Biomedical subjects

Birgitte Regenberg

Publications and source records attributed to Birgitte Regenberg.

13 recordsLinked to original sources

PubMed2025

Spatial-Temporal Diversity of Extrachromosomal DNA Shapes Urothelial Carcinoma Evolution and Tumor-Immune Microenvironment.

Extrachromosomal DNA (ecDNA) presents a promising target for cancer therapy; however, its spatial-temporal diversity and influence on tumor evolution and the immune microenvironment remain largely unclear. We apply computational methods to analyze ecDNA from whole-genome sequencing data of 595 urothelial carcinoma (UC) patients. We demonstrate that ecDNA drives clonal evolution through structural rearrangements during malignant transformation and recurrence of UC. This supports a model wherein tumors evolve via the selective expansion of ecDNA-bearing cells. Through multi-regional sampling of tumors, we demonstrate that ecDNA contributes to the evolution of multifocality and increased intratumoral heterogeneity. EcDNA is present in 36% of UC tumors and correlates with an immunosuppressive phenotype and poor prognosis. Single-cell RNA sequencing analyses reveal that ecDNA+ malignant cells exhibit diminished expression of major histocompatibility complex class I molecules, enabling them to evade T-cell immunity. Finally, we show that sequencing of urinary sediment-derived DNA has excellent specificity in detecting ecDNA.

Journal Article↗

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↗

PubMed2006

Deletion of RTS1, encoding a regulatory subunit of protein phosphatase 2A, results in constitutive amino acid signaling via increased Stp1p processing.

In Saccharomyces cerevisiae, extracellular amino acids are sensed at the plasma membrane by the SPS sensor, consisting of the transporter homologue Ssy1p, Ptr3p, and the endoprotease Ssy5p. Amino acid sensing results in proteolytic truncation of the transcription factors Stp1p and Stp2p, followed by their relocation from the cytoplasm to the nucleus, where they activate transcription of amino acid permease genes. We screened a transposon mutant library for constitutively signaling mutants, with the aim of identifying down-regulating components of the SPS-mediated pathway. Three isolated mutants were carrying a transposon in the RTS1 gene, which encodes a regulatory subunit of protein phosphatase 2A. We investigated the basal activity of the AGP1 and BAP2 promoters in rts1delta cells and found increased transcription from these promoters, as well as increased Stp1p processing, even in the absence of amino acids. Based on our findings we propose that the phosphatase complex containing Rts1p keeps the SPS-mediated pathway down-regulated in the absence of extracellular amino acids by dephosphorylating a component of the pathway.

Amino Acid Transport Systems↗

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

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

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

Grr1p is required for transcriptional induction of amino acid permease genes and proper transcriptional regulation of genes in carbon metabolism of Saccharomyces cerevisiae.

The F-box protein Grr1p is involved in cell cycle regulation, glucose repression and transcriptional induction of the amino acid permease (AAP) gene AGP1. We investigated the role of Grr1p in amino acid-mediated induction of AAP genes by performing batch cultivations with a wild-type strain and a grr1Delta strain and adding citrulline in the exponential phase. Whole-genome transcription analyses were performed on samples from each cultivation, both immediately before and 30 min after citrulline addition. Transcriptional induction of the AAP genes AGP1, BAP2, BAP3, DIP5, GNP1 and TAT1 is fully dependent on Grr1p. Comparison of the grr1Delta strain with the reference strain in the absence of citrulline revealed that GRR1 disruption leads to increased transcription of numerous genes. These encode enzymes in the tricarboxylic acid cycle, the pentose-phosphate pathway and both glucose and starch metabolism. Promoter analysis showed that many of the genes with increased transcription display Mig1p- and/or Msn2p/Msn4p-binding sites. Increased expression of glucose-repressed genes in the grr1Delta strain may be explained by the reduced expression of the hexose transporter genes HXT1, HXT2, HXT3 and HXT4 and a subsequent lowering of the glucose uptake; and the effect of GRR1 deletion on general carbon metabolism may therefore be indirect. Finally, none of the genes known to be primarily involved in cell cycle regulation displayed different expression levels in the grr1Delta cells as compared with the reference strain, suggesting that the role of Grr1p in cell cycle regulation does not include any transcriptional component.

Amino Acid Transport Systems↗

PubMed2004

Use of laminar flow patterning for miniaturised biochemical assays.

Laminar flow in microfluidic chambers was used to construct low (one dimensional) density arrays suitable for miniaturized biochemical assays. By varying the ratio of flows of two guiding streams flanking a sample stream, precise focusing and positioning of the latter was achieved, and reactive species carried in the sample stream were deposited on functionalized chip surfaces as discrete 50 microm wide lanes. Using different model systems we have confirmed the method's suitability for qualitative screening and quantification tasks in receptor-ligand assays, recording biotin-streptavidin interactions, DNA-hybridization and DNA-triplex formation. The system is simple, fast, reproducible, flexible, and has small sample requirements.

Flow Injection Analysis↗

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

Transcriptional profiling of extracellular amino acid sensing in Saccharomyces cerevisiae and the role of Stp1p and Stp2p.

S. cerevisiae responds to the presence of amino acids in the environment through the membrane-bound complex SPS, by altering transcription of several genes. Global transcription analysis shows that 46 genes are induced by L-citrulline. Under the given conditions there appears to be only one pathway for induction with L-citrulline, and this pathway is completely dependent on the SPS component, Ssy1p, and either of the transcription factors, Stp1p and Stp2p. Besides the effects on amino acid permease genes, an ssy1 and an stp1 stp2 mutant exhibit a number of other transcriptional phenotypes, such as increased expression of genes subject to nitrogen catabolite repression and genes involved in stress response. A group of genes involved in the upper part of the glycolysis, including those encoding hexose transporters Hxt4p, Hxt5p, Hxt6p, Hxt7p, hexokinase Hxk1p, glyceraldehyde 3-phosphate dehydrogenase Tdh1p and glucokinase (Glk1p), shows increased transcription levels in either or both of the mutants. Also, most of the structural genes involved in trehalose and glycogen synthesis and a few genes in the glyoxylate cycle and the pentose phosphate pathway are derepressed in the ssy1 and stp1 stp2 strains.

Citrulline↗

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↗