil bacterium Pseudomonas putida is increasingly attracting considerable interest as a platform for advanced metabolic engineering through synthetic biology approaches. However, genomic context, gene copy number, and transcription/translation interplay often introduce considerable uncertainty to the design of reliable genetic constructs. In this work, we have established a standardized heterologous expression device in which the promoter strength is the only variable; the remaining parameters of the flow have stable default values. To this end, we tailored a mini-Tn7 delivery transposon vector that inserts the constructs in a single genomic locus of P. putida's chromosome. This was then merged with a promoter insertion site, an unvarying translational coupler, and a downstream location for placing the gene(s) of interest under fixed assembly rules. This arrangement was exploited to benchmark a collection of synthetic promoters with low transcriptional noise in this bacterial host. Growth experiments and flow cytometry with single-copy promoter-GFP constructs revealed a robust, constitutive behavior of these promoters, whose strengths and properties could be faithfully compared. This standardized expression device significantly extends the repertoire of tools available for reliable metabolic engineering and other genetic enhancements of P. putida.

Protein Engineering of Coenzyme‐A‐Dependent Aldehyde Dehydrogenase for Commercial Scale 1,4‐Butanediol Production in Escherichia coli

Genomatica has developed a novel commercial process, the GENO BDO™ process, for direct production of the intermediate 1,4‐butanediol (BDO) from carbohydrate feedstocks. BDO is used in a variety of polymer applications, including polyurethanes and polyesters, with over 1.7 million tons of BDO produced annually. Genomatica has leveraged its integrated metabolic engineering platform to maximize carbon flux through the BDO synthetic pathway. This heterologous pathway includes a coenzyme‐A‐dependent aldehyde dehydrogenase (Ald), which catalyzes the conversion of 4‐hydroxybutryl‐CoA to 4‐hydroxybutyraldehyde in the presence of reduced cofactor. Genomatica has performed extensive protein engineering on this enzyme to develop an Ald biocatalyst with increased substrate specificity that can support the required high flux over the course of the entire fermentation. In this poster, the biochemical characteristics of the Ald variants and their impact on performance will be highlighted.

An integrated biotechnology platform for developing sustainable chemical processes.

Genomatica has established an integrated computational/experimental metabolic engineering platform to design, create, and optimize novel high performance organisms and bioprocesses. Here we present our platform and its use to develop E. coli strains for production of the industrial chemical 1,4-butanediol (BDO) from sugars. A series of examples are given to demonstrate how a rational approach to strain engineering, including carefully designed diagnostic experiments, provided critical insights about pathway bottlenecks, byproducts, expression balancing, and commercial robustness, leading to a superior BDO production strain and process.

An integrated network visualization framework towards metabolic engineering applications.

BackgroundOver the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential.ResultsIn this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks.ConclusionsThe framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-014-0420-0) contains supplementary material, which is available to authorized users.

Preliminary investigation of metabolic engineering in a novel host bacterium Corynebacterium crenatum for alcohol biofuel production

Bio-engineered microorganisms have been proposed as candidates to produce alcohols that can replace dwindling fossil fuel resources. In this paper, we are the first to investigate using a novel engineered bacterium, Corynebacterium crenatum, as a potential cell factory to produce alcohols. We investigated the metabolic engineering of Corynebacterium crenatum by testing the heterologous expression of 2-keto acid decarboxylases and branched-chain amino transferases. We verified that C. crenatum can produce alcohol biofuels by over-expressing several tandem KDCs (2-keto acid decarboxylases) and alcohol dehydrogenases derived from different yeast species. In addition, BAT2 gene (branched-chain amino acid transaminase) from Saccharomyces cerevisiae have also been introduced and investigated the effect of producing alcohols. We successfully enabled this C. crenatum strain to produce ethanol, including the higher alcohols isobutanol, butanol, and 3-methyl-1-butanol. Our results demonstrate that when the kivd gene from Lactococcus lactis subsp. cremoris and the BAT2 gene from S. cerevisiae are simultaneously over-expressed in C. crenatum, ethanol can be produced at concentrations of 5.85 g L−1 from hexose glucose, 7.28 g L−1 from pentose xylose and 6.38 g L−1 from mixed sugars. Additional alcohols can be produced at the following concentrations: isobutanol at 193.66 mg L−1, butanol at 173.07 mg L−1, 3-methyl-1-butanol at 449.60 mg L−1, and pentanol at 28.61 mg L−1. Our results demonstrate that this novel bioengineered strain of C. crenatum can produce a mixture of alcohols and seems to preferentially produce ethanol. Our results also suggest that it may be possible to use this bacterium to synthesize higher alcohols. Our preliminary investigation demonstrates it is possible to develop new bacterial hosts as metabolic engineering platforms for the production of biofuel energy.

IOD907, the first genome-scale metabolic model for the milk yeast Kluyveromyces lactis.

We describe here the first genome-scale metabolic model of Kluyveromyces lactis, iOD907. It is partially compartmentalized (four compartments), composed of 1867 reactions and 1476 metabolites. The iOD907 model performed well when comparing the positive growth of K. lactis to Biolog experiments and to an online catalogue of strains that provides information on carbon sources in which K. lactis is able to grow. Chemostat experiments were used to adjust non-growth-associated energy requirements, and the model proved accurate when predicting the biomass, oxygen and carbon dioxide yields. When compared to published experiments, in silico knockouts accurately predicted in vivo phenotypes. The iOD907 genome-scale metabolic model complies with the MIRIAM (minimum information required for the annotation of biochemical models) standards for the annotation of enzymes, transporters, metabolites and reactions. Moreover, it contains direct links to Kyoto encyclopedia of genes and genomes (KEGG; for enzymes, metabolites and reactions) and to the Transporters Classification Database (TCDB) for transporters, allowing easy comparisons to other models. Furthermore, this model is provided in the well-established systems biology markup language (SBML) format, which means that it can be used in most metabolic engineering platforms, such as OptFlux or Cobra. The model is able to predict the behavior of K. lactis under different environmental conditions and genetic perturbations. Furthermore, by performing simulations and optimizations, it can be important in the design of minimal media and will allow insights on the milk yeast's metabolism, as well as identifying metabolic engineering targets for improving the production of products of interest.

Thermophilic lignocellulose deconstruction

Thermophilic microorganisms are attractive candidates for conversion of lignocellulose to biofuels because they produce robust, effective, carbohydrate-degrading enzymes and survive under harsh bioprocessing conditions that reflect their natural biotopes. However, no naturally occurring thermophile is known that can convert plant biomass into a liquid biofuel at rates, yields and titers that meet current bioprocessing and economic targets. Meeting those targets requires either metabolically engineering solventogenic thermophiles with additional biomass-deconstruction enzymes or engineering plant biomass degraders to produce a liquid biofuel. Thermostable enzymes from microorganisms isolated from diverse environments can serve as genetic reservoirs for both efforts. Because of the sheer number of enzymes that are required to hydrolyze plant biomass to fermentable oligosaccharides, the latter strategy appears to be the preferred route and thus has received the most attention to date. Thermophilic plant biomass degraders fall into one of two categories: cellulosomal (i.e. multienzyme complexes) and noncellulosomal (i.e. 'free' enzyme systems). Plant-biomass-deconstructing thermophilic bacteria from the genera Clostridium (cellulosomal) and Caldicellulosiruptor (noncellulosomal), which have potential as metabolic engineering platforms for producing biofuels, are compared and contrasted from a systems biology perspective.

Modification of β-oxidation pathway in Ralstonia eutropha for production of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) from soybean oil

Ralstonia eutropha H16 is a useful platform for metabolic engineering aiming at efficient production of polyhydroxyalkanaotes being attracted as practical bioplastics. This study focused on bifunctional (S)-specific 2-enoyl-CoA hydratase/(S)-3-hydroxyacyl-CoA dehydrogenase encoded by fadB to obtain information regarding β-oxidation in this bacterium and to achieve compositional regulation of poly((R)-3-hydroxybutyrate-co-(R)-3-hydroxyhexanoate) [P(3HB-co-3HHx)] synthesized from soybean oil. In addition to two FadB homologs (FadB1 and FadB') encoded within the previously identified β-oxidation gene clusters on the chromosome 1, a gene of third homolog (FadB2) was found on chromosome 2 of R.eutropha. The fadB homologs were disrupted in R.eutropha strain NSDG expressing a mutant geneof PHA synthase from Aeromonas caviae. The gene disruptions affected neither growth nor PHA production on fructose. On soybean oil, fadB' deletion led to reduction of PHA quantity attributed to decrease of 3HB unit, while fadB1 deletion slightly increased 3HHx composition without serious negative impact on both cell growth and PHA biosynthesis. Double deletion of fadB1 and fadB' significantly impaired the cell growth and PHA biosynthesis, indicating the major roles of fadB1 and fadB' in β-oxidation. When fadB1 was deleted in several engineered strains of R.eutropha possessing additional (R)-enoyl-CoA hydratase gene(s), the net amounts of 3HHx unit in the PHA fractions showed 6-21% increase probably due to slightly enhanced supply of medium-chain-length 2-enoyl-CoAs through the partially impaired β-oxidation. These results demonstrated that modification of β-oxidation by fadB1 deletion was effective for increasing 3HHx composition in the copolyesters produced from soybean oil.

TNA4OptFlux – a software tool for the analysis of strain optimization strategies

BackgroundRational approaches for Metabolic Engineering (ME) deal with the identification of modifications that improve the microbes’ production capabilities of target compounds. One of the major challenges created by strain optimization algorithms used in these ME problems is the interpretation of the changes that lead to a given overproduction. Often, a single gene knockout induces changes in the fluxes of several reactions, as compared with the wild-type, and it is therefore difficult to evaluate the physiological differences of the in silico mutant. This is aggravated by the fact that genome-scale models per se are difficult to visualize, given the high number of reactions and metabolites involved.FindingsWe introduce a software tool, the Topological Network Analysis for OptFlux (TNA4OptFlux), a plug-in which adds to the open-source ME platform OptFlux the capability of creating and performing topological analysis over metabolic networks. One of the tool’s major advantages is the possibility of using these tools in the analysis and comparison of simulated phenotypes, namely those coming from the results of strain optimization algorithms. We illustrate the capabilities of the tool by using it to aid the interpretation of two E. coli strains designed in OptFlux for the overproduction of succinate and glycine.ConclusionsBesides adding new functionalities to the OptFlux software tool regarding topological analysis, TNA4OptFlux methods greatly facilitate the interpretation of non-intuitive ME strategies by automating the comparison between perturbed and non-perturbed metabolic networks. The plug-in is available on the web site http://www.optflux.org, together with extensive documentation.

Computational evaluation of Synechococcus sp. PCC 7002 metabolism for chemical production

Cyanobacteria are ideal metabolic engineering platforms for carbon-neutral biotechnology because they directly convert CO2 to a range of valuable products. In this study, we present a computational assessment of biochemical production in Synechococcus sp. PCC 7002 (Synechococcus 7002), a fast growing cyanobacterium whose genome has been sequenced, and for which genetic modification methods have been developed. We evaluated the maximum theoretical yields (mol product per mol CO2 or mol photon) of producing various chemicals under photoautotrophic and dark conditions using a genome-scale metabolic model of Synechococcus 7002. We found that the yields were lower under dark conditions, compared to photoautotrophic conditions, due to the limited amount of energy and reductant generated from glycogen. We also examined the effects of photon and CO2 limitations on chemical production under photoautotrophic conditions. In addition, using various computational methods such as minimization of metabolic adjustment (MOMA), relative metabolic change (RELATCH), and OptORF, we identified gene-knockout mutants that are predicted to improve chemical production under photoautotrophic and/or dark anoxic conditions. These computational results are useful for metabolic engineering of cyanobacteria to synthesize value-added products.

In silico strain optimization by adding reactions to metabolic models

Summary Nowadays, the concerns about the environment and the needs to increase the productivity at low costs, demand for the search of new ways to produce compounds with industrial interest. Based on the increasing knowledge of biological processes, through genome sequencing projects, and high-throughput experimental techniques as well as the available computational tools, the use of microorganisms has been considered as an approach to produce desirable compounds. However, this usually requires to manipulate these organisms by genetic engineering and/ or changing the enviromental conditions to make the production of these compounds possible. In many cases, it is necessary to enrich the genetic material of those microbes with hereologous pathways from other species and consequently adding the potential to produce novel compounds.This paper introduces a new plug-in for the OptFlux Metabolic Engineering platform, aimed at finding suitable sets of reactions to add to the genomes of selected microbes (wild type strain), as well as finding complementary sets of deletions, so that the mutant becomes able to overproduce compounds with industrial interest, while preserving their viability. The necessity of adding reactions to the metabolic model arises from existing gaps in the original model or motivated by the productions of new compounds by the organism. The optimization methods used are metaheuristics such as Evolutionary Algorithms and Simulated Annealing. The usefulness of this plug-in is demonstrated by a case study, regarding the production of vanillin by the bacterium E. coli.

Characterization of rhamnolipids produced by wild-type and engineered Burkholderia kururiensis

Biosurfactants are a class of functional molecules produced and secreted by microorganisms, which play important roles in cell physiology such as flagellum-dependent or -independent bacterial spreading, cell signaling, and biofilm formation. They are amphipathic compounds and comprise a variety of chemical structures, including rhamnolipids, typically produced by Pseudomonas spp. and also reported within other bacterial genera. The present study is focused on Burkholderia kururiensis KP23(T), a trichloroethylene (TCE)-degrading, N-fixing, and plant growth-promoting bacterium. Herein, we describe the production of rhamnolipids by B. kururiensis, and its characterization by LTQ-Orbitrap Hybrid Mass Spectrometry, a powerful tool that allowed efficient identification of molecular subpopulations, due to its high selectivity, mass accuracy, and resolving power. The population of rhamnolipids produced by B. kururiensis revealed molecular species commonly observed in Pseudomonas spp. and/or Burkholderia spp. In addition, this strain was used as a platform for expression of two Pseudomonas aeruginosa biosynthetic enzymes: RhlA, which directly utilizes β-hydroxydecanoyl-ACP intermediates in fatty acid synthesis to generate the HAA, and RhlB, the rhamnosyltransferase 1, which catalyzes the transfer of dTDP-L-rhamnose to β-hydroxy fatty acids in the biosynthesis of rhamnolipids. We show that rhamnolipid production by the engineered B. kururiensis was increased over 600% when compared to the wild type. Structural analyses demonstrated a molecular population composed mainly of monorhamnolipids, as opposed to wild-type B. kururiensis and P. aeruginosa in which dirhamnolipids are predominant. We conclude that B. kururiensis is a promising biosurfactant-producing organism, with great potential for environmental and biotechnological applications due to its non-pathogenic characteristics and efficiency as a platform for metabolic engineering and production of tailor-made biosurfactants.