A Quantitative RNAi Screen for JNK Modifiers Identifies Pvr as a Novel Regulator of Drosophila Immune Signaling
Bibliographic record
Abstract
Drosophila melanogaster responds to gram-negative bacterial challenges through the IMD pathway, a signal transduction cassette that is driven by the coordinated activities of JNK, NF-kappaB and caspase modules. While many modifiers of NF-kappaB activity were identified in cell culture and in vivo assays, the regulatory apparatus that determines JNK inputs into the IMD pathway is relatively unexplored. In this manuscript, we present the first quantitative screen of the entire genome of Drosophila for novel regulators of JNK activity in the IMD pathway. We identified a large number of gene products that negatively or positively impact on JNK activation in the IMD pathway. In particular, we identified the Pvr receptor tyrosine kinase as a potent inhibitor of JNK activation. In a series of in vivo and cell culture assays, we demonstrated that activation of the IMD pathway drives JNK-dependent expression of the Pvr ligands, Pvf2 and Pvf3, which in turn act through the Pvr/ERK MAP kinase pathway to attenuate the JNK and NF-kappaB arms of the IMD pathway. Our data illuminate a poorly understood arm of a critical and evolutionarily conserved innate immune response. Furthermore, given the pleiotropic involvement of JNK in eukaryotic cell biology, we believe that many of the novel regulators identified in this screen are of interest beyond immune signaling.
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 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) | 0.001 | 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".