Temperate phages as self-replicating weapons in bacterial competition
Bibliographic record
Abstract
Microbial communities are accompanied by a diverse array of viruses. Through infections of abundant microbes, these viruses have the potential to mediate competition within the community, effectively weakening competitive interactions and promoting coexistence. This is of particular relevance for host-associated microbial communities, because the diversity of the microbiota has been linked to host health and functioning. Here, we study the interaction between two key members of the microbiota of the freshwater metazoan Hydra vulgaris . The two commensal bacteria Curvibacter sp. and Duganella sp. protect their host from fungal infections, but only if both of them are present. Coexistence of the two bacteria is thus beneficial for Hydra . Intriguingly, Duganella sp. appears to be the superior competitor in vitro due to its higher growth rate when both bacteria are grown separately, but in co-culture the outcome of competition depends on the relative initial abundances of the two species. The presence of an inducible prophage in the Curvibacter sp. genome, which is able to lytically infect Duganella sp., led us to hypothesize that the phage modulates the interaction between these two key members of the Hydra microbiota. Using a mathematical model, we show that the interplay of the lysogenic life cycle of the Curvibacter phage and the lytic life cycle on Duganella sp. can explain the observed complex competitive interaction between the two bacteria. Our results highlight the importance of taking lysogeny into account for understanding microbe–virus interactions and show the complex role phages can play in promoting coexistence of their bacterial hosts.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".