Cell factories and transcription factor engineering for bioproducts: the case of Candida glabrata for α-ketoglutarate production
Bibliographic record
Abstract
α-Ketoglutarate, a key intermediate in the TCA cycle, is crucial for amino acid synthesis and nitrogen transport. However, microbial engineering for α-ketoglutarate production is hindered by the intrinsic inefficiency of the metabolic network. In this study, transcription factor engineering was performed for the reconstruction of the metabolic network to boost α-ketoglutarate biosynthesis in Candida glabrata. Transcription factors GCR2 and RTG1 were first reinstalled to kick-start the glycolytic pathway and the TCA cycle, respectively, and then optimized to redistribute carbon flux between the two pathways. In addition, pyruvate carriers, MPC1 and MPC2, were introduced to facilitate the transport of cytoplasmic pyruvate to mitochondria, thereby feeding it into the TCA cycle for α-ketoglutarate biosynthesis. Next, transcription factor HAP4 was utilized to rewire the electron transport chain for improving redox balance and reducing overflow metabolism, thereby channeling more carbon flux to α-ketoglutarate production. Finally, the engineered strain C. glabrata KGA17 was capable of producing 210.4 g/L α-ketoglutarate in a 5-L bioreactor. This approach showed significant promise for developing efficient microbial cell factories for high-value chemical production.
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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 | 0.001 | 0.001 |
| 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".