Engineering Hyperthermostable Nylonase, TvgC, to Improve Catalytic Efficiency for Degradation
Bibliographic record
Abstract
Nylons are too inert to be recycled in a cost-effective manner. The Howe Group’s recent discovery of TvgC, a hyperthermostable amidase with the capability to degrade nylon, hints at an exciting possibility: sustainable biocatalytic nylon recycling. While experiments showed that TvgC degraded nylon at rates even greater than those achieved by the most highly engineered enzymes, significant improvements are still required to improve the catalytic efficiency of TvgC such that the protein can enable biocatalytic recycling on an industrial scale. This proposal will develop the directed evolution pipeline to facilitate the production of TvgC variants with increased catalytic efficiencies. We have already identified a method to force E. coli cells to overexpress and secrete TvgC into the surrounding media. This project will use nylon-doped agar plates harbouring many E. coli colonies, with each expressing one member of a TvgC mutant library generated by error- prone PCR and site-saturation mutagenesis. State-of-the-art ambient ionization mass spectrometry techniques will then be used to analyze the nylon-doped surface in the vicinity of each colony. Cells expressing TvgC variants with higher activities will exhibit more nylon degradation, and these cells can be isolated, so that variants of interest can be identified and further analyzed. By developing this on-plate selection method, this proposal has the potential to enable biocatalytic nylon recycling and to transform how directed evolution campaigns are carried out.
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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 | 0.000 |
| 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".