20 research outputs found

    PWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix

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    Transcription factors (TFs) regulate gene expression by binding to specific short DNA sequences of 5 to 20-bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or TF binding site model from a public database

    Targeting self- and foreign antigens to dendritic cells via DC-ASGPR generates IL-10-producing suppressive CD4+ T cells

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    Dendritic cells (DCs) can initiate and shape host immune responses toward either immunity or tolerance by their effects on antigen-specific CD4(+) T cells. DC-asialoglycoprotein receptor (DC-ASGPR), a lectinlike receptor, is a known scavenger receptor. Here, we report that targeting antigens to human DCs via DC-ASGPR, but not lectin-like oxidized-LDL receptor, Dectin-1, or DC-specific ICAM-3-grabbing nonintegrin favors the generation of antigen-specific suppressive CD4(+) T cells that produce interleukin 10 (IL-10). These findings apply to both self-and foreign antigens, as well as memory and naive CD4(+) T cells. The generation of such IL-10-producing CD4(+) T cells requires p38/extracellular signal-regulated kinase phosphorylation and IL-10 induction in DCs. We further demonstrate that immunization of nonhuman primates with antigens fused to anti-DC-ASGPR monoclonal antibody generates antigen-specific CD4(+) T cells that produce IL-10 in vivo. This study provides a new strategy for the establishment of antigen-specific IL-10-producing suppressive T cells in vivo by targeting whole protein antigens to DCs via DC-ASGPR

    Endocytosis of the Anthrax Toxin Is Mediated by Clathrin, Actin and Unconventional Adaptors

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    The anthrax toxin is a tripartite toxin, where the two enzymatic subunits require the third subunit, the protective antigen (PA), to interact with cells and be escorted to their cytoplasmic targets. PA binds to cells via one of two receptors, TEM8 and CMG2. Interestingly, the toxin times and triggers its own endocytosis, in particular through the heptamerization of PA. Here we show that PA triggers the ubiquitination of its receptors in a β-arrestin-dependent manner and that this step is required for clathrin-mediated endocytosis. In addition, we find that endocytosis is dependent on the heterotetrameric adaptor AP-1 but not the more conventional AP-2. Finally, we show that endocytosis of PA is strongly dependent on actin. Unexpectedly, actin was also found to be essential for efficient heptamerization of PA, but only when bound to one of its 2 receptors, TEM8, due to the active organization of TEM8 into actin-dependent domains. Endocytic pathways are highly modular systems. Here we identify some of the key players that allow efficient heptamerization of PA and subsequent ubiquitin-dependent, clathrin-mediated endocytosis of the anthrax toxin

    The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

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    The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

    SPar-K: a method to partition NGS signal data

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    We present SPar-K (Signal Partitioning with K-means), a method to search for archetypical chromatin architectures by partitioning a set of genomic regions characterized by chromatin signal profiles around ChIP-seq peaks and other kinds of functional sites. This method efficiently deals with problems of data heterogeneity, limited misalignment of anchor points and unknown orientation of asymmetric patterns

    Computational study of transcription factor binding sites

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    Any living organism contains a whole set of instructions encoded as genes on the DNA. This set of instructions contains all the necessary information that the organism will ever need, from its development to a mature individual to environment specific responses. Since all these instructions are not needed at the same time, the gene expression needs to be regulated. Eukaryotic genomes are stored inside nuclei as chromatin. The chromatin is the association of DNA with dedicated storage proteins - the histones - and the necessary machinery to regulate and express genes (RNA polymerases or RNAPs). In the nuclei, histones are assembled into octamers around which are wrapped ~148bp of DNA. This structure is known as the nucleosome. The repetition of nucleosomes along the genome allows to drastically compact the genome, eventually allowing to fit it inside the nucleus. However, this comes at the cost of rendering the DNA sequence inaccessible to DNA readers, such as the RNAPs and transcription factors (TFs). TFs are a class of proteins that have the remarkable property of recognizing and binding specific DNA sequences. More striking, each TF can recognize a multitude of different - but similar - DNA sequences providing TFs with a wide sequence specificity range. Eventually, this allows the cell to recruit TFs at dedicated locations in the genome called regulatory elements (REs). The action of TFs at REs is crucial to gene expression. Indeed, TFs are involved in many processes such as the opening of the chromatin structure or the recruitment of RNAPs. However if TFs can influence the chromatin structure, the opposite is also true as histones impede TF binding on DNA. Thus the regulation of genes relies on a subtle and complex crosstalk between the chromatin and TFs. To better understand how TFs and chromatin interact together to regulate gene expression, I lead several projects prospecting TF binding specificity and the chromatin structure at REs in human. First, I used ENCODE next generation sequencing (NGS) data to explore how TF binding influences the nearby nucleosome organization and the propensity of some TFs to bind together. The results suggest that regular nucleosome arrays are found near all TFs. They also point out two special cases. When CTCF binds with the cohesin complex, it seems to drive the nucleosome organization, which is a unique feature among all TFs investigated. Additionally I present evidence supporting that EBF1 is a pioneer factor - a special class of TFs able to bind nucleosome. Secondly, I developed several clustering algorithms and software to partition genomic regions according to NGS data and/or on their DNA sequences. These methods allow to discover important trends, for instance different nucleosome architectures . I illustrated the usefulness of these methods for the study of chromatin accessibility data and the identification of REs. Thirdly, I participated to the assessment of SMiLE-seq, a new microfluidic device that generates TF specificity data. The creation of TF specificity models and their comparison with other publicly available models demonstrated the value of SMiLE-seq to study TF specificity. Finally, I participated in the development of a software that predicts TF binding sites. A careful benchmarking suggested that this software is - at the time of writing - the best available software in terms of speed while showing other performances similar to its competitors

    PWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix

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    Abstract Summary Transcription factors regulate gene expression by binding to specific short DNA sequences of 5-20 bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or transcription factor binding site model from a public database. Availability and implementation The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively. Supplementary information Supplementary data are available at Bioinformatics online
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