Profiling miRNA changes in Epstein-Barr virus lytic infection identifies a function for BZLF1 in upregulating miRNAs from the DLK1-DIO3 locus
Bibliographic record
Abstract
Cellular and viral miRNAs are thought to play important roles in regulating Epstein-Barr virus (EBV) latent and lytic infections, however, to date, most studies have focussed on latent infections in B cells. To determine how cellular and viral miRNAs contribute to EBV lytic infection in epithelial cells, the main sites of lytic infection, we conducted miRNA-sequencing experiments in EBV-infected AGS gastric carcinoma cells, before and after reactivation to the lytic cycle, analysing both total miRNA and Ago2-associated miRNAs. We identified over 100 miRNAs whose association with Ago2 was affected upon EBV reactivation, most of which were due to changes in miRNA abundance. For EBV miRNAs, the most striking result was that the BHRF1 miRNAs, previously only reported to be expressed in B cells, were upregulated upon reactivation. The largest changes in cellular miRNAs upon EBV reactivation were increases in the abundance and Ago2-association of miR-409-3p, miR-381-3p and miR-370-3p, which appear to have pro-viral effects. In particular, inhibiting miR-409-3p reduced BZLF1 and other EBV lytic protein expression, at least in part through modulation of ZEB1. Interestingly, these miRNAs all originate from the DLK1-DIO3 locus (14q32.2 - 32.31), which encodes multiple lncRNAs. We showed that the lncRNAs MEG9, MIR381HG, and MEG8, from which miR-409-3p, miR-381-3p and miR-370-3p are derived, were also upregulated upon reactivation in AGS and nasopharyngeal carcinoma cells lines and occurred very early in the lytic cycle at the time of BZLF1 expression. In keeping with this timing, BZLF1 was sufficient to induce these lncRNAs dependent on its transactivation activity, and was detected at a key DLK1-DIO3 control element, consistent with a direct role in transcriptional activation. Therefore, we have identified a new role for BZFL1 in activating the expression of lncRNAs in the DLK1-DIO3 locus, resulting in induction of a subset of encoded miRNAs that promote lytic infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".