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      Salivary proteotypes of gingivitis tolerance and resilience

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          Abstract

          Aim

          This study aimed to characterize the salivary proteome during the induction and resolution of gingival inflammation in the course of human experimental gingivitis (EG), and to cluster the proteomic profiles based on the clinically defined “slow” and “fast” response patterns.

          Materials and Methods

          A total of 50 unstimulated whole saliva were obtained from the EG model which was induced over 21 days (days 0, 7, 14 and 21), followed by a two‐week resolution phase (day 35). Label‐free quantitative proteomics using liquid chromatography–tandem mass spectrometry was applied. Regulated proteins were subject to Gene Ontology enrichment analysis.

          Results

          A total of 804 human proteins were quantified by ≥ 2 peptides. Principal component analysis depicted significant differences between “fast” and “slow” responders. Despite gingival and plaque scores being similar at baseline among the two groups, “fast” responders presented with 48 proteins that were at > 4‐fold higher levels than “slow” responders. These up‐regulated proteins showed enrichment in “antigen presentation” and “proteolysis.”

          Conclusions

          Together, these findings highlight the utility of integrative systems‐level quantitative proteomic approaches to unravel the molecular basis of “salivary proteotypes” associated with gingivitis dubbed as “fast” and “slow” responders. Hence, these differential responses may help prognosticate individual susceptibility to gingival inflammation.

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          Most cited references47

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          The PRIDE database and related tools and resources in 2019: improving support for quantification data

          Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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            The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

            A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein–protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein–protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
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              Periodontitis: a polymicrobial disruption of host homeostasis.

              Periodontitis, or gum disease, affects millions of people each year. Although it is associated with a defined microbial composition found on the surface of the tooth and tooth root, the contribution of bacteria to disease progression is poorly understood. Commensal bacteria probably induce a protective response that prevents the host from developing disease. However, several bacterial species found in plaque (the 'red-complex' bacteria: Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola) use various mechanisms to interfere with host defence mechanisms. Furthermore, disease may result from 'community-based' attack on the host. Here, I describe the interaction of the host immune system with the oral bacteria in healthy states and in diseased states.
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                Author and article information

                Contributors
                nagihan.bostanci@ki.se
                rlopez@dent.au.dk
                Journal
                J Clin Periodontol
                J Clin Periodontol
                10.1111/(ISSN)1600-051X
                JCPE
                Journal of Clinical Periodontology
                John Wiley and Sons Inc. (Hoboken )
                0303-6979
                1600-051X
                16 September 2020
                November 2020
                : 47
                : 11 ( doiID: 10.1111/jcpe.v47.11 )
                : 1304-1316
                Affiliations
                [ 1 ] Section of Periodontology and Dental Prevention Division of Oral Diseases Department of Dental Medicine Karolinska Institutet Stockholm Sweden
                [ 2 ] Functional Genomic Center Zurich ETH Zurich and University of Zurich Zurich Switzerland
                [ 3 ] Section of Periodontology Department of Dentistry and Oral Health Aarhus University Aarhus Denmark
                Author notes
                [*] [* ] Correspondence

                Nagihan Bostanci, Section of Periodontology and Dental Prevention, Division of Oral Diseases of Department of Dental Medicine, Karolinska Institutet, Alfred Nobels Allé 8, 14152 Huddinge, Sweden.

                Email: nagihan.bostanci@ 123456ki.se

                Rodrigo Lopez, Section of Periodontology, Department of Dentistry and Oral Health, Aarhus University, Vennelyst Boulevard 9, building 1610, office 2.84, 8000 Aarhus, Denmark.

                Email: rlopez@ 123456dent.au.dk

                Author information
                https://orcid.org/0000-0002-6742-3556
                https://orcid.org/0000-0003-3717-6969
                https://orcid.org/0000-0002-1183-5607
                https://orcid.org/0000-0002-6899-9020
                https://orcid.org/0000-0002-4288-6300
                https://orcid.org/0000-0002-8164-0653
                https://orcid.org/0000-0001-6170-507X
                Article
                JCPE13358
                10.1111/jcpe.13358
                7692908
                32777086
                0ff29464-0457-43ef-a591-956703424b72
                © 2020 The Authors. Journal of Clinical Periodontology published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 21 March 2020
                : 19 July 2020
                : 05 August 2020
                Page count
                Figures: 5, Tables: 2, Pages: 13, Words: 6979
                Funding
                Funded by: Swedish Research Council , open-funder-registry 10.13039/501100004359;
                Award ID: 2017‐01198
                Funded by: Karolinska Institutet strategic fund , open-funder-registry 10.13039/501100004047;
                Funded by: Aarhus University Research Foundation , open-funder-registry 10.13039/501100002739;
                Categories
                Original Article Clinical Periodontology
                Periodontal Health & Diseases
                Custom metadata
                2.0
                November 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.4 mode:remove_FC converted:27.11.2020

                Dentistry
                biomarkers,experimental gingivitis,proteomics,saliva,salivary proteotypes
                Dentistry
                biomarkers, experimental gingivitis, proteomics, saliva, salivary proteotypes

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