Biomedical subjects

Christine Brun

Publications and source records attributed to Christine Brun.

15 recordsLinked to original sources

PubMed2006

TreeDyn: towards dynamic graphics and annotations for analyses of trees.

BACKGROUND: Analyses of biomolecules for biodiversity, phylogeny or structure/function studies often use graphical tree representations. Many powerful tree editors are now available, but existing tree visualization tools make little use of meta-information related to the entities under study such as taxonomic descriptions or gene functions that can hardly be encoded within the tree itself (if using popular tree formats). Consequently, a tedious manual analysis and post-processing of the tree graphics are required if one needs to use external information for displaying or investigating trees. RESULTS: We have developed TreeDyn, a tool using annotations and dynamic graphical methods for editing and analyzing multiple trees. The main features of TreeDyn are 1) the management of multiple windows and multiple trees per window, 2) the export of graphics to several standard file formats with or without HTML encapsulation and a new format called TGF, which enables saving and restoring graphical analysis, 3) the projection of texts or symbols facing leaf labels or linked to nodes, through manual pasting or by using annotation files, 4) the highlight of graphical elements after querying leaf labels (or annotations) or by selection of graphical elements and information extraction, 5) the highlight of targeted trees according to a source tree browsed by the user, 6) powerful scripts for automating repetitive graphical tasks, 7) a command line interpreter enabling the use of TreeDyn through CGI scripts for online building of trees, 8) the inclusion of a library of packages dedicated to specific research fields involving trees. CONCLUSION: TreeDyn is a tree visualization and annotation tool which includes tools for tree manipulation and annotation and uses meta-information through dynamic graphical operators or scripting to help analyses and annotations of single trees or tree collections.

Computer Graphics↗

PubMed2006

The pitfalls of proteomics experiments without the correct use of bioinformatics tools.

The elucidation of the entire genomic sequence of various organisms, from viruses to complex metazoans, most recently man, is undoubtedly the greatest triumph of molecular biology since the discovery of the DNA double helix. Over the past two decades, the focus of molecular biology has gradually moved from genomes to proteomes, the intention being to discover the functions of the genes themselves. The postgenomic era stimulated the development of new techniques (e.g. 2-DE and MS) and bioinformatics tools to identify the functions, reactions, interactions and location of the gene products in tissues and/or cells of living organisms. Both 2-DE and MS have been very successfully employed to identify proteins involved in biological phenomena (e.g. immunity, cancer, host-parasite interactions, etc.), although recently, several papers have emphasised the pitfalls of 2-DE experiments, especially in relation to experimental design, poor statistical treatment and the high rate of 'false positive' results with regard to protein identification. In the light of these perceived problems, we review the advantages and misuses of bioinformatics tools - from realisation of 2-DE gels to the identification of candidate protein spots - and suggest some useful avenues to improve the quality of 2-DE experiments. In addition, we present key steps which, in our view, need to be to taken into consideration during such analyses. Lastly, we present novel biological entities named 'interactomes', and the bioinformatics tools developed to analyse the large protein-protein interaction networks they form, along with several new perspectives of the field.

Amino Acid Sequence↗

PubMed2005

PRODISTIN Web Site: a tool for the functional classification of proteins from interaction networks.

UNLABELLED: The PRODISTIN Web Site is a web service allowing users to functionally classify genes/proteins from any type of interaction network. The resulting computation provides a classification tree in which (1) genes/proteins are clustered according to the identity of their interaction partners and (2) functional classes are delineated in the tree using the Biological Process Gene Ontology annotations. AVAILABILITY: The PRODISTIN Web Site is freely accessible at http://gin.univ-mrs.fr/webdistin

Algorithms↗

PubMed2005

Protein interaction mapping: a Drosophila case study.

The Drosophila (fruit fly) model system has been instrumental in our current understanding of human biology, development, and diseases. Here, we used a high-throughput yeast two-hybrid (Y2H)-based technology to screen 102 bait proteins from Drosophila melanogaster, most of them orthologous to human cancer-related and/or signaling proteins, against high-complexity fly cDNA libraries. More than 2300 protein-protein interactions (PPI) were identified, of which 710 are of high confidence. The computation of a reliability score for each protein-protein interaction and the systematic identification of the interacting domain combined with a prediction of structural/functional motifs allow the elaboration of known complexes and the identification of new ones. The full data set can be visualized using a graphical Web interface, the PIMRider (http://pim.hybrigenics.com), and is also accessible in the PSI standard Molecular Interaction data format. Our fly Protein Interaction Map (PIM) is surprisingly different from the one recently proposed by Giot et al. with little overlap between the two data sets. Analysis of the differences in data sets and methods suggests alternative strategies to enhance the accuracy and comprehensiveness of the post-genomic generation of broad-scale protein interaction maps.

Animals↗

PubMed2005

In vivo RNA localization of I factor, a non-LTR retrotransposon, requires a cis-acting signal in ORF2 and ORF1 protein.

According to the current model of non-LTR retrotransposon (NLR) mobilization, co-expression of the RNA transposition intermediate, and the proteins it encodes (ORF1p and ORF2p), is a requisite for the formation of cytoplasmic ribonucleoprotein complexes which contain necessary elements to complete a retrotransposition cycle later in the nucleus. To understand these early processes of NLR mobilization, here we analyzed in vivo the protein and RNA expression patterns of the I factor, a model NLR in Drosophila. We show that ORF1p and I factor RNA, specifically produced during transposition, are co-expressed and tightly co-localize with a specific pattern (Loc+) exclusively in the cytoplasm of germ cells permissive for retrotransposition. Using an ORF2 mutated I factor, we show that ORF2p plays no role in the Loc+ patterning. With deletion derivatives of an I factor we define an RNA localization signal required to display the Loc+ pattern. Finally, by complementation experiments we show that ORF1p is necessary for the efficient localization of I factor RNA. Our data suggest that ORF1p is involved in proper folding and stabilization of I factor RNA for efficient targeting, through Loc+ patterning, to the nuclear neighborhood where downstream steps of the retrotransposition process occur.

Animals↗

PubMed2004

GOToolBox: functional analysis of gene datasets based on Gene Ontology.

We have developed methods and tools based on the Gene Ontology (GO) resource allowing the identification of statistically over- or under-represented terms in a gene dataset; the clustering of functionally related genes within a set; and the retrieval of genes sharing annotations with a query gene. GO annotations can also be constrained to a slim hierarchy or a given level of the ontology. The source codes are available upon request, and distributed under the GPL license.

Animals↗

PubMed2004

A scale of functional divergence for yeast duplicated genes revealed from analysis of the protein-protein interaction network.

BACKGROUND: Studying the evolution of the function of duplicated genes usually implies an estimation of the extent of functional conservation/divergence between duplicates from comparison of actual sequences. This only reveals the possible molecular function of genes without taking into account their cellular function(s). We took into consideration this latter dimension of gene function to approach the functional evolution of duplicated genes by analyzing the protein-protein interaction network in which their products are involved. For this, we derived a functional classification of the proteins using PRODISTIN, a bioinformatics method allowing comparison of protein function. Our work focused on the duplicated yeast genes, remnants of an ancient whole-genome duplication. RESULTS: Starting from 4,143 interactions, we analyzed 41 duplicated protein pairs with the PRODISTIN method. We showed that duplicated pairs behaved differently in the classification with respect to their interactors. The different observed behaviors allowed us to propose a functional scale of conservation/divergence for the duplicated genes, based on interaction data. By comparing our results to the functional information carried by GO annotations and sequence comparisons, we showed that the interaction network analysis reveals functional subtleties, which are not discernible by other means. Finally, we interpreted our results in terms of evolutionary scenarios. CONCLUSIONS: Our analysis might provide a new way to analyse the functional evolution of duplicated genes and constitutes the first attempt of protein function evolutionary comparisons based on protein-protein interactions.

Computational Biology↗

PubMed2004

Clustering proteins from interaction networks for the prediction of cellular functions.

BACKGROUND: Developing reliable and efficient strategies allowing to infer a function to yet uncharacterized proteins based on interaction networks is of crucial interest in the current context of high-throughput data generation. In this paper, we develop a new algorithm for clustering vertices of a protein-protein interaction network using a density function, providing disjoint classes. RESULTS: Applied to the yeast interaction network, the classes obtained appear to be biological significant. The partitions are then used to make functional predictions for uncharacterized yeast proteins, using an annotation procedure that takes into account the binary interactions between proteins inside the classes. We show that this procedure is able to enhance the performances with respect to previous approaches. Finally, we propose a new annotation for 37 previously uncharacterized yeast proteins. CONCLUSION: We believe that our results represent a significant improvement for the inference of cellular functions, that can be applied to other organism as well as to other type of interaction graph, such as genetic interactions.

Cluster Analysis↗

PubMed2004

The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

Database Management Systems↗

PubMed2003

Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network.

We here describe PRODISTIN, a new computational method allowing the functional clustering of proteins on the basis of protein-protein interaction data. This method, assessed biologically and statistically, enabled us to classify 11% of the Saccharomyces cerevisiae proteome into several groups, the majority of which contained proteins involved in the same biological process(es), and to predict a cellular function for many otherwise uncharacterized proteins.

Cluster Analysis↗

PubMed2003

Approach of the functional evolution of duplicated genes in Saccharomyces cerevisiae using a new classification method based on protein-protein interaction data.

The concept of protein function is widely used and manipulated by biologists. However, the means of the concept and its understanding may vary depending on the level of functionality one considers (molecular, cellular, physiological, etc.). Genomic studies and new high-throughput methods of the post-genomic era provide the opportunity to shed a new light on the concept of protein function: protein-protein interactions can now be considered as pieces of incomplete but still gigantic networks and the analysis of these networks will permit the emergence of a more integrated view of protein function. In this context, we propose a new functional classification method, which, unlike usual methods based on sequence homology, allows the definition of functional classes of protein based on the identity of their interacting partners. An example of such classification will be shown and discussed for a subset of Saccharomyces cerevisiae proteins, accounting for 7% of the yeast proteome. The genome of the budding yeast contains 50% of protein-coding genes that are paralogs, including 457 pairs of duplicated genes coming probably from an ancient whole genome duplication. We will comment on the functional classification of the duplicated genes when using our method and discuss the contribution of these results to the understanding of function evolution for the duplicated genes.

Evolution, Molecular↗

PubMed2002

Human telomeric position effect is determined by chromosomal context and telomeric chromatin integrity.

We investigated the influence of telomere proximity and composition on the expression of an EGFP reporter gene in human cells. In transient transfection assays, telomeric DNA does not repress EGFP but rather slightly increases its expression. In contrast, in stable cell lines, the same reporter construct is repressed when inserted at a subtelomeric location. The telomeric repression is transiently alleviated by increasing the dosage of the TTAGGG repeat factor 1 (TRF1). Upon a prolongated treatment with trichostatin A, the derepression of the subtelomeric reporter gene correlates with the delocalization of HP1alpha and HP1beta. In contrast, treating the cells with 5 azacytidin, a demethylating agent, or with sirtinol, an inhibitor of the Sir2 family of deacetylase, has no apparent effect on telomeric repression. Overall, position effects at human chromosome ends are dependent on a specific higher-order organization of the telomeric chromatin. The possible involvement of HP1 isoforms is discussed.

Chromatin↗

PubMed2002

Chimeric RNA transposition intermediates of the I factor produce precise retrotransposed copies.

I elements in Drosophila melanogaster are non-long terminal repeat (LTR) retrotransposons of particular interest because high levels of transposition can be induced by appropriate crosses. They use a full-length RNA transposition intermediate as a template for reverse transcription. Detailed molecular characterization of this intermediate is rendered difficult because of the many transcripts produced by defective elements. The use of an active I element marked with a sequence encoding the HA epitope solves this problem. We used an RNA circularization procedure followed by RT-PCR to analyze the transcripts produced by actively transposing tagged I elements. Most start at the 5' end at the second nucleotide of the I element and all are polyadenylated at a site located in genomic sequences downstream of the 3' end. One of the tagged I elements, inserted in locus 88A, produces chimeric transcripts that carry sequences from both 5'- and 3'-flanking genomic DNA. We show that synthesis of these chimeric transcripts is controlled by the I element itself. Analysis of full-length transposed copies of this element shows that the extra sequences at the 5' and 3' ends are not integrated during retrotransposition. This suggests that initiation and arrest of reverse transcription during retrotransposition are precise processes.

3' Flanking Region↗

PubMed2002

Targeting assay to study the cis functions of human telomeric proteins: evidence for inhibition of telomerase by TRF1 and for activation of telomere degradation by TRF2.

We investigated the control of telomere length by the human telomeric proteins TRF1 and TRF2. To this end, we established telomerase-positive cell lines in which the targeting of these telomeric proteins to specific telomeres could be induced. We demonstrate that their targeting leads to telomere shortening. This indicates that these proteins act in cis to repress telomere elongation. Inhibition of telomerase activity by a modified oligonucleotide did not further increase the pace of telomere erosion caused by TRF1 targeting, suggesting that telomerase itself is the target of TRF1 regulation. In contrast, TRF2 targeting and telomerase inhibition have additive effects. The possibility that TRF2 can activate a telomeric degradation pathway was directly tested in human primary cells that do not express telomerase. In these cells, overexpression of full-length TRF2 leads to an increased rate of telomere shortening.

Bacterial Proteins↗

PubMed2001

Mapping and identification of essential gene functions on the X chromosome of Drosophila.

The Drosophila melanogaster genome consists of four chromosomes that contain 165 Mb of DNA, 120 Mb of which are euchromatic. The two Drosophila Genome Projects, in collaboration with Celera Genomics Systems, have sequenced the genome, complementing the previously established physical and genetic maps. In addition, the Berkeley Drosophila Genome Project has undertaken large-scale functional analysis based on mutagenesis by transposable P element insertions into autosomes. Here, we present a large-scale P element insertion screen for vital gene functions and a BAC tiling map for the X chromosome. A collection of 501 X-chromosomal P element insertion lines was used to map essential genes cytogenetically and to establish short sequence tags (STSs) linking the insertion sites to the genome. The distribution of the P element integration sites, the identified genes and transcription units as well as the expression patterns of the P-element-tagged enhancers is described and discussed.

Animals↗