Drosophila immune priming to Enterococcus faecalis relies on immune tolerance rather than resistance
Bibliographic record
Abstract
Abstract Most multicellular organisms, including fruit flies, possess an innate immune response, but lack an adaptive immune response. Even without adaptive immunity, “immune priming” allows organisms to survive a second infection more effectively after an initial, non-lethal infection. We used Drosophila melanogaster to study the transcriptional program that underlies priming. Using an insect-derived strain of Gram-positive Enterococcus faecalis , we found a low dose infection enhances survival of a subsequent high dose infection. The enhanced survival in primed animals does not correlate with a decreased bacterial load, implying that the organisms tolerate, rather than resist the infection. We measured the transcriptome associated with immune priming in the fly immune organs: the fat body and hemocytes. We found many genes that were only upregulated in re-infected flies. In contrast, there are very few genes that either remained transcriptionally active throughout the experiment or more efficiently re-activated upon reinfection. Measurements of priming in immune deficient mutants revealed IMD signaling is largely dispensable for responding to a single infection, but needed to fully prime; while Toll signaling is required to respond to a single infection, but dispensable for priming. Overall, we found a primed immune response to E. faecalis relies on immune tolerance rather than bacterial resistance and drives a unique transcriptional response.
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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 | 0.001 |
| 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".