BK Virus Epigenetically Regulates Transcription of Genes in Proximal Tubular Cells of Kidney.
Bibliographic record
Abstract
Background: BK virus induces fibrosis which promotes graft failure in transplant recipients. Epigenetic regulation has been shown to play a key role in controlling epithelial mesenchymal transition ultimately leading to fibrosis. DNA methyl transferase 1 (DNMT1) is a key regulator of DNA methylation (an epigenetic mechanism) which hypermethylates promoters to silence certain genes. EMT can be characterized by loss of expression of epithelial markers, for example E-cadherin and the basement membrane component Collagen IV. Hypothesis: Our hypothesis is that BK virus epigenetically modifies host epithelial cells to induce EMT and fibrosis. Aim: To determine the mechanisms BK virus uses to induce EMT and fibrosis in human proximal tubular cells (HPTCs). Methods: HPTCs were infected with BK polyoma virus and RNA/DNA isolation was carried out. Induction and repression of gene expression was measured using RT-PCR. Methylation Specific PCR (MSP) was performed to analyze the DNA methylation signature of the promoter segment of the COLIVA1 gene. To test whether the epigenetic mechanism that BK polyoma virus uses is DNA methylation, the cells were treated with 5-Azacytidine demethylating agent. The statistical calculation was performed by using Graphpad Prism version5 and REST 2009 software. Results: RT-PCR demonstrated increased expression of transcription factor E2F1 (p-value 0.001) required for cell cycle induction. RT-PCR also demonstrated the upregulation of DNMT1 (DNA methyltransferase required for epigenetic downregulation of genes) and the TAp73 gene (p53 family), both of which are E2F1 regulated genes. COLIVA1 expressison was downregulated (significant p-value=0.003), and by Methylation Specific PCR (MSP) shown to be epigenetically controlled by the hypermethylation of the promoter sequence in BK polyoma virus infected HPTCs compared to non-infected cells. 5-Azacytidine treatment increased the expression level of COLIVA1 with mean factor 30.368 demonstrating the mechanism to be DNA methylation. Conclusion: Our results suggest that BK polyoma virus epigenetically orchestrates the fibrosis by inducing E2F1 for cell cycle progression and promotes EMT by DNA methylation. Significance: Understanding of epigenetic mechanisms controlling fibrosis is critical to abrogate the negative effects of viral infection in promoting long-term graft loss.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".