Identification of the Potential Molecular Mechanism of TGFBI Gene in Persistent Atrial Fibrillation.

Background: Transforming growth factor beta-induced protein (TGFBI, encoded by TGFBI gene), is an extracellular matrix protein, widely expressed in variety of tissues. It binds to collagens type I, II, and IV and plays important roles in the interactions of cell with cell, collagen, and matrix. It has been reported to be associated with myocardial fibrosis, and the latter is an important pathophysiologyical basis of atrial fibrillation (AF). However, the mechanism of TGFBI in AF remains unclear. We aimed to detect the potential mechanism of TGFBI in AF via bioinformatics analysis. Methods: The microarray dataset of GSE115574 was examined to detect the genes coexpressed with TGFBI from 14 left atrial tissue samples of AF patients. TGFBI coexpression genes were then screened using the R package. Using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of TGFBI and its coexpression genes. The modules and hub genes of the PPI-network were then identified. Another dataset, GSE79768 was examined to verify the hub genes. DrugBank was used to detect the potential target drugs. Results: In GSE115574 dataset, a total of 1818 coexpression genes (769 positive and 1049 negative) were identified, enriched in 120 biological processes (BP), 38 cellular components (CC), 36 molecular functions (MF), and 39 KEGG pathways. A PPI-network with average 12.2-degree nodes was constructed. The genes clustered in the top module constructed from this network mainly play a role in PI3K-Akt signaling pathway, viral myocarditis, inflammatory bowel disease, and platelet activation. CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 were identified and finally verified as the hub genes, mainly enriched in pathways like leukocyte transendothelial migration, PI3K-Akt signaling pathway, viral myocarditis, rheumatoid arthritis, and platelet activation. Pegcetacoplan, ocriplasmin, and carvedilol were the potential target drugs. Conclusions: We used microdataset to identify the potential functions and mechanisms of the TGFBI and its coexpression genes in AF patients. Our findings suggest that CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 may be the hub genes.

Evaluation of two high-abundance protein depletion kits and optimization of downstream isoelectric focusing.

Disease biomarkers for diagnostic and prognostic purposes are most likely within an extremely low concentration range and are thus masked by the presence of high­abundance proteins. Therefore, removing high­abundance proteins is the main challenge for identifying disease biomarkers. In addition, the solution obtained from high­abundance protein depletion kits contains a rich array of compounds, which interfere with isoelectric focusing (IEF). In the present study, the effect of two commercial kits was evaluated and the downstream IEF protocol was optimized. High­resolution results could be obtained according to the following conditions: The ProteoPrep Blue Albumin and IgG Depletion kit depleted albumin and IgG; immobilized pH gradient strips (typically 18 cm) were rehydrated with sample buffer containing 250 µg serum proteins at 30 v for 6 h, 60 v for 6 h, 200 v for 2 h, 500 v for 2 h, 1,000 v for 2 h, 5,000 v for 2 h, 10,000 v for 2 h and then focusing at 10,000 v up to 110 k vhs. In addition, the protein spots identified by matrix­assisted laser desorption ionization time­of­flight mass spectrometry demonstrated that all proteins had a low abundance. The present study not only provides a definite and effective method for removing high­abundance proteins, but also provides a proper protocol (protocol C) for downstream IEF. The present study includes a comprehensive investigation of serum proteomics, which paves the way for serum protein research.