Biomedical subjects

Christoffer Bro

Publications and source records attributed to Christoffer Bro.

10 recordsLinked to original sources

PubMed2007

A systems biology approach to study glucose repression in the yeast Saccharomyces cerevisiae.

Glucose repression in the yeast Saccharomyces cerevisiae has evolved as a complex regulatory system involving several different pathways. There are two main pathways involved in signal transduction. One has a role in glucose sensing and regulation of glucose transport, while another takes part in repression of a wide range of genes involved in utilization of alternative carbon sources. In this work, we applied a systems biology approach to study the interaction between these two pathways. Through genome-wide transcription analysis of strains with disruption of HXK2, GRR1, MIG1, the combination of MIG1 and MIG2, and the parental strain, we identified 393 genes to have significantly changed expression levels. To identify co-regulation patterns in the different strains we applied principal component analysis. Disruption of either GRR1 or HXK2 were both found to have profound effects on transcription of genes related to TCA cycle and respiration, as well as ATP synthesis coupled proton transport, all displaying an increased expression. The hxk2Delta strain showed reduced overflow metabolism towards ethanol relative to the parental strain. We also used a genome-scale metabolic model to identify reporter metabolites, and found that there is a high degree of consistency between the identified reporter metabolites and the physiological effects observed in the different mutants. Our systems biology approach points to close interaction between the two pathways, and our metabolism driven analysis of transcription data may find a wider application for analysis of cross-talk between different pathways involved in regulation of metabolism.

Gene Expression Profiling↗

PubMed2006

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.

Cell Growth Processes↗

PubMed2005

In silico aided metabolic engineering of Saccharomyces cerevisiae for improved bioethanol production.

In silico genome-scale cell models are promising tools for accelerating the design of cells with improved and desired properties. We demonstrated this by using a genome-scale reconstructed metabolic network of Saccharomyces cerevisiae to score a number of strategies for metabolic engineering of the redox metabolism that will lead to decreased glycerol and increased ethanol yields on glucose under anaerobic conditions. The best-scored strategies were predicted to completely eliminate formation of glycerol and increase ethanol yield with 10%. We successfully pursued one of the best strategies by expressing a non-phosphorylating, NADP(+)-dependent glyceraldehyde-3-phosphate dehydrogenase in S. cerevisiae. The resulting strain had a 40% lower glycerol yield on glucose while the ethanol yield increased with 3% without affecting the maximum specific growth rate. Similarly, expression of GAPN in a strain harbouring xylose reductase and xylitol dehydrogenase led to an improvement in ethanol yield by up to 25% on xylose/glucose mixtures.

Computer Simulation↗

PubMed2005

Improvement of galactose uptake in Saccharomyces cerevisiae through overexpression of phosphoglucomutase: example of transcript analysis as a tool in inverse metabolic engineering.

Through genome-wide transcript analysis of a reference strain and two recombinant Saccharomyces cerevisiae strains with different rates of galactose uptake, we obtained information about the global transcriptional response to metabolic engineering of the GAL gene regulatory network. One of the recombinant strains overexpressed the gene encoding the transcriptional activator Gal4, and in the other strain the genes encoding Gal80, Gal6, and Mig1, which are negative regulators of the GAL system, were deleted. Even though the galactose uptake rates were significantly different in the three strains, we surprisingly did not find any significant changes in the expression of the genes encoding the enzymes catalyzing the first steps of the pathway (i.e., the genes encoding Gal2, Gal1, Gal7, and Gal10). We did, however, find that PGM2, encoding the major isoenzyme of phosphoglucomutase, was slightly up-regulated in the two recombinant strains with higher galactose uptake rates. This indicated that PGM2 is a target for overexpression in terms of increasing the flux through the Leloir pathway, and through overexpression of PGM2 the galactose uptake rate could be increased by 70% compared to that of the reference strain. Based on our findings, we concluded that phosphoglucomutase plays a key role in controlling the flux through the Leloir pathway, probably due to increased conversion of glucose-1-phosphate to glucose-6-phosphate. This conclusion was supported by measurements of sugar phosphates, which showed that there were increased concentrations of glucose-6-phosphate, galactose-6-phosphate, and fructose-6-phosphate in the strain construct overexpressing PGM2.

Culture Media↗

PubMed2004

Genome-wide transcriptional response of a Saccharomyces cerevisiae strain with an altered redox metabolism.

The genome-wide transcriptional response of a Saccharomyces cerevisiae strain deleted in GDH1 that encodes a NADP(+)-dependent glutamate dehydrogenase was compared to a wild-type strain under anaerobic steady-state conditions. The GDH1-deleted strain has a significantly reduced NADPH requirement, and therefore, an altered redox metabolism. Identification of genes with significantly changed expression using a t-test and a Bonferroni correction yielded only 16 transcripts when accepting two false-positives, and 7 of these were Open Reading Frames (ORFs) with unknown function. Among the 16 transcripts the only one with a direct link to redox metabolism was GND1, encoding phosphogluconate dehydrogenase. To extract additional information we analyzed the transcription data for a gene subset consisting of all known genes encoding metabolic enzymes that use NAD(+) or NADP(+). The subset was analyzed for genes with significantly changed expression again with a t-test and correction for multiple testing. This approach was found to enrich the analysis since GND1, ZWF1 and ALD6, encoding the most important enzymes for regeneration of NADPH under anaerobic conditions, were down-regulated together with eight other genes encoding NADP(H)-dependent enzymes. This indicates a possible common redox-dependent regulation of these genes. Furthermore, we showed that it might be necessary to analyze the expression of a subset of genes to extract all available information from global transcription analysis.

Gene Deletion↗

PubMed2004

Elucidation of the role of Grr1p in glucose sensing by Saccharomyces cerevisiae through genome-wide transcription analysis.

The role of Grr1p in glucose sensing in Saccharomyces cerevisiae was elucidated through genome-wide transcription analysis. From triplicate analysis of a strain with deletion of the GRR1-gene from the genome and an isogenic reference strain, 68 genes were identified to have significantly altered expression using a Student's t-test with Bonferroni correction. These 68 genes were widely distributed across different parts of the cellular metabolism and GRR1-deletion is therefore concluded to result in polytrophic effects, indicating multiple roles for Grr1p. Using a less conservative statistical test, namely the SAM test, 232 genes were identified as having significantly altered expression, and also these genes were widely distributed across different parts of the cellular metabolism. Promoter analyses on a genome-wide scale and on the genes with significant changes revealed an over-representation of DNA-binding motifs for the transcriptional regulators Mig1p and Rgt1p in the promoter region of the significantly altered genes, indicating that Grr1p plays an important role in the regulatory pathways that ultimately lead to transcriptional regulation by each of the components Mig1p and Rgt1p.

Amino Acid Motifs↗

PubMed2004

Impact of 'ome' analyses on inverse metabolic engineering.

Genome-wide or large-scale methodologies employed in functional genomics such as DNA sequencing, transcription profiling, proteomics, and metabolite profiling have become important tools in many metabolic engineering strategies. These techniques allow the identification of genetic differences and insight into their cellular effects. In the field of inverse metabolic engineering mapping of differences between strains with different degree of a certain desired phenotype and subsequent identification of factors conferring that phenotype are an essential part. Therefore, the tools of functional genomics in particular have the potential to promote and expand inverse metabolic engineering. Here, we review the use of functional genomics methods in inverse metabolic engineering, examples are presented, and we discuss the identification of targets for metabolic engineering with low fold changes using these techniques.

Animals↗

PubMed2003

Transcriptional, proteomic, and metabolic responses to lithium in galactose-grown yeast cells.

Lithium is highly toxic to yeast when grown in galactose medium mainly because phosphoglucomutase, a key enzyme of galactose metabolism, is inhibited. We studied the global protein and gene expression profiles of Saccharomyces cerevisiae grown in galactose in different time intervals after addition of lithium. These results were related to physiological studies where both secreted and intracellular metabolites were determined. Microarray analysis showed that 664 open reading frames were down-regulated and 725 up-regulated in response to addition of lithium. Genes involved in transcription, translation, and nucleotide metabolism were down-regulated at the transcriptional level, whereas genes responsive to different stresses as well as genes from energy reserve metabolism and monosaccharide metabolism were up-regulated. Compared with the proteomic data, 26% of the down-regulated and 48% of the up-regulated proteins were also identified as being changed on the mRNA level. Functional clusters obtained from proteome data were coincident with transcriptional clusters. Physiological studies showed that acetate, glycerol, and glycogen accumulate in response to lithium, as reflected in expression data, whereas a change from respiro-fermentative to respiratory growth could not be predicted from the expression analyses.

Galactose↗

PubMed2002

Reproducibility of oligonucleotide microarray transcriptome analyses. An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae.

Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray analysis in functional genomics and metabolic engineering, we designed a set of experiments to specifically address this issue. Saccharomyces cerevisiae CEN.PK113-7D was grown under defined conditions in glucose-limited chemostats, followed by transcriptome analysis with Affymetrix GeneChip arrays. In each of the laboratories, three independent replicate cultures were grown aerobically as well as anaerobically. Although variations introduced by in vitro handling steps were small and unbiased, greater variation from replicate cultures underscored that, to obtain reliable information, experimental replication is essential. Under aerobic conditions, 86% of the most highly expressed yeast genes showed an average intralaboratory coefficient of variation of 0.23. This is significantly lower than previously reported for shake-flask-culture transcriptome analyses and probably reflects the strict control of growth conditions in chemostats. Using the triplicate data sets and appropriate statistical analysis, the change calls from anaerobic versus aerobic comparisons yielded an over 95% agreement between the laboratories for transcripts that changed by over 2-fold, leaving only a small fraction of genes that exhibited laboratory bias.

Aerobiosis↗

PubMed2002

Steady-state and transient-state analyses of aerobic fermentation in Saccharomyces kluyveri.

Some yeasts, such as Saccharomyces cerevisiae, produce ethanol at fully aerobic conditions, whereas other yeasts, such as Kluyveromyces lactis, do not. In this study we investigated the occurrence of aerobic alcoholic fermentation in the petite-negative yeast Saccharomyces kluyveri that is only distantly related to S. cerevisiae. In aerobic glucose-limited continuous cultures of S. kluyveri, two growth regimens were observed: at dilution rates below 0.5 h(-1) the metabolism was purely respiratory, and at dilution rates above 0.5 h(-1) the metabolism was respiro-fermentative. The dilution rate at which the switch in metabolism occurred, i.e. the critical dilution rate, was 66% higher than the typical critical dilution rate of S. cerevisiae. The maximum specific oxygen consumption rate around the critical dilution rate was found to 13.6 mmol (g dry weight)(-1) h(-1) and the capacity of the pyruvate dehydrogenase-bypass pathway was estimated to be high from in vitro enzyme activities; especially the specific activity of acetyl-CoA synthetase was much higher than in S. cerevisiae at all tested conditions. Addition of glucose to respiring cells of S. kluyveri led to ethanol formation after a delay of 20-50 min (depending on culture conditions prior to the pulse), which is in contrast to S. cerevisiae that ferments immediately after glucose addition.

Aerobiosis↗