Gut flora odours attract <i>Drosophila</i> to best squidgy fruit
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Humans aren't the only animals that like to hang out; birds and sheep flock, cattle herd and even Drosophila enjoy swarming around a juicy piece of fruit. Reuven Dukas and colleagues from McMaster University, Canada, explain that fruit flies are particularly partial to fruit that is already infested with larvae. However, Dukas and his team had already shown that the odour that attracts the flies to feast was not produced by the fruit, the yeast residing on it, or fly and larval waste. Could bacteria associated with the flies and their larvae be responsible for the irresistible scent? Dukas and his colleagues, Isvarya Venu, Zachary Durisko and Jianping Xu, began investigating the source of the tantalising aroma (p. 1346).First, the team tested the allure of fruit infested with normal larvae (complete with their usual gut flora) and sterilised larvae for larvae and adult flies. They found that both the adults and larvae found the infested fruit most attractive when the resident larvae retained their usual gut flora, so the bacteria were responsible for the attractive odour. Next, the team investigated the larvae to discover which bacterium produced the essential scent by isolating the gut flora, which they identified as Lactobacillus brevis. And when the team tested the effect of odours produced by another bacterium – Lactobacillus plantarum, which is also harboured in the insect's intestines – on foraging larvae, they confirmed that the odours were as attractive as the odours produced by larvae that had normal gut flora. Finally, the team offered L. brevis to the fly larvae on several different food sources and found that the odours produced by the isolated bacteria were sufficient to attract the larvae.Having confirmed that Drosophila larvae are attracted by odours produced by gut bacteria, the team was curious to find out how the insects benefit from being lured to areas that the flies have already infested. However, when the team tested the larvae's preferences for food that had previously been occupied either by larvae that produced the attractive odours or by larvae that did not, they were surprised to find that the larvae didn't seem particularly attracted to fruit that had been infested with larvae producing an odour. ‘That led us to search for another factor that may lead to larval preference for used over fresh food’, says Dukas. So the team tested the larvae's preferences for food that had been churned up by burrowing larvae and food that they had poked with needles to simulate a larval infestation. This time they found that compared with intact fresh food, the larvae were much keener on the food that had already been used.So fruit fly larvae use the odours produced by the gut flora of other larvae to direct them to the best squidgy fruit. The team also suggests that a patch of food infested with hoards of munching larvae is the best recommendation of a meal's quality and point out that the insect gut flora suppress harmful microbes in the vicinity, encouraging the proliferation of microbes that are beneficial to the larvae at the expense of unsafe species, making it favourable for foraging fruit fly larvae to congregate rather than go it alone.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it