Establishing Vibrio natriegens as a high-performance host for acetate-based poly-3-hydroxybutyrate production
Bibliographic record
Abstract
Acetate can be a sustainable and renewable carbon source that holds significant promise for biotechnological production but is underutilized industrially due to limited microbial efficiency. Vibrio natriegens, recognized for exceptionally fast growth rates, represents a compelling host for developing efficient acetate-based bioprocesses. In this study, adaptive laboratory evolution significantly enhanced V. natriegens' ability to grow on acetate as the sole carbon source, achieving an 89 % increase in growth rate. Genetic and transcriptomic analyses revealed key adaptations improving acetate uptake and metabolism via increased salt tolerance, boosted Pta/AckA pathway activity, and rewired quorum sensing. Further metabolic engineering and bioprocess optimization enabled the evolved strain to reach high cell densities and efficiently convert acetate into the bioplastic poly-3-hydroxybutyrate (PHB), with productivities up to 0.27 g/L/h and PHB accumulation reaching 45.66 % of cell biomass. These advances position V. natriegens as a highly promising microbial platform for sustainable, scalable, and cost-effective biomanufacturing using acetate as a green feedstock.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".