Biomedical subjects

Lars J Jensen

Publications and source records attributed to Lars J Jensen.

15 recordsLinked to original sources

PubMed2007

Identification of tightly regulated groups of genes during Drosophila melanogaster embryogenesis.

Time-series analysis of whole-genome expression data during Drosophila melanogaster development indicates that up to 86% of its genes change their relative transcript level during embryogenesis. By applying conservative filtering criteria and requiring 'sharp' transcript changes, we identified 1534 maternal genes, 792 transient zygotic genes, and 1053 genes whose transcript levels increase during embryogenesis. Each of these three categories is dominated by groups of genes where all transcript levels increase and/or decrease at similar times, suggesting a common mode of regulation. For example, 34% of the transiently expressed genes fall into three groups, with increased transcript levels between 2.5-12, 11-20, and 15-20 h of development, respectively. We highlight common and distinctive functional features of these expression groups and identify a coupling between downregulation of transcript levels and targeted protein degradation. By mapping the groups to the protein network, we also predict and experimentally confirm new functional associations.

Analysis of Variance↗

PubMed2006

STRING 7--recent developments in the integration and prediction of protein interactions.

Information on protein-protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and predicted interactions from a variety of sources. The underlying infrastructure includes a consistent body of completely sequenced genomes and exhaustive orthology classifications, based on which interaction evidence is transferred between organisms. Although primarily developed for protein interaction analysis, the resource has also been successfully applied to comparative genomics, phylogenetics and network studies, which are all facilitated by programmatic access to the database backend and the availability of compact download files. As of release 7, STRING has almost doubled to 373 distinct organisms, and contains more than 1.5 million proteins for which associations have been pre-computed. Novel features include AJAX-based web-navigation, inclusion of additional resources such as BioGRID, and detailed protein domain annotation. STRING is available at http://string.embl.de/

Databases, Protein↗

PubMed2006

Assessing systems properties of yeast mitochondria through an interaction map of the organelle.

Mitochondria carry out specialized functions; compartmentalized, yet integrated into the metabolic and signaling processes of the cell. Although many mitochondrial proteins have been identified, understanding their functional interrelationships has been a challenge. Here we construct a comprehensive network of the mitochondrial system. We integrated genome-wide datasets to generate an accurate and inclusive mitochondrial parts list. Together with benchmarked measures of protein interactions, a network of mitochondria was constructed in their cellular context, including extra-mitochondrial proteins. This network also integrates data from different organisms to expand the known mitochondrial biology beyond the information in the existing databases. Our network brings together annotated and predicted functions into a single framework. This enabled, for the entire system, a survey of mutant phenotypes, gene regulation, evolution, and disease susceptibility. Furthermore, we experimentally validated the localization of several candidate proteins and derived novel functional contexts for hundreds of uncharacterized proteins. Our network thus advances the understanding of the mitochondrial system in yeast and identifies properties of genes underlying human mitochondrial disorders.

Disease Susceptibility↗

PubMed2006

The more the merrier: comparative analysis of microarray studies on cell cycle-regulated genes in fission yeast.

The last two years have seen the publication of three genome-wide gene expression studies of the fission yeast cell cycle. While these microarray papers largely agree on the main patterns of cell cycle-regulated transcription and its control, there are discrepancies with regard to the identity and numbers of periodically expressed genes. We present benchmark and reproducibility analyses showing that the main discrepancies do not reflect differences in the data themselves (microarray or synchronization methods seem to lead only to minor biases) but rather in the interpretation of the data. Our reanalysis of the three datasets reveals that combining all independent information leads to an improved identification of periodically expressed genes. These evaluations suggest that the available microarray data do not allow reliable identification of more than about 500 cell cycle-regulated genes. The temporal expression pattern of the top 500 periodically expressed genes is generally consistent across experiments and the three studies, together with our integrated analysis, provide a coherent and rich source of information on cell cycle-regulated gene expression in Schizosaccharomyces pombe. The reanalysed datasets and other supplementary information are available from an accompanying website: http://www.cbs.dtu.dk/cellcycle/. We hope that this paper will resolve the apparent discrepancies between the previous studies and be useful both for wet-lab biologists and for theoretical scientists who wish to take advantage of the data for follow-up work.

Cell Cycle↗

PubMed2006

A temporal map of transcription factor activity: mef2 directly regulates target genes at all stages of muscle development.

Dissecting components of key transcriptional networks is essential for understanding complex developmental processes and phenotypes. Genetic studies have highlighted the role of members of the Mef2 family of transcription factors as essential regulators in myogenesis from flies to man. To understand how these transcription factors control diverse processes in muscle development, we have combined chromatin immunoprecipitation analysis with gene expression profiling to obtain a temporal map of Mef2 activity during Drosophila embryonic development. This global approach revealed three temporal patterns of Mef2 enhancer binding, providing a glimpse of dynamic enhancer use within the context of a developing embryo. Our results provide mechanistic insight into the regulation of Mef2's activity at the level of DNA binding and suggest cooperativity with the bHLH protein Twist. The number and diversity of new direct target genes indicates a much broader role for Mef2, at all stages of myogenesis, than previously anticipated.

Animals↗

PubMed2006

Origin of replication in circular prokaryotic chromosomes.

To predict origins of replication in prokaryotic chromosomes, we analyse the leading and lagging strands of 200 chromosomes for differences in oligomer composition and show that these correlate strongly with taxonomic grouping, lifestyle and molecular details of the replication process. While all bacteria have a preference for Gs over Cs on the leading strand, we discover that the direction of the A/T skew is determined by the polymerase-alpha subunit that replicates the leading strand. The strength of the strand bias varies greatly between both phyla and environments and appears to correlate with growth rate. Finally we observe much greater diversity of skew among archaea than among bacteria. We have developed a program that accurately locates the origins of replication by measuring the differences between leading and lagging strand of all oligonucleotides up to 8 bp in length. The program and results for all publicly available genomes are available from http://www.cbs.dtu.dk/services/GenomeAtlas/suppl/origin.

Archaea↗

PubMed2005

Extraction of transcript diversity from scientific literature.

Transcript diversity generated by alternative splicing and associated mechanisms contributes heavily to the functional complexity of biological systems. The numerous examples of the mechanisms and functional implications of these events are scattered throughout the scientific literature. Thus, it is crucial to have a tool that can automatically extract the relevant facts and collect them in a knowledge base that can aid the interpretation of data from high-throughput methods. We have developed and applied a composite text-mining method for extracting information on transcript diversity from the entire MEDLINE database in order to create a database of genes with alternative transcripts. It contains information on tissue specificity, number of isoforms, causative mechanisms, functional implications, and experimental methods used for detection. We have mined this resource to identify 959 instances of tissue-specific splicing. Our results in combination with those from EST-based methods suggest that alternative splicing is the preferred mechanism for generating transcript diversity in the nervous system. We provide new annotations for 1,860 genes with the potential for generating transcript diversity. We assign the MeSH term "alternative splicing" to 1,536 additional abstracts in the MEDLINE database and suggest new MeSH terms for other events. We have successfully extracted information about transcript diversity and semiautomatically generated a database, LSAT, that can provide a quantitative understanding of the mechanisms behind tissue-specific gene expression. LSAT (Literature Support for Alternative Transcripts) is publicly available at http://www.bork.embl.de/LSAT/.

Journal Article↗

PubMed2005

Systematic association of genes to phenotypes by genome and literature mining.

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene-phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases.

Bacteria↗

PubMed2005

STRING: known and predicted protein-protein associations, integrated and transferred across organisms.

A full description of a protein's function requires knowledge of all partner proteins with which it specifically associates. From a functional perspective, 'association' can mean direct physical binding, but can also mean indirect interaction such as participation in the same metabolic pathway or cellular process. Currently, information about protein association is scattered over a wide variety of resources and model organisms. STRING aims to simplify access to this information by providing a comprehensive, yet quality-controlled collection of protein-protein associations for a large number of organisms. The associations are derived from high-throughput experimental data, from the mining of databases and literature, and from predictions based on genomic context analysis. STRING integrates and ranks these associations by benchmarking them against a common reference set, and presents evidence in a consistent and intuitive web interface. Importantly, the associations are extended beyond the organism in which they were originally described, by automatic transfer to orthologous protein pairs in other organisms, where applicable. STRING currently holds 730,000 proteins in 180 fully sequenced organisms, and is available at http://string.embl.de/.

Databases, Protein↗

PubMed2005

Large-scale extraction of gene regulation for model organisms in an ontological context.

This paper presents an approach using syntactosemantic rules for the extraction of relational information from biomedical abstracts. The results show that by overcoming the hurdle of technical terminology, high precision results can be achieved. From abstracts related to baker's yeast, we manage to extract a regulatory network comprised of 441 pairwise relations from 58,664 abstracts with an accuracy of 83 - 90%. To achieve this, we made use of a resource of gene/protein names considerably larger than those used in most other biology related information extraction approaches. This list of names was included in the lexicon of our retrained partof- speech tagger for use on molecular biology abstracts. For the domain in question an accuracy of 93.6 - 97.7% was attained on Part-of-speech-tags. The method can be easily adapted to other organisms than yeast, allowing us to extract many more biologically relevant relations. The main reason for the comparable precision rates is the ontological model that was built beforehand and served as a guiding force for the manual coding of the syntactosemantic rules.

Abstracting and Indexing↗

PubMed2004

Depolarization-induced calcium influx in rat mesenteric small arterioles is mediated exclusively via mibefradil-sensitive calcium channels.

1. In this study, intracellular Ca(2+) was measured as the Fura-2 ratio (R) of fluorescence excited at 340 and 380 nm (F(340)/F(380)) in nonpressurized rat mesenteric small arterioles ( (lumen diameter) 10-25 microm). 2. The response to depolarization using 75 mm KCl was an increase in R from a baseline of 0.96+/-0.01 ([Ca(2+)](i) approximately 74 nm) to 1.04+/-0.01 ( approximately 128 nm) (n=80). The response to 75 mm K(+) was reversibly abolished in Ca(2+)-free physiological saline solution, whereas phentolamine (10 microm) or tetrodotoxin (1 microm) had no effects. LaCl(3) (200 microm) inhibited 61+/-9% of the response. 3. A [K(+)]-response curve indicated that the Ca(2+) response was activated between 15 and 25 mm K(+). The data suggest that the Ca(2+) response was caused by the activation of voltage-dependent Ca(2+) channels. 4. Mibefradil use dependently inhibited the Ca(2+) response to 75 mm K(+) by 29+/-2% (100 nm), 73+/-7% (1 microm) or 89+/-7% (10 microm). Pimozide (500 nm) use dependently inhibited the Ca(2+) response by 85+/-1%. 5. Nifedipine (1 microm) inhibited the Ca(2+) response to 75 mm K(+) by 41+/-12%. The response was not inhibited by calciseptine (500 nm), omega-agatoxin IVA (100 nm), omega-conotoxin MVIIA (500 nm), or SNX-482 (100 nm). 6. Using reverse transcriptase-polymerase chain reaction, it was shown that neither Ca(V)2.1a (P-type) nor Ca(V)2.1b (Q-type) voltage-dependent Ca(2+) channels were expressed in mesenteric arterioles, whereas the Ca(V)3.1 (T-type) channel was expressed. Furthermore, no amplification products were detected when using specific primers for the beta(1b), beta(2), or beta(3) auxiliary subunits of high-voltage-activated Ca(2+) channels. 7. The results suggest that the voltage-dependent Ca(2+) channel activated by sustained depolarization in mesenteric arterioles does not classify as any of the high-voltage-activated channels (L-, P/Q-, N-, or R-type), but is likely to be a T-type channel. The possibility that the sustained Ca(2+) influx observed was the result of a T-type window current is discussed.

Animals↗

PubMed2004

Protein interaction networks from yeast to human.

Protein interaction networks summarize large amounts of protein-protein interaction data, both from individual, small-scale experiments and from automated high-throughput screens. The past year has seen a flood of new experimental data, especially on metazoans, as well as an increasing number of analyses designed to reveal aspects of network topology, modularity and evolution. As only minimal progress has been made in mapping the human proteome using high-throughput screens, the transfer of interaction information within and across species has become increasingly important. With more and more heterogeneous raw data becoming available, proper data integration and quality control have become essential for reliable protein network reconstruction, and will be especially important for reconstructing the human protein interaction network.

Animals↗

PubMed2004

Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs.

Several widely used methods for predicting functional associations between proteins are based on the systematic analysis of genomic context. Efforts are ongoing to improve these methods and to search for novel aspects in genomes that could be exploited for function prediction. Here, we use gene expression data to demonstrate two functional implications of genome organization: first, chromosomal proximity indicates gene coregulation in prokaryotes independent of relative gene orientation; and second, adjacent bidirectionally transcribed genes (that is,'divergently' organized coding regions) with conserved gene orientation are strongly coregulated. We further demonstrate that such bidirectionally transcribed gene pairs are functionally associated and derive from this a novel genomic context method that reliably predicts links between >2,500 pairs of genes in approximately 100 species. Around 650 of these functional associations are supported by other genomic context methods. In most instances, one gene encodes a transcriptional regulator, and the other a nonregulatory protein. In-depth analysis in Escherichia coli shows that the vast majority of these regulators both control transcription of the divergently transcribed target gene/operon and auto-regulate their own biosynthesis. The method thus enables the prediction of target processes and regulatory features for several hundred transcriptional regulators.

Amino Acid Sequence↗

PubMed2003

Protein feature based identification of cell cycle regulated proteins in yeast.

DNA microarrays have been used extensively to identify cell cycle regulated genes in yeast; however, the overlap in the genes identified is surprisingly small. We show that certain protein features can be used to distinguish cell cycle regulated genes from other genes with high confidence (features include protein phosphorylation, glycosylation, subcellular location and instability/degradation). We demonstrate that co-expressed, periodic genes encode proteins which share combinations of features, and provide an overview of the proteome dynamics during the cycle. A large set of novel putative cell cycle regulated proteins were identified, many of which have no known function.

Cell Cycle↗

PubMed2003

Expression of connexin 37, 40 and 43 in rat mesenteric arterioles and resistance arteries.

Connexins are the protein constituents of gap junctions which mediate intercellular communication in most tissues. In arterioles gap junctions appear to be important for conduction of vasomotor responses along the vessel. Studies of the expression pattern of connexin isoforms in the microcirculation are sparse. We investigated the expression of the three major vascular connexins in mesenteric arterioles (diameter <50 micro m) from male Sprague-Dawley rats, since conducted vasomotor responses have been described in these vessels. The findings were compared with those obtained from upstream small resistance arteries. Indirect immunofluorescence techniques were used on whole mounts of mesenteric arterioles and on frozen sections of resistance arteries (diameter approximately 300 micro m). Mesenteric arterioles expressed Cx40 and Cx43 in the endothelial layer, and Cx37 was found in most but not all vessels. Connexins were not demonstrated in the media. In resistance arteries endothelial cells expressed Cx37, Cx40 and Cx43. Ultrastructural studies of mesenteric arterioles confirmed that gap junction plaques between endothelial cells are present, whereas myoendothelial, or smooth muscle cell gap junctions could not be demonstrated. The findings suggest that smooth muscle cells in mesenteric arterioles may not be well coupled and favour that conducted vasomotor responses in these vessels are propagated through the endothelial cell layer.

Animals↗