Designing Probiotic Therapies With Broad-Spectrum Activity Against a Wildlife Pathogen
Bibliographic record
Abstract
Host-associated microbes form an important component of immunity that protect against infection by pathogens. Treating wild individuals with these protective microbes, known as probiotics, can reduce rates of infection and disease in both wild and captive settings. However, the utility of probiotics for tackling wildlife disease requires that they offer consistent protection across the broad genomic variation of the pathogen that hosts can encounter in natural settings. Here we develop multi-isolate probiotic consortia with the aim of effecting broad-spectrum inhibition of growth of the lethal amphibian pathogen Batrachochytrium dendrobatidis (Bd) when tested against nine Bd isolates from two distinct lineages. Though we achieved strong growth inhibition between 70-100% for seven Bd isolates, two isolates appeared consistently resistant to inhibition, irrespective of probiotic strategy employed. We found no evidence that genomic relatedness of the chytrid predicted similarity of inhibition scores, nor that increasing the genetic diversity of the bacterial consortia could offer stronger inhibition of pathogen growth, even for the two resistant isolates. Our findings have important consequences for the application of probiotics to mitigate wildlife diseases in the face of extensive pathogen genomic 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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".