Binding of SGTA to Rpn13 selectively modulates protein quality control

YesRpn13 is an intrinsic ubiquitin receptor of the 26S proteasome regulatory subunit that facilitates substrate capture prior to degradation. Here we show that the C-terminal region of Rpn13 binds to the tetratricopeptide repeat (TPR) domain of SGTA, a cytosolic factor implicated in the quality control of mislocalised membrane proteins (MLPs). The overexpression of SGTA results in a substantial increase in steady-state MLP levels, consistent with an effect on proteasomal degradation. However, this effect is strongly dependent upon the interaction of SGTA with the proteasomal component Rpn13. Hence, overexpression of the SGTA-binding region of Rpn13 or point mutations within the SGTA TPR domain both inhibit SGTA binding to the proteasome and substantially reduce MLP levels. These findings suggest that SGTA can regulate the access of MLPs to the proteolytic core of the proteasome, implying that a protein quality control cycle that involves SGTA and the BAG6 complex can operate at the 19S regulatory particle. We speculate that the binding of SGTA to Rpn13 enables specific polypeptides to escape proteasomal degradation and/or selectively modulates substrate degradation.BBSRC [grant number: BB/L006510/1] and the Wellcome Trust [grant number: 092107/Z/10/Z]. K.K. was supported by the UPStream network [EU, FP7, ITN project 290257

BioXSD: the common data-exchange format for everyday bioinformatics web services

Motivation: The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types

Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling

The Joint Evolutionary Trees (JET) method detects protein interfaces, the core residues involved in the folding process, and residues susceptible to site-directed mutagenesis and relevant to molecular recognition. The approach, based on the Evolutionary Trace (ET) method, introduces a novel way to treat evolutionary information. Families of homologous sequences are analyzed through a Gibbs-like sampling of distance trees to reduce effects of erroneous multiple alignment and impacts of weakly homologous sequences on distance tree construction. The sampling method makes sequence analysis more sensitive to functional and structural importance of individual residues by avoiding effects of the overrepresentation of highly homologous sequences and improves computational efficiency. A carefully designed clustering method is parametrized on the target structure to detect and extend patches on protein surfaces into predicted interaction sites. Clustering takes into account residues' physical-chemical properties as well as conservation. Large-scale application of JET requires the system to be adjustable for different datasets and to guarantee predictions even if the signal is low. Flexibility was achieved by a careful treatment of the number of retrieved sequences, the amino acid distance between sequences, and the selective thresholds for cluster identification. An iterative version of JET (iJET) that guarantees finding the most likely interface residues is proposed as the appropriate tool for large-scale predictions. Tests are carried out on the Huang database of 62 heterodimer, homodimer, and transient complexes and on 265 interfaces belonging to signal transduction proteins, enzymes, inhibitors, antibodies, antigens, and others. A specific set of proteins chosen for their special functional and structural properties illustrate JET behavior on a large variety of interactions covering proteins, ligands, DNA, and RNA. JET is compared at a large scale to ET and to Consurf, Rate4Site, siteFiNDER|3D, and SCORECONS on specific structures. A significant improvement in performance and computational efficiency is shown

ProteinHistorian: Tools for the Comparative Analysis of Eukaryote Protein Origin

The evolutionary history of a protein reflects the functional history of its ancestors. Recent phylogenetic studies identified distinct evolutionary signatures that characterize proteins involved in cancer, Mendelian disease, and different ontogenic stages. Despite the potential to yield insight into the cellular functions and interactions of proteins, such comparative phylogenetic analyses are rarely performed, because they require custom algorithms. We developed ProteinHistorian to make tools for performing analyses of protein origins widely available. Given a list of proteins of interest, ProteinHistorian estimates the phylogenetic age of each protein, quantifies enrichment for proteins of specific ages, and compares variation in protein age with other protein attributes. ProteinHistorian allows flexibility in the definition of protein age by including several algorithms for estimating ages from different databases of evolutionary relationships. We illustrate the use of ProteinHistorian with three example analyses. First, we demonstrate that proteins with high expression in human, compared to chimpanzee and rhesus macaque, are significantly younger than those with human-specific low expression. Next, we show that human proteins with annotated regulatory functions are significantly younger than proteins with catalytic functions. Finally, we compare protein length and age in many eukaryotic species and, as expected from previous studies, find a positive, though often weak, correlation between protein age and length. ProteinHistorian is available through a web server with an intuitive interface and as a set of command line tools; this allows biologists and bioinformaticians alike to integrate these approaches into their analysis pipelines. ProteinHistorian's modular, extensible design facilitates the integration of new datasets and algorithms. The ProteinHistorian web server, source code, and pre-computed ages for 32 eukaryotic genomes are freely available under the GNU public license at http://lighthouse.ucsf.edu/ProteinHistorian/

Ensembl 2007

The Ensembl () project provides a comprehensive and integrated source of annotation of chordate genome sequences. Over the past year the number of genomes available from Ensembl has increased from 15 to 33, with the addition of sites for the mammalian genomes of elephant, rabbit, armadillo, tenrec, platypus, pig, cat, bush baby, common shrew, microbat and european hedgehog; the fish genomes of stickleback and medaka and the second example of the genomes of the sea squirt (Ciona savignyi) and the mosquito (Aedes aegypti). Some of the major features added during the year include the first complete gene sets for genomes with low-sequence coverage, the introduction of new strain variation data and the introduction of new orthology/paralog annotations based on gene trees

Ensembl 2008.

The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases and other information for chordate and selected model organism and disease vector genomes. As of release 47 (October 2007), Ensembl fully supports 35 species, with preliminary support for six additional species. New species in the past year include platypus and horse. Major additions and improvements to Ensembl since our previous report include extensive support for functional genomics data in the form of a specialized functional genomics database, genome-wide maps of protein-DNA interactions and the Ensembl regulatory build; support for customization of the Ensembl web interface through the addition of user accounts and user groups; and increased support for genome resequencing. We have also introduced new comparative genomics-based data mining options and report on the continued development of our software infrastructure

KB-Rank: efficient protein structure and functional annotation identification via text query

The KB-Rank tool was developed to help determine the functions of proteins. A user provides text query and protein structures are retrieved together with their functional annotation categories. Structures and annotation categories are ranked according to their estimated relevance to the queried text. The algorithm for ranking first retrieves matches between the query text and the text fields associated with the structures. The structures are next ordered by their relative content of annotations that are found to be prevalent across all the structures retrieved. An interactive web interface was implemented to navigate and interpret the relevance of the structures and annotation categories retrieved by a given search. The aim of the KB-Rank tool is to provide a means to quickly identify protein structures of interest and the annotations most relevant to the queries posed by a user. Informational and navigational searches regarding disease topics are described to illustrate the tool’s utilities. The tool is available at the URL http://protein.tcmedc.org/KB-Rank

Human Tumour Immune Evasion via TGF-β Blocks NK Cell Activation but Not Survival Allowing Therapeutic Restoration of Anti-Tumour Activity

Immune evasion is now recognized as a key feature of cancer progression. In animal models, the activity of cytotoxic lymphocytes is suppressed in the tumour microenvironment by the immunosuppressive cytokine, Transforming Growth Factor (TGF)-β. Release from TGF-β-mediated inhibition restores anti-tumour immunity, suggesting a therapeutic strategy for human cancer. We demonstrate that human natural killer (NK) cells are inhibited in a TGF-β dependent manner following chronic contact-dependent interactions with tumour cells in vitro. In vivo, NK cell inhibition was localised to the human tumour microenvironment and primary ovarian tumours conferred TGF-β dependent inhibition upon autologous NK cells ex vivo. TGF-β antagonized the interleukin (IL)-15 induced proliferation and gene expression associated with NK cell activation, inhibiting the expression of both NK cell activation receptor molecules and components of the cytotoxic apparatus. Interleukin-15 also promotes NK cell survival and IL-15 excluded the pro-apoptotic transcription factor FOXO3 from the nucleus. However, this IL-15 mediated pathway was unaffected by TGF-β treatment, allowing NK cell survival. This suggested that NK cells in the tumour microenvironment might have their activity restored by TGF-β blockade and both anti-TGF-β antibodies and a small molecule inhibitor of TGF-β signalling restored the effector function of NK cells inhibited by autologous tumour cells. Thus, TGF-β blunts NK cell activation within the human tumour microenvironment but this evasion mechanism can be therapeutically targeted, boosting anti-tumour immunity

IL-10 transcription is negatively regulated by BAF180, a component of the SWI/SNF chromatin remodeling enzyme

<p>Abstract</p> <p>Background</p> <p>SWI/SNF chromatin remodeling enzymes play a critical role in the development of T helper lymphocytes, including Th2 cells, and directly program chromatin structure at Th2 cytokine genes. Different versions of SWI/SNF complexes, including BAF and PBAF, have been described based on unique subunit composition. However, the relative role of BAF and PBAF in Th cell function and cytokine expression has not been reported.</p> <p>Results</p> <p>Here we examine the role of the PBAF SWI/SNF complex in Th cell development and gene expression using mice deficient for a PBAF-specific component, BAF180. We find that T cell development in the thymus and lymphoid periphery is largely normal when the BAF180 gene is deleted late in thymic development. However, BAF180-deficient Th2 cells express high levels of the immunoregulatory cytokine IL-10. BAF180 binds directly to regulatory elements in the Il-10 locus but is replaced by BAF250 BAF complexes in the absence of BAF180, resulting in increased histone acetylation and CBP recruitment to the IL-10 locus.</p> <p>Conclusions</p> <p>These results demonstrate that BAF180 is a repressor of IL-10 transcription in Th2 cells and suggest that the differential recruitment of different SWI/SNF subtypes can have direct consequences on chromatin structure and gene transcription.</p