Marine Mammal Microbiota Yields Novel Antibiotic with Potent Activity Against <i>Clostridium difficile</i>
Bibliographic record
Abstract
The recent explosion of research on the microbiota has highlighted the important interplay between commensal microorganisms and the health of their cognate hosts. Metabolites isolated from commensal bacteria have been demonstrated to possess a range of antimicrobial activities, and it is widely believed that some of these metabolites modulate host behavior, affecting predisposition to disease and pathogen invasion. Our access to the local marine mammal stranding network and previous successes in mining the fish microbiota poised us to test the hypothesis that the marine mammal microbiota is a novel source of commensal bacteria-produced bioactive metabolites. Examination of intestinal contents from five marine mammals led to the identification of a Micromonospora strain with potent and selective activity against a panel of Gram-positive pathogens and no discernible human cytotoxicity. Compound isolation afforded a new complex glycosylated polyketide, phocoenamicin, with potent activity against the intestinal pathogen Clostridium difficile, an organism challenging to treat in hospital settings. Use of our activity-profiling platform, BioMAP, clustered this metabolite with other known ionophore antibiotics. Fluorescence imaging and flow cytometry confirmed that phocoenamicin is capable of shifting membrane potential without damaging membrane integrity. Thus, exploration of gut microbiota in hosts from diverse environments can serve as a powerful strategy for the discovery of novel antibiotics against human pathogens.
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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".