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      Unveiling the effect of dietary essential oils supplementation in Sparus aurata gills and its efficiency against the infestation by Sparicotyle chrysophrii

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          Abstract

          A microencapsulated feed additive composed by garlic, carvacrol and thymol essential oils (EOs) was evaluated regarding its protective effect in gills parasitized by Sparicotyle chrysophrii in Sparus aurata. A nutritional trial (65 days) followed by a cohabitation challenge with parasitized fish (39 days) were performed. Transcriptomic analysis by microarrays of gills of fish fed the EOs diet showed an up-regulation of genes related to biogenesis, vesicular transport and exocytosis, leukocyte-mediated immunity, oxidation–reduction and overall metabolism processes. The functional network obtained indicates a tissue-specific pro-inflammatory immune response arbitrated by degranulating acidophilic granulocytes, sustained by antioxidant and anti-inflammatory responses. The histochemical study of gills also showed an increase of carboxylate glycoproteins containing sialic acid in mucous and epithelial cells of fish fed the EOs diet, suggesting a mucosal defence mechanism through the modulation of mucin secretions. The outcomes of the in vivo challenge supported the transcriptomic results obtained from the nutritional trial, where a significant reduction of 78% in the abundance of S. chrysophrii total parasitation and a decrease in the prevalence of most parasitic developmental stages evaluated were observed in fish fed the EOs diet. These results suggest that the microencapsulation of garlic, carvacrol and thymol EOs could be considered an effective natural dietary strategy with antiparasitic properties against the ectoparasite S. chrysophrii.

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          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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            UniProt: a worldwide hub of protein knowledge

            (2018)
            Abstract The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of these proteins. These annotations are supplemented by annotations provided by rule based automated systems, and those imported from other resources. In this article we describe significant updates that we have made over the last 2 years to the resource. We have greatly expanded the number of Reference Proteomes that we provide and in particular we have focussed on improving the number of viral Reference Proteomes. The UniProt website has been augmented with new data visualizations for the subcellular localization of proteins as well as their structure and interactions. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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              The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses.

              GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It automatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. VarElect's capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. © 2016 by John Wiley & Sons, Inc.
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                Author and article information

                Contributors
                Felipe.Reyes@uab.cat
                Enric.Gisbert@irta.cat
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 October 2020
                20 October 2020
                2020
                : 10
                : 17764
                Affiliations
                [1 ]GRID grid.8581.4, ISNI 0000 0001 1943 6646, IRTA, Centre de Sant Carles de la Ràpita (IRTA-SCR), Aquaculture Program, ; Crta. Poble Nou km 5.5, 43540 Sant Carles de la Ràpita, Spain
                [2 ]TECNOVIT-FARMFAES, S.L. Pol. Ind. Les Sorts, parc. 10, 43365 Alforja, Spain
                [3 ]GRID grid.7080.f, PhD Program in Aquaculture, Universitat Autònoma de Barcelona, ; 08193 Bellaterra, Spain
                [4 ]GRID grid.412179.8, ISNI 0000 0001 2191 5013, Centro de Biotecnología Acuícola, Departamento de Biología, Facultad de Química y Biología, , Universidad de Santiago de Chile, ; Santiago, Chile
                [5 ]GRID grid.7759.c, ISNI 0000000103580096, Instituto de Ciencias Marinas de Andalucía (ICMAN-CSIC), , Universidad de Cádiz, ; Campus Universitario Río San Pedro, Puerto Real, Cádiz, Spain
                [6 ]GRID grid.7080.f, Department of Cell Biology, Physiology and Immunology, , Universitat Autònoma de Barcelona, ; 08193 Bellaterra, Spain
                Article
                74625
                10.1038/s41598-020-74625-5
                7576129
                33082387
                8f93cafd-403d-4900-84dd-04f7ec0a8485
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 March 2020
                : 29 September 2020
                Funding
                Funded by: AGAUR, Industrial PhD program, Generalitat de Catalunya
                Funded by: DICYT-USACH Postdoctoral fellowship
                Award ID: Nb.022043IB
                Award Recipient :
                Funded by: JACUMAR (Ministry of Agriculture, Fisheries and Environment of Spain, MAPAMA)
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                immunology,infection,innate immunity,molecular biology,transcriptomics,pathogens,gene expression analysis,microarray analysis

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