Flux balance analysis of primary metabolism in the diatom Phaeodactylum tricornutum.

Diatoms (Bacillarophyceae) are photosynthetic unicellular microalgae that have risen to ecological prominence in oceans over the past 30 million years. They are of interest as potential feedstocks for sustainable biofuels. Maximizing production of these feedstocks will require genetic modifications and an understanding of algal metabolism. These processes may benefit from genome-scale models, which predict intracellular fluxes and theoretical yields, as well as the viability of knockout and knock-in transformants. Here we present a genome-scale metabolic model of a fully sequenced and transformable diatom: Phaeodactylum tricornutum. The metabolic network was constructed using the P. tricornutum genome, biochemical literature, and online bioinformatic databases. Intracellular fluxes in P. tricornutum were calculated for autotrophic, mixotrophic and heterotrophic growth conditions, as well as knockout conditions that explore the in silico role of glycolytic enzymes in the mitochondrion. The flux distribution for lower glycolysis in the mitochondrion depended on which transporters for TCA cycle metabolites were included in the model. The growth rate predictions were validated against experimental data obtained using chemostats. Two published studies on this organism were used to validate model predictions for cyclic electron flow under autotrophic conditions, and fluxes through the phosphoketolase, glycine and serine synthesis pathways under mixotrophic conditions. Several gaps in annotation were also identified. The model also explored unusual features of diatom metabolism, such as the presence of lower glycolysis pathways in the mitochondrion, as well as differences between P. tricornutum and other photosynthetic organisms.

Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli.

An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain. Unexpectedly the mutant had a higher energy efficiency, indicated by a much lower rate of oxygen consumption, under glucose-limited conditions, caused by the deletion of the transcription factors IclR and ArcA. Furthermore the mutant had a much lower uptake capacity for succinate (26-fold) and oxygen (17-fold under succinate excess) compared to the wild-type strain. The mutant strain produced 7.9 mmol.CmolX(-1).h(-1) succinate during chemostat cultivation, showing that the choice of the applied genetic modifications was a successful strategy. Furthermore, the applied genetic modifications resulted in multiple large changes in metabolite levels (FBP, pyruvate, 6PG, NAD(+) /NADH ratio, α-ketogluarate) corresponding to large changes in fluxes. Compared to the wild-type a considerable flux shift occurred from the tricarboxylic acid (TCA) cycle to the oxidative part of the pentose phosphate pathway, including an inversion of the pyruvate kinase flux. The mutant responded very differently to excess of succinate, with a remarkable possible reversal of the TCA cycle. The mutant and the wild-type both showed homeostatic behaviour with respect to the energy charge. In contrast, large changes in redox ratios (NAD(+) /NADH) occurred in the wild-type, while the mutant showed even larger changes. This large redox change can be associated to the reversal of flux directions. The observed large flexibility in the central metabolism following genetic (deletions) and environmental (substrate excess) perturbations of the mutant, indicates that introducing a more efficient succinate exporter could result in an even higher succinate production rate.

Tracking the sterol biosynthesis pathway of the diatom Phaeodactylum tricornutum.

Diatoms are unicellular photosynthetic microalgae that play a major role in global primary production and aquatic biogeochemical cycling. Endosymbiotic events and recurrent gene transfers uniquely shaped the genome of diatoms, which contains features from several domains of life. The biosynthesis pathways of sterols, essential compounds in all eukaryotic cells, and many of the enzymes involved are evolutionarily conserved in eukaryotes. Although well characterized in most eukaryotes, the pathway leading to sterol biosynthesis in diatoms has remained hitherto unidentified. Through the DiatomCyc database we reconstructed the mevalonate and sterol biosynthetic pathways of the model diatom Phaeodactylum tricornutum in silico. We experimentally verified the predicted pathways using enzyme inhibitor, gene silencing and heterologous gene expression approaches. Our analysis revealed a peculiar, chimeric organization of the diatom sterol biosynthesis pathway, which possesses features of both plant and fungal pathways. Strikingly, it lacks a conventional squalene epoxidase and utilizes an extended oxidosqualene cyclase and a multifunctional isopentenyl diphosphate isomerase/squalene synthase enzyme. The reconstruction of the P. tricornutum sterol pathway underscores the metabolic plasticity of diatoms and offers important insights for the engineering of diatoms for sustainable production of biofuels and high-value chemicals.

Detection of flavonoids in microalgae from different evolutionary lineages.

Flavonoids are important secondary plant metabolites believed to be present mainly in land plants. As phenolics were detected previously in microalgae using photometric assays, we wanted to investigate the nature of these phenolics and verify whether flavonoids are present. Therefore, in this study, we used state-of-the-art ultra-high performance liquid chromatography-two-dimensional mass spectrometry (UHPLC-MS/MS) technology to investigate whether microalgae also contain flavonoids. For this, representative microalgal biomass samples from divergent evolutionary lineages (Cyanobacteria, Rhodophyta, Chlorophyta, Haptophyta, Ochrophyta) were screened for a set of carefully selected precursors, intermediates, and end products of the flavonoid biosynthesis pathways. Our data unequivocally showed that microalgae contain a wide range of flavonoids and thus must possess the enzyme pool required for their biosynthesis. Further, some of the microalgae displayed an intricate flavonoid pattern that is compatible with the established basic flavonoid pathway as observed in higher plants. This implies that the flavonoid biosynthesis pathway arose much earlier in evolution compared to what is generally accepted.

CathaCyc, a metabolic pathway database built from Catharanthus roseus RNA-Seq data.

The medicinal plant Madagascar periwinkle (Catharanthus roseus) synthesizes numerous terpenoid indole alkaloids (TIAs), such as the anticancer drugs vinblastine and vincristine. The TIA pathway operates in a complex metabolic network that steers plant growth and survival. Pathway databases and metabolic networks reconstructed from 'omics' sequence data can help to discover missing enzymes, study metabolic pathway evolution and, ultimately, engineer metabolic pathways. To date, such databases have mainly been built for model plant species with sequenced genomes. Although genome sequence data are not available for most medicinal plant species, next-generation sequencing is now extensively employed to create comprehensive medicinal plant transcriptome sequence resources. Here we report on the construction of CathaCyc, a detailed metabolic pathway database, from C. roseus RNA-Seq data sets. CathaCyc (version 1.0) contains 390 pathways with 1,347 assigned enzymes and spans primary and secondary metabolism. Curation of the pathways linked with the synthesis of TIAs and triterpenoids, their primary metabolic precursors, and their elicitors, the jasmonate hormones, demonstrated that RNA-Seq resources are suitable for the construction of pathway databases. CathaCyc is accessible online (http://www.cathacyc.org) and offers a range of tools for the visualization and analysis of metabolic networks and 'omics' data. Overlay with expression data from publicly available RNA-Seq resources demonstrated that two well-characterized C. roseus terpenoid pathways, those of TIAs and triterpenoids, are subject to distinct regulation by both developmental and environmental cues. We anticipate that databases such as CathaCyc will become key to the study and exploitation of the metabolism of medicinal plants.

Changes in substrate availability in Escherichia coli lead to rapid metabolite, flux and growth rate responses.

The interactions between the intracellular metabolome, fluxome and growth rate of Escherichia coli after sudden glycolytic/gluconeogenic substrate shifts are studied based on pulses of different substrates to an aerobic glucose-limited steady-state (dilution rate=0.1h(-1)). After each added glycolytic (glucose) and gluconeogenic (pyruvate and succinate) substrate pulse, no by-products were secreted and a pseudo steady state in flux and metabolites was achieved in about 30-40s. In the pulse experiments a large oxygen uptake capacity of the cells was observed. The in vivo dynamic responses showed massive reorganization and flexibility (1/100-14-fold change) of extra/intracellular metabolic fluxes, matching with large changes in the concentrations of intracellular metabolites, including reversal of reaction rate for pseudo/near equilibrium reactions. The coupling of metabolome and fluxome could be described by Q-linear kinetics. Remarkably, the three different substrate pulses resulted in a very similar increase in growth rate (0.13-0.3h(-1)). Data analysis showed that there must exist as yet unknown mechanisms which couple the protein synthesis rate to changes in central metabolites.

The metabolic blueprint of Phaeodactylum tricornutum reveals a eukaryotic Entner-Doudoroff glycolytic pathway.

Diatoms are one of the most successful groups of unicellular eukaryotic algae. Successive endosymbiotic events contributed to their flexible metabolism, making them competitive in variable aquatic habitats. Although the recently sequenced genomes of the model diatoms Phaeodactylum tricornutum and Thalassiosira pseudonana have provided the first insights into their metabolic organization, the current knowledge on diatom biochemistry remains fragmentary. By means of a genome-wide approach, we developed DiatomCyc, a detailed pathway/genome database of P. tricornutum. DiatomCyc contains 286 pathways with 1719 metabolic reactions and 1613 assigned enzymes, spanning both the central and parts of the secondary metabolism of P. tricornutum. Central metabolic pathways, such as those of carbohydrates, amino acids and fatty acids, were covered. Furthermore, our understanding of the carbohydrate model in P. tricornutum was extended. In particular we highlight the discovery of a functional Entner-Doudoroff pathway, an ancient alternative for the glycolytic Embden-Meyerhof-Parnas pathway, and a putative phosphoketolase pathway, both uncommon in eukaryotes. DiatomCyc is accessible online (http://www.diatomcyc.org), and offers a range of software tools for the visualization and analysis of metabolic networks and 'omics' data. We anticipate that DiatomCyc will be key to gaining further understanding of diatom metabolism and, ultimately, will feed metabolic engineering strategies for the industrial valorization of diatoms.

Genome-scale metabolic models: reconstruction and analysis.

Metabolism can be defined as the complete set of chemical reactions that occur in living organisms in order to maintain life. Enzymes are the main players in this process as they are responsible for catalyzing the chemical reactions. The enzyme-reaction relationships can be used for the reconstruction of a network of reactions, which leads to a metabolic model of metabolism. A genome-scale metabolic network of chemical reactions that take place inside a living organism is primarily reconstructed from the information that is present in its genome and the literature and involves steps such as functional annotation of the genome, identification of the associated reactions and determination of their stoichiometry, assignment of localization, determination of the biomass composition, estimation of energy requirements, and definition of model constraints. This information can be integrated into a stoichiometric model of metabolism that can be used for detailed analysis of the metabolic potential of the organism using constraint-based modeling approaches and hence is valuable in understanding its metabolic capabilities.

Integration of metabolic databases for the reconstruction of genome-scale metabolic networks.

BACKGROUND: Genome-scale metabolic reconstructions have been recognised as a valuable tool for a variety of applications ranging from metabolic engineering to evolutionary studies. However, the reconstruction of such networks remains an arduous process requiring a high level of human intervention. This process is further complicated by occurrences of missing or conflicting information and the absence of common annotation standards between different data sources. RESULTS: In this article, we report a semi-automated methodology aimed at streamlining the process of metabolic network reconstruction by enabling the integration of different genome-wide databases of metabolic reactions. We present results obtained by applying this methodology to the metabolic network of the plant Arabidopsis thaliana. A systematic comparison of compounds and reactions between two genome-wide databases allowed us to obtain a high-quality core consensus reconstruction, which was validated for stoichiometric consistency. A lower level of consensus led to a larger reconstruction, which has a lower quality standard but provides a baseline for further manual curation. CONCLUSION: This semi-automated methodology may be applied to other organisms and help to streamline the process of genome-scale network reconstruction in order to accelerate the transfer of such models to applications.

Catching prompt metabolite dynamics in Escherichia coli with the BioScope at oxygen rich conditions.

The design and application of a BioScope, a mini plug-flow reactor for carrying out pulse response experiments, specifically designed for Escherichia coli is presented. Main differences with the previous design are an increased volume-specific membrane surface for oxygen transfer and significantly decreased sampling intervals. The characteristics of the new device (pressure drop, residence time distribution, plug-flow behavior and O2 mass transfer) were determined and evaluated. Subsequently, 2.8 mM glucose perturbation experiments on glucose-limited aerobic E. coli chemostat cultures were carried out directly in the chemostat as well as in the BioScope (for two time frames: 8 and 40 s). It was ensured that fully aerobic conditions were maintained during the perturbation experiments. To avoid metabolite leakage during quenching, metabolite quantification (glycolytic and TCA-cycle intermediates and nucleotides) was carried out with a differential method, whereby the amounts measured in the filtrate were subtracted from the amounts measured in total broth. The dynamic metabolite profiles obtained from the BioScope perturbations were very comparable with the profiles obtained from the chemostat perturbation. This agreement demonstrates that the BioScope is a promising device for studying in vivo kinetics in E. coli that shows much faster response (< 10 s) in comparison with eukaryotes.

Expression of phosphofructokinase in Neisseria meningitidis.

Neisseria meningitidis serogroup B is a pathogen that can infect diverse sites within the human host. According to the N. meningitidis genomic information and experimental observations, glucose can be completely catabolized through the Entner-Doudoroff pathway and the pentose phosphate pathway. The Embden-Meyerhof-Parnas pathway is not functional, because the gene for phosphofructokinase (PFK) is not present. The phylogenetic distribution of PFK indicates that in most obligate aerobic organisms, PFK is lacking. We conclude that this is because of the limited contribution of PFK to the energy supply in aerobically grown organisms in comparison with the energy generated through oxidative phosphorylation. Under anaerobic or microaerobic conditions, the available energy is limiting, and PFK provides an advantage, which explains the presence of PFK in many (facultatively) anaerobic organisms. In accordance with this, in silico flux balance analysis predicted an increase of biomass yield as a result of PFK expression. However, analysis of a genetically engineered N. meningitidis strain that expressed a heterologous PFK showed that the yield of biomass on substrate decreased in comparison with a pfkA-deficient control strain, which was associated mainly with an increase in CO(2) production, whereas production of by-products was similar in the two strains. This might explain why the pfkA gene has not been obtained by horizontal gene transfer, since it is initially unfavourable for biomass yield. No large effects related to heterologous expression of pfkA were observed in the transcriptome. Although our results suggest that introduction of PFK does not contribute to a more efficient strain in terms of biomass yield, achievement of a robust, optimal metabolic network that enables a higher growth rate or a higher biomass yield might be possible after adaptive evolution of the strain, which remains to be investigated.

Modeling Neisseria meningitidis B metabolism at different specific growth rates.

Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. At the Netherlands Vaccine Institute (NVI) a vaccine against serogroup B organisms is currently being developed. This study describes the influence of the growth rate of N. meningitidis on its macro-molecular composition and its metabolic activity and was determined in chemostat cultures. In the applied range of growth rates, no significant changes in RNA content and protein content with growth rate were observed in N. meningitidis. The DNA content in N. meningitidis was somewhat higher at the highest applied growth rate. The phospholipid and lipopolysaccharide content in N. meningitidis changed with growth rate but no specific trends were observed. The cellular fatty acid composition and the amino acid composition did not change significantly with growth rate. Additionally, it was found that the PorA content in outer membrane vesicles was significantly lower at the highest growth rate. The metabolic fluxes at various growth rates were calculated using flux balance analysis. Errors in fluxes were calculated using Monte Carlo Simulation and the reliability of the calculated flux distribution could be indicated, which has not been reported for this type of analysis. The yield of biomass on substrate (Y(x/s)) and the maintenance coefficient (m(s)) were determined as 0.44 (+/-0.04) g g(-1) and 0.04 (+/-0.02) g g(-1) h(-1), respectively. The growth associated energy requirement (Y(x/ATP)) and the non-growth associated ATP requirement for maintenance (m(ATP)) were estimated as 0.13 (+/-0.04) mol mol(-1) and 0.43 (+/-0.14) mol mol(-1) h(-1), respectively. It was found that the split ratio between the Entner-Doudoroff and the pentose phosphate pathway, the sole glucose utilizing pathways in N. meningitidis, had a minor effect on ATP formation rate but a major effect on the fluxes going through for instance the citric-acid cycle. For this reason, we presented flux ranges for underdetermined parts of metabolic network rather than presenting single flux values, which is more commonly done in literature.

Modeling Neisseria meningitidis metabolism: from genome to metabolic fluxes.

BACKGROUND: Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years. RESULTS: Using the genomic database of N. meningitidis serogroup B together with biochemical and physiological information in the literature we constructed a genome-scale flux model for the primary metabolism of N. meningitidis. The validity of a simplified metabolic network derived from the genome-scale metabolic network was checked using flux-balance analysis in chemostat cultures. Several useful predictions were obtained from in silico experiments, including substrate preference. A minimal medium for growth of N. meningitidis was designed and tested successfully in batch and chemostat cultures. CONCLUSION: The verified metabolic model describes the primary metabolism of N. meningitidis in a chemostat in steady state. The genome-scale model is valuable because it offers a framework to study N. meningitidis metabolism as a whole, or certain aspects of it, and it can also be used for the purpose of vaccine process development (for example, the design of growth media). The flux distribution of the main metabolic pathways (that is, the pentose phosphate pathway and the Entner-Douderoff pathway) indicates that the major part of pyruvate (69%) is synthesized through the ED-cleavage, a finding that is in good agreement with literature.

Scale-up for bulk production of vaccine against meningococcal disease.

At the Netherlands Vaccine Institute (NVI) a vaccine against Neisseria meningitidis serogroup B organisms based on different porA subtypes contained in outer membrane vesicles (OMVs) is in advanced stage of development and will be evaluated in clinical trial studies in the near future. In order to meet the expected demand for product, the current biopharmaceutical production process is being scaled-up. This study describes the scale-up approach for the upstream process and the resulting bioreactor design and operation strategy leading towards a feasible solution for bulk production of a vaccine against meningococcal disease. The technically realized 1.2 m(3) bioreactor, equipped with a turbine impeller for gas dispersion, was complemented with an upward pumping impeller and a rotary plate foam breaker to contain foam inside the bioreactor. Aeration and ventilation in the culture broth were controlled by increasing the stirrer speed and gas flow rate simultaneously at increasing oxygen demand. The scale-up was successful and comparable growth curves and nutrient consumption profiles were reached on 0.06 and 1.2 m(3).

Identification of formaldehyde-induced modifications in proteins: reactions with insulin.

Formaldehyde is frequently used to inactivate, stabilize, or immobilize proteins. The treatment results in a large variety of chemical modifications in proteins, such as the formation of methylol groups, Schiff bases, and methylene bridges. The purpose of the present study was to identify the stable formaldehyde-induced modifications in a small protein. Therefore, insulin was treated with excess formaldehyde (CH2O) or deuterated formaldehyde (CD2O). In a separate experiment, insulin was modified by formaldehyde (CH2O vs CD2O) and glycine. The mixture of CH2O-treated and CD2O-treated insulin was digested by the proteinase Glu-C. The peptide fragments obtained were analyzed by liquid chromatography-mass spectrometry (LC-MS). Seven intramolecular cross-links were identified in formaldehyde-treated insulin. Furthermore, eight out of the sixteen potentially reactive sites of the insulin molecule were modified by incubation with formaldehyde and glycine. Both the location and the chemical nature of the modifications could be assigned based on the mass increase of potential adducts as elucidated in our previous study (B. Metz et al. (2004) J. Biol. Chem. 279, 6235-6243). To confirm the assigned structures, LC-MS measurements with collision-induced dissociation (LC-MS/MS) were performed on insulin fragments. The results of the LC-MS/MS analyses agreed excellently with the assignments. The study showed that arginine, tyrosine, and lysine residues were very reactive. However, eight theoretically reactive residues did not show detectable modifications, probably because of their low intrinsic reactivity, inaccessibility, or both. The asparagine, glutamine, and histidine residues were not converted in insulin. The N-termini of insulin were partly converted to the expected imidazolidinone adducts, indicating that the protein conformation affects the accessibility and reactivity of these residues. In conclusion, this study shows that, based on our current insights in the chemistry of the reactions between proteins and formaldehyde, we are able to elucidate the location and nature of formaldehyde-induced modifications in a small protein. The approach followed in this study may be generally applicable to larger formaldehyde-treated proteins, such as toxoids used in vaccines.

Mass tag-assisted identification of naturally processed HLA class II-presented meningococcal peptides recognized by CD4+ T lymphocytes.

The meningococcal class I outer membrane protein porin A plays an important role in the development of T cell-dependent protective immunity against meningococcal serogroup B infection and is therefore a major component of candidate meningococcal vaccines. T cell epitopes from porin A are poorly characterized because of weak in vitro memory T cell responses against purified Ag and strain variation. We applied a novel strategy to identify relevant naturally processed and MHC class II-presented porin A epitopes, based on stable isotope labeling of Ag. Human immature HLA-DR1-positive dendritic cells were used for optimal uptake and MHC class II processing of (14)N- and (15)N-labeled isoforms of the neisserial porin A serosubtype P1.5-2,10 in bacterial outer membrane vesicles. HLA-DR1 bound peptides, obtained after 48 h of Ag processing, contained typical spectral doublets in mass spectrometry that could easily be assigned to four porin A regions, expressed at diverging densities ( approximately 30-4000 copies/per cell). Epitopes from two of these regions are recognized by HLA-DR1-restricted CD4(+) T cell lines and are conserved among different serosubtypes of meningococcal porin A. This mass tag-assisted approach provides a useful methodology for rapid identification of MHC class II presented bacterial CD4(+) T cell epitopes relevant for vaccine development.