Inhibiting Neddylation with MLN4924 Suppresses Growth and Delays Multicellular Development in Dictyostelium discoideum
Bibliographic record
Abstract
Neddylation is a post-translational modification that is essential for a variety of cellular processes and is linked to many human diseases including cancer, neurodegeneration, and autoimmune disorders. Neddylation involves the conjugation of the ubiquitin-like modifier neural precursor cell expressed developmentally downregulated protein 8 (NEDD8) to target proteins, and has been studied extensively in various eukaryotes including fungi, plants, and metazoans. Here, we examine the biological processes influenced by neddylation in the social amoeba, Dictyostelium discoideum, using a well-established inhibitor of neddylation, MLN4924 (pevonedistat). NEDD8, and the target of MLN4924 inhibition, NEDD8-activating enzyme E1 (NAE1), are highly conserved in D. discoideum (Nedd8 and Nae1, respectively). Treatment of D. discoideum cells with MLN4924 increased the amount of free Nedd8, suggesting that MLN4924 inhibited neddylation. During growth, MLN4924 suppressed cell proliferation and folic acid-mediated chemotaxis. During multicellular development, MLN4924 inhibited cyclic adenosine monophosphate (cAMP)-mediated chemotaxis, delayed aggregation, and suppressed fruiting body formation. Together, these findings indicate that neddylation plays an important role in regulating cellular and developmental events during the D. discoideum life cycle and that this organism can be used as a model system to better understand the essential roles of neddylation in eukaryotes, and consequently, its involvement in human disease.
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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) | 0.000 | 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 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".