456 research outputs found

    Discovery and molecular characterization of West Nile virus NY 1999

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    An account of the 1999 outbreak of West Nile virus infections in New York City

    Characterization of the major nuclear localization signal of the Borna disease virus phosphoprotein

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    Borna disease virus (BDV) replicates and transcribes its negative-sense RNA genome in the nucleus. The BDV phosphoprotein (P) is localized in the nucleus of infected cells and cells transfected with P expression constructs. To identify the nuclear localization signal (NLS) of P, COS- 7 cells were transfected with wild-type or mutant forms of P fused with green fluorescent protein (GFP). Whereas GFP alone was exclusively cytoplasmic, P or P-GFP were nuclear. Analysis of carboxy- and amino- terminal truncation mutants of P indicated that amino acids (aa) 20-37 are sufficient to promote efficient nuclear accumulation of the fusion protein. Residual nuclear import of GFP was observed with portions of P including aa 33-134 or aa 134-201, suggesting the presence of additional NLS motifs. The major NLS of P appears to be bipartite. It consists of two basic aa domains, R22RER25 and R30PRKIPR36, separated by four non-basic aa, S26GSP29

    Centroid based clustering of high throughput sequencing reads based on n-mer counts

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    Background: Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. Results: We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. Conclusions: We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read

    Authentic Borna disease virus transcripts are spliced less efficiently than cDNA-derived viral RNAs

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    Borna disease virus (BDV) is a non-segmented, negative-strand RNA virus that replicates and transcribes its genome in the nucleus of infected cells. It uses the cellular splicing machinery to generate a set of alternatively spliced mRNAs from the 2.8 and 7.1 kb primary transcripts, each harbouring two introns. To determine whether splicing of these transcripts is regulated by viral factors, the extent of splicing was studied in infected cells and COS-7 cells transiently transfected with plasmids encoding the 2.8 kb RNA of BDV. Unspliced RNA was found to be the most abundant RNA species in infected cells, whereas viral transcripts lacking both introns were only found in minute amounts. In sharp contrast, plasmid-derived 2.8 kb RNA was predominantly intron 1-spliced and double-spliced. Co-expression of the BDV proteins P, N and X did not influence splicing of plasmid-expressed 2.8 kb RNA. Furthermore, the splicing pattern did not change when the 2.8 kb RNA was expressed in BDV-infected cells. Based on these results we speculate that splicing of authentic BDV transcripts is tightly linked to transcription by the viral polymerase

    Cluster analysis of the origins of the new influenza A(H1N1) virus

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    In March and April 2009, a new strain of influenza A(H1N1) virus has been isolated in Mexico and the United States. Since the initial reports more than 10,000 cases have been reported to the World Health Organization, all around the world. Several hundred isolates have already been sequenced and deposited in public databases. We have studied the genetics of the new strain and identified its closest relatives through a cluster analysis approach. We show that the new virus combines genetic information related to different swine influenza viruses. Segments PB2, PB1, PA, HA, NP and NS are related to swine H1N2 and H3N2 influenza viruses isolated in North America. Segments NA and M are related to swine influenza viruses isolated in Eurasia
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