Design Of Metabolic Engineering Strategies Research Articles

Mechanistic modeling of redox balance effects on the fermentation of eucalyptus wood-derived xylose to acetone-butanol-ethanol

A Michaelis-Menten-like kinetic model is proposed to simulate the effects of redox balance on Clostridium beijerinckii NCIMB 8052 metabolism during fermentation of biomass-derived xylose to acetone-butanol-ethanol (ABE). The model builds on previous metabolic kinetic models by introducing six mass balance differential equations for the redox pairs NADH/NAD+, NADPH/NADP+, and oxidized/reduced ferredoxin. Batch cultures were conducted using laboratory-grade or eucalyptus-derived xylose, and kinetic parameters were estimated by minimizing the difference between experimental (substrate, metabolites, and cell) and model results using a genetic optimization algorithm. The simulations agreed well with experimental data, and a sensitivity analysis showed that the rate of reoxidation of reduced ferredoxin used for NADPH regeneration is the most relevant reaction for the synthesis of acids and ABE. Furthermore, an increase in NADPH consumption due to the reduction of eucalyptus-derived furfural to furfuryl alcohol was only significant for the production of butanol. Differences in the values of the Michaelis-Menten constants, Km’s, depending on the xylose source, suggest that a decrease in the conversion rates of lactate to pyruvate and acetate to acetyl-CoA considerably affected the biosynthesis of butanol from eucalyptus-derived xylose. The proposed model was effective in assessing the effects of redox balance on ABE fermentation, suggesting its use for the design of metabolic engineering strategies to improve butanol synthesis from furfural-containing biomass hydrolysates.

Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies

BackgroundPseudomonas putida is a promising candidate for the industrial production of biofuels and biochemicals because of its high tolerance to toxic compounds and its ability to grow on a wide variety of substrates. Engineering this organism for improved performances and predicting metabolic responses upon genetic perturbations requires reliable descriptions of its metabolism in the form of stoichiometric and kinetic models.ResultsIn this work, we developed kinetic models of P. putida to predict the metabolic phenotypes and design metabolic engineering interventions for the production of biochemicals. The developed kinetic models contain 775 reactions and 245 metabolites. Furthermore, we introduce here a novel set of constraints within thermodynamics-based flux analysis that allow for considering concentrations of metabolites that exist in several compartments as separate entities. We started by a gap-filling and thermodynamic curation of iJN1411, the genome-scale model of P. putida KT2440. We then systematically reduced the curated iJN1411 model, and we created three core stoichiometric models of different complexity that describe the central carbon metabolism of P. putida. Using the medium complexity core model as a scaffold, we generated populations of large-scale kinetic models for two studies. In the first study, the developed kinetic models successfully captured the experimentally observed metabolic responses to several single-gene knockouts of a wild-type strain of P. putida KT2440 growing on glucose. In the second study, we used the developed models to propose metabolic engineering interventions for improved robustness of this organism to the stress condition of increased ATP demand.ConclusionsThe study demonstrates the potential and predictive capabilities of the kinetic models that allow for rational design and optimization of recombinant P. putida strains for improved production of biofuels and biochemicals. The curated genome-scale model of P. putida together with the developed large-scale stoichiometric and kinetic models represents a significant resource for researchers in industry and academia.

Modulation of benzylisoquinoline alkaloid biosynthesis by overexpression berberine bridge enzyme in Macleaya cordata

Macleaya cordata produces a variety of benzylisoquinoline alkaloids (BIAs), such as sanguinarine, protopine, and berberine, which are potential anticancer drugs and natural growth promoters. The genes encoding the berberine bridge enzyme (BBE) were isolated from M. cordata and Papaver somniferum, and then the two genes were overexpressed in M. cordata. Through liquid chromatography with triple-quadrupole mass spectrometry analysis, it was determined that McBBE-OX caused higher levels of (S)-norcoclaurine, (S)-coclaurine, (S)-N-cis-methylcoclaurine, (S)-reticuline, (S)-tetrahydrocolumbamine, (S)-tetrahydroberberine, (S)-cheilanthifoline, and (S)-scoulerine than PsBBE-OX, empty vector or control treatments. qRT-PCR analysis demonstrated that the introduced genes in the transgenic lines were all highly expressed. However, the levels of sanguinarine (SAN) and chelerythrine (CHE) in all the transgenic lines were slightly lower than those in the wild-type lines, possibly because the overexpression of McBBE causes feedback-inhibition. This is the first report on the overexpression of potential key genes in M. cordata, and the findings are important for the design of metabolic engineering strategies that target BIAs biosynthesis.

Microbial Cell Factories à la Carte: Elimination of Global Regulators Cra and ArcA Generates Metabolic Backgrounds Suitable for the Synthesis of Bioproducts in Escherichia coli.

Manipulation of global regulators is one of the strategies used for the construction of bacterial strains suitable for the synthesis of bioproducts. However, the pleiotropic effects of these regulators can vary under different conditions and are often strain dependent. This study analyzed the effects of ArcA, CreC, Cra, and Rob using single deletion mutants of the well-characterized and completely sequenced Escherichia coli strain BW25113. Comparison of the effects of each regulator on the synthesis of major extracellular metabolites, tolerance to several compounds, and synthesis of native and nonnative bioproducts under different growth conditions allowed the discrimination of the particular phenotypes that can be attributed to the individual mutants and singled out Cra and ArcA as the regulators with the most important effects on bacterial metabolism. These data were used to identify the most suitable backgrounds for the synthesis of the reduced bioproducts succinate and 1,3-propanediol (1,3-PDO). The Δcra mutant was further modified to enhance succinate synthesis by the addition of enzymes that increase NADH and CO2 availability, achieving an 80% increase compared to the parental strain. Production of 1,3-PDO in the ΔarcA mutant was optimized by overexpression of PhaP, which increased more than twice the amount of the diol compared to the wild type in a semidefined medium using glycerol, resulting in 24 g · liter-1 of 1,3-PDO after 48 h, with a volumetric productivity of 0.5 g · liter-1 h-1IMPORTANCE Although the effects of many global regulators, especially ArcA and Cra, have been studied in Escherichia coli, the metabolic changes caused by the absence of global regulators have been observed to differ between strains. This scenario complicates the identification of the individual effects of the regulators, which is essential for the design of metabolic engineering strategies. The genome of Escherichia coli BW25113 has been completely sequenced and does not contain additional mutations that could mask or interfere with the effects of the global regulator mutations. The uniform genetic background of the Keio collection mutants enabled the characterization of the physiological consequences of altered carbon and redox fluxes caused by each global regulator deletion, eliminating possible strain-dependent results. As a proof of concept, Δcra and ΔarcA mutants were subjected to further manipulations to obtain large amounts of succinate and 1,3-PDO, demonstrating that the metabolic backgrounds of the mutants were suitable for the synthesis of bioproducts.

Design of Metabolic Engineering Strategies for Biosynthesis of Valuable Products

Design of Metabolic Engineering Strategies for Biosynthesis of Valuable Products

Genome-scale model guided design of Propionibacterium for enhanced propionic acid production

Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in Propionibacterium. We also describe the benefit of carbon dioxide to propionibacteria growth, substrate conversion and propionate yield.

Designing metabolic engineering strategies with genome-scale metabolic flux modeling

Designing metabolic engineering strategies with genome-scale metabolic flux modeling Jiun Y Yen,1,2 Imen Tanniche,1 Amanda K Fisher,1–3 Glenda E Gillaspy,2 David R Bevan,2,3 Ryan S Senger,1 1Department of Biological Systems Engineering, 2Department of Biochemistry, 3Genomics, Bioinformatics, and Computational Biology Interdisciplinary Program, Virginia Tech, Blacksburg, VA, USA Abstract: New in silico tools that make use of genome-scale metabolic flux modeling are improving the design of metabolic engineering strategies. This review highlights the latest developments in this area, explains the interface between these in silico tools and the experimental implementation tools of metabolic engineers, and provides a way forward so that in silico predictions can better mimic reality and more experimental methods can be considered in simulation studies. The several methodologies for solving genome-scale models (eg, flux balance analysis [FBA], parsimonious FBA, flux variability analysis, and minimization of metabolic adjustment) all have unique advantages and applications. There are two basic approaches to designing metabolic engineering strategies in silico, and both have demonstrated success in the literature. The first involves: 1) making a genetic manipulation in a model; 2) testing for improved performance through simulation; and 3) iterating the process. The second approach has been used in more recently designed in silico tools and involves: 1) comparing metabolic flux profiles of a wild-type and ideally engineered state and 2) designing engineering strategies based on the differences in these flux profiles. Improvements in genome-scale modeling are anticipated in areas such as the inclusion of all relevant cellular machinery, the ability to understand and anticipate the results of combinatorial enrichment experiments, and constructing dynamic and flexible biomass equations that can respond to environmental and genetic manipulations. Keywords: genome-scale modeling, genome-scale modeling, flux balance analysis, flux variability analysis, minimization of metabolic adjustment, metabolic bottleneck, pathway optimization

Reconstruction of the Saccharopolyspora erythraea genome-scale model and its use for enhancing erythromycin production

Genome-scale metabolic reconstructions are routinely used for the analysis and design of metabolic engineering strategies for production of primary metabolites. The use of such reconstructions for metabolic engineering of antibiotic production is not common due to the lack of simple design algorithms in the absence of a cellular growth objective function. Here, we present the metabolic network reconstruction for the erythromycin producer Saccharopolyspora erythraea NRRL23338. The model was manually curated for primary and secondary metabolism pathways and consists of 1,482 reactions (2,075 genes) and 1,646 metabolites. As part of the model validation, we explored the potential benefits of supplying amino acids and identified five amino acids "compatible" with erythromycin production, whereby if glucose is supplemented with this amino acid on a carbon mole basis, the in silico model predicts that high erythromycin yield is possible without lowering biomass yield. Increased erythromycin titre was confirmed for four of the five amino acids, namely valine, isoleucine, threonine and proline. In bioreactor experiments, supplementation with 2.5 % carbon mole of valine increased the growth rate by 20 % and simultaneously the erythromycin yield on biomass by 50 %. The model presented here can be used as a framework for the future integration of high-throughput biological data sets in S. erythraea and ultimately to realise strain designs capable of increasing erythromycin production closer to the theoretical yield.

Evaluating Sphingolipid Biochemistry in the Consensus Reconstruction of Yeast Metabolism

Abstract Reconstructed metabolic networks are the basis for genome-scale models of cellular metabolism. Such models have demonstrated good predictive accuracy when analyzed with the optimization-based approach of flux balance analysis, so are of particular interest for informing the rational design of metabolic engineering strategies for industrial biotechnology applications. As a preliminary step towards applying a metabolic model of the industrially important yeast Saccharomyces cerevisiae, we validated the underlying reconstruction of yeast metabolism in the Yeast Consensus Reconstruction by examining the model’s representation of yeast sphingolipid metabolism. Sphingolipids, which comprise 30% of the plasma membrane lipids in yeast, incorporate very long chain fatty acids of lengths up to C-26. Such long-chain hydrocarbons are of particular interest for the production of liquid transportation fuels. We began with a literature review and consultation with experts in yeast sphingolipid metabolism to com...

A systems-level approach for metabolic engineering of yeast cell factories

The generation of novel yeast cell factories for production of high-value industrial biotechnological products relies on three metabolic engineering principles: design, construction, and analysis. In the last two decades, strong efforts have been put on developing faster and more efficient strategies and/or technologies for each one of these principles. For design and construction, three major strategies are described in this review: (1) rational metabolic engineering; (2) inverse metabolic engineering; and (3) evolutionary strategies. Independent of the selected strategy, the process of designing yeast strains involves five decision points: (1) choice of product, (2) choice of chassis, (3) identification of target genes, (4) regulating the expression level of target genes, and (5) network balancing of the target genes. At the construction level, several molecular biology tools have been developed through the concept of synthetic biology and applied for the generation of novel, engineered yeast strains. For comprehensive and quantitative analysis of constructed strains, systems biology tools are commonly used and using a multi-omics approach. Key information about the biological system can be revealed, for example, identification of genetic regulatory mechanisms and competitive pathways, thereby assisting the in silico design of metabolic engineering strategies for improving strain performance. Examples on how systems and synthetic biology brought yeast metabolic engineering closer to industrial biotechnology are described in this review, and these examples should demonstrate the potential of a systems-level approach for fast and efficient generation of yeast cell factories.

Genome-scale reconstruction of metabolic network for a halophilic extremophile, Chromohalobacter salexigens DSM 3043.

BackgroundChromohalobacter salexigens (formerly Halomonas elongata DSM 3043) is a halophilic extremophile with a very broad salinity range and is used as a model organism to elucidate prokaryotic osmoadaptation due to its strong euryhaline phenotype.ResultsC. salexigens DSM 3043's metabolism was reconstructed based on genomic, biochemical and physiological information via a non-automated but iterative process. This manually-curated reconstruction accounts for 584 genes, 1386 reactions, and 1411 metabolites. By using flux balance analysis, the model was extensively validated against literature data on the C. salexigens phenotypic features, the transport and use of different substrates for growth as well as against experimental observations on the uptake and accumulation of industrially important organic osmolytes, ectoine, betaine, and its precursor choline, which play important roles in the adaptive response to osmotic stress.ConclusionsThis work presents the first comprehensive genome-scale metabolic model of a halophilic bacterium. Being a useful guide for identification and filling of knowledge gaps, the reconstructed metabolic network iOA584 will accelerate the research on halophilic bacteria towards application of systems biology approaches and design of metabolic engineering strategies.

Design of Metabolic Engineering Strategies for Maximizing l-(-)-Carnitine Production by Escherichia coli. Integration of the Metabolic and Bioreactor Levels

In this work metabolic engineering strategies for maximizing L-(-)-carnitine production by Escherichia coli based on the Biochemical System Theory and the Indirect Optimization Method are presented. The model integrates the metabolic and the bioreactor levels using power-law formalism. Based on the S-system model, the Indirect Optimization Method was applied, leading to profiles of parameter values that are compatible with both the physiology of the cells and the bioreactor system operating conditions. This guarantees their viability and fitness and yields higher rates of L-(-)-carnitine production. Experimental results using a high cell density reactor were compared with optimized predictions from the Indirect Optimization Method. When two parameters (the dilution rate and the initial crotonobetaine concentration) were directly changed in the real experimental system to the prescribed optimum values, the system showed better performance in L-(-)-carnitine production (74% increase in production rate), in close agreement with the model's predictions. The model shows control points at macroscopic (reactor operation) and microscopic (molecular) levels where conversion and productivity can be increased. In accordance with the optimized solution, the next logical step to improve the L-(-)-carnitine production rate will involve metabolic engineering of the E. coli strain by overexpressing the carnitine transferase, CaiB, activity and the protein carrier, CaiT, responsible for substrate and product transport in and out of the cell. By this means it is predicted production may be enhanced by up to three times the original value.

Modulation of berberine bridge enzyme levels in transgenic root cultures of California poppy alters the accumulation of benzophenanthridine alkaloids.

California poppy (Eschscholzia californica Cham.) root cultures produce a variety of benzophenanthridine alkaloids, such as sanguinarine, chelirubine and macarpine, with potent biological activity. Sense and antisense constructs of genes encoding the berberine bridge enzyme (BBE) were introduced into California poppy root cultures. Transgenic roots expressing BBE from opium poppy (Papaver somniferum L.) displayed higher levels of BBE mRNA, protein and enzyme activity, and increased accumulation of benzophenanthridine alkaloids compared to control roots transformed with a beta-glucuronidase gene. In contrast, roots transformed with an antisense-BBE construct from California poppy had lower levels of BBE mRNA and enzyme activity, and reduced benzophenanthridine alkaloid accumulation, relative to controls. Pathway intermediates were not detected in any transgenic root lines. Suppression of benzophenanthridine alkaloid biosynthesis using antisense-BBE also reduced the growth rate of the root cultures. Two-dimensional 1H-NMR spectroscopy showed no difference in the abundance of carbohydrate metabolites in the various transgenic roots lines. However, transformed roots with low levels of benzophenanthridine alkaloids contained larger cellular pools of certain amino acids compared to controls. In contrast, cellular pools of several amino acids were reduced in transgenic roots with elevated benzophenanthridine alkaloid levels relative to controls. The relative abundance of tyrosine, from which benzophenanthridine alkaloids are derived, was only marginally altered in all transgenic root lines; thus, altering metabolic flux through benzophenanthridine alkaloid pathways can affect cellular pools of specific amino acids. Consideration of such interactions is important for the design of metabolic engineering strategies that target benzophenanthridine alkaloid biosynthesis.

Metabolic characterization of Lactococcus lactis deficient in lactate dehydrogenase using in vivo 13C-NMR.

The metabolism of glucose by nongrowing cells of Lactococcus lactis strain FI7851, constructed from the wild-type L. lactis strain MG1363 by disruption of the lactate dehydrogenase (ldh) gene [Gasson, M.J., Benson, K., Swindel, S. & Griffin, H. (1996) Lait 76, 33-40] was studied in a noninvasive manner by 13C-NMR. The kinetics of the build-up and consumption of the pools of intracellular intermediates mannitol 1-phosphate, fructose 1,6-bisphosphate, 3-phosphoglycerate, and phosphoenolpyruvate as well as the utilization of [1-13C]glucose and formation of products (lactate, acetate, mannitol, ethanol, acetoin, 2,3-butanediol) were monitored in vivo with a time resolution of 30 s. The metabolism of glucose by the parental wild-type strain was also examined for comparison. A clear shift from typical homolactic fermentation (parental strain) to a mixed acid fermentation (lactate dehdydrogenase deficient; LDHd strain) was observed. Furthermore, high levels of mannitol were transiently produced and metabolized once glucose was depleted. Mannitol 1-phosphate accumulated intracellularly up to 76 mM concentration. Mannitol was formed from fructose 6-phosphate by the combined action of mannitol-1-phosphate dehydrogenase and phosphatase. The results show that the formation of mannitol 1-phosphate by the LDHd strain during glucose catabolism is a consequence of impairment in NADH oxidation caused by a highly reduced LDH activity, the transient production of mannitol 1-phosphate serving as a regeneration pathway for NAD+ regeneration. Oxygen availability caused a drastic change in the pattern of intermediates and end-products, reinforcing the key-role of the fulfilment of the redox balance. The flux control coefficients for the step catalysed by mannitol-1-phosphate dehydrogenase were calculated and the implications in the design of metabolic engineering strategies are discussed.

Exopolysaccharides produced by Lactococcus lactis: from genetic engineering to improved rheological properties?

Over the last years, important advances have been made in the study of the production of exopolysaccharides (EPS) by several lactic acid bacteria, including Lactococcus lactis. From different EPS-producing lactococcal strains the specific eps gene clusters have been characterised. They contain eps genes, which are involved in EPS repeating unit synthesis, export, polymerisation, and chain length determination. The function of the glycosyltransferase genes has been established and the availability of these genes opened the way to EPS engineering. In addition to the eps genes, biosynthesis of EPS requires a number of housekeeping genes that are involved in the metabolic pathways leading to the EPS-building blocks, the nucleotide sugars. The identification and characterisation of several of these housekeeping genes (galE, galU, rfbABCD) allows the design of metabolic engineering strategies that should lead to increased EPS production levels by L. lactis. Finally, model development has been initiated in order to predict the physicochemical consequences of the addition of a EPS to a product.