Social attraction mediated by fruit flies' microbiome
Bibliographic record
Abstract
Larval and adult fruit flies are attracted to volatiles emanating from food substrates that have been occupied by larvae. We tested whether such volatiles are emitted by the larval gut bacteria by conducting tests under bacteria-free (axenic) conditions. We also tested attraction to two bacteria species, Lactobacillus brevis, which we cultured from larvae in our lab, and L. plantarum, a common constituent of fruit flies' microbiome in other laboratory populations and in wild fruit flies. Neither larvae nor adults showed attraction to axenic food that had been occupied by axenic larvae, but both showed the previously reported attraction to standard food that had been occupied by larvae with an intact microbiome. Larvae also showed significant attraction to volatiles from axenic food and larvae to which we added only either L. brevis or L. plantarum, and volatiles from L. brevis reared on its optimal growth medium. Controlled learning experiments indicated that larvae experienced with both standard and axenic used food do not perceive either as superior, while focal larvae experienced with simulated used food, which contains burrows, perceive it as superior to unused food. Our results suggest that flies rely on microbiome-derived volatiles for long-distance attraction to suitable food patches. Under natural settings, fruits often contain harmful fungi and bacteria, and both L. brevis and L. plantarum produce compounds that suppress the growth of some antagonistic fungi and bacteria. The larval microbiome volatiles may therefore lead prospective fruit flies towards substrates with a hospitable microbial environment.
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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) | 0.002 | 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".