Browsing by Author "Cafferata, Emilio A."

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    Capsular-defective Porphyromonas gingivalis mutant strains induce less alveolar bone resorption than W50 wild-type strain due to a decreased Th1/Th17 immune response and less osteoclast activity
    (2019) Monasterio, Gustavo; Fernandez, Baltasar; Castillo, Francisca; Rojas, Carolina; Cafferata, Emilio A.; Rojas, Leticia; Alvarez, Carla; Fernandez, Alejandra; Hernandez, Marcela; Bravo, Denisse; Vernal, Rolando
    Background Encapsulation of Porphyromonas gingivalis has been demonstrated as responsible of several host immunological changes, which have been associated with the pathogenesis of periodontitis. Using a murine model of periodontitis and two isogenic non-capsulated mutants of P. gingivalis, this study aimed to analyze whether P. gingivalis encapsulation induces more severe alveolar bone resorption, and whether this bone loss is associated with a T-helper (Th)1 and Th17-pattern of immune response. Methods Experimental periodontal infections were generated by oral inoculation with the encapsulated W50 wild-type strain or isogenic non-encapsulated Delta PG0116-PG0120 (GPA) and Delta PG0109-PG0118 (GPC) mutants of P. gingivalis. Periodontal infections induced with the encapsulated HG184 or non-encapsulated ATCC 33277 strains of P. gingivalis were used as controls. Alveolar bone resorption was analyzed using microcomputed tomography and scanning electron microscopy. The expression levels of Th1, Th2, Th17, or T regulatory-associated cytokines and RANKL, as well as the periodontal bacterial load, were quantified by quantitative polymerase chain reaction. The detection of Th1 and Th17 lymphocytes was analyzed by flow cytometry. Results In the periodontal lesions, both capsular-defective knockout mutant strains of P. gingivalis induced less alveolar bone resorption than the encapsulated W50 wild-type strain. This decreased bone loss was associated with a dismissed RANKL expression, decreased Th1- and Th17-type of cytokine expression, reduced Th1 and Th17 lymphocyte detection, and low osteoclast finding. Conclusion These data demonstrate that encapsulation of P. gingivalis plays a key role in the alveolar bone resorption induced during periodontitis, and this bone loss is associated with a Th1- and Th17-pattern of immune response triggered in the periodontal lesions.
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    Regulatory T lymphocytes in periodontitis: a translational view
    (2018) Alvarez, Carla; Rojas, Carolina; Rojas Cortéz, Leticia Andrea; Cafferata, Emilio A.; Monasterio, Gustavo; Vernal, Rolando
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    Transcriptional Signatures and Network-Based Approaches Identified Master Regulators Transcription Factors Involved in Experimental Periodontitis Pathogenesis
    (2023) Vicencio, Emiliano; Nunez-Belmar, Josefa; Cardenas, Juan P.; Cortes, Bastian I.; Martin, Alberto J. M.; Maracaja-Coutinho, Vinicius; Rojas, Adolfo; Cafferata, Emilio A.; Gonzalez-Osuna, Luis; Vernal, Rolando; Cortez, Cristian
    Periodontitis is a chronic inflammatory disease characterized by the progressive and irreversible destruction of the periodontium. Its aetiopathogenesis lies in the constant challenge of the dysbiotic biofilm, which triggers a deregulated immune response responsible for the disease phenotype. Although the molecular mechanisms underlying periodontitis have been extensively studied, the regulatory mechanisms at the transcriptional level remain unclear. To generate transcriptomic data, we performed RNA shotgun sequencing of the oral mucosa of periodontitis-affected mice. Since genes are not expressed in isolation during pathological processes, we disclose here the complete repertoire of differentially expressed genes (DEG) and co-expressed modules to build Gene Regulatory Networks (GRNs) and identify the Master Transcriptional Regulators of periodontitis. The transcriptional changes revealed 366 protein-coding genes and 42 non-coding genes differentially expressed and enriched in the immune response. Furthermore, we found 13 co-expression modules with different representation degrees and gene expression levels. Our GRN comprises genes from 12 gene clusters, 166 nodes, of which 33 encode Transcription Factors, and 201 connections. Finally, using these strategies, 26 master regulators of periodontitis were identified. In conclusion, combining the transcriptomic analyses with the regulatory network construction represents a powerful and efficient strategy for identifying potential periodontitis-therapeutic targets.