The fly factor phenomenon is mediated by interkingdom signaling between bacterial symbionts and their blow fly hosts
Bibliographic record
Abstract
We tested the recent hypothesis that the "fly factor" phenomenon (food currently or previously fed on by flies attracts more flies than the same type of food kept inaccessible to flies) is mediated by bacterial symbionts deposited with feces or regurgitated by feeding flies. We allowed laboratory-reared black blow flies, Phormia regina (Meigen), to feed and defecate on bacterial Luria-Bertani medium solidified with agar, and isolated seven morphologically distinct bacterial colonies. We identified these using matrix-assisted laser desorption/ionization mass spectrometry and sequencing of the 16S rRNA gene. In two-choice laboratory experiments, traps baited with cultures of Proteus mirabilis Hauser, Morganella morganii subsp. sibonii Jensen, or Serratia marcescens Bizio, captured significantly more flies than corresponding control jars baited with tryptic soy agar only. A mixture of seven bacterial strains as a trap bait was more attractive to flies than a single bacterial isolate (M. m. sibonii). In a field experiment, traps baited with agar cultures of P. mirabilis and M. m. sibonii in combination captured significantly more flies than traps baited with either bacterial isolate alone or the agar control. As evident by gas chromatography-mass spectrometry, the odor profiles of bacterial isolates differ, which may explain the additive effect of bacteria to the attractiveness of bacterial trap baits. As "generalist bacteria," P. mirabilis and M. m. sibonii growing on animal protein (beef liver) or plant protein (tofu) are similarly effective in attracting flies. Bacteria-derived airborne semiochemicals appear to mediate foraging by flies and to inform their feeding and oviposition decisions.
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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) | 0.001 | 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".