Development of an industrial yeast strain for efficient production of 2,3-butanediol
Bibliographic record
Abstract
As part of the transition from a fossil resources-based economy to a bio-based economy, the production of platform chemicals by microbial cell factories has gained strong interest. 2,3-butanediol (2,3-BDO) has various industrial applications, but its production by microbial fermentation poses multiple challenges. We have engineered the bacterial 2,3-BDO synthesis pathway, composed of AlsS, AlsD and BdhA, in a pdc-negative version of an industrial Saccharomyces cerevisiae yeast strain. The high concentration of glycerol caused by the excess NADH produced in the pathway from glucose to 2,3-BDO was eliminated by overexpression of NoxE and also in a novel way by combined overexpression of NDE1, encoding mitochondrial external NADH dehydrogenase, and AOX1, encoding a heterologous alternative oxidase expressed inside the mitochondria. This was combined with strong downregulation of GPD1 and deletion of GPD2, to minimize glycerol production while maintaining osmotolerance. The HGS50 strain produced a 2,3-BDO titer of 121.04 g/L from 250 g/L glucose, the highest ever reported in batch fermentation, with a productivity of 1.57 g/L.h (0.08 g/L.h per gCDW) and a yield of 0.48 g/g glucose or with 96% the closest to the maximum theoretical yield ever reported. Expression of Lactococcus lactis NoxE, encoding a water-forming NADH oxidase, combined with similar genetic modifications, as well as expression of Candida albicans STL1, also minimized glycerol production while maintaining high osmotolerance. The HGS37 strain produced 130.64 g/L 2,3-BDO from 280 g/L glucose, with productivity of 1.58 g/L.h (0.11 g/L.h per gCDW). Both strains reach combined performance criteria adequate for industrial implementation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".