Biofilm Formation and Detachment in Gram-Negative Pathogens Is Modulated by Select Bile Acids
Bibliographic record
Abstract
Biofilms are a ubiquitous feature of microbial community structure in both natural and host environments; they enhance transmission and infectivity of pathogens and provide protection from human defense mechanisms and antibiotics. However, few natural products are known that impact biofilm formation or persistence for either environmental or pathogenic bacteria. Using the combination of a novel natural products library from the fish microbiome and an image-based screen for biofilm inhibition, we describe the identification of taurine-conjugated bile acids as inhibitors of biofilm formation against both Vibrio cholerae and Pseudomonas aeruginosa. Taurocholic acid (1) was isolated from the fermentation broth of the fish microbiome-derived strain of Rhodococcus erythropolis and identified using standard NMR and MS methods. Screening of the twelve predominant human steroidal bile acid components revealed that a subset of these compounds can inhibit biofilm formation, induce detachment of preformed biofilms under static conditions, and that these compounds display distinct structure-activity relationships against V. cholerae and P. aeruginosa. Our findings highlight the significance of distinct bile acid components in the regulation of biofilm formation and dispersion in two different clinically relevant bacterial pathogens, and suggest that the bile acids, which are endogenous mammalian metabolites used to solubilize dietary fats, may also play a role in maintaining host health against bacterial infection.
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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) | 0.000 | 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".