89 research outputs found

    AutoPSI: a database for automatic structural classification of protein sequences and structures

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    In protein research, structural classifications of protein domains provided by databases such as SCOP play an important role. However, as such databases have to be curated and prepared carefully, they update only up to a few times per year, and in between newly entered PDB structures cannot be used in cases where a structural classification is required. The Automated Protein Structure Identification (AutoPSI) database delivers predicted SCOP classifications for several thousand yet unclassified PDB entries as well as millions of UniProt sequences in an automated fashion. In order to obtain predictions, we make use of two recently published methods, namely AutoSCOP (sequence-based) and Vorolign (structure-based) and the consensus of both. With our predictions, we bridge the gap between SCOP versions for proteins with known structures in the PDB and additionally make structure predictions for a very large number of UniProt proteins. AutoPSI is freely accessible at http://www.bio.ifi.lmu.de/AutoPSIDB

    ProSAS: a database for analyzing alternative splicing in the context of protein structures

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    Alternative splicing is known to be one of the major sources for functional diversity in higher eukaryotes. Several splicing isoforms have been characterized in the literature that play important roles in cellular processes like apoptosis or signal transduction pathways. Splicing events can often be detected on the mRNA level by large-scale cDNA or EST experiments and such data is collected and annotated in several databases. Nevertheless, the effects of splicing on the structure of a protein are largely unknown. The ProSAS (Protein Structure and Alternative Splicing) database fills this gap and provides a unified resource for analyzing effects of alternative splicing events in the context of protein structures. ProSAS comprehensively annotates and models protein structures for several Ensembl genomes as well as SwissProt entries harbouring splicing events. Alternative isoforms annotated in Ensembl or SwissProt can be analyzed on the protein structure and protein function level using an intuitive user interface that provides several features and tools for a structure-based analysis of alternative splicing events. The ProSAS database is freely accessible at http://www.bio.ifi.lmu.de/ProSAS

    LKB1 and AMPK differentially regulate pancreatic β-cell identity.

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    Fully differentiated pancreatic β cells are essential for normal glucose homeostasis in mammals. Dedifferentiation of these cells has been suggested to occur in type 2 diabetes, impairing insulin production. Since chronic fuel excess ("glucotoxicity") is implicated in this process, we sought here to identify the potential roles in β-cell identity of the tumor suppressor liver kinase B1 (LKB1/STK11) and the downstream fuel-sensitive kinase, AMP-activated protein kinase (AMPK). Highly β-cell-restricted deletion of each kinase in mice, using an Ins1-controlled Cre, was therefore followed by physiological, morphometric, and massive parallel sequencing analysis. Loss of LKB1 strikingly (2.0-12-fold, E<0.01) increased the expression of subsets of hepatic (Alb, Iyd, Elovl2) and neuronal (Nptx2, Dlgap2, Cartpt, Pdyn) genes, enhancing glutamate signaling. These changes were partially recapitulated by the loss of AMPK, which also up-regulated β-cell "disallowed" genes (Slc16a1, Ldha, Mgst1, Pdgfra) 1.8- to 3.4-fold (E<0.01). Correspondingly, targeted promoters were enriched for neuronal (Zfp206; P=1.3×10(-33)) and hypoxia-regulated (HIF1; P=2.5×10(-16)) transcription factors. In summary, LKB1 and AMPK, through only partly overlapping mechanisms, maintain β-cell identity by suppressing alternate pathways leading to neuronal, hepatic, and other characteristics. Selective targeting of these enzymes may provide a new approach to maintaining β-cell function in some forms of diabetes.-Kone, M., Pullen, T. J., Sun, G., Ibberson, M., Martinez-Sanchez, A., Sayers, S., Nguyen-Tu, M.-S., Kantor, C., Swisa, A., Dor, Y., Gorman, T., Ferrer, J., Thorens, B., Reimann, F., Gribble, F., McGinty, J. A., Chen, L., French, P. M., Birzele, F., Hildebrandt, T., Uphues, I., Rutter, G. A. LKB1 and AMPK differentially regulate pancreatic β-cell identity

    Coding potential of the products of alternative splicing in human

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    Background: Analysis of the human genome has revealed that as much as an order of magnitude more of the genomic sequence is transcribed than accounted for by the predicted and characterized genes. A number of these transcripts are alternatively spliced forms of known protein coding genes; however, it is becoming clear that many of them do not necessarily correspond to a functional protein. Results: In this study we analyze alternative splicing isoforms of human gene products that are unambiguously identified by mass spectrometry and compare their properties with those of isoforms of the same genes for which no peptide was found in publicly available mass spectrometry datasets. We analyze them in detail for the presence of uninterrupted functional domains, active sites as well as the plausibility of their predicted structure. We report how well each of these strategies and their combination can correctly identify translated isoforms and derive a lower limit for their specificity, that is, their ability to correctly identify non-translated products. Conclusions: The most effective strategy for correctly identifying translated products relies on the conservation of active sites, but it can only be applied to a small fraction of isoforms, while a reasonably high coverage, sensitivity and specificity can be achieved by analyzing the presence of non-truncated functional domains. Combining the latter with an assessment of the plausibility of the modeled structure of the isoform increases both coverage and specificity with a moderate cost in terms of sensitivity

    Acute tumour response to a bispecific Ang-2-VEGF-A antibody: insights from multiparametric MRI and gene expression profiling.

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    Background To assess antivascular effects, and evaluate clinically translatable magnetic resonance imaging (MRI) biomarkers of tumour response in vivo, following treatment with vanucizumab, a bispecific human antibody against angiopoietin-2 (Ang-2) and vascular endothelial growth factor-A (VEGF-A).Methods Colo205 colon cancer xenografts were imaged before and 5 days after treatment with a single 10 mg kg(-1) dose of either vanucizumab, bevacizumab (anti-human VEGF-A), LC06 (anti-murine/human Ang-2) or omalizumab (anti-human IgE control). Volumetric response was assessed using T2-weighted MRI, and diffusion-weighted, dynamic contrast-enhanced (DCE) and susceptibility contrast MRI used to quantify tumour water diffusivity (apparent diffusion coefficient (ADC), × 10(6) mm(2) s(-1)), vascular perfusion/permeability (K(trans), min(-1)) and fractional blood volume (fBV, %) respectively. Pathological correlates were sought, and preliminary gene expression profiling performed.Results Treatment with vanucizumab, bevacizumab or LC06 induced a significant (P<0.01) cytolentic response compared with control. There was no significant change in tumour ADC in any treatment group. Uptake of Gd-DTPA was restricted to the tumour periphery in all post-treatment groups. A significant reduction in tumour K(trans) (P<0.05) and fBV (P<0.01) was determined 5 days after treatment with vanucizumab only. This was associated with a significant (P<0.05) reduction in Hoechst 33342 uptake compared with control. Gene expression profiling identified 20 human genes exclusively regulated by vanucizumab, 6 of which are known to be involved in vasculogenesis and angiogenesis.Conclusions Vanucizumab is a promising antitumour and antiangiogenic treatment, whose antivascular activity can be monitored using DCE and susceptibility contrast MRI. Differential gene expression in vanucizumab-treated tumours is regulated by the combined effect of Ang-2 and VEGF-A inhibition

    Methods to study splicing from high-throughput RNA Sequencing data

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    The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

    Per-arnt-sim (PAS) domain-containing protein kinase is downregulated in human islets in type 2 diabetes and regulates glucagon secretion.

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    AIMS/HYPOTHESIS: We assessed whether per-arnt-sim (PAS) domain-containing protein kinase (PASK) is involved in the regulation of glucagon secretion. METHODS: mRNA levels were measured in islets by quantitative PCR and in pancreatic beta cells obtained by laser capture microdissection. Glucose tolerance, plasma hormone levels and islet hormone secretion were analysed in C57BL/6 Pask homozygote knockout mice (Pask-/-) and control littermates. Alpha-TC1-9 cells, human islets or cultured E13.5 rat pancreatic epithelia were transduced with anti-Pask or control small interfering RNAs, or with adenoviruses encoding enhanced green fluorescent protein or PASK. RESULTS: PASK expression was significantly lower in islets from human type 2 diabetic than control participants. PASK mRNA was present in alpha and beta cells from mouse islets. In Pask-/- mice, fasted blood glucose and plasma glucagon levels were 25 ± 5% and 50 ± 8% (mean ± SE) higher, respectively, than in control mice. At inhibitory glucose concentrations (10 mmol/l), islets from Pask-/- mice secreted 2.04 ± 0.2-fold (p < 0.01) more glucagon and 2.63 ± 0.3-fold (p < 0.01) less insulin than wild-type islets. Glucose failed to inhibit glucagon secretion from PASK-depleted alpha-TC1-9 cells, whereas PASK overexpression inhibited glucagon secretion from these cells and human islets. Extracellular insulin (20 nmol/l) inhibited glucagon secretion from control and PASK-deficient alpha-TC1-9 cells. PASK-depleted alpha-TC1-9 cells and pancreatic embryonic explants displayed increased expression of the preproglucagon (Gcg) and AMP-activated protein kinase (AMPK)-alpha2 (Prkaa2) genes, implying a possible role for AMPK-alpha2 downstream of PASK in the control of glucagon gene expression and release. CONCLUSIONS/INTERPRETATION: PASK is involved in the regulation of glucagon secretion by glucose and may be a useful target for the treatment of type 2 diabetes
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