Biomedical subjects

Thomas Grotkjaer

Publications and source records attributed to Thomas Grotkjaer.

5 recordsLinked to original sources

PubMed2006

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.

Anaerobiosis↗

PubMed2006

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.

Alanine↗

PubMed2005

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.

Algorithms↗

PubMed2005

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.

Computer Simulation↗

PubMed2004

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.

Amino Acids↗