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Biomedical subjects

Thomas Wilhelm

Publications and source records attributed to Thomas Wilhelm.

13 recordsLinked to original sources
PubMed2006

DASS: efficient discovery and p-value calculation of substructures in unordered data.

MOTIVATION: Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. RESULTS: We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. AVAILABILITY: The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

Algorithms↗
PubMed2006

Hypusination of eukaryotic initiation factor 5A (eIF5A): a novel therapeutic target in BCR-ABL-positive leukemias identified by a proteomics approach.

Inhibition of BCR-ABL tyrosine kinase with imatinib represents a major breakthrough in the treatment of patients with chronic myeloid leukemia (CML). However, resistance to imatinib develops frequently, particularly in late-stage disease. To identify new cellular BCR-ABL downstream targets, we analyzed differences in global protein expression in BCR-ABL-positive K562 cells treated with or without imatinib in vitro. Among the 19 proteins found to be differentially expressed, we detected the down-regulation of eukaryotic initiation factor 5A (eIF5A), a protein essential for cell proliferation. eIF5A represents the only known eukaryotic protein activated by posttranslational hypusination. Hypusination inhibitors (HIs) alone exerted an antiproliferative effect on BCR-ABL-positive and -negative leukemia cell lines in vitro. However, the synergistic dose-response relationship found for the combination of imatinib and HI was restricted to Bcr-Abl-positive cells. Furthermore, this synergistic effect was confirmed by cytotoxicity assays, cell-cycle analysis, and CFSE labeling of primary CD34+ CML cells. Specificity of this effect could be demonstrated by cotreatment of K562 cells with imatinib and siRNA against eIF5. In conclusion, through a comparative proteomics approach and further functional analysis, we identified the inhibition of eIF5A hypusination as a promising new approach for combination therapy in BCR-ABL-positive leukemias.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2006

Integrated assessment and prediction of transcription factor binding.

Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF-target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which "standard conditions" are ill defined.

Algorithms↗
PubMed2006

Brachial plexus hypertrophy in chronic inflammatory demyelinating polyradiculoneuropathy.

We present the clinical, imaging and neuropathological findings in three patients with predominant brachial plexus neuropathy. MR scanning was key to determining the brachial plexus involvement. Biopsy of the brachial plexus was performed in one patient. The appearances of the brachial plexus on MRI, in conjunction with the clinical presentations of these patients, suggest that they are unusual variants within the spectrum of chronic inflammatory demyelinating polyradiculoneuropathy.

Adult↗
PubMed2006

The new classification scheme of the genetic code, its early evolution, and tRNA usage.

We present a new classification scheme of the genetic code. In contrast to the standard form it clearly shows five codon symmetries: codon-anticodon, codon-reverse codon, and sense-antisense symmetry, as well as symmetries with respect to purine-pyrimidine (A versus G, U versus C) and keto-aminobase (G versus U, A versus C) exchanges. We study the number of tRNA genes of 16 archaea, 81 bacteria and 7 eucaryotes to analyze whether these symmetries are reflected in the corresponding tRNA usage patterns. Two features are especially striking: reverse stop codons do not have their own tRNAs (just one exception in human), and A** anticodons are significantly suppressed. Our classification scheme of the genetic code and the identified tRNA usage patterns support recent speculations about the early evolution of the genetic code. In particular, pre-tRNAs might have had the ability to bind their codons in two directions to the corresponding codons.

Biological Evolution↗
PubMed2005

Common patterns in type II restriction enzyme binding sites.

Restriction enzymes are among the best studied examples of DNA binding proteins. In order to find general patterns in DNA recognition sites, which may reflect important properties of protein-DNA interaction, we analyse the binding sites of all known type II restriction endonucleases. We find a significantly enhanced GC content and discuss three explanations for this phenomenon. Moreover, we study patterns of nucleotide order in recognition sites. Our analysis reveals a striking accumulation of adjacent purines (R) or pyrimidines (Y). We discuss three possible reasons: RR/YY dinucleotides are characterized by (i) stronger H-bond donor and acceptor clusters, (ii) specific geometrical properties and (iii) a low stacking energy. These features make RR/YY steps particularly accessible for specific protein-DNA interactions. Finally, we show that the recognition sites of type II restriction enzymes are underrepresented in host genomes and in phage genomes.

Bacteriophages↗
PubMed2005

Identification and characterization of protein subcomplexes in yeast.

Protein complexes are major components of cellular organization. Based on large-scale protein complex data, we present the first statistical procedure to find insightful substructures in protein complexes: we identify protein subcomplexes (SCs), i.e., multiprotein assemblies residing in different protein complexes. Four protein complex datasets with different origins and variable reliability are separately analyzed. Our method identifies well-characterized protein assemblies with known functions, thereby confirming the utility of the procedure. In addition, we also identify hitherto unknown functional entities consisting of either functionally unknown proteins or proteins with different functional annotation. We show that SCs represent more reliable protein assemblies than the original complexes. Finally, we demonstrate unique properties of subcomplex proteins that underline the distinct roles of SCs: (i) SCs are functionally and spatially more homogeneous than complete protein complexes (this fact is utilized to predict functional roles and subcellular localizations for so far unannotated proteins); (ii) the abundance of subcomplex proteins is less variable than the abundance of other proteins; (iii) SCs are enriched with essential and synthetic lethal proteins; and (iv) mutations in SC-proteins have higher fitness effects than mutations in other proteins.

Gene Deletion↗
PubMed2004

Post-transcriptional expression regulation in the yeast Saccharomyces cerevisiae on a genomic scale.

Based on large-scale data for the yeast Saccharomyces cerevisiae (protein and mRNA abundance, translational status, transcript length), we investigate the relation of transcription, translation, and protein turnover on a genome-wide scale. We elucidate variations between different spatial cell compartments and functional modules by comparing protein-to-mRNA ratios, translational activity, and a novel descriptor for protein-specific degradation (protein half-life descriptor). This analysis helps to understand the cell's strategy to use transcriptional and post-transcriptional regulation mechanisms for managing protein levels. For instance, it is possible to identify modules that are subject to suppressed translation under normal conditions ("translation on demand"). In order to reduce inconsistencies between the datasets, we compiled a new reference mRNA abundance dataset and we present a novel approach to correct large microarray signals for a saturation bias. Accounting for ribosome density based on transcript length rather than ORF length improves the correlation of observed protein levels to translational activity. We discuss potential causes for the deviations of these correlations. Finally, we introduce a quantitative descriptor for protein degradation (protein half-life descriptor) and compare it to measured half-lives. The study demonstrates significant post-transcriptional control of protein levels for a number of different compartments and functional modules, which is missed when exclusively focusing on transcript levels.

Cell Compartmentation↗
PubMed2004

A new classification scheme of the genetic code.

Since the early days of the discovery of the genetic code nonrandom patterns have been searched for in the code in the hope of providing information about its origin and early evolution. Here we present a new classification scheme of the genetic code that is based on a binary representation of the purines and pyrimidines. This scheme reveals known patterns more clearly than the common one, for instance, the classification of strong, mixed, and weak codons as well as the ordering of codon families. Furthermore, new patterns have been found that have not been described before: Nearly all quantitative amino acid properties, such as Woese's polarity and the specific volume, show a perfect correlation to Lagerkvist's codon-anticodon binding strength. Our new scheme leads to new ideas about the evolution of the genetic code. It is hypothesized that it started with a binary doublet code and developed via a quaternary doublet code into the contemporary triplet code. Furthermore, arguments are presented against suggestions that a "simpler" code, where only the midbase was informational, was at the origin of the genetic code.

Amino Acids↗
PubMed2003

Physical and functional modularity of the protein network in yeast.

While protein-protein interactions have been studied largely as a network graph without physicality, here we analyze two protein complex data sets of Saccharomyces cerevisiae to relate physical and functional modularity to the network topology. We study for the first time the number of different protein complexes as a function of the protein complex size and find that it follows an exponential decay with a characteristic number of about 7. This reflects the dynamics of complex formation and dissociation in the cell. The analysis of the protein usage by complexes shows an extensive sharing of subunits that is due to the particular organization of the proteome into physical complexes and functional modules. This promiscuity accounts for the high clustering in the protein net-work graph. Our results underscore the need to include the information contained in observed protein complexes into protein network analyses.

Models, Theoretical↗
PubMed2003

[Fast 1H-NR spectroscopic imaging of the human brain].

Techniques allowing the reduction of the measurement time of MR spectroscopic imaging of protons (1H SI) were studied in a 1.5-T whole-body MR tomograph. The purpose was to facilitate the inclusion of the modality into an MRT routine protocol for examination of the human brain. The techniques were evaluated in a study with 6 healthy volunteers. Shortening of the measurement times can be achieved by reducing the number of phase-encoding steps with spherical k-space sampling, or by using delay times during TR periods for excitation and detection of several slices or echos. Since the tomograph enables echo-planar imaging, multi-gradiennt-echo techniques were implemented, thus sparing one phase-encoding gradient and shortening the measurement time by a factor of N. Due to signal loss, however, this technique is applicable only when the concentration of the metabolites of interest is sufficiently high to obtain a signal-to-noise ratio of at least 2 with a single acquisition.

Brain↗
PubMed2002

Characterization and manipulation of microscopic biochemically active regions by scanning electrochemical microscopy (SECM).

Preparation and characterization of microscopic biochemically active regions are important for the development of miniaturized bioanalytical systems with proteins, such as miniaturized enzyme electrode arrays. Scanning electrochemical microscopy (SECM) has emerged as an ideal tool for prototyping such systems. The technique is based on electrochemical conversions of dissolved species at a micrometer-sized probe electrode. It offers several mechanisms for local surface modifications under conditions compatible with conservation of protein functionality of enzymes and antibodies. The subsequent imaging of the immobilized activity provides direct information about local immobilized enzyme activities. The working modes of the techniques are illustrated by recent studies from this laboratory for the design and characterization of patterned enzyme layers covalently linked to gold surfaces via thiol self-assembly chemistry.

Binding Sites↗