Rapid evolution of a novel protective symbiont into keystone taxon in Caenorhabditis elegans microbiota
Bibliographic record
Abstract
Protective microbes have a major role in shaping host-pathogen interactions, but their relative importance in the structure of the host microbiota remains unclear. Here, we used a network approach to characterize the impact of a novel, experimentally evolved 'protective microbial symbiont' (Enterococcus faecalis) on the structure and predicted function of the natural microbiota of the model organism Caenorhabditis elegans. We used microbial network analysis to identify keystone taxa and describe the hierarchical placement of protective and non-protective symbionts in the microbiota. We found that early colonization with symbionts produce statistically significant changes in the structure of the community. Notably, only the protective E. faecalis became a keystone taxon in the nematode microbiota. Non-protective lineages of the same bacterial species remained comparatively unimportant to the community. Prediction of functional profiles in bacterial communities using PICRUSt2 showed that the presence of highly protective E. faecalis decreased the abundance of ergothioneine (EGT) biosynthesis pathway involved in the synthesis of the antioxidant molecule EGT, a potential public good. These data show that in addition to direct antagonism with virulent pathogens, keystone protective symbionts are linked to modified bacterial community structure and possible reductions in public goods, potentially driving decreased antioxidant defense. We suggest that this response could suppress infection via wholesale microbial community changes to further benefit the host. These findings extend the concept of protective symbionts beyond bodyguards to ecosystem engineers.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".