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Impact of Porphyromonas gingivalis Peptidylarginine Deiminase on Bacterial Biofilm Formation, Epithelial Cell Invasion, and Epithelial Cell Transcriptional Landscape.

Ardita Aliko | Marta Kamińska | Brith Bergum | Katarzyna Gawron | Małgorzata Benedyk | Richard J Lamont | Stanisław Malicki | Nicolas Delaleu | Jan Potempa | Piotr Mydel
Scientific reports | 2018

Peptidylarginine deiminase (PPAD) is a virulence factor unique to pathogenic Porphyromonas species, especially P. gingivalis. Mechanistically, PPAD activity, in conjunction with Arg-specific gingipains, generates protein fragments with citrullinated C-termini. Such polypeptides are potential de novo epitopes that are key drivers of rheumatoid arthritis. This process could underlie the observed clinical association between rheumatoid arthritis and periodontitis. However, the role of PPAD in host colonization by P. gingivalis and, subsequently, in triggering periodontitis is not known. Therefore, the aim of the current study was to delineate the role of PPAD in bacterial biofilm formation, and to define whether adherence to, invasion of, and host responses to bacteria of gingival keratinocytes depend on PPAD activity. We studied these aspects using PPAD-competent and PPAD-incompetent strains of P. gingivalis, and demonstrated that neither biofilm formation nor its composition was affected by PPAD activity. Similarly, flow cytometry revealed that PPAD did not impact the ability of P. gingivalis to adhere to and, subsequently, invade keratinocytes. Network analyses of gene expression patterns, however, revealed a group of host genes that were sensitive to PPAD activity (CXCL8, IL36G, CCL20, and IL1B). These genes can be categorized as potent immune modulators belonging to the interleukin 1 system, or chemoattractants of lymphocytes and neutrophils. Thus, we conclude that PPAD, although it is a potent modulator of the immune response, does not affect bacterial biofilm formation or the ability of P. gingivalis to adhere to and invade gingival epithelial cells.

Pubmed ID: 30237466

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Associated grants

  • Agency: NIDCR NIH HHS, United States
    Id: R01 DE011111
  • Agency: NIDCR NIH HHS, United States
    Id: R37 DE011111
  • Agency: Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.), International
    Id: DE022597
  • Agency: Narodowe Centrum Nauki (National Science Centre), International
    Id: 2016/23/B/NZ5/011469
  • Agency: Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.), International
    Id: DE011111
  • Agency: NIDCR NIH HHS, United States
    Id: R01 DE022597
  • Agency: Narodowe Centrum Nauki (National Science Centre), International
    Id: 2014/14/E/NZ6/00162

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Cytoscape (tool)

RRID:SCR_003032

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

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RRID:SCR_005748

A Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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