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      RNAi reveals proteins for metabolism and protein processing associated with Langat virus infection in Ixodes scapularis (black-legged tick) ISE6 cells

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          Abstract

          Background

          Tick-borne flaviviruses (TBFs) cause thousands of human cases of encephalitis worldwide each year, with some TBF infections progressing to hemorrhagic fever. TBFs are of medical and veterinary importance and strategies to reduce flavivirus transmission by the tick vector may have significant application. Analyses of the proteome of ISE6 cells derived from the black legged tick, Ixodes scapularis infected with the TBF, Langat virus (LGTV), have provided insights into proteins and cellular processes involved with LGTV infection.

          Methods

          RNA interference (RNAi)-induced knockdown of transcripts was used to investigate the role of ten tick proteins in the LGTV infection cycle in ISE6 cells. LGTV-infected cells were separately transfected with dsRNA corresponding to each gene of interest and the effect on LGTV genome replication and release of infectious virus was assessed by RT-qPCR and plaque assays, respectively.

          Results

          RNAi-induced knockdown of transcripts for two enzymes that likely function in amino acid, carbohydrate, lipid, terpenoid/polykeytide and vitamin metabolism, and a transcript for one protein of unknown function were associated with decreased replication of the LGTV genome and release of infectious virus from cells. The knockdown of transcripts for five enzymes predicted to function in metabolism, a protein likely associated with folding, sorting and degradation, and a protein of unknown function was associated with a decrease only in the amount of infectious LGTV released from cells.

          Conclusions

          These data suggest tick proteins potentially associated with metabolism and protein processing may be involved in LGTV infection of ISE6 cells. Our study provides information to begin to elucidate the function of these proteins and identify targets for the development of new interventions aimed at controlling the transmission of TBFs.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13071-016-1944-0) contains supplementary material, which is available to authorized users.

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          Most cited references 58

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          STRING v10: protein–protein interaction networks, integrated over the tree of life

          The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.
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            KEGG as a reference resource for gene and protein annotation

            KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an integrated database resource for biological interpretation of genome sequences and other high-throughput data. Molecular functions of genes and proteins are associated with ortholog groups and stored in the KEGG Orthology (KO) database. The KEGG pathway maps, BRITE hierarchies and KEGG modules are developed as networks of KO nodes, representing high-level functions of the cell and the organism. Currently, more than 4000 complete genomes are annotated with KOs in the KEGG GENES database, which can be used as a reference data set for KO assignment and subsequent reconstruction of KEGG pathways and other molecular networks. As an annotation resource, the following improvements have been made. First, each KO record is re-examined and associated with protein sequence data used in experiments of functional characterization. Second, the GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes. Third, new automatic annotation servers, BlastKOALA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from the GENES database. As a resource for translational bioinformatics, various data sets are created for antimicrobial resistance and drug interaction networks.
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              • Abstract: found
              • Article: found
              Is Open Access

              Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction

              Background Choosing appropriate primers is probably the single most important factor affecting the polymerase chain reaction (PCR). Specific amplification of the intended target requires that primers do not have matches to other targets in certain orientations and within certain distances that allow undesired amplification. The process of designing specific primers typically involves two stages. First, the primers flanking regions of interest are generated either manually or using software tools; then they are searched against an appropriate nucleotide sequence database using tools such as BLAST to examine the potential targets. However, the latter is not an easy process as one needs to examine many details between primers and targets, such as the number and the positions of matched bases, the primer orientations and distance between forward and reverse primers. The complexity of such analysis usually makes this a time-consuming and very difficult task for users, especially when the primers have a large number of hits. Furthermore, although the BLAST program has been widely used for primer target detection, it is in fact not an ideal tool for this purpose as BLAST is a local alignment algorithm and does not necessarily return complete match information over the entire primer range. Results We present a new software tool called Primer-BLAST to alleviate the difficulty in designing target-specific primers. This tool combines BLAST with a global alignment algorithm to ensure a full primer-target alignment and is sensitive enough to detect targets that have a significant number of mismatches to primers. Primer-BLAST allows users to design new target-specific primers in one step as well as to check the specificity of pre-existing primers. Primer-BLAST also supports placing primers based on exon/intron locations and excluding single nucleotide polymorphism (SNP) sites in primers. Conclusions We describe a robust and fully implemented general purpose primer design tool that designs target-specific PCR primers. Primer-BLAST offers flexible options to adjust the specificity threshold and other primer properties. This tool is publicly available at http://www.ncbi.nlm.nih.gov/tools/primer-blast.
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                Author and article information

                Contributors
                jeffrey.grabowski@nih.gov
                mgulianuss@unr.edu
                kuhnr@purdue.edu
                hillca@purdue.edu
                Journal
                Parasit Vectors
                Parasit Vectors
                Parasites & Vectors
                BioMed Central (London )
                1756-3305
                13 January 2017
                13 January 2017
                2017
                : 10
                Affiliations
                [1 ]Department of Entomology, College of Agriculture, Purdue University, 901 W State Street, West Lafayette, IN 47907 USA
                [2 ]Markey Center for Structural Biology, Department of Biological Sciences, College of Science, Purdue University, 915 W State Street, West Lafayette, IN 47907 USA
                [3 ]Purdue Institute for Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN 47907 USA
                [4 ]Current Address: NIH/NIAID, Rocky Mountain Laboratories, Laboratory of Virology, Biology of Vector-Borne Viruses Section, 903 S 4th St, Hamilton, MT 59840 USA
                [5 ]Current Address: Department of Biochemistry and Molecular Biology, College of Agriculture, Biotechnology, and Natural Resources, University of Nevada-Reno, 1664 N Virginia Street, Reno, NV 89503 USA
                Article
                1944
                10.1186/s13071-016-1944-0
                5237174
                28086865
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100006291, Entomological Society of America;
                Award ID: Monsanto Research Grant Award
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DGE-1333468
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100006975, Indiana Clinical and Translational Sciences Institute;
                Award ID: NIH/NCATS-ICTSI TL1 TR000162
                Award Recipient :
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                © The Author(s) 2017

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