Defense Heterogeneity in Host Populations Gives Rise to Pathogen Diversity
Bibliographic record
Abstract
Host organisms can harbor microbial symbionts that defend them from pathogen infection in addition to the resistance encoded by the host genome. Here, we investigated how variation in defenses, generated from host genetic background and symbiont presence, affects the emergence of pathogen genetic diversity across evolutionary time. We passaged the opportunistic pathogen Pseudomonas aeruginosa through populations of the nematode Caenorhabditis elegans varying in genetic-based defenses and prevalence of a protective symbiont. After 14 passages, we assessed the amount of genetic variation accumulated in evolved pathogen lineages. We found that diversity begets diversity. An overall greater level of pathogen whole-genome and per-gene genetic diversity was measured in pathogens evolved in mixed host populations compared with those evolved in host populations composed of one type of defense. Our findings directly demonstrate that symbiont-generated heterogeneity in host defense can be a significant contributor to pathogen genetic variation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".