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We have reported previously that Short Interspersed Degenerate Retroposons of the SIDER2 subfamily, largely located within 3'UTRs of Leishmania transcripts, promote rapid turnover of mRNAs through endonucleolytic cleavage within the highly conserved second tandem 79-nt hallmark sequence (79-nt SII). Here, we used site-directed mutagenesis and in silico RNA structural studies to delineate the cis-acting requirements within 79-nt SII for cleavage and mRNA degradation. The putative cleavage site(s) and other nucleotides predicted to alter the RNA secondary structure of 79-nt SII were either deleted or mutated and their effect on mRNA turnover was monitored using a gene reporter system. We found that short deletions of 8-nt spanning the two predicted cleavage sites block degradation of SIDER2-containing transcripts, leading to mRNA accumulation. Furthermore, single or double substitutions of the dinucleotides targeted for cleavage as well as mutations altering the predicted RNA secondary structure encompassing both cleavage sites also prevent mRNA degradation, confirming that these dinucleotides are the bona fide cleavage sites. In line with these results, we show that stage-regulated SIDER2 inactivation correlates with the absence of endonucleolytic cleavage. Overall, these data demonstrate that both cleavage sites within the conserved 79-nt SII as well as RNA folding in this region are essential for SIDER2-mediated mRNA decay, and further support that SIDER2-harboring transcripts are targeted for degradation by endonucleolytic cleavage.
NMR spectroscopy is a powerful technique to study ribonucleic acids (RNAs) which are key players in a plethora of cellular processes. Although the NMR toolbox for structural studies of RNAs expanded during the last decades, they often remain challenging. Here, we show that solvent paramagnetic relaxation enhancements (sPRE) induced by the soluble, paramagnetic compound Gd(DTPA-BMA) provide a quantitative measure for RNA solvent accessibility and encode distance-to-surface information that correlates well with RNA structure and improves accuracy and convergence of RNA structure determination. Moreover, we show that sPRE data can be easily obtained for RNAs with any isotope labeling scheme and is advantageous regarding sample preparation, stability and recovery. sPRE data show a large dynamic range and reflect the global fold of the RNA suggesting that they are well suited to identify interaction surfaces, to score structural models and as restraints in RNA structure determination.
The website Sci-Hub provides access to scholarly literature via full text PDF downloads. The site enables users to access articles that would otherwise be paywalled. Since its creation in 2011, Sci-Hub has grown rapidly in popularity. However, until now, the extent of Sci-Hub's coverage was unclear. As of March 2017, we find that Sci-Hub's database contains 68.9% of all 81.6 million scholarly articles, which rises to 85.2% for those published in closed access journals. Furthermore, Sci-Hub contains 77.0% of the 5.2 million articles published by inactive journals. Coverage varies by discipline, with 92.8% coverage of articles in chemistry journals compared to 76.3% for computer science. Coverage also varies by publisher, with the coverage of the largest publisher, Elsevier, at 97.3%. Our interactive browser at https://greenelab.github.io/scihub allows users to explore these findings in more detail. Finally, we estimate that over a six-month period in 2015–2016, Sci-Hub provided access for 99.3% of valid incoming requests. Hence, the scope of this resource suggests the subscription publishing model is becoming unsustainable. For the first time, the overwhelming majority of scholarly literature is available gratis to anyone with an Internet connection.
The website Sci-Hub provides access to scholarly literature via full text PDF downloads. The site enables users to access articles that would otherwise be paywalled. Since its creation in 2011, SciHub has grown rapidly in popularity. However, until now, the extent of Sci-Hub’s coverage was unclear. As of March 2017, we find that Sci-Hub’s database contains 68.9% of all 81.6 million scholarly articles, which rises to 85.2% for those published in toll access journals. Coverage varies by discipline, with 92.8% coverage of articles in chemistry journals compared to 76.3% for computer science. Coverage also varies by publisher, with the coverage of the largest publisher, Elsevier, at 97.3%. Our interactive browser at greenelab.github.io/scihub allows users to explore these findings in more detail. We find Sci-Hub preferentially covers popular, paywalled content, containing 96.2% of citations to toll access journals since 2015. For recently requested articles by Unpaywall users, oaDOI provided access to 48.8% whereas Sci-Hub contained 81.5%. Together, oaDOI and Sci-Hub covered 94.1%, demonstrating that gaps in Sci-Hub’s coverage, especially for open access articles, can be filled using licit services. For the first time, nearly all scholarly literature is available gratis to anyone with an Internet connection. Sci-Hub’s scope suggests the subscription publishing model is becoming unsustainable.
In search for new natural products, which may lead to the development of new drugs for all kind of applications, novel methods are needed. Here we describe the identification of electrophilic natural products in crude extracts via their reactivity against azide as a nucleophile followed by their subsequent enrichment using a cleavable azide-reactive resin (CARR). Using this approach, natural products carrying epoxides and α,β-unsaturated enones as well as several unknown compounds were identified in crude extracts from entomopathogenic Photorhabdus bacteria.
Box C/D snoRNAs are known to guide site-specific ribose methylation of ribosomal RNA. Here, we demonstrate a novel and unexpected role for box C/D snoRNAs in guiding 18S rRNA acetylation in yeast. Our results demonstrate, for the first time, that the acetylation of two cytosine residues in 18S rRNA catalyzed by Kre33 is guided by two orphan box C/D snoRNAs–snR4 and snR45 –not known to be involved in methylation in yeast. We identified Kre33 binding sites on these snoRNAs as well as on the 18S rRNA, and demonstrate that both snR4 and snR45 establish extended bipartite complementarity around the cytosines targeted for acetylation, similar to pseudouridylation pocket formation by the H/ACA snoRNPs. We show that base pairing between these snoRNAs and 18S rRNA requires the putative helicase activity of Kre33, which is also needed to aid early pre-rRNA processing. Compared to yeast, the number of orphan box C/D snoRNAs in higher eukaryotes is much larger and we hypothesize that several of these may be involved in base-modifications.
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain–inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson () and Spearman () correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ( = 0.64 and = 0.66 for ABFE; = 0.39 and = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: = 0.55 and = 0.56 when including an entropy estimate, and = 0.53 and = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein–ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.
The transporter associated with antigen processing (TAP) selectively translocates antigenic peptides into the endoplasmic reticulum. Loading onto major histocompatibility complex class I molecules and proofreading of these bound epitopes are orchestrated within the macromolecular peptide-loading complex, which assembles on TAP. This heterodimeric ABC-binding cassette (ABC) transport complex is therefore a major component in the adaptive immune response against virally or malignantly transformed cells. Its pivotal role predestines TAP as a target for infectious diseases and malignant disorders. The development of therapies or drugs therefore requires a detailed comprehension of structure and function of this ABC transporter, but our knowledge about various aspects is still insufficient. This review highlights recent achievements on the structure and dynamics of antigenic peptides in complex with TAP. Understanding the binding mode of antigenic peptides in the TAP complex will crucially impact rational design of inhibitors, drug development, or vaccination strategies.
Genetic data in studies of systematics of Amazonian amphibians frequently reveal that purportedly widespread single species in reality comprise species complexes. This means that real species richness may be significantly higher than current estimates. Here we combine genetic, morphological, and bioacoustic data to assess the phylogenetic relationships and species boundaries of two Amazonian species of the Dendropsophus leucophyllatus species group: D. leucophyllatus and D. triangulum. Our results uncovered the existence of five confirmed and four unconfirmed candidate species. Among the confirmed candidate species, three have available names: Dendropsophus leucophyllatus, Dendropsophus triangulum, and Dendropsophus reticulatus, this last being removed from the synonymy of D. triangulum. A neotype of D. leucophyllatus is designated. We describe the remaining two confirmed candidate species, one from Bolivia and another from Peru. All confirmed candidate species are morphologically distinct and have much smaller geographic ranges than those previously reported for D. leucophyllatus and D. triangulum sensu lato. Dendropsophus leucophyllatus sensu stricto occurs in the Guianan region. Dendropsophus reticulatus comb. nov. corresponds to populations in the Amazon basin of Brazil, Ecuador, and Peru previously referred to as D. triangulum. Dendropsophus triangulum sensu stricto is the most widely distributed species; it occurs in Amazonian Ecuador, Peru and Brazil, reaching the state of Pará. We provide accounts for all described species including an assessment of their conservation status.
Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.