A database of microRNA expression patterns in Xenopus laevis

MicroRNAs (miRNAs) are short, non-coding RNAs around 22 nucleotides long. They inhibit gene expression either by translational repression or by causing the degradation of the mRNAs they bind to. Many are highly conserved amongst diverse organisms and have restricted spatio-temporal expression patterns during embryonic development where they are thought to be involved in generating accuracy of developmental timing and in supporting cell fate decisions and tissue identity. We determined the expression patterns of 180 miRNAs in Xenopus laevis embryos using LNA oligonucleotides. In addition we carried out small RNA-seq on different stages of early Xenopus development, identified 44 miRNAs belonging to 29 new families and characterized the expression of 5 of these. Our analyses identified miRNA expression in many organs of the developing embryo. In particular a large number were expressed in neural tissue and in the somites. Surprisingly none of the miRNAs we have looked at show expression in the heart. Our results have been made freely available as a resource in both XenMARK and Xenbase

Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage.

One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis

Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD

VASCo: computation and visualization of annotated protein surface contacts

<p>Abstract</p> <p>Background</p> <p>Structural data from crystallographic analyses contain a vast amount of information on protein-protein contacts. Knowledge on protein-protein interactions is essential for understanding many processes in living cells. The methods to investigate these interactions range from genetics to biophysics, crystallography, bioinformatics and computer modeling. Also crystal contact information can be useful to understand biologically relevant protein oligomerisation as they rely in principle on the same physico-chemical interaction forces. Visualization of crystal and biological contact data including different surface properties can help to analyse protein-protein interactions.</p> <p>Results</p> <p>VASCo is a program package for the calculation of protein surface properties and the visualization of annotated surfaces. Special emphasis is laid on protein-protein interactions, which are calculated based on surface point distances. The same approach is used to compare surfaces of two aligned molecules. Molecular properties such as electrostatic potential or hydrophobicity are mapped onto these surface points. Molecular surfaces and the corresponding properties are calculated using well established programs integrated into the package, as well as using custom developed programs. The modular package can easily be extended to include new properties for annotation. The output of the program is most conveniently displayed in PyMOL using a custom-made plug-in.</p> <p>Conclusion</p> <p>VASCo supplements other available protein contact visualisation tools and provides additional information on biological interactions as well as on crystal contacts. The tool provides a unique feature to compare surfaces of two aligned molecules based on point distances and thereby facilitates the visualization and analysis of surface differences.</p

EGCG Enhances the Therapeutic Potential of Gemcitabine and CP690550 by Inhibiting STAT3 Signaling Pathway in Human Pancreatic Cancer

Background: Signal Transducer and Activator of Transcription 3 (STAT3) is an oncogene, which promotes cell survival, proliferation, motility and progression in cancer cells. Targeting STAT3 signaling may lead to the development of novel therapeutic approaches for human cancers. Here, we examined the effects of epigallocathechin gallate (EGCG) on STAT3 signaling in pancreatic cancer cells, and assessed the therapeutic potential of EGCG with gemcitabine or JAK3 inhibitor CP690550 (Tasocitinib) for the treatment and/or prevention of pancreatic cancer. Methodology/Principal Findings: Cell viability and apoptosis were measured by XTT assay and TUNEL staining, respectively. Gene and protein expressions were measured by qRT-PCR and Western blot analysis, respectively. The results revealed that EGCG inhibited the expression of phospho and total JAK3 and STAT3, STAT3 transcription and activation, and the expression of STAT3-regulated genes, resulting in the inhibition of cell motility, migration and invasion, and the induction of caspase-3 and PARP cleavage. The inhibition of STAT3 enhanced the inhibitory effects of EGCG on cell motility and viability. Additionally, gemcitabine and CP690550 alone inhibited STAT3 target genes and synergized with EGCG to inhibit cell viability and induce apoptosis in pancreatic cancer cells. Conclusions/Significance: Overall, these results suggest that EGCG suppresses the growth, invasion and migration of pancreatic cancer cells, and induces apoptosis by interfering with the STAT3 signaling pathway. Moreover, EGCG furthe

Identification of hot-spot residues in protein-protein interactions by computational docking

<p>Abstract</p> <p>Background</p> <p>The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'). These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex.</p> <p>Results</p> <p>We have applied here normalized interface propensity (<it>NIP</it>) values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value), and the advantage of not requiring any prior structural knowledge of the complex.</p> <p>Conclusion</p> <p>The <it>NIP </it>values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.</p

Are Long-Range Structural Correlations Behind the Aggregration Phenomena of Polyglutamine Diseases?

We have characterized the conformational ensembles of polyglutamine peptides of various lengths (ranging from to ), both with and without the presence of a C-terminal polyproline hexapeptide. For this, we used state-of-the-art molecular dynamics simulations combined with a novel statistical analysis to characterize the various properties of the backbone dihedral angles and secondary structural motifs of the glutamine residues. For (i.e., just above the pathological length for Huntington's disease), the equilibrium conformations of the monomer consist primarily of disordered, compact structures with non-negligible -helical and turn content. We also observed a relatively small population of extended structures suitable for forming aggregates including - and -strands, and - and -hairpins. Most importantly, for we find that there exists a long-range correlation (ranging for at least residues) among the backbone dihedral angles of the Q residues. For polyglutamine peptides below the pathological length, the population of the extended strands and hairpins is considerably smaller, and the correlations are short-range (at most residues apart). Adding a C-terminal hexaproline to suppresses both the population of these rare motifs and the long-range correlation of the dihedral angles. We argue that the long-range correlation of the polyglutamine homopeptide, along with the presence of these rare motifs, could be responsible for its aggregation phenomena

Distinct mechanisms of loss of IFN-gamma mediated HLA class I inducibility in two melanoma cell lines

BACKGROUND: The inability of cancer cells to present antigen on the cell surface via MHC class I molecules is one of the mechanisms by which tumor cells evade anti-tumor immunity. Alterations of Jak-STAT components of interferon (IFN)-mediated signaling can contribute to the mechanism of cell resistance to IFN, leading to lack of MHC class I inducibility. Hence, the identification of IFN-γ-resistant tumors may have prognostic and/or therapeutic relevance. In the present study, we investigated a mechanism of MHC class I inducibility in response to IFN-γ treatment in human melanoma cell lines. METHODS: Basal and IFN-induced expression of HLA class I antigens was analyzed by means of indirect immunofluorescence flow cytometry, Western Blot, RT-PCR, and quantitative real-time RT-PCR (TaqMan(® )Gene Expression Assays). In demethylation studies cells were cultured with 5-aza-2'-deoxycytidine. Electrophoretic Mobility Shift Assay (EMSA) was used to assay whether IRF-1 promoter binding activity is induced in IFN-γ-treated cells. RESULTS: Altered IFN-γ mediated HLA-class I induction was observed in two melanoma cells lines (ESTDAB-004 and ESTDAB-159) out of 57 studied, while treatment of these two cell lines with IFN-α led to normal induction of HLA class I antigen expression. Examination of STAT-1 in ESTDAB-004 after IFN-γ treatment demonstrated that the STAT-1 protein was expressed but not phosphorylated. Interestingly, IFN-α treatment induced normal STAT-1 phosphorylation and HLA class I expression. In contrast, the absence of response to IFN-γ in ESTDAB-159 was found to be associated with alterations in downstream components of the IFN-γ signaling pathway. CONCLUSION: We observed two distinct mechanisms of loss of IFN-γ inducibility of HLA class I antigens in two melanoma cell lines. Our findings suggest that loss of HLA class I induction in ESTDAB-004 cells results from a defect in the earliest steps of the IFN-γ signaling pathway due to absence of STAT-1 tyrosine-phosphorylation, while absence of IFN-γ-mediated HLA class I expression in ESTDAB-159 cells is due to epigenetic blocking of IFN-regulatory factor 1 (IRF-1) transactivation

Solvent accessible surface area approximations for rapid and accurate protein structure prediction

The burial of hydrophobic amino acids in the protein core is a driving force in protein folding. The extent to which an amino acid interacts with the solvent and the protein core is naturally proportional to the surface area exposed to these environments. However, an accurate calculation of the solvent-accessible surface area (SASA), a geometric measure of this exposure, is numerically demanding as it is not pair-wise decomposable. Furthermore, it depends on a full-atom representation of the molecule. This manuscript introduces a series of four SASA approximations of increasing computational complexity and accuracy as well as knowledge-based environment free energy potentials based on these SASA approximations. Their ability to distinguish correctly from incorrectly folded protein models is assessed to balance speed and accuracy for protein structure prediction. We find the newly developed “Neighbor Vector” algorithm provides the most optimal balance of accurate yet rapid exposure measures

A polygenic burden of rare disruptive mutations in schizophrenia.

Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease