201 research outputs found

    Atomic-Resolution Simulations Predict a Transition State for Vesicle Fusion Defined by Contact of a Few Lipid Tails

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    Membrane fusion is essential to both cellular vesicle trafficking and infection by enveloped viruses. While the fusion protein assemblies that catalyze fusion are readily identifiable, the specific activities of the proteins involved and nature of the membrane changes they induce remain unknown. Here, we use many atomic-resolution simulations of vesicle fusion to examine the molecular mechanisms for fusion in detail. We employ committor analysis for these million-atom vesicle fusion simulations to identify a transition state for fusion stalk formation. In our simulations, this transition state occurs when the bulk properties of each lipid bilayer remain in a lamellar state but a few hydrophobic tails bulge into the hydrophilic interface layer and make contact to nucleate a stalk. Additional simulations of influenza fusion peptides in lipid bilayers show that the peptides promote similar local protrusion of lipid tails. Comparing these two sets of simulations, we obtain a common set of structural changes between the transition state for stalk formation and the local environment of peptides known to catalyze fusion. Our results thus suggest that the specific molecular properties of individual lipids are highly important to vesicle fusion and yield an explicit structural model that could help explain the mechanism of catalysis by fusion proteins

    Fusing simulation and experiment: The effect of mutations on the structure and activity of the influenza fusion peptide

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    During the infection process, the influenza fusion peptide (FP) inserts into the host membrane, playing a crucial role in the fusion process between the viral and host membranes. In this work we used a combination of simulation and experimental techniques to analyse the molecular details of this process, which are largely unknown. Although the FP structure has been obtained by NMR in detergent micelles, there is no atomic structure information in membranes. To answer this question, we performed bias-exchange metadynamics (BE-META) simulations, which showed that the lowest energy states of the membrane-inserted FP correspond to helical-hairpin conformations similar to that observed in micelles. BE-META simulations of the G1V, W14A, G12A/G13A and G4A/G8A/G16A/G20A mutants revealed that all the mutations affect the peptide's free energy landscape. A FRET-based analysis showed that all the mutants had a reduced fusogenic activity relative to the WT, in particular the mutants G12A/G13A and G4A/G8A/G16A/G20A. According to our results, one of the major causes of the lower activity of these mutants is their lower membrane affinity, which results in a lower concentration of peptide in the bilayer. These findings contribute to a better understanding of the influenza fusion process and open new routes for future studies

    Nodeomics: Pathogen Detection in Vertebrate Lymph Nodes Using Meta-Transcriptomics

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    The ongoing emergence of human infections originating from wildlife highlights the need for better knowledge of the microbial community in wildlife species where traditional diagnostic approaches are limited. Here we evaluate the microbial biota in healthy mule deer (Odocoileus hemionus) by analyses of lymph node meta-transcriptomes. cDNA libraries from five individuals and two pools of samples were prepared from retropharyngeal lymph node RNA enriched for polyadenylated RNA and sequenced using Roche-454 Life Sciences technology. Protein-coding and 16S ribosomal RNA (rRNA) sequences were taxonomically profiled using protein and rRNA specific databases. Representatives of all bacterial phyla were detected in the seven libraries based on protein-coding transcripts indicating that viable microbiota were present in lymph nodes. Residents of skin and rumen, and those ubiquitous in mule deer habitat dominated classifiable bacterial species. Based on detection of both rRNA and protein-coding transcripts, we identified two new proteobacterial species; a Helicobacter closely related to Helicobacter cetorum in the Helicobacter pylori/Helicobacter acinonychis complex and an Acinetobacter related to Acinetobacter schindleri. Among viruses, a novel gamma retrovirus and other members of the Poxviridae and Retroviridae were identified. We additionally evaluated bacterial diversity by amplicon sequencing the hypervariable V6 region of 16S rRNA and demonstrate that overall taxonomic diversity is higher with the meta-transcriptomic approach. These data provide the most complete picture to date of the microbial diversity within a wildlife host. Our research advances the use of meta-transcriptomics to study microbiota in wildlife tissues, which will facilitate detection of novel organisms with pathogenic potential to human and animals

    An incremental approach to automated protein localisation

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    Tscherepanow M, Jensen N, Kummert F. An incremental approach to automated protein localisation. BMC Bioinformatics. 2008;9(1): 445.Background: The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected. Results: We introduce a novel approach to automated protein localisation in living cells. In contrast to well-known techniques, the protein localisation technique presented in this article aims at combining the two types of approaches described above: After an automatic identification of unknown protein locations, a potential user is enabled to incorporate them into the pre-trained system. An incremental neural network allows the classification of a fixed set of protein location as well as the detection, clustering and incorporation of additional patterns that occur during an experiment. Here, the proposed technique achieves promising results with respect to both tasks. In addition, the protein localisation procedure has been adapted to an existing cell recognition approach. Therefore, it is especially well-suited for high-throughput investigations where user interactions have to be avoided. Conclusion: We have shown that several aspects required for developing an automatic protein localisation technique – namely the recognition of cells, the classification of protein distribution patterns into a set of learnt protein locations, and the detection and learning of new locations – can be combined successfully. So, the proposed method constitutes a crucial step to render image-based protein localisation techniques amenable to large-scale experiments

    Cadophora margaritata sp. nov. and other fungi associated with the longhorn beetles Anoplophora glabripennis and Saperda carcharias in Finland

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    Symbiosis with microbes is crucial for survival and development of wood-inhabiting longhorn beetles (Coleoptera: Cerambycidae). Thus, knowledge of the endemic fungal associates of insects would facilitate risk assessment in cases where a new invasive pest occupies the same ecological niche. However, the diversity of fungi associated with insects remains poorly understood. The aim of this study was to investigate fungi associated with the native large poplar longhorn beetle (Saperda carcharias) and the recently introduced Asian longhorn beetle (Anoplophora glabripennis) infesting hardwood trees in Finland. We studied the cultivable fungal associates obtained from Populus tremula colonised by S. carcharias, and Betula pendula and Salix caprea infested by A. glabripennis, and compared these to the samples collected from intact wood material. This study detected a number of plant pathogenic and saprotrophic fungi, and species with known potential for enzymatic degradation of wood components. Phylogenetic analyses of the most commonly encountered fungi isolated from the longhorn beetles revealed an association with fungi residing in the Cadophora-Mollisia species complex. A commonly encountered fungus was Cadophora spadicis, a recently described fungus associated with wood-decay. In addition, a novel species of Cadophora, for which the name Cadophora margaritata sp. nov. is provided, was isolated from the colonised wood.Peer reviewe

    Phylogenomic analysis of a 55.1 kb 19-gene dataset resolves a monophyletic Fusarium that includes the Fusarium solani Species Complex

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    Scientific communication is facilitated by a data-driven, scientifically sound taxonomy that considers the end-user¿s needs and established successful practice. In 2013, the Fusarium community voiced near unanimous support for a concept of Fusarium that represented a clade comprising all agriculturally and clinically important Fusarium species, including the F. solani species complex (FSSC). Subsequently, this concept was challenged in 2015 by one research group who proposed dividing the genus Fusarium into seven genera, including the FSSC described as members of the genus Neocosmospora, with subsequent justification in 2018 based on claims that the 2013 concept of Fusarium is polyphyletic. Here, we test this claim and provide a phylogeny based on exonic nucleotide sequences of 19 orthologous protein-coding genes that strongly support the monophyly of Fusarium including the FSSC. We reassert the practical and scientific argument in support of a genus Fusarium that includes the FSSC and several other basal lineages, consistent with the longstanding use of this name among plant pathologists, medical mycologists, quarantine officials, regulatory agencies, students, and researchers with a stake in its taxonomy. In recognition of this monophyly, 40 species described as genus Neocosmospora were recombined in genus Fusarium, and nine others were renamed Fusarium. Here the global Fusarium community voices strong support for the inclusion of the FSSC in Fusarium, as it remains the best scientific, nomenclatural, and practical taxonomic option availabl

    Beside the Seaside. The archaeology of the twentieth-century English seaside holiday experience: a phenomenological context.

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    A recent survey commissioned by English Heritage highlights the rich cultural history of the traditional English seaside resort (Brodie and Winter 2007). Emerging in the eighteenth century, these towns grew in significance before the advent of cheaper continental holidays in the 1960s signalled their demise. Nevertheless they retain an affectionate place within English social memory, and are in their own right distinctive maritime communities. Using an archaeological case study and a broadly phenomenological approach this contribution analyses the experience of the resort holiday through reference to place, space and materiality. Further, it seeks to situate the English seaside resort, as a functionally distinctive post-medieval urban and maritime phenomenon, within a global context of the archaeology of tourism

    Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

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    BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)
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