30 research outputs found
Genome wide mining of alternative splicing in metazoan model organisms
Tese de doutoramento, CiĂȘncias BiomĂ©dicas (CiĂȘncias MorfolĂłgicas), Universidade de Lisboa, Faculdade de Medicina, 2009Background: Mining current mRNA and EST databases for novel alternatively spliced isoforms is of paramount importance for shedding light on the way in which the maturation of RNA is used to regulate gene expression. Preliminary observations revealed a tendency for greater amounts of potentially non protein-coding alternative transcripts in human genes than in orthologous genes from other organisms. However, many of these isoforms did not appear in recently published alternative splicing databases on account of constraints imposed in the selection of transcripts. This prompted us to develop a less constrained database with the aim of contributing to the identification of the full repertoire of splice variants in the transcriptome of different organisms. Given that mechanisms of control of gene expression involving non-protein-coding splice variants have been described in a variety of genes, this information may be crucial to deciphering more intricate layers of gene regulation in complex organisms brought about by alternative splicing. Description: An algorithm was developed to cluster mRNA and EST BLAT alignments to annotated gene regions. Consensus splice sites were the main requirement imposed on the selection of transcripts. The method was applied to thirteen model organisms. The alternative splicing information generated has been incorporated into a database with clear graphical displays representing the splicing patterns and is available from the ExonMine website (http://www.imm.fm.ul.pt/exonmine). It incorporates information on constitutive exons, poly-A signals, open reading frames and translation, expression specificity of any exon or splicing pattern relative to biological source of mRNA/EST, alternative splicing events and respective exon and junction sequences for microarray probe design. The ExonMine interface also provides several tools to support laboratory validation of splicing patterns. Conclusions: ExonMine detects a higher percentage of spliced genes and isoforms than currently available alternative splicing databases. The analysis reveals a marked increase, in complex organisms, of splice variants with either retained introns or incorporating novel exons with no apparent protein-coding potential. About 18% of unannotated exons detected in ExonMine were found expressed in primary human cells using tiling arrays. Validation of some of these results for the U2AF family of splicing factors was successfully performed in collaboration with members of the lab revealing primate specific transcripts and an alternatively spliced transcript carrying a microRNA. The database was also successfully used for genome wide analysis of sequence elements involved in the regulation of alternative splicing and for custom alternative splicing microarray design. Matching of ExonMine data to a commercial exon microarray platform covering the majority of human exons was also performed and will assist in large-scale analysis of alternative splicing data. The algorithm developed also provides for easy updatability, taking only 48 hours to generate data for the whole human genome and far less time for less complex organisms. In conclusion, ExonMine represents a new useful resource for future research on alternative splicing and gene regulation.Muscular Dystrophy Association (MDA3662), European Commission (LSHG-CT-2005-518238, EURASNET) and Fundação para a CiĂȘncia e Tecnologia, Portugal (PTDC/SAU-GMG/69739/2006)
Endothelial Cell Processing and Alternatively Spliced Transcripts of Factor VIII: Potential Implications for Coagulation Cascades and Pulmonary Hypertension
Background: Coagulation factor VIII (FVIII) deficiency leads to haemophilia A. Conversely, elevated plasma levels are a strong predictor of recurrent venous thromboemboli and pulmonary hypertension phenotypes in which in situ thromboses are implicated. Extrahepatic sources of plasma FVIII are implicated, but have remained elusive. Methodology/Principal Findings: Immunohistochemistry of normal human lung tissue, and confocal microscopy, flow cytometry, and ELISA quantification of conditioned media from normal primary endothelial cells were used to examine endothelial expression of FVIII and coexpression with von Willebrand Factor (vWF), which protects secreted FVIII heavy chain from rapid proteloysis. FVIII transcripts predicted from database mining were identified by rt-PCR and sequencing. FVIII mAb-reactive material was demonstrated in CD31+ endothelial cells in normal human lung tissue, and in primary pulmonary artery, pulmonary microvascular, and dermal microvascular endothelial cells. In pulmonary endothelial cells, this protein occasionally colocalized with vWF, centered on Weibel Palade bodies. Pulmonary artery and pulmonary microvascular endothelial cells secreted low levels of FVIII and vWF to conditioned media, and demonstrated cell surface expression of FVIII and vWF Abâreacting proteins compared to an isotype control. Four endothelial splice isoforms were identified. Two utilize transcription start sites in alternate 59 exons within the int22h-1 repeat responsible for intron 2
Diversity of human U2AF splicing factors
© 2006 The Authors Journal compilation ©2006 FEBSU2 snRNP auxiliary factor (U2AF) is an essential heterodimeric splicing factor composed of two subunits, U2AF(65) and U2AF(35). During the past few years, a number of proteins related to both U2AF(65) and U2AF(35) have been discovered. Here, we review the conserved structural features that characterize the U2AF protein families and their evolutionary emergence. We perform a comprehensive database search designed to identify U2AF protein isoforms produced by alternative splicing, and we discuss the potential implications of U2AF protein diversity for splicing regulation.This work was supported by grants from Fundação para a CiĂȘncia e Tecnologia (FCT), Portugal (POCTI/MGI/49430/2002, SFRH/BD/2914/2000), the Muscular Dystrophy Association (MDA3662), and the European Commission (EURASNET, LSHGâCTâ2005â518238).info:eu-repo/semantics/publishedVersio
Identification of shared and unique serum lipid profiles in diabetes mellitus and myocardial infarction
Background-Diabetes mellitus (DM) and cardiovascular disease are associated with dyslipidemia, but the detailed lipid molecular pattern in both diseases remains unknown. Methods and Results-We used shotgun mass spectrometry to determine serum levels of 255 molecular lipids in 316 controls, 171 DM, and 99 myocardial infarction (MI) events from a cohort derived from the Malmö Diet and Cancer study. Orthogonal projections to latent structures analyses were conducted between the lipids and clinical parameters describing DM or MI. Fatty acid desaturases (FADS) and elongation of very long chain fatty acid protein 5 (ELOVL5) activities were estimated by calculating product to precursor ratios of polyunsaturated fatty acids in complex lipids. FADS genotypes encoding these desaturases were then tested for association with lipid levels and ratios. Differences in the levels of lipids belonging to the phosphatidylcholine and triacylglyceride (TAG) classes contributed the most to separating DM from controls. TAGs also played a dominating role in discriminating MI from controls. Levels of C18:2 fatty acids in complex lipids were lower both in DM and MI versus controls (DM, P=0.004; MI, P=6.0E-06) at least due to an acceleration in the metabolic flux from C18:2 to C20:4 (eg, increased estimated ELOVL5: DM, P=0.02; MI, P=0.04, and combined elongase-desaturase activities: DM, P=3.0E-06; MI, P=2.0E-06). Minor allele carriers of FADS genotypes were associated with increased levels of C18:2 (Pâ€0.007) and lower desaturase activity (Pâ€0.002). Conclusions-We demonstrate a possible relationship between decreased levels of C18:2 in complex lipids and DM or MI. We thereby highlight the importance of molecular lipids in the pathogenesis of both diseases
Dual Effect of Rosuvastatin on Glucose Homeostasis Through Improved Insulin Sensitivity and Reduced Insulin Secretion
Statins are beneficial in the treatment of cardiovascular disease (CVD), but these lipid-lowering drugs are associated with increased incidence of new on-set diabetes. The cellular mechanisms behind the development of diabetes by statins are elusive. Here we have treated mice on normal diet (ND) and high fat diet (HFD) with rosuvastatin. Under ND rosuvastatin lowered blood glucose through improved insulin sensitivity and increased glucose uptake in adipose tissue. In vitro rosuvastatin reduced insulin secretion and insulin content in islets. In the beta cell Ca2+ signaling was impaired and the density of granules at the plasma membrane was increased by rosuvastatin treatment. HFD mice developed insulin resistance and increased insulin secretion prior to administration of rosuvastatin. Treatment with rosuvastatin decreased the compensatory insulin secretion and increased glucose uptake. In conclusion, our data shows dual effects on glucose homeostasis by rosuvastatin where insulin sensitivity is improved, but beta cell function is impaired
Pancreatic slices from OPN<sup>-/-</sup> and WT mice have similar histology.
<p>Representative images from (A) eosin and hematoxylin stainings and (B) insulin stainings on pancreatic slices from WT (left) and OPN<sup>-/-</sup> (right) mice. Scale bar 100 ÎŒm.</p
Example traces from intracellular Ca<sup>2+</sup> measurements in WT and OPN<sup>-/-</sup> islets.
<p>Representative examples of Ca<sup>2+</sup> traces obtained from an islet from a WT (A) or OPN<sup>-/-</sup> (B) mouse. Marked on the traces are the measurements mentioned in the text. C<sub>0</sub> is the area of the Ca<sup>2+</sup> dip that initially occurs upon glucose-stimulation. C<sub>1</sub> is the amplitude of the first peak. 16.7 G is 16.7 mM glucose and 2.8 G is 2.8 mM glucose. The baseline is marked with a dashed line. Histogram of the cytoplasmic Ca<sup>2+</sup> concentration (measured as area under the curve but above the baseline; C), C<sub>0</sub> (D), C<sub>1</sub> (E), and the frequency of ocillations during the sustained phase (F) in islets from WT (white bars) and OPN<sup>-/-</sup> (black bars) mice. Data are obtained from 16â21 islets from 3 mice per condition. ** p†0.01; *** p†0.001.</p
Expression pattern of proteins associated with ER and Ca<sup>2+</sup> handling in WT and OPN<sup>-/-</sup> islets.
<p>Expression pattern of <i>Mig 6</i> (A), <i>SEl1L</i> (B), <i>Atp2A2</i> (C) and <i>ATP 2A3</i> (D) in islets from WT and OPN<sup>-/-</sup> mice as marked in the figure. Data are described using the median with interquartile range for 6 biological replicates with 3 technical replicates in each experiment. * p†0.05.</p
Altered cell-cell connections and insulin granule distribution in beta cells from OPN<sup>-/-</sup> mice.
<p>(A) Ultrastructural images from a section of a WT (left) and OPN<sup>-/-</sup> (right) islet. Scale bar 5 ÎŒM. (B) Ultrastructural images from a section of an OPN<sup>-/-</sup> islet. The atypical structure on the beta cell is marked with a black arrow. Scale bar 2ÎŒM. (C, D, and E) Histogram of the calculated volume density (C), surface density (D), and distribution of the insulin containing large dense-core vesicles (LDCVs; E) in pancreatic beta cells from WT and OPN<sup>-/-</sup> mice. Data are given as mean ± SEM from 24â26 cells taken from 3 animals per condition. ** p†0.01; *** p†0.001.</p
Deletion of OPN has modest effects on metabolism.
<p>(A) Body weight in WT and OPN<sup>-/-</sup> mice measured at 12 weeks. (B) Non-fasted blood glucose levels from WT and OPN<sup>-/-</sup> mice measured at 12 weeks. (C) Insulin content in isolated islets from WT and OPN<sup>-/-</sup> mice. (D) Glucose-induced insulin secretion at 11.1 mM glucose from isolated WT and OPN<sup>-/-</sup> islets described as fold increase over basal insulin secretion at 2.8 mM glucose with and without the addition of 200 ng/ml OPN and/or 100 nM GIP. (E) Same experiment as in (D) but displaying the non-processed data as ng/islet/h. Data are given as mean ± SEM from 28â30 animals (A and B) or from 4 biological experiments with 3 technical replicates in each experiment (C, D, and E). * p†0.05.</p