An Improved Whole-Cell Biosensor for the Discovery of Lignin-Transforming Enzymes in Functional Metagenomic Screens
Why this work is in the frame
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Bibliographic record
Abstract
The discovery and utilization of biocatalysts that selectively valorize lignocellulose is critical to the profitability of next-generation biorefineries. Here, we report the development of a refactored, whole-cell, GFP-based biosensor for high-throughput identification of biocatalysts that transform lignin into specialty chemicals from environmental DNA of uncultivable archaea and bacteria. The biosensor comprises the transcriptional regulator and promoter of the emrRAB operon of E. coli, and the configuration of the biosensor was tuned with the aid of mathematical model. The biosensor sensitively and selectively detects vanillin and syringaldehyde, and responds linearly over a wide detection range. We employed the biosensor to screen 42 520 fosmid clones comprising environmental DNA isolated from two coal beds and successfully identified 147 clones that transform hardwood kraft lignin to vanillin and syringaldehyde.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 it