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      Urine peptidome analysis in cardiorenal syndrome reflects molecular processes

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          Abstract

          The cardiorenal syndrome (CRS) is defined as the confluence of heart-kidney dysfunction. This study investigates the molecular differences at the level of the urinary peptidome between CRS patients and controls and their association to disease pathophysiology. The urinary peptidome of CRS patients (n = 353) was matched for age and sex with controls (n = 356) at a 1:1 ratio. Changes in the CRS peptidome versus controls were identified after applying the Mann–Whitney test, followed by correction for multiple testing. Proteasix tool was applied to investigate predicted proteases involved in CRS-associated peptide generation. Overall, 559 differentially excreted urinary peptides were associated with CRS patients. Of these, 193 peptides were specifically found in CRS when comparing with heart failure and chronic kidney disease urinary peptide profiles. Proteasix predicted 18 proteases involved in > 1% of proteolytic cleavage events including multiple forms of MMPs, proprotein convertases, cathepsins and kallikrein 4. Forty-four percent of the cleavage events were produced by 3 proteases including MMP13, MMP9 and MMP2. Pathway enrichment analysis supported that ECM-related pathways, fibrosis and inflammation were represented. Collectively, our study describes the changes in urinary peptides of CRS patients and potential proteases involved in their generation, laying the basis for further validation.

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          Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

          A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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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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              Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

              The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55 000 organisms (>4800 viruses, >40 000 prokaryotes and >10 000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management.
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                Author and article information

                Contributors
                jjankowski@ukaachen.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 August 2021
                10 August 2021
                2021
                : 11
                : 16219
                Affiliations
                [1 ]GRID grid.412301.5, ISNI 0000 0000 8653 1507, Institute for Molecular Cardiovascular Research, , RWTH Aachen University Hospital, ; Pauwelsstraße 30, 52074 Aachen, Germany
                [2 ]GRID grid.417975.9, ISNI 0000 0004 0620 8857, Biotechnology Division, , Biomedical Research Foundation of the Academy of Athens, ; Athens, Greece
                [3 ]GRID grid.421873.b, Mosaiques Diagnostics GmbH, ; Hannover, Germany
                [4 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Experimental Vascular Pathology, Cardiovascular Research Institute Maastricht (CARIM), , University of Maastricht, ; Maastricht, The Netherlands
                Article
                95695
                10.1038/s41598-021-95695-z
                8355128
                34376786
                afbaa53d-514a-4cad-b302-e62d54282971
                © The Author(s) 2021

                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
                : 27 May 2021
                : 19 July 2021
                Funding
                Funded by: European Union’s Horizon 2020/Marie Skłodowska-Curie
                Award ID: No 764474
                Funded by: DFG, German Research Foundation
                Award ID: SFB/TRR 219; Project-ID 322900939; S-03; C-04
                Award Recipient :
                Funded by: RWTH Aachen University (3131)
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                biomarkers,cardiology,nephrology,proteomic analysis
                Uncategorized
                biomarkers, cardiology, nephrology, proteomic analysis

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