A Potential Collective Defense of Drosophila Larvae Against the Invasion of a Harmful Fungus
Bibliographic record
Abstract
The establishment of a collective defence is an important means of controlling the spread of harmful microbes in group-living animals. Collective defences are associated with costs resulting from the investment in resources and risk taking of infections or exposure to microbial toxins for the performing individual and are often assumed to have evolved in (eu)social insects, like bees and ants, as a result of close contact and pathogen transmission between nest mates. We hypothesise that collective antimicrobial defence mechanisms are potentially also found in insects that exhibit simpler forms of sociality or even mere aggregation behaviour. Larvae of the saprophagous fruit fly Drosophila melanogaster develop in high-density aggregations on rotting fruits, which are often colonized by insecticidal filamentous fungi. Here we show that fruit fly larvae suppress the invasion of a harmful fungus not only by the summative effect of individuals at high densities, but also that larger groups of larvae at the same density can control fungal growth more efficiently. We achieved the necessary manipulation of the group size by increasing the number of larvae in proportion to an increase in habitat size, thereby excluding the effect of density changes on fungal growth as a confounding factor. We found evidence that part of the variation in the ability to suppress the fungus in this group size dependent manner can be explained by genetic variation at the insects’ foraging locus (for). Group size therefore influences the extent to which the larval aggregates suppress the spread of a harmful fungus. This indicates a potential collective defence against habitat invasion by pathogenic fungi. Selection pressure on the efficiency of this potential defence strategy may contribute to the evolution of aggregation behaviour in non-(eu)social insects.
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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".