A genome-wide screen of Epstein-Barr virus proteins that modulate host SUMOylation identifies a SUMO E3 ligase conserved in herpesviruses
Bibliographic record
Abstract
Many cellular processes pertinent for viral infection are regulated by the addition of small ubiquitin-like modifiers (SUMO) to key regulatory proteins, making SUMOylation an important mechanism by which viruses can commandeer cellular pathways. Epstein-Barr virus (EBV) is a master at manipulating of cellular processes, which enables life-long infection but can also lead to the induction of a variety of EBV-associated cancers. To identify new mechanisms by which EBV proteins alter cells, we screened a library of 51 EBV proteins for global effects on cellular SUMO1 and SUMO2 modifications (SUMOylation), identifying several proteins not previously known to manipulate this pathway. One EBV protein (BRLF1) globally induced the loss of SUMOylated proteins, in a proteasome-dependent manner, as well as the loss of promeylocytic leukemia nuclear bodies. However, unlike its homologue (Rta) in Kaposi's sarcoma associated herpesvirus, it did not appear to have ubiquitin ligase activity. In addition we identified the EBV SM protein as globally upregulating SUMOylation and showed that this activity was conserved in its homologues in herpes simplex virus 1 (HSV1 UL54/ICP27) and cytomegalovirus (CMV UL69). All three viral homologues were shown to bind SUMO and Ubc9 and to have E3 SUMO ligase activity in a purified system. These are the first SUMO E3 ligases discovered for EBV, HSV1 and CMV. Interestingly the homologues had different specificities for SUMO1 and SUMO2, with SM and UL69 preferentially binding SUMO1 and inducing SUMO1 modifications, and UL54 preferentially binding SUMO2 and inducing SUMO2 modifications. The results provide new insights into the function of this family of conserved herpesvirus proteins, and the conservation of this SUMO E3 ligase activity across diverse herpesviruses suggests the importance of this activity for herpesvirus infections.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".