Metabolic engineering of Saccharomyces cerevisiae for production of Eicosapentaenoic Acid, using a novel {Delta}5-Desaturase from Paramecium tetraurelia.

Very-long-chain polyunsaturated fatty acids, such as arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), have well-documented importance in human health and nutrition. Sustainable production in robust host organisms that do not synthesize them naturally requires the coordinated expression of several heterologous desaturases and elongases. In the present study we show production of EPA in Saccharomyces cerevisiae using glucose as the sole carbon source through expression of five heterologous fatty acid desaturases and an elongase. Novel Δ5-desaturases from the ciliate protozoan Paramecium tetraurelia and from the microalgae Ostreococcus tauri and Ostreococcus lucimarinus were identified via a BLAST search, and their substrate preferences and desaturation efficiencies were assayed in a yeast strain producing the ω6 and ω3 fatty acid substrates for Δ5-desaturation. The Δ5-desaturase from P. tetraurelia was up-to-2-fold more efficient than the microalgal desaturases and was also more efficient than Δ5-desaturases from Mortierella alpina and Leishmania major. In vivo investigation of acyl carrier substrate specificities showed that the Δ5-desaturases from P. tetraurelia, O. lucimarinus, O. tauri, and M. alpina are promiscuous toward the acyl carrier substrate but prefer phospholipid-bound substrates. In contrast, the Δ5-desaturase from L. major showed no activity on phospholipid-bound substrate and thus appears to be an exclusively acyl coenzyme A-dependent desaturase.

Studies of the production of fungal polyketides in Aspergillus nidulans by using systems biology tools.

Many filamentous fungi produce polyketide molecules with great significance as human pharmaceuticals; these molecules include the cholesterol-lowering compound lovastatin, which was originally isolated from Aspergillus terreus. The chemical diversity and potential uses of these compounds are virtually unlimited, and it is thus of great interest to develop a well-described microbial production platform for polyketides. Using genetic engineering tools available for the model organism Aspergillus nidulans, we constructed two recombinant strains, one expressing the Penicillium griseofulvum 6-methylsalicylic acid (6-MSA) synthase gene and one expressing the 6-MSA synthase gene and overexpressing the native xylulose-5-phosphate phosphoketolase gene (xpkA) for increasing the pool of polyketide precursor levels. The physiology of the recombinant strains and that of a reference wild-type strain were characterized on glucose, xylose, glycerol, and ethanol media in controlled bioreactors. Glucose was found to be the preferred carbon source for 6-MSA production, and 6-MSA concentrations up to 455 mg/liter were obtained for the recombinant strain harboring the 6-MSA gene. Our findings indicate that overexpression of xpkA does not directly improve 6-MSA production on glucose, but it is possible, if the metabolic flux through the lower part of glycolysis is reduced, to obtain quite high yields for conversion of sugar to 6-MSA. Systems biology tools were employed for in-depth analysis of the metabolic processes. Transcriptome analysis of 6-MSA-producing strains grown on glucose and xylose in the presence and absence of xpkA overexpression, combined with flux and physiology data, enabled us to propose an xpkA-msaS interaction model describing the competition between biomass formation and 6-MSA production for the available acetyl coenzyme A.

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.

Systems analysis unfolds the relationship between the phosphoketolase pathway and growth in Aspergillus nidulans.

BACKGROUND: Aspergillus nidulans is an important model organism for studies on fundamental eukaryotic cell biology and on industrial processes due to its close relation to A. niger and A. oryzae. Here we identified the gene coding for a novel metabolic pathway in A. nidulans, namely the phosphoketolase pathway, and investigated the role of an increased phosphoketolase activity. METHODOLOGY/PRINCIPAL FINDINGS: Over-expression of the phosphoketolase gene (phk) improved the specific growth rate on xylose, glycerol and ethanol. Transcriptome analysis showed that a total of 1,222 genes were significantly affected by over-expression of the phk, while more than half of the affected genes were carbon source specific. During growth on glucose medium, the transcriptome analysis showed that the response to phk over-expression is targeted to neutralize the effect of the over-expression by regulating the acetate metabolism and initiate a growth dampening response. CONCLUSIONS/SIGNIFICANCE: Metabolic flux analysis using (13)C-labelled glucose, showed that over-expression of phosphoketolase added flexibility to the central metabolism. Our findings further suggests that A. nidulans is not optimized for growth on xylose, glycerol or ethanol as the sole carbon sources.

Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae.

BACKGROUND: Growth rate is central to the development of cells in all organisms. However, little is known about the impact of changing growth rates. We used continuous cultures to control growth rate and studied the transcriptional program of the model eukaryote Saccharomyces cerevisiae, with generation times varying between 2 and 35 hours. RESULTS: A total of 5930 transcripts were identified at the different growth rates studied. Consensus clustering of these revealed that half of all yeast genes are affected by the specific growth rate, and that the changes are similar to those found when cells are exposed to different types of stress (>80% overlap). Genes with decreased transcript levels in response to faster growth are largely of unknown function (>50%) whereas genes with increased transcript levels are involved in macromolecular biosynthesis such as those that encode ribosomal proteins. This group also covers most targets of the transcriptional activator RAP1, which is also known to be involved in replication. A positive correlation between the location of replication origins and the location of growth-regulated genes suggests a role for replication in growth rate regulation. CONCLUSION: Our data show that the cellular growth rate has great influence on transcriptional regulation. This, in turn, implies that one should be cautious when comparing mutants with different growth rates. Our findings also indicate that much of the regulation is coordinated via the chromosomal location of the affected genes, which may be valuable information for the control of heterologous gene expression in metabolic engineering.

Global transcriptional and physiological responses of Saccharomyces cerevisiae to ammonium, L-alanine, or L-glutamine limitation.

The yeast Saccharomyces cerevisiae encounters a range of nitrogen sources at various concentrations in its environment. The impact of these two parameters on transcription and metabolism was studied by growing S. cerevisiae in chemostat cultures with l-glutamine, l-alanine, or l-ammonium in limitation and by growing cells in an excess of ammonium. Cells grown in l-alanine-limited cultures had higher biomass yield per nitrogen mole (19%) than those from ammonium-limited cultures. Whole-genome transcript profiles were analyzed with a genome-scale metabolic model that suggested increased anabolic activity in l-alanine-limited cells. The changes in these cells were found to be focused around pyruvate, acetyl coenzyme A, glyoxylate, and alpha-ketoglutarate via increased levels of ALT1, DAL7, PYC1, GDH2, and ADH5 and decreased levels of GDH3, CIT2, and ACS1 transcripts. The transcript profiles were then clustered. Approximately 1,400 transcripts showed altered levels when amino acid-grown cells were compared to those from ammonium. Another 400 genes had low transcript levels when ammonium was in excess. Overrepresentation of the GATAAG element in their promoters suggests that nitrogen catabolite repression (NCR) may be responsible for this regulation. Ninety-one genes had transcript levels on both l-glutamine and ammonium that were decreased compared to those on l-alanine, independent of the concentration. The GATAAG element in these genes suggests two groups of NCR-responsive genes, those that respond to high levels of nitrogen and those that respond to levels below 30 muM. In conclusion, our results reveal that the nitrogen source has substantial influence on the transcriptome of yeasts and that transcriptional changes may be correlated to physiology via a metabolic model.

Engineering of the redox imbalance of Fusarium oxysporum enables anaerobic growth on xylose.

Dissimilatory nitrate reduction metabolism, of the natural xylose-fermenting fungus Fusarium oxysporum, was used as a strategy to achieve anaerobic growth and ethanol production from xylose. Beneficial alterations of the redox fluxes and thereby of the xylose metabolism were obtained by taking advantage of the regeneration of the cofactor NAD(+) during the denitrification process. In batch cultivations, nitrate sustained growth under anaerobic conditions (1.21 g L(-1) biomass) and simultaneously a maximum yield of 0.55 moles of ethanol per mole of xylose was achieved, whereas substitution of nitrate with ammonium limited the growth significantly (0.15 g L(-1) biomass). Using nitrate, the maximum acetate yield was 0.21 moles per mole of xylose and no xylitol excretion was observed. Furthermore, the network structure in the central carbon metabolism of F. oxysporum was characterized in steady state. F. oxysporum grew anaerobically on [1-(13)C] labelled glucose and unlabelled xylose in chemostat cultivation with nitrate as nitrogen source. The use of labelled substrate allowed the precise determination of the glucose and xylose contribution to the carbon fluxes in the central metabolism of this poorly described microorganism. It was demonstrated that dissimilatory nitrate reduction allows F. oxysporum to exhibit typical respiratory metabolic behaviour with a highly active TCA cycle and a large demand for NADPH.

Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm.

MOTIVATION: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods give results which are dependent on the initialization of the algorithm. Therefore, it is difficult to assess the significance of the results. We have developed a consensus clustering algorithm, where the final result is averaged over multiple clustering runs, giving a robust and reproducible clustering, capable of capturing small signal variations. The algorithm preserves valuable properties of hierarchical clustering, which is useful for visualization and interpretation of the results. RESULTS: We show for the first time that one can take advantage of multiple clustering runs in DNA microarray analysis by collecting re-occurring clustering patterns in a co-occurrence matrix. The results show that consensus clustering obtained from clustering multiple times with Variational Bayes Mixtures of Gaussians or K-means significantly reduces the classification error rate for a simulated dataset. The method is flexible and it is possible to find consensus clusters from different clustering algorithms. Thus, the algorithm can be used as a framework to test in a quantitative manner the homogeneity of different clustering algorithms. We compare the method with a number of state-of-the-art clustering methods. It is shown that the method is robust and gives low classification error rates for a realistic, simulated dataset. The algorithm is also demonstrated for real datasets. It is shown that more biological meaningful transcriptional patterns can be found without conservative statistical or fold-change exclusion of data. AVAILABILITY: Matlab source code for the clustering algorithm ClusterLustre, and the simulated dataset for testing are available upon request from T.G. and O.W.

Comparative metabolic network analysis of two xylose fermenting recombinant Saccharomyces cerevisiae strains.

The recombinant xylose fermenting strain Saccharomyces cerevisiae TMB3001 can grow on xylose, but the xylose utilisation rate is low. One important reason for the inefficient fermentation of xylose to ethanol is believed to be the imbalance of redox co-factors. In the present study, a metabolic flux model was constructed for two recombinant S. cerevisiae strains: TMB3001 and CPB.CR4 which in addition to xylose metabolism have a modulated redox metabolism, i.e. ammonia assimilation was shifted from being NADPH to NADH dependent by deletion of gdh1 and over-expression of GDH2. The intracellular fluxes were estimated for both strains in anaerobic continuous cultivations when the growth limiting feed consisted of glucose (2.5 g L-1) and xylose (13 g L-1). The metabolic network analysis with 13C labelled glucose showed that there was a shift in the specific xylose reductase activity towards use of NADH as co-factor rather than NADPH. This shift is beneficial for solving the redox imbalance and it can therefore partly explain the 25% increase in the ethanol yield observed for CPB.CR4. Furthermore, the analysis indicated that the glyoxylate cycle was activated in CPB.CR4.

Impact of transamination reactions and protein turnover on labeling dynamics in (13)C-labeling experiments.

A dynamic model describing carbon atom transitions in the central metabolism of Saccharomyces cerevisiae is used to investigate the influence of transamination reactions and protein turnover on the transient behavior of (13)C-labeling chemostat experiments. The simulations performed suggest that carbon exchange due to transamination and protein turnover can significantly increase the required time needed for metabolites in the TCA cycle to reach isotopic steady state, which is in agreement with published experimental observations. On the other hand, transamination and protein turnover will speed-up the net rate of incorporation of labeled carbon into some free and protein-bound amino acids. The simulation results indicate that the pattern of labeled carbon incorporation into amino acids obtained from biomass hydrolysate shows significant deviation from the commonly assumed first-order kinetics behavior until after three residence times. These observations suggest that greater caution should be used while also pointing to new opportunities in the design and interpretation of (13)C-labeling experiments.