Transcriptional Signatures and Network-Based Approaches Identified Master Regulators Transcription Factors Involved in Experimental Periodontitis Pathogenesis.
Emiliano VicencioJosefa Nuñez-BelmarJuan P CardenasBastian I CortésAlberto Jesus Martín MartínVinicius Maracaja-CoutinhoAdolfo RojasEmilio A CafferataLuis Gustavo Gonzalez OsunaRolando VernalCristian CortezPublished in: International journal of molecular sciences (2023)
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.
Keyphrases
- transcription factor
- genome wide identification
- genome wide
- gene expression
- immune response
- single cell
- dna binding
- dna methylation
- bioinformatics analysis
- multiple sclerosis
- staphylococcus aureus
- poor prognosis
- rna seq
- pseudomonas aeruginosa
- dendritic cells
- cystic fibrosis
- adipose tissue
- single molecule
- long non coding rna
- metabolic syndrome
- heat shock
- small molecule
- copy number
- climate change
- toll like receptor
- radiation therapy
- lymph node
- heat shock protein