Biomedical subjects

Steen Knudsen

Publications and source records attributed to Steen Knudsen.

14 recordsLinked to original sources

PubMed2006

Identification of novel genes regulated in the developing human ventral mesencephalon.

In the human embryo, from approximately 6 weeks gestational age (GA), dopaminergic (DA) neurons can be found in the ventral mesencephalon (VM). More specifically, the post-mitotic neurons are located in the ventral part of the tegmentum (VT), whereas no mature DA neurons are found in the neighboring dorsal part. We used Affymetrix HG-U133 GeneChip technology to compare genome-wide expression profiles of ventral and dorsal tegmentum from 8 weeks GA human embryos, in order to identify genes involved in specification, differentiation, and survival of mesencephalic DA (mDA) neurons. Known mDA marker genes including ALDH1A1, DAT1, VMAT2, TH, CALB1, NURR1, FOXA1, GIRK2, PITX3, RET, and DRD2 topped the list of 96 genes from HG-U133A with higher expression in VT, validating the experimental set-up. In addition, 28 probes from HG-U133B were identified whereof most are annotated to UniGene clusters with no gene associated or to genes of unknown function. Of these, the fifteen most regulated transcripts, representing changes down to 56% could be verified by quantitative real-time PCR (Q-PCR) on a developmental series of subdissected human embryonic and fetal brain material, resulting in not only a regional but also a temporal expression profile. This revealed a distinct DA-associated profile for in particular a putative transcription factor (FLJ45455) and the uncharacterized transmembrane proteins KIAA1145 and SLC10A4. The data presented here may help to device cell replacement and regenerative therapies for Parkinson's disease (PD).

Cluster Analysis↗

PubMed2005

New weakly expressed cell cycle-regulated genes in yeast.

We present an approach combining bioinformatics prediction with experimental microarray validation to identify new cell cycle-regulated genes in Saccharomyces cerevisiae. We identify in the order of 100 new cell cycle-regulated genes and show by independent data that these genes in general tend to be more weakly expressed than the genes identified hitherto. Among the genes not previously suggested to be periodically expressed we find genes linked to DNA repair, cell size monitoring and transcriptional control, as well as a number of genes of unknown function. Several of the gene products are believed to be phosphorylated by Cdc28. For many of these new genes, homologues exist in Schizosaccharomyces pombe and Homo sapiens for which the expression also varies with cell cycle progression.

Cell Cycle Proteins↗

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

Implementation of a gene expression index calculation method based on the PDNN model.

UNLABELLED: Gene expression index calculations from Affymetrix GeneChips have been dominated by the Affymetrix MAS, dChip, and RMA methods. A new method to estimate the gene expression value utilizing the probe sequence information named position-dependent nearest-neighbor (PDNN) has been suggested by Zhang et al. (2003). Here we describe an open source implementation of the PDNN method for the statistical language R. AVAILABILITY: The package can be downloaded from http://www.bioconductor.org/repository/devel/package/html/affypdnn.html CONTACT: hbjorn@cbs.dtu.dk.

Algorithms↗

PubMed2004

Alternative mapping of probes to genes for Affymetrix chips.

BACKGROUND: Short oligonucleotide arrays have several probes measuring the expression level of each target transcript. Therefore the selection of probes is a key component for the quality of measurements. However, once probes have been selected and synthesized on an array, it is still possible to re-evaluate the results using an updated mapping of probes to genes, taking into account the latest biological knowledge available. METHODS: We investigated how probes found on recent commercial microarrays for human genes (Affymetrix HG-U133A) were matching a recent curated collection of human transcripts: the NCBI RefSeq database. We also built mappings and used them in place of the original probe to genes associations provided by the manufacturer of the arrays. RESULTS: In a large number of cases, 36%, the probes matching a reference sequence were consistent with the grouping of probes by the manufacturer of the chips. For the remaining cases there were discrepancies and we show how that can affect the analysis of data. CONCLUSIONS: While the probes on Affymetrix arrays remain the same for several years, the biological knowledge concerning the genomic sequences evolves rapidly. Using up-to-date knowledge can apparently change the outcome of an analysis.

Base Sequence↗

PubMed2004

The transcriptional activation program of human neutrophils in skin lesions supports their important role in wound healing.

To investigate the cellular fate and function of polymorphonuclear neutrophilic granulocytes (PMNs) attracted to skin wounds, we used a human skin-wounding model and microarray technology to define differentially expressed genes in PMNs from peripheral blood, and PMNs that had transmigrated to skin lesions. After migration to skin lesions, PMNs demonstrated a significant transcriptional response including genes from several different functional categories. The up-regulation of anti-apoptotic genes concomitant with the down-regulation of proapoptotic genes suggested a transient anti-apoptotic priming of PMNs. Among the up-regulated genes were cytokines and chemokines critical for chemotaxis of macrophages, T cells, and PMNs, and for the modulation of their inflammatory responses. PMNs in skin lesions down-regulated receptors mediating chemotaxis and anti-microbial activity, but up-regulated other receptors involved in inflammatory responses. These findings indicate a change of responsiveness to chemotactic and immunoregulatory mediators once PMNs have migrated to skin lesions and have been activated. Other effects of the up-regulated cytokines/chemokines/enzymes were critical for wound healing. These included the breakdown of fibrin clots and degradation of extracellular matrix, the promotion of angiogenesis, the migration and proliferation of keratinocytes and fibroblasts, the adhesion of keratinocytes to the dermal layer, and finally, the induction of anti-microbial gene expression in keratinocytes. Notably, the up-regulation of genes, which activate lysosomal proteases, indicate a priming of skin lesion-PMNs for degradation of phagocytosed material. These findings demonstrate that migration of PMNs to skin lesions induces a transcriptional activation program, which regulates cellular fate and function, and promotes wound healing.

Apoptosis↗

PubMed2003

Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays.

Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer with an overview of these parameters. We present here a flexible tool named OligoWiz for designing oligonucleotides for multiple purposes. OligoWiz presents a set of parameter scores in a graphical interface to facilitate an overview for the user. Additional custom parameter scores can easily be added to the program to extend the default parameters: homology, DeltaTm, low-complexity, position and GATC-only. Furthermore we present an analysis of the limitations in designing oligonucleotide sets that can detect transcripts from multiple organisms. OligoWiz is available at www.cbs.dtu.dk/services/OligoWiz/.

DNA Primers↗

PubMed2003

GenePublisher: Automated analysis of DNA microarray data.

GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with a specification of the data. The server performs normalization, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user.

Automation↗

PubMed2003

Classification of Dukes' B and C colorectal cancers using expression arrays.

PURPOSE: Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene expression microarrays could be used to classify colorectal tumors. METHODS: We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each of the Dukes' stages A, B, C, and D. Expression data were filtered based on either covariance or a selection of the most significantly varying genes between tumor stages. RESULTS: A nearest neighbor classifier was used to classify normal, and Dukes' B and C samples with less than 20% error, whereas Dukes' A and D could not be classified correctly. A number of interesting gene clusters showed a discriminating difference between Dukes' B and C samples. These included mitochondrial genes, stromal remodeling genes, and genes related to cell adhesion. CONCLUSION: Molecular classification based on gene expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays.

Adenocarcinoma↗

PubMed2002

A new non-linear normalization method for reducing variability in DNA microarray experiments.

BACKGROUND: Microarray data are subject to multiple sources of variation, of which biological sources are of interest whereas most others are only confounding. Recent work has identified systematic sources of variation that are intensity-dependent and non-linear in nature. Systematic sources of variation are not limited to the differing properties of the cyanine dyes Cy(5) and Cy(3) as observed in cDNA arrays, but are the general case for both oligonucleotide microarray (Affymetrix GeneChips) and cDNA microarray data. Current normalization techniques are most often linear and therefore not capable of fully correcting for these effects. RESULTS: We present here a simple and robust non-linear method for normalization using array signal distribution analysis and cubic splines. These methods compared favorably to normalization using robust local-linear regression (lowess). The application of these methods to oligonucleotide arrays reduced the relative error between replicates by 5-10% compared with a standard global normalization method. Application to cDNA arrays showed improvements over the standard method and over Cy(3)-Cy(5) normalization based on dye-swap replication. In addition, a set of known differentially regulated genes was ranked higher by the t-test. In either cDNA or Affymetrix technology, signal-dependent bias was more than ten times greater than the observed print-tip or spatial effects. CONCLUSIONS: Intensity-dependent normalization is important for both high-density oligonucleotide array and cDNA array data. Both the regression and spline-based methods described here performed better than existing linear methods when assessed on the variability of replicate arrays. Dye-swap normalization was less effective at Cy(3)-Cy(5) normalization than either regression or spline-based methods alone.

Cell Line↗

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

Transcriptome analysis documents induced competence of Bacillus subtilis during nitrogen limiting conditions.

DNA microarrays were used to analyze the changes in gene expression in Bacillus subtilis strain 168 when nitrogen limiting (glutamate) and nitrogen excess (ammonium plus glutamate) growth conditions were compared. Among more than 100 genes that were significantly induced during nitrogen starvation we detected the comG, comF, comE, nin-nucA and comK transcription units together with recA. DNA was added to B. subtilis grown in minimal medium with glutamate as the sole nitrogen source and it was demonstrated that the cells were competent. Based on these observations we propose a simplification of previously designed one-step transformation procedures for B. subtilis strain 168.

Bacillus subtilis↗

PubMed2002

Neural network predicts sequence of TP53 gene based on DNA chip.

UNLABELLED: We have trained an artificial neural network to predict the sequence of the human TP53 tumor suppressor gene based on a p53 GeneChip. The trained neural network uses as input the fluorescence intensities of DNA hybridized to oligonucleotides on the surface of the chip and makes between zero and four errors in the predicted 1300 bp sequence when tested on wild-type TP53 sequence. AVAILABILITY: The trained neural network is available for academic use by contacting steen@cbs.dtu.dk

Base Sequence↗

PubMed2001

Sigma A recognition sites in the Bacillus subtilis genome.

A hidden Markov model of sigma(A) RNA polymerase cofactor recognition sites in Bacillus subtilis, containing either the common or the extended -10 motifs, has been constructed based on experimentally verified sigma(A) recognition sites. This work suggests that more information exists at the initiation site of transcription in both types of promoters than previously thought. When tested on the entire B. subtilis genome, the model predicts that approximately half of the sigma(A) recognition sites are of the extended type. Some of the response-regulator aspartate phosphatases were among the predictions of promoters containing extended sites. The expression of rapA and rapB was confirmed by site-directed mutagenesis to depend on the extended -10 region.

Bacillus subtilis↗