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Biomedical subjects

E Wingender

Publications and source records attributed to E Wingender.

At least 19 recordsLinked to original sources

Experimental analysis and computer prediction of CTF/NFI transcription factor DNA binding sites.

Accurate prediction of transcription factor binding sites is needed to unravel the function and regulation of genes discovered in genome sequencing projects. To evaluate current computer prediction tools, we have begun a systematic study of the sequence-specific DNA-binding of a transcription factor belonging to the CTF/NFI family. Using a systematic collection of rationally designed oligonucleotides combined with an in vitro DNA binding assay, we found that the sequence specificity of this protein cannot be represented by a simple consensus sequence or weight matrix. For instance, CTF/NFI uses a flexible DNA binding mode that allows for variations of the binding site length. From the experimental data, we derived a novel prediction method using a generalised profile as a binding site predictor. Experimental evaluation of the generalised profile indicated that it accurately predicts the binding affinity of the transcription factor to natural or synthetic DNA sequences. Furthermore, the in vitro measured binding affinities of a subset of oligonucleotides were found to correlate with their transcriptional activities in transfected cells. The combined computational-experimental approach exemplified in this work thus resulted in an accurate prediction method for CTF/NFI binding sites potentially functioning as regulatory regions in vivo.

Adenoviruses, Human↗

COMPEL: a database on composite regulatory elements providing combinatorial transcriptional regulation.

COMPEL is a database on composite regulatory elements, the basic structures of combinatorial regulation. Composite regulatory elements contain two closely situated binding sites for distinct transcription factors and represent minimal functional units providing combinatorial transcriptional regulation. Both specific factor-DNA and factor-factor interactions contribute to the function of composite elements (CEs). Information about the structure of known CEs and specific gene regulation achieved through such CEs appears to be extremely useful for promoter prediction, for gene function prediction and for applied gene engineering as well. The structure of the relational model of COMPEL is determined by the concept of molecular structure and regulatory role of CEs. Based on the set of a particular CE, a program has been developed for searching potential CEs in gene regulatory regions. WWW search and browse routines were developed for COMPEL release 3.0. The COMPEL database equipped with the search and browse tools is available at http://compel.bionet.nsc.ru/. The program for prediction of potential CEs of NFAT type is available at http://compel.bionet.nsc. ru/FunSite.html and http://transfac.gbf.de/dbsearch/funsitep/ s_comp.html

Database Management Systems↗

TRANSFAC: an integrated system for gene expression regulation.

TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles (http://transfac.gbf.de/TRANSFAC/). Its content has been enhanced, in particular by information about training sequences used for the construction of nucleotide matrices as well as by data on plant sites and factors. Moreover, TRANSFAC has been extended by two new modules: PathoDB provides data on pathologically relevant mutations in regulatory regions and transcription factor genes, whereas S/MARt DB compiles features of scaffold/matrix attached regions (S/MARs) and the proteins binding to them. Additionally, the databases TRANSPATH, about signal transduction, and CYTOMER, about organs and cell types, have been extended and are increasingly integrated with the TRANSFAC data sources.

Database Management Systems↗

Recognition of NFATp/AP-1 composite elements within genes induced upon the activation of immune cells.

Composite elements are regulatory modules of promoters or enhancers that consist of binding sites of two different but synergizing transcription factors. A well-studied example is nuclear factors of activated T-cell (NFAT) sites which are composite elements of a NFATp/c and an activating protein 1 (AP-1) binding site. We have developed a computational approach to identify potential NFAT target genes which (a) comprises an improved method to scan for individual NFAT composite elements; (b) considers positional effects relative to transcription start sites; and (c) involves cluster analysis of potential NFAT composite elements. All three steps progressively helpX?ed to discriminate T-cell-specific promoter sequences against other functional regions (coding and intronic sequences) of the same genes, against promoters of muscle-specific genes or against random sequences. Using this approach, we identified potential NFAT composite elements in promoters of cytokine genes and their receptors as well as in promoters of genes for AP-1 family members, Ca2+-binding proteins and some other components of the regulatory network operating in activated T-cells and other immune cells. The method developed can be adapted to characterize and identify other composite elements as well. The program for recognition NFAT composite elements is available through the World Wide Web (http://compel.bionet.nsc.ru/FunSite/CompelScan. html and http://transfac.gbf.de/dbsearch/funsitep/s _comp.html).

Animals↗

Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms.

TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles. In addition to being updated and extended by new features, it has been complemented now by a series of additional database modules. Among them, modules which provide data about signal transduction pathways (TRANSPATH) or about cell types/organs/developmental stages (CYTOMER) are available as well as an updated version of the previously described COMPEL database. The databases are available on the WWW at http://transfac.gbf.de/

Animals↗

Databases on transcriptional regulation: TRANSFAC, TRRD and COMPEL.

TRANSFAC, TRRD (Transcription Regulatory Region Database) and COMPEL are databases which store information about transcriptional regulation in eukaryotic cells. The three databases provide distinct views on the components involved in transcription: transcription factors and their binding sites and binding profiles (TRANSFAC), the regulatory hierarchy of whole genes (TRRD), and the structural and functional properties of composite elements (COMPEL). The quantitative and qualitative changes of all three databases and connected programs are described. The databases are accessible via WWW:http://transfac.gbf.de/TRANSFAC orhttp://www.bionet.nsc.ru/TRRD

Animals↗

Activation of nuclear factor-kappaB in macrophages by mycoplasmal lipopeptides.

Mycoplasmas are potent macrophage stimulators. The active principle are lipopeptides or lipoproteins with a characteristic N-terminal S-[dihydroxypropyl]-cysteinyl group bearing two ester-bound fatty acids and lacking the amide-bound one common to other bacterial lipoproteins. Using synthetic analogues of mycoplasmal lipopeptides, we investigated activation of the transcription factor NF-kappaB in the C3H/HeJ mouse-derived DMBM-3 cell line. The lipopeptides activated NF-kappaB at below nanomolar concentrations. Activation in the murine system occurred distinctly earlier than TNF-alpha liberation, excluding autocrine stimulation by TNF-alpha. As determined from a supershift experiment, the active NF-kappaB complex consisted of the heterodimer p50/p65(RelA). The relevance of these findings for the inflammatory response to mycoplasmas and for mycoplasma-mediated effects on HIV-infected macrophages is discussed.

Animals↗

Transcription regulatory region analysis using signal detection and fuzzy clustering.

MOTIVATION: Presently available programs for the recognition of potential transcription factor binding sites in genomic sequences generally yield a huge amount of output. These output lists have to be filtered to obtain biologically significant elements, which is highly laborious work to be done manually. RESULTS: We developed a strategy for systematic verification and improvement of the underlying profiles, and for their contextual analysis by a fuzzy clustering approach using non-redundant libraries of search profiles as a prerequisite. AVAILABILITY: The tools mentioned in the paper are available upon request. CONTACT: ewi@gbf.de

Algorithms↗

GeneExpress: a computer system for description, analysis, and recognition of regulatory sequences in eukaryotic genome.

GeneExpress system has been designed to integrate description, analysis, and recognition of eukaryotic regulatory sequences. The system includes 5 basic units: (1) GeneNet contains an object-oriented database for accumulation of data on gene networks and signal transduction pathways and a Java-based viewer that allows an exploration and visualization of the GeneNet information; (2) Transcription Regulation combines the database on transcription regulatory regions of eukaryotic genes (TRRD) and TRRD Viewer; (3) Transcription Factor Binding Site Recognition contains a compilation of transcription factor binding sites (TFBSC) and programs for their analysis and recognition; (4) mRNA Translation is designed for analysis of structural and contextual features of mRNA 5'UTRs and prediction of their translation efficiency; and (5) ACTIVITY is the module for analysis and site activity prediction of a given nucleotide sequence. Integration of the databases in the GeneExpress is based on the Sequence Retrieval System (SRS) created in the European Bioinformatics Institute.

Artificial Intelligence↗

TRANSFAC, TRRD and COMPEL: towards a federated database system on transcriptional regulation.

Three databases that provide data on transcriptional regulation are described. TRANSFAC is a database on transcription factors and their DNA binding sites. TRRD (Transcription Regulatory Region Database) collects information about complete regulatory regions, their regulation properties and architecture. COMPEL comprises specific information on composite regulatory elements. Here, we describe the present status of these databases and the first steps towards their federation.

Animals↗

Expression of the RT6 mono(ADP-ribosyl)transferases is regulated by two promoter regions.

The structure of the RT6 mono(ADP-ribosyl)transferase gene was studied. Analysis of cDNA clones revealed eight exons and suggested two independent transcriptional start sites. The existence of the downstream initiation site was confirmed by S1-nuclease protection and localized to position +29 of exon 2. The corresponding 5' flanking regions were found to contain typical promoter structures such as TATA- and CCAAT-boxes. Comparison with sequences deposited in the TRANSFAC database of transcription factor binding sites revealed few putative regulatory elements in the region associated with exon 1 (promoter 1). In contrast, several elements contained in the regulatory regions of other T cell-specific genes, such as ets, lyf-1 and ikaros were found in in promoter 2. Analysis of RT6-transcripts showed this region to be the most active promoter in spleen cells of adult rats. Finally, transient transfection assays with reporter gene constructs showed promoter 2 to mediate T-cell specific transcription.

ADP Ribose Transferases↗

TRANSFAC database as a bridge between sequence data libraries and biological function.

The TRANSFAC database contains information about regulatory DNA sequences and the proteins (transcription factors) binding to and acting through them. It may thus serve as a dictionary for the biological meaning of these sequence elements. Moreover, the TRANSFAC data can be used to describe these elements, to define consensi and matrices for elements of certain function, and thus to provide means of identifying regulatory signals in newly unravelled genomic sequences.

Base Sequence↗

Structure of the gene encoding the rat T cell ecto-ADP-ribosyltransferase RT6.

Cellular functions, such as the cytolytic potential of CTLs, can be regulated by mono-ADP-ribosylation of target proteins. Recently, the T cell differentiation marker RT6 has been shown to possess mono-ADP-ribosyltransferase activity. Defects in RT6 expression coincide with increased susceptibility in animal models for insulin-dependent diabetes mellitus and other autoimmune diseases. We present an analysis of the rat RT6 gene, providing a basis for studying the regulation of this gene in T cells of normal and diabetes-prone rats. It is the first structural analysis of a mammalian mono-ADP-ribosyltransferase gene. The RT6 gene consists of eight exons spanning approximately 20 kb. The proximal four exons encode 5' untranslated region sequences and are found in multiple alternatively spliced variants. Exon 5 encodes the N-terminal signal sequence. An unusually large exon 7 encodes the entire native polypeptide. The final exon 8 encodes the C-terminal signal sequence for glycosylphosphatidylinositol anchor attachment and the 3' untranslated region. Two independent TATA box-containing promoters associated with exons 1 and 2 were identified, and their activity was verified in transient transfection assays. The distal promoter displays elements contained in the regulatory regions of T cell-specific genes, such as ets and ikaros. Analysis of RT6 transcripts showed that this promoter is the major one in adult rat spleen cells. The 3' end of the gene does not display alternative splicing. However, two polyadenylation signals are found in the 3' untranslated region.

ADP Ribose Transferases↗

Parathyroid hormone-related protein antagonizes the action of parathyroid hormone on adult cardiomyocytes.

Ventricular cardiomyocytes have been identified as target cells for parathyroid hormone (PTH). A structurally related peptide hormone, parathyroid hormone-related peptide (PTH-rP), is expressed in the heart. In the present study, it was investigated whether PTH-rP can mimic or modify effects of PTH on cardiomyocytes. The investigated effect was induction of creatine kinase (CK) activity, which is associated with cardiac hypertrophy. PTH and PTH-rP have a similar secondary structure within the active domain 28 34, with exception of amino acid 29. At this position the hydrophilic glutamine in the PTH molecule corresponds to hydrophobic alanine in the PTH-rP molecule. Synthetic PTH or PTH-rP peptides covering domain 28 34 and recombinant full-length PTH(1 84) were used. PTH(28 48) (100 nm) induced CK activity within 24 h (123 +/- 3%; means +/- S.D., n = 4). PTH-rP(7-34) (1 nm to 1 microm) failed to induce CK activity in cardiomyocytes. Given simultaneously, PTH-rP (1 mum) reduced the stimulation of CK activity by PTH(1-84), PTH(1-34), and PTH(28-48) by 94 +/- 9, 79 +/- 8, and 69 +/- 14%, respectively (means +/- S.D., n = 4). In contrast, PTH-rP(7-34) was sufficient to stimulate proliferation of chicken chondrocytes. Thus, PTH-rP exerts different effects on cardiomyocytes and classical target cells for PTH. A synthetic hybrid peptide was synthesized, [Ala29]PTH(28-48), in which alanine replaced glutamine at position 29, as in the PTH-rP molecule. In contrast to PTH(28-48), this mutated peptide [Ala29]PTH(28-48) had no intrinsic activity but antagonized the effect of PTH(1-84) and PTH(28-48) on cardiomyocytes. The results demonstrate that on cardiomyocytes the effect of PTH can be antagonized by PTH-rP. This antagonism seems due to a hydrophobic replacement at position 29.

Animals↗

Combining structural analysis of DNA with search routines for the detection of transcription regulatory elements.

MOTIVATION: Analysis of unannotated genomic sequences for regulatory regions depends on a reliable recognition of individual cis-acting elements. Since some of them have a very low conserved sequence pattern, additional criteria are required. RESULTS: Using molecular modelling techniques, we have created a complete database for the conversion of base sequences into profiles of structural parameters of DNA. On this basis, search routines can be developed that scan for profile matches. They may be used instead of or, probably most appropriate in most cases, in combination with conventional sequence pattern searches.

Algorithms↗

Structure of recombinant human parathyroid hormone in solution using multidimensional NMR spectroscopy.

The solution structure of human parathyroid hormone, in the form of recombinant prolyl-hPTH(1-84), has been investigated by multidimensional NMR spectroscopy under conditions (aqueous trifluoroethanol) which favour the structured-state of the protein. Spin systems were identified from 3D 1H DQF (double-quantum filtered)-COSY and TOCSY spectra and sequence-specific assignments were from 2D 1H phase-sensitive NOESY spectra. Signal overlap was resolved in a 3D-NOESY-TOCSY spectrum and assignments were confirmed with 2D NOESY-15N-HMQC (heteronuclear multiple-quantum coherence) spectra taken of a sample universally labeled with 15N. A satisfactory set of final structures was calculated from the quantitative NOE data using restrained molecular dynamics and energy minimization calculations. The N-terminus is dominated by three, well defined helices between Ser-3 to Asn-10, Ser-17 to Lys-27 and Asp-30 to Leu-37, while the most significant structural features in the C-terminus are a short, less-well defined helix between Asn-57 to Ser-62 and a series of loose turns. These two terminal units are joined by an unstructured mid-region. The molecule shows a tendency towards tertiary structure, defined by a number of long-range NOEs. A detailed RMS deviation analysis allowed the final refined structures to be classified into a limited ensemble of stable conformations that reflect the inherent flexibility of the hormone in solution.

Amino Acid Sequence↗