Growth energetics and metabolic fluxes in continuous cultures of Penicillium chrysogenum

Optogenetic control of Cdc48 for dynamic metabolic engineering in yeast

Dynamic metabolic engineering is a strategy to switch key metabolic pathways in microbial cell factories from biomass generation to accumulation of target products. Here, we demonstrate that optogenetic intervention in the cell cycle of budding yeast can be used to increase production of valuable chemicals, such as the terpenoid β-carotene or the nucleoside analog cordycepin. We achieved optogenetic cell-cycle arrest in the G2/M phase by controlling activity of the ubiquitin-proteasome system hub Cdc48. To analyze the metabolic capacities in the cell cycle arrested yeast strain, we studied their proteomes by timsTOF mass spectrometry. This revealed widespread, but highly distinct abundance changes of metabolic key enzymes. Integration of the proteomics data in protein-constrained metabolic models demonstrated modulation of fluxes directly associated with terpenoid production as well as metabolic subsystems involved in protein biosynthesis, cell wall synthesis, and cofactor biosynthesis. These results demonstrate that optogenetically triggered cell cycle intervention is an option to increase the yields of compounds synthesized in a cellular factory by reallocation of metabolic resources.

Reconciliation and evolution of Penicillium rubens genome-scale metabolic networks-What about specialised metabolism?

In recent years, genome sequencing of filamentous fungi has revealed a high proportion of specialised metabolites with growing pharmaceutical interest. However, detecting such metabolites through in silico genome analysis does not necessarily guarantee their expression under laboratory conditions. However, one plausible strategy for enabling their production lies in modifying the growth conditions. Devising a comprehensive experimental design testing in different culture environments is time-consuming and expensive. Therefore, using in silico modelling as a preliminary step, such as Genome-Scale Metabolic Network (GSMN), represents a promising approach to predicting and understanding the observed specialised metabolite production in a given organism. To address these questions, we reconstructed a new high-quality GSMN for the Penicillium rubens Wisconsin 54-1255 strain, a commonly used model organism. Our reconstruction, iPrub22, adheres to current convention standards and quality criteria, incorporating updated functional annotations, orthology searches with different GSMN templates, data from previous reconstructions, and manual curation steps targeting primary and specialised metabolites. With a MEMOTE score of 74% and a metabolic coverage of 45%, iPrub22 includes 5,192 unique metabolites interconnected by 5,919 reactions, of which 5,033 are supported by at least one genomic sequence. Of the metabolites present in iPrub22, 13% are categorised as belonging to specialised metabolism. While our high-quality GSMN provides a valuable resource for investigating known phenotypes expressed in P. rubens, our analysis identifies bottlenecks related, in particular, to the definition of what is a specialised metabolite, which requires consensus within the scientific community. It also points out the necessity of accessible, standardised and exhaustive databases of specialised metabolites. These questions must be addressed to fully unlock the potential of natural product production in P. rubens and other filamentous fungi. Our work represents a foundational step towards the objective of rationalising the production of natural products through GSMN modelling.

Penicillium chrysogenum, a Vintage Model with a Cutting-Edge Profile in Biotechnology

The discovery of penicillin entailed a decisive breakthrough in medicine. No other medical advance has ever had the same impact in the clinical practise. The fungus Penicillium chrysogenum (reclassified as P. rubens) has been used for industrial production of penicillin ever since the forties of the past century; industrial biotechnology developed hand in hand with it, and currently P. chrysogenum is a thoroughly studied model for secondary metabolite production and regulation. In addition to its role as penicillin producer, recent synthetic biology advances have put P. chrysogenum on the path to become a cell factory for the production of metabolites with biotechnological interest. In this review, we tell the history of P. chrysogenum, from the discovery of penicillin and the first isolation of strains with high production capacity to the most recent research advances with the fungus. We will describe how classical strain improvement programs achieved the goal of increasing production and how the development of different molecular tools allowed further improvements. The discovery of the penicillin gene cluster, the origin of the penicillin genes, the regulation of penicillin production, and a compilation of other P. chrysogenum secondary metabolites will also be covered and updated in this work.

The soil microbial food web revisited: Predatory myxobacteria as keystone taxa?

Trophic interactions are crucial for carbon cycling in food webs. Traditionally, eukaryotic micropredators are considered the major micropredators of bacteria in soils, although bacteria like myxobacteria and Bdellovibrio are also known bacterivores. Until recently, it was impossible to assess the abundance of prokaryotes and eukaryotes in soil food webs simultaneously. Using metatranscriptomic three-domain community profiling we identified pro- and eukaryotic micropredators in 11 European mineral and organic soils from different climes. Myxobacteria comprised 1.5-9.7% of all obtained SSU rRNA transcripts and more than 60% of all identified potential bacterivores in most soils. The name-giving and well-characterized predatory bacteria affiliated with the Myxococcaceae were barely present, while Haliangiaceae and Polyangiaceae dominated. In predation assays, representatives of the latter showed prey spectra as broad as the Myxococcaceae. 18S rRNA transcripts from eukaryotic micropredators, like amoeba and nematodes, were generally less abundant than myxobacterial 16S rRNA transcripts, especially in mineral soils. Although SSU rRNA does not directly reflect organismic abundance, our findings indicate that myxobacteria could be keystone taxa in the soil microbial food web, with potential impact on prokaryotic community composition. Further, they suggest an overlooked, yet ecologically relevant food web module, independent of eukaryotic micropredators and subject to separate environmental and evolutionary pressures.

Metabolic flux analysis and the NAD(P)H/NAD(P)+ ratios in chemostat cultures of Azotobacter vinelandii

BACKGROUND

Azotobacter vinelandii is a bacterium that produces alginate and polyhydroxybutyrate (P3HB); however, the role of NAD(P)H/NAD(P)+ ratios on the metabolic fluxes through biosynthesis pathways of these biopolymers remains unknown. The aim of this study was to evaluate the NAD(P)H/NAD(P) + ratios and the metabolic fluxes involved in alginate and P3HB biosynthesis, under oxygen-limiting and non-limiting oxygen conditions.

RESULTS

The results reveal that changes in the oxygen availability have an important effect on the metabolic fluxes and intracellular NADPH/NADP+ ratio, showing that at the lowest OTR (2.4 mmol L-1 h-1), the flux through the tricarboxylic acid (TCA) cycle decreased 27.6-fold, but the flux through the P3HB biosynthesis increased 6.6-fold in contrast to the cultures without oxygen limitation (OTR = 14.6 mmol L-1 h-1). This was consistent with the increase in the level of transcription of phbB and the P3HB biosynthesis. In addition, under conditions without oxygen limitation, there was an increase in the carbon uptake rate (twofold), as well as in the flux through the pentose phosphate (PP) pathway (4.8-fold), compared to the condition of 2.4 mmol L-1 h-1. At the highest OTR condition, a decrease in the NADPH/NADP+ ratio of threefold was observed, probably as a response to the high respiration rate induced by the respiratory protection of the nitrogenase under diazotrophic conditions, correlating with a high expression of the uncoupled respiratory chain genes (ndhII and cydA) and induction of the expression of the genes encoding the nitrogenase complex (nifH).

CONCLUSIONS

We have demonstrated that changes in oxygen availability affect the internal redox state of the cell and carbon metabolic fluxes. This also has a strong impact on the TCA cycle and PP pathway as well as on alginate and P3HB biosynthetic fluxes.

Fine-tuning the P. pastoris iMT1026 genome-scale metabolic model for improved prediction of growth on methanol or glycerol as sole carbon sources

The methylotrophic yeast Pichia pastoris (Komagataella spp.) is widely used as cell factory for recombinant protein production. In the past recent years, important breakthroughs in the systems-level quantitative analysis of its physiology have been achieved. This wealth of information has allowed the development of genome-scale metabolic models, which make new approaches possible for host cell and bioprocess engineering. Nevertheless, the predictive accuracy of the previous consensus model required to be upgraded and validated with new experimental data sets for P. pastoris growing on glycerol or methanol as sole carbon sources, two of the most relevant substrates for this cell factory. In this study, we have characterized P. pastoris growing in chemostat cultures using glycerol or methanol as sole carbon sources over a wide range of growth rates, thereby providing physiological data on the effect of growth rate and culture conditions on biomass macromolecular and elemental composition. In addition, these data sets were used to improve the performance of the P. pastoris consensus genomic-scale metabolic model iMT1026. Thereupon, new experimentally determined bounds, including the representation of biomass composition for these growth conditions, have been incorporated. As a result, here, we present version 3 (v3.0) of the consensus P. pastoris genome-scale metabolic model as an update of the iMT1026 model. The v3.0 model was validated for growth on glycerol and methanol as sole carbon sources, demonstrating improved prediction capabilities over an extended substrate range including two biotechnologically relevant carbon sources.

Computing the various pathways of penicillin synthesis and their molar yields

More than 80 years after its discovery, penicillin is still a widely used and commercially highly important antibiotic. Here, we analyse the metabolic network of penicillin synthesis in Penicillium chrysogenum based on the concept of elementary flux modes. In particular, we consider the synthesis of the invariant molecular core of the various subtypes of penicillin and the two major ways of incorporating sulfur: transsulfuration and direct sulfhydrylation. 66 elementary modes producing this invariant core are obtained. These show four different yields with respect to glucose, notably ½, 2/5, 1/3, and 2/7, with the highest yield of ½ occurring only when direct sulfhydrylation is used and α-aminoadipate is completely recycled. In the case of no recycling of this intermediate, we find the maximum yield to be 2/7. We compare these values with earlier literature values. Our analysis provides a systematic overview of the redundancy in penicillin synthesis and a detailed insight into the corresponding routes. Moreover, we derive suggestions for potential knockouts that could increase the average yield.

Acthi, a thiazole biosynthesis enzyme, is essential for thiamine biosynthesis and CPC production in Acremonium chrysogenum

Background

The filamentous fungus Acremonium chrysogenum is an important industrial fungus and is used in the production of the β-lactam antibiotic cephalosporin C. Little is known regarding the molecular and biological mechanisms of how this industrial strain was improved by mutagenesis and molecular breeding. Comparative proteomics is one of the most powerful methods to evaluate the influence of gene expression on metabolite production.

Results

In this study, we used comparative proteomics to investigate the molecular mechanisms involved in the biosynthesis of cephalosporin C between a high-producer (HY) strain and a wide-type (WT) strain. We found that the expression levels of thiamine biosynthesis-related enzymes, including the thiazole biosynthesis enzyme (Acthi), pyruvate oxidase, flavin adenine dinucleotide (FAD)-dependent oxidoreductase and sulfur carrier protein-thiS, were up-regulated in the HY strain. An Acthi-silencing mutant of the WT strain grew poorly on chemically defined medium (MMC) in the absence of thiamine, and its growth was recovered on MMC medium supplemented with thiamine. The intracellular thiamine content was changed in the Acthi silencing or over-expression mutants. In addition, we demonstrated that the manipulation of the Acthi gene can affect the hyphal growth of Acremonium chrysogenum, the transcription levels of cephalosporin C biosynthetic genes, the quantification levels of precursor amino acids for cephalosporin C synthesis and the expression levels of thiamine diphosphate-dependent enzymes. Over-expression of Acthi can significantly increase the cephalosporin C yield in both the WT strain and the HY mutant strain.

Conclusions

Using comparative proteomics, four differently expressed proteins were exploited, whose functions may be involved in thiamine diphosphate metabolism. Among these proteins, the thiazole biosynthesis enzyme (ActhiS) may play an important role in cephalosporin C biosynthesis. Our studies suggested that Acthi might be involved in the transcriptional regulation of cephalosporin C biosynthesis. Therefore, the thiamine metabolic pathway could be a potential target for the molecular breeding of this cephalosporin C producer for industrial applications.

De novo comparative transcriptome analysis of Acremonium chrysogenum: high-yield and wild-type strains of cephalosporin C producer

β-lactam antibiotics are widely used in clinic. Filamentous fungus Acremonium chrysogenum is an important industrial fungus for the production of CPC, one of the major precursors of β-lactam antibiotics. Although its fermentation yield has been bred significantly over the past decades, little is known regarding molecular changes between the industrial strain and the wild type strain. This limits the possibility to improve CPC production further by molecular breeding. Comparative transcriptome is a powerful tool to understand the molecular mechanisms of CPC industrial high yield producer compared to wild type. A total of 57 million clean sequencing reads with an average length of 100 bp were generated from Illumina sequencing platform. 22,878 sequences were assembled. Among the assembled unigenes, 9502 were annotated and 1989 annotated sequences were assigned to 121 pathways by searching against the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) database. Furthermore, we compared the transcriptome differences between a high-yield and a wild-type strain during fermentation. A total of 4329 unigenes with significantly different transcription level were identified, among which 1737 were up-regulated and 2592 were down-regulated. 24 pathways were subsequently determined which involve glycerolipid metabolism, galactose metabolism, and pyrimidine metabolism. We also examined the transcription levels of 18 identified genes, including 11 up-regulated genes and 7 down-regulated genes using reverse transcription quantitative -PCR (RT-qPCR). The results of RT-qPCR were consistent with the Illumina sequencing. In this study, the Illumina sequencing provides the most comprehensive sequences for gene expression profile of Acremonium chrysogenum and allows de novo transcriptome assembly while lacking genome information. Comparative analysis of RNA-seq data reveals the complexity of the transcriptome in the fermentation of different yield strains. This is an important public information platform which could be used to accelerate the research to improve CPC production in Acremonium chrysogenum.

Strategies for strain improvement in Fusarium fujikuroi: overexpression and localization of key enzymes of the isoprenoid pathway and their impact on gibberellin biosynthesis

The rice pathogen Fusarium fujikuroi is known to produce a wide range of secondary metabolites, such as the pigments bikaverin and fusarubins, the mycotoxins fusarins and fusaric acid, and the phytohormones gibberellic acids (GAs), which are applied as plant growth regulators in agri- and horticulture. The development of high-producing strains is a prerequisite for the efficient biotechnological production of GAs. In this work, we used different molecular approaches for strain improvement to directly affect expression of early isoprenoid genes as well as GA biosynthetic genes. Overexpression of the first GA pathway gene ggs2, encoding geranylgeranyl diphosphate synthase 2, or additional integration of ggs2 and cps/ks, the latter encoding the bifunctional ent-copalyldiphosphate synthase/ent-kaurene synthase, revealed an enhanced production level of 150%. However, overexpression of hmgR and fppS, encoding the key enzymes of the mevalonate pathway, hydroxymethylglutaryl coenzyme A reductase, and farnesyldiphosphate synthase, resulted in a reduced production level probably due to a negative feedback regulation of HmgR. Subsequent deletion of the transmembrane domains of HmgR and overexpression of the remaining catalytic domain led to an increased GA content (250%). Using green fluorescent protein and mCherry fusion constructs, we localized Cps/Ks in the cytosol, Ggs2 in small point-like structures, which are not the peroxisomes, and HmgR at the endoplasmatic reticulum. In summary, it was shown for the first time that amplification or truncation of key enzymes of the isoprenoid and GA pathway results in elevated production levels (2.5-fold). Fluorescence microscopy revealed localization of the key enzymes in different compartments.

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.

Cytosolic NADPH balancing in Penicillium chrysogenum cultivated on mixtures of glucose and ethanol

The in vivo flux through the oxidative branch of the pentose phosphate pathway (oxPPP) in Penicillium chrysogenum was determined during growth in glucose/ethanol carbon-limited chemostat cultures, at the same growth rate. Non-stationary (13)C flux analysis was used to measure the oxPPP flux. A nearly constant oxPPP flux was found for all glucose/ethanol ratios studied. This indicates that the cytosolic NADPH supply is independent of the amount of assimilated ethanol. The cofactor assignment in the model of van Gulik et al. (Biotechnol Bioeng 68(6):602-618, 2000) was supported using the published genome annotation of P. chrysogenum. Metabolic flux analysis showed that NADPH requirements in the cytosol remain nearly the same in these experiments due to constant biomass growth. Based on the cytosolic NADPH balance, it is known that the cytosolic aldehyde dehydrogenase in P. chrysogenum is NAD(+) dependent. Metabolic modeling shows that changing the NAD(+)-aldehyde dehydrogenase to NADP(+)-aldehyde dehydrogenase can increase the penicillin yield on substrate.

Quantitative metabolic flux analysis revealed uneconomical utilization of ATP and NADPH in Acremonium chrysogenum fed with soybean oil

A metabolic network was constructed for the Acremonium chrysogenum cultivation fed with soybean oil. Metabolic flux analysis indicated that the shift from exponential growth to rapid cephalosporin C (CPC) formation was accompanied by 1.63- and 5-fold carbon flux enlargement in TCA cycle and glyoxylate by-pass, respectively. The flux via pentose phosphate pathway branch was little affected during the rapid CPC formation period; the contributory explanation was that 35.6% of NADPH was consumed in the dissimilation of fatty acids. Estimation of NADPH, ATP generation, and consumption demonstrated that, with soybean oil as carbon source in rapid CPC formation phase, the NADPH consumed in fatty acid catabolism was fourfold greater than that used in the CPC biosynthesis-relevant part; simultaneously, more than 90% energy spent was not directly related to the CPC formation. Therefore, the improvement of CPC production yield through optimization of the NADPH, ATP generation, and consumption was put forward.

Proteome analysis of the penicillin producer Penicillium chrysogenum: characterization of protein changes during the industrial strain improvement

Proteomics is a powerful tool to understand the molecular mechanisms causing the production of high penicillin titers by industrial strains of the filamentous fungus Penicillium chrysogenum as the result of strain improvement programs. Penicillin biosynthesis is an excellent model system for many other bioactive microbial metabolites. The recent publication of the P. chrysogenum genome has established the basis to understand the molecular processes underlying penicillin overproduction. We report here the proteome reference map of P. chrysogenum Wisconsin 54-1255 (the genome project reference strain) together with an in-depth study of the changes produced in three different strains of this filamentous fungus during industrial strain improvement. Two-dimensional gel electrophoresis, peptide mass fingerprinting, and tandem mass spectrometry were used for protein identification. Around 1000 spots were visualized by "blue silver" colloidal Coomassie staining in a non-linear pI range from 3 to 10 with high resolution, which allowed the identification of 950 proteins (549 different proteins and isoforms). Comparison among the cytosolic proteomes of the wild-type NRRL 1951, Wisconsin 54-1255 (an improved, moderate penicillin producer), and AS-P-78 (a penicillin high producer) strains indicated that global metabolic reorganizations occurred during the strain improvement program. The main changes observed in the high producer strains were increases of cysteine biosynthesis (a penicillin precursor), enzymes of the pentose phosphate pathway, and stress response proteins together with a reduction in virulence and in the biosynthesis of other secondary metabolites different from penicillin (pigments and isoflavonoids). In the wild-type strain, we identified enzymes to utilize cellulose, sorbitol, and other carbon sources that have been lost in the high penicillin producer strains. Changes in the levels of a few specific proteins correlated well with the improved penicillin biosynthesis in the high producer strains. These results provide useful information to improve the production of many other bioactive secondary metabolites.

Engineering of Penicillium chrysogenum for fermentative production of a novel carbamoylated cephem antibiotic precursor

Penicillium chrysogenum was successfully engineered to produce a novel carbamoylated cephalosporin that can be used as a synthon for semi-synthetic cephalosporins. To this end, genes for Acremonium chrysogenum expandase/hydroxylase and Streptomyces clavuligerus carbamoyltransferase were expressed in a penicillinG high-producing strain of P.chrysogenum. Growth of the engineered strain in the presence of adipic acid resulted in production of adipoyl-7-amino-3-carbamoyloxymethyl-3-cephem-4-carboxylic acid (ad7-ACCCA) and of several adipoylated pathway intermediates. A combinatorial chemostat-based transcriptome study, in which the ad7-ACCCA-producing strain and a strain lacking key genes in beta-lactam synthesis were grown in the presence and absence of adipic acid, enabled the dissection of transcriptional responses to adipic acid per se and to ad7-ACCCA production. Transcriptome analysis revealed that adipate catabolism in P.chrysogenum occurs via beta-oxidation and enabled the identification of putative genes for enzymes involved in mitochondrial and peroxisomal beta-oxidation pathways. Several of the genes that showed a specifically altered transcript level in ad7-ACCCA-producing cultures were previously implicated in oxidative stress responses.

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.

ATP in current biotechnology: regulation, applications and perspectives

Adenosine tri-phosphate (ATP), the most important energy source for metabolic reactions and pathways, plays a vital role in the growth of industrial strain and the production of target metabolites. In this review, current advances in manipulating ATP in industrial strains, including altering NADH availability, and regulating NADH oxidation pathway, oxygen supply, proton gradient, the electron transfer chain activity and the F(0)F(1)-ATPase activity, are summarized and discussed. By applying these strategies, optimal product concentrations, yields and productivity in industrial biotechnology have been achieved. Furthermore, the mechanisms by which ATP extends the substrate utilization spectra and enhances the ability to challenge harsh environmental stress have been elucidated. Finally, three critical issues related to ATP manipulation have been addressed.

HEMET: mathematical model of biochemical pathways for simulation and prediction of HEpatocyte METabolism

Many computer studies and models have been developed in order to simulate cell biochemical pathways. The difficulty of integrating all the biochemical reactions that occur in a cell in a single model is the main reason for the poor results in the prediction and simulation of cell behaviour under different chemical and physical stimuli. In this paper we have translated biochemical reactions into differential equations for the development of modular model of metabolism of a hepatocyte cultured in static and standard conditions (in a plastic multiwell placed in an incubator at 37 degrees C with 5% of CO(2)). Using biochemical equations and energetic considerations a set of non-linear differential equations has been derived and implemented in Simulink. This set of equations mimics some of the principal metabolic pathways of biomolecules present in the culture medium. The software platform developed is subdivided into separate modules, each one describing a different metabolic pathway; they constitute a library which can be used for developing new modules and models to project, predict and validate cell behaviour in vitro.

Overexpression of a novel endogenous NADH kinase in Aspergillus nidulans enhances growth

The complete genome sequence of the filamentous fungi Aspergillus nidulans has paved the way for fundamental research on this industrially important species. To the best of our knowledge, this is the first time a gene encoding for ATP-dependent NADH kinase (ATP:NADH 2'-phosphotransferase, EC 2.7.1.86) has been identified. The enzyme has a predicted molecular weight of 49 kDa. We characterised the role of this NADH kinase by genomic integration of the putative gene AN8837.2 under a strong constitutive promoter. The physiological effects of overexpressed NADH kinase in combination with different aeration rates were studied in well-controlled glucose batch fermentations. Metabolite profiling and metabolic network analysis with [1-(13)C] glucose were used for characterisation of the strains, and the results demonstrated that NADH kinase activity has paramount influence on growth physiology. Biomass yield on glucose and the maximum specific growth rate increased from 0.47 g/g and 0.22 h(-1) (wild type) to 0.54 g/g and 0.26 h(-1) (NADH kinase overexpressed), respectively. The results suggest that overexpression of NADH kinase improves the growth efficiency of the cell by increasing the access to NADPH. Our findings indicate that A. nidulans is not optimised for growth in nutrient-rich conditions typically found in laboratory and industrial fermentors. This conclusion may impact the design of new strains capable of generating reducing power in the form of NADPH, which is crucial for efficient production of many industrially important metabolites and enzymes.

Metabolic model integration of the bibliome, genome, metabolome and reactome of Aspergillus niger

The release of the genome sequences of two strains of Aspergillus niger has allowed systems-level investigations of this important microbial cell factory. To this end, tools for doing data integration of multi-ome data are necessary, and especially interesting in the context of metabolism. On the basis of an A. niger bibliome survey, we present the largest model reconstruction of a metabolic network reported for a fungal species. The reconstructed gapless metabolic network is based on the reportings of 371 articles and comprises 1190 biochemically unique reactions and 871 ORFs. Inclusion of isoenzymes increases the total number of reactions to 2240. A graphical map of the metabolic network is presented. All levels of the reconstruction process were based on manual curation. From the reconstructed metabolic network, a mathematical model was constructed and validated with data on yields, fluxes and transcription. The presented metabolic network and map are useful tools for examining systemwide data in a metabolic context. Results from the validated model show a great potential for expanding the use of A. niger as a high-yield production platform.

Comparison of metabolite production capability indices generated by network analysis methods

A framework of constraint-based reconstruction and analysis (COBRA) is used for modeling large-scale metabolic networks. In COBRA, extreme pathway and optimization analyses are commonly used to study the properties of networks. While the results of both methods are completely consistent, extreme pathway analysis is considered to be better because of its wider representational ability. In this study, we assessed these two methods by computational knockout experiments. We examined a simple pathway model and found that the extreme pathway method led to misguided conclusions in specific cases, while optimization analysis calculated the correct knockout effects. We also investigated the Escherichia coli metabolic pathway model, and found that these methods result in inconsistent interpretations of the network properties.

IN CONCLUSION

it has been claimed that these two methods result in the same producible metabolites, but we found a difference in individual results for a biological pathway. Our results could provide helpful guidance for when to use the methods, particularly extreme pathway analysis.

Engineering primary metabolic pathways of industrial micro-organisms

Metabolic engineering is a powerful tool for the optimisation and the introduction of new cellular processes. This is mostly done by genetic engineering. Since the introduction of this multidisciplinary approach, the success stories keep accumulating. The primary metabolism of industrial micro-organisms has been studied for long time and most biochemical pathways and reaction networks have been elucidated. This large pool of biochemical information, together with data from proteomics, metabolomics and genomics underpins the strategies for design of experiments and choice of targets for manipulation by metabolic engineers. These targets are often located in the primary metabolic pathways, such as glycolysis, pentose phosphate pathway, the TCA cycle and amino acid biosynthesis and mostly at major branch points within these pathways. This paper describes approaches taken for metabolic engineering of these pathways in bacteria, yeast and filamentous fungi.

Determining Actinobacillus succinogenes metabolic pathways and fluxes by NMR and GC-MS analyses of 13C-labeled metabolic product isotopomers

Actinobacillus succinogenes is a promising candidate for industrial succinate production. However, in addition to producing succinate, it also produces formate and acetate. To understand carbon flux distribution to succinate and alternative products we fed A. succinogenes [1-(13)C]glucose and analyzed the resulting isotopomers of excreted organic acids, proteinaceous amino acids, and glycogen monomers by gas chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy. The isotopomer data, together with the glucose consumption and product formation rates and the A. succinogenes biomass composition, were supplied to a metabolic flux model. Oxidative pentose phosphate pathway flux supplied, at most, 20% of the estimated NADPH requirement for cell growth. The model indicated that NADPH was instead produced primarily by the conversion of NADH to NADPH by transhydrogenase and/or by NADP-dependent malic enzyme. Transhydrogenase activity was detected in A. succinogenes cell extracts, as were formate and pyruvate dehydrogenases, which the model suggested were contributing to NADH production. Malic enzyme activity was also detected in cell extracts, consistent with the flux analysis results. Labeling patterns in amino acids and organic acids showed that oxaloacetate and malate were being decarboxylated to pyruvate. These are the first in vivo experiments to show that the partitioning of flux between succinate and alternative fermentation products can occur at multiple nodes in A. succinogenes. The implications for designing effective metabolic engineering strategies to increase A. succinogenes succinate production are discussed.

13C-labeled gluconate tracing as a direct and accurate method for determining the pentose phosphate pathway split ratio in Penicillium chrysogenum

In this study we developed a new method for accurately determining the pentose phosphate pathway (PPP) split ratio, an important metabolic parameter in the primary metabolism of a cell. This method is based on simultaneous feeding of unlabeled glucose and trace amounts of [U-13C]gluconate, followed by measurement of the mass isotopomers of the intracellular metabolites surrounding the 6-phosphogluconate node. The gluconate tracer method was used with a penicillin G-producing chemostat culture of the filamentous fungus Penicillium chrysogenum. For comparison, a 13C-labeling-based metabolic flux analysis (MFA) was performed for glycolysis and the PPP of P. chrysogenum. For the first time mass isotopomer measurements of 13C-labeled primary metabolites are reported for P. chrysogenum and used for a 13C-based MFA. Estimation of the PPP split ratio of P. chrysogenum at a growth rate of 0.02 h(-1) yielded comparable values for the gluconate tracer method and the 13C-based MFA method, 51.8% and 51.1%, respectively. A sensitivity analysis of the estimated PPP split ratios showed that the 95% confidence interval was almost threefold smaller for the gluconate tracer method than for the 13C-based MFA method (40.0 to 63.5% and 46.0 to 56.5%, respectively). From these results we concluded that the gluconate tracer method permits accurate determination of the PPP split ratio but provides no information about the remaining cellular metabolism, while the 13C-based MFA method permits estimation of multiple fluxes but provides a less accurate estimate of the PPP split ratio.

Cytosolic NADPH metabolism in penicillin-G producing and non-producing chemostat cultures of Penicillium chrysogenum

This study addresses the relation between NADPH supply and penicillin synthesis, by comparing the flux through the oxidative branch of the pentose phosphate pathway (PPP; the main source of cytosolic NADPH) in penicillin-G producing and non-producing chemostat cultures of Penicillium chrysogenum. The fluxes through the oxidative part of the PPP were determined using the recently introduced gluconate-tracer method. Significantly higher oxidative PPP fluxes were observed in penicillin-G producing chemostat cultures, indicating that penicillin production puts a major burden on the supply of cytosolic NADPH. To our knowledge this is the first time direct experimental proof is presented for the causal relationship between penicillin production and NADPH supply. Additional insight in the metabolism of P. chrysogenum was obtained by comparing the PPP fluxes from the gluconate-tracer experiment to oxidative PPP fluxes derived via metabolic flux analysis, using different assumptions for the stoichiometry of NADPH consumption and production.

Hybrid dynamic/static method for large-scale simulation of metabolism

Background

Many computer studies have employed either dynamic simulation or metabolic flux analysis (MFA) to predict the behaviour of biochemical pathways. Dynamic simulation determines the time evolution of pathway properties in response to environmental changes, whereas MFA provides only a snapshot of pathway properties within a particular set of environmental conditions. However, owing to the large amount of kinetic data required for dynamic simulation, MFA, which requires less information, has been used to manipulate large-scale pathways to determine metabolic outcomes.

Results

Here we describe a simulation method based on cooperation between kinetics-based dynamic models and MFA-based static models. This hybrid method enables quasi-dynamic simulations of large-scale metabolic pathways, while drastically reducing the number of kinetics assays needed for dynamic simulations. The dynamic behaviour of metabolic pathways predicted by our method is almost identical to that determined by dynamic kinetic simulation.

Conclusion

The discrepancies between the dynamic and the hybrid models were sufficiently small to prove that an MFA-based static module is capable of performing dynamic simulations as accurately as kinetic models. Our hybrid method reduces the number of biochemical experiments required for dynamic models of large-scale metabolic pathways by replacing suitable enzyme reactions with a static module.

Increased NADPH concentration obtained by metabolic engineering of the pentose phosphate pathway in Aspergillus niger

Many biosynthetic reactions and bioconversions are limited by low availability of NADPH. With the purpose of increasing the NADPH concentration and/or the flux through the pentose phosphate pathway in Aspergillus niger, the genes encoding glucose 6-phosphate dehydrogenase (gsdA), 6-phosphogluconate dehydrogenase (gndA) and transketolase (tktA) were cloned and overexpressed in separate strains. Intracellular NADPH concentration was increased two- to ninefold as a result of 13-fold overproduction of 6-phosphogluconate dehydrogenase. Although overproduction of glucose 6-phosphate dehydrogenase and transketolase changed the concentration of several metabolites it did not result in increased NADPH concentration. To establish the effects of overexpression of the three genes, wild-type and overexpressing strains were characterized in detail in exponential and stationary phase of bioreactor cultures containing minimal media, with glucose as the carbon source and ammonium or nitrate as the nitrogen source and final cell density limiting substrate. Enzymes, intermediary metabolites, polyol pools (intra- and extracellular), organic acids, growth rates and rate constant of induction of acid production in postexponential phase were measured. None of the modified strains had a changed growth rate. Partial least square regressions showed the correlations between NADPH and up to 40 other variables (concentration of enzymes and metabolites) and it was possible to predict the intracellular NADPH concentration from relatively easily obtainable data (the concentration of enzymes, polyols and oxalate). This prediction might be used in screening for high NADPH levels in engineered strains or mutants of other organisms.

The nagA gene of Penicillium chrysogenum encoding beta-N-acetylglucosaminidase

We purified the beta-N-acetylglucosaminidase from the filamentous fungus Penicillium chrysogenum and its N-terminal sequence was determined, showing the presence of a mixture of two proteins (P1 and P2). A genomic DNA fragment was cloned by using degenerated oligonucleotides from the Nt sequences. The nucleotide sequence showed the presence of an ORF (nagA gene) lacking introns, with a length of 1791 bp, and coding for a protein of 66.5 kDa showing similarity to acetylglucosaminidases. The NagA deduced protein includes P1 and P2 as incomplete forms of the mature protein, and contains putative features for protein maturation: an 18-amino acid signal peptide, a KEX2 processing site, and four glycosylation motifs. The sequence just after the signal peptide corresponds to P2 and that after the KEX2 site to P1. The nagA transcript has a size of about 2.1 kb and is present until the end of the fermentation process for penicillin production. NagA is one of the most largely represented proteins in P. chrysogenum, increasing along the fermentation process. The suitability of the nagA promoter (PnagA) for gene expression in fungi was demonstrated by expressing the bleomycin resistance gene (ble(R)) from Streptoalloteichus hindustanus in P. chrysogenum.

A computational model for the identification of biochemical pathways in the krebs cycle

We have applied an algorithmic methodology which provably decomposes any complex network into a complete family of principal subcircuits to study the minimal circuits that describe the Krebs cycle. Every operational behavior that the network is capable of exhibiting can be represented by some combination of these principal subcircuits and this computational decomposition is linearly efficient. We have developed a computational model that can be applied to biochemical reaction systems which accurately renders pathways of such reactions via directed hypergraphs (Petri nets). We have applied the model to the citric acid cycle (Krebs cycle). The Krebs cycle, which oxidizes the acetyl group of acetyl CoA to CO(2) and reduces NAD and FAD to NADH and FADH(2), is a complex interacting set of nine subreaction networks. The Krebs cycle was selected because of its familiarity to the biological community and because it exhibits enough complexity to be interesting in order to introduce this novel analytic approach. This study validates the algorithmic methodology for the identification of significant biochemical signaling subcircuits, based solely upon the mathematical model and not upon prior biological knowledge. The utility of the algebraic-combinatorial model for identifying the complete set of biochemical subcircuits as a data set is demonstrated for this important metabolic process.

Metabolic flux and metabolic network analysis of Penicillium chrysogenum using 2D [13C, 1H] COSY NMR measurements and cumulative bondomer simulation

At present two alternative methods are available for analyzing the fluxes in a metabolic network: (1) combining measurements of net conversion rates with a set of metabolite balances including the cofactor balances, or (2) leaving out the cofactor balances and fitting the resulting free fluxes to measured (13)C-labeling data. In this study these two approaches are applied to the fluxes in the glycolysis and pentose phosphate pathway of Penicillium chrysogenum growing on either ammonia or nitrate as the nitrogen source, which is expected to give different pentose phosphate pathway fluxes. The presented flux analyses are based on extensive sets of 2D [(13)C, (1)H] COSY data. A new concept is applied for simulation of this type of (13)C-labeling data: cumulative bondomer modeling. The outcomes of the (13)C-labeling based flux analysis substantially differ from those of the pure metabolite balancing approach. The fluxes that are determined using (13)C-labeling data are shown to be highly dependent on the chosen metabolic network. Extending the traditional nonoxidative pentose phosphate pathway with additional transketolase and transaldolase reactions, extending the glycolysis with a fructose 6-phosphate aldolase/dihydroxyacetone kinase reaction sequence or adding a phosphoenolpyruvate carboxykinase reaction to the model considerably improves the fit of the measured and the simulated NMR data. The results obtained using the extended version of the nonoxidative pentose phosphate pathway model show that the transketolase and transaldolase reactions need not be assumed reversible to get a good fit of the (13)C-labeling data. Strict statistical testing of the outcomes of (13)C-labeling based flux analysis using realistic measurement errors is demonstrated to be of prime importance for verifying the assumed metabolic model.

Metabolic engineering of beta-lactam production

Metabolic engineering has become a rational alternative to classical strain improvement in optimisation of beta-lactam production. In metabolic engineering directed genetic modification are introduced to improve the cellular properties of the production strains. This has resulted in substantial increases in the existing beta-lactam production processes. Furthermore, pathway extension, by heterologous expression of novel genes in well-characterised strains, has led to introduction of new fermentation processes that replace environmentally damaging chemical methods. This minireview discusses the recent developments in metabolic engineering and the applications of this approach for improving beta-lactam production.

Statistical reconciliation of the elemental and molecular biomass composition of Saccharomyces cerevisiae

A systematic mathematical procedure capable of detecting the presence of a gross error in the measurements and of reconciling connected data sets by using the maximum likelihood principle is applied to the biomass composition data of yeast. The biomass composition of Saccharomyces cerevisiae grown in a chemostat under glucose limitation was analyzed for its elemental and for its molecular composition. Both descriptions initially resulted in conflicting results concerning the elemental composition, molecular weight, and degrees of reduction. The application of the statistical reconciliation method, based on elemental balances and equality relations, is used to obtain a consistent biomass composition. Simultaneously, the error margins of the data sets are significantly reduced in the reconciliation process. On the basis of statistical analysis it was found that inclusion of about 4% water in the list of biomass constituents is essential to adequately describe the dry biomass and match both set of measurements. The reconciled carbon content of the biomass varied 4% from the ones obtained from the molecular analysis. The proposed method increases the accuracy of biomass composition data of its elements and its molecules by providing a best estimate based on all available data and thus provides an improved and consistent basis for metabolic flux analysis as well as black box modeling approaches.

Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions

An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed-integer optimization problems using binary 0-1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non-E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route.

Metabolic modeling of microbial strains in silico

The large volume of genome-scale data that is being produced and made available in databases on the World Wide Web is demanding the development of integrated mathematical models of cellular processes. The analysis of reconstructed metabolic networks as systems leads to the development of an in silico or computer representation of collections of cellular metabolic constituents, their interactions and their integrated function as a whole. The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.

Quantitative analysis of Penicillium chrysogenum Wis54-1255 transformants overexpressing the penicillin biosynthetic genes

The low penicillin-producing, single gene copy strain Wis54-1255 was used to study the effect of overexpressing the penicillin biosynthetic genes in Penicillium chrysogenum. Transformants of Wis54-1255 were obtained with the amdS expression-cassette using the four combinations: pcbAB, pcbC, pcbC-penDE, and pcbAB-pcbC-penDE of the three penicillin biosynthetic genes. Transformants showing an increased penicillin production were investigated during steady-state continuous cultivations with glucose as the growth-limiting substrate. The transformants were characterized with respect to specific penicillin productivity, the activity of the two pathway enzymes delta-(L-alpha-aminoadipyl)-L-cysteinyl-D-valine synthetase (ACVS) and isopenicillin N synthetase (IPNS) and the intracellular concentration of the metabolites: delta-(L-alpha-aminoadipyl)-L-cysteinyl-D-valine (ACV), bis-delta-(L-alpha-aminoadipyl)-L-cysteinyl-D-valine (bisACV), isopenicillin N (IPN), glutathione (GSH), and glutathione disulphide (GSSG). Transformants with the whole gene cluster amplified showed the largest increase in specific penicillin productivity (r(p))-124% and 176%, respectively, whereas transformation with the pcbC-penDE gene fragment resulted in a decrease in r(p) of 9% relative to Wis54-1255. A marked increase in r(p) is clearly correlated with a balanced amplification of both the ACVS and IPNS activity or a large amplification of either enzyme activity. The increased capacity of a single enzyme occurs surprisingly only in the transformants where all the three biosynthetic genes are overexpressed but is not found within the group of pcbAB or pcbC transformants. The indication of the pcbAB and pcbC genes being closely regulated in fungi might explain why high-yielding strains of P. chrysogenum have been found to contain amplifications of a large region including the whole penicillin gene cluster and not single gene amplifications. Measurements of the total ACV concentration showed a large span of variability, which reflected the individual status of enzyme overexpression and activity found in each strain. The ratio ACV:bisACV remained constant, also at high ACV concentrations, indicating no limitation in the capacity of the thioredoxin-thioredoxin reductase (TR) system, which is assumed to keep the pathway intermediate LLD-ACV in its reduced state. The total GSH pool was at a constant level of approx. 5.7 mM in all cultivations.

Energetics of growth and penicillin production in a high-producing strain of Penicillium chrysogenum

The results of a large number of carbon-limited chemostat cultures of Penicillium chrysogenum carried out on glucose, ethanol, and acetate as the growth limiting substrate have been used to obtain an estimation of the adenosine triphosphate (ATP) costs for mycelium growth, penicillin production, and maintenance and the overall stoichiometry of oxidative phosphorylation of the fungus. It was found that penicillin production was accompanied by a significant additional energy drain (73 mol of ATP per mole of penicillin-G) from primary metabolism. This finding has been confirmed in independent experiments and has been shown to result in a significantly lower estimate for the maximum theoretical yield of penicillin-G on the carbon source.

Application of metabolic flux analysis for the identification of metabolic bottlenecks in the biosynthesis of penicillin-G

A detailed stoichiometric model was developed for growth and penicillin-G production in Penicillium chrysogenum. From an a priori metabolic flux analysis using this model it appeared that penicillin production requires significant changes in fluxes through the primary metabolic pathways. This is brought about by the biosynthesis of carbon precursors for the beta-lactan nucleus and an increased demand for NADPH, mainly for sulfate reduction. As a result, significant changes in flux partitioning occur around four principal nodes in primary metabolism. These are located at: (1) glucose-6-phosphate; (2) 3-phosphoglycerate; (3) mitochondrial pyruvate; and (4) mitochondrial isocitrate. These nodes should be regarded as potential bottlenecks for increased productivity. The flexibility of these principal nodes was investigated by experimental manipulation of the fluxes through the central metabolic pathways using a high-producing strain of P. chrysogenum. Metabolic fluxes were manipulated through growth of the cells on different substrates in carbon-limited chemostat culture. Metabolic flux analysis, based on measured input and output fluxes, was used to calculate the fluxes around the principal nodes. It was found that, for growth on glucose, ethanol, and acetate, the flux partitioning around these nodes differed significantly. However, this had hardly any effect on penicillin productivity, showing that primary carbon metabolism is not likely to contain potential bottlenecks. Further experiments were performed to manipulate the total metabolic demand for the cofactor nicotinamide adenine dinucleotide phosphate (NADPH). NADPH demand was increased stepwise by cultivating the cells on glucose or xylose as the carbon source combined with either ammonia or nitrate as the nitrogen source, which resulted in a stepwise decrease of penicillin production. This clearly shows that, in penicillin fermentation, possible limitations in primary metabolism reside in the supply/regeneration of cofactors (NADPH) rather than in the supply of carbon precursors.