A Screening Assay for Bile Acid-Transforming Microorganisms Using Engineered Bacterial Biosensors
Bibliographic record
Abstract
Bile salt hydrolase (BSH) enables microbial-mediated deconjugation of bile acids (BAs) in the gastrointestinal tract. BSH enzymes initiate bile acid metabolism by catalyzing the first, essential deconjugation step. Due to the strict connection between dysregulations of the BA pool and human or animal diseases, identification and characterization of strains with BSH activity are relevant for both healthcare and agroindustry. However, current methods are expensive, poorly sensitive, or require complex procedures. Here, a BSH screening assay for cultivated microbes is proposed, based on a bacterial biosensor that reports the concentration of different BA types via fluorescence. Although the biosensor is broadly responsive to various bile acids, the assay was designed to guarantee specificity by testing individual primary BAs within controlled concentration ranges. The assay was evaluated on two recombinant Escherichia coli strains bearing BSH genes from Lactobacillus johnsonii PF01 and a BSH-positive probiotic strain (Lactobacillus rhamnosus GG). Data showed a consistent activity pattern with previous assays on these enzymes. A crucial aspect addressed was the matrix effect, i.e., the impact of the growth media of the BSH-containing strains on biosensor output. This assay is expected to be a reproducible and accessible option, compatible with automated protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".