Production of Glyoxylate from Glucose in Engineered Escherichia coli
Bibliographic record
Abstract
Glyoxylates are essential intermediates in several metabolic pathways and have a broad range of industrial applications. In this study, we propose a novel method for producing glyoxylate from glucose using engineered Escherichia coli BW25113. To direct the production of glyoxylate from glucose, malate synthase A (aceB), malate synthase G (glcB), glyoxylate carboligase (gcl), and glyoxylate/hydroxypyruvate reductase A (ycdW) genes were disrupted, and the glyoxylate shunt was reinforced in the disruptants by the overexpression of citrate synthase (gltA) and isocitrate lyase (aceA). In flask cultivation using M9 medium supplemented with 1% glucose, the disruptant E. coli BW25113 ΔaceB ΔglcB Δgcl ΔycdW produced 0.93 ± 0.17 g/L of glyoxylate. Further overexpression of gltA and aceA in the disruptant resulted in an improvement in glyoxylate production to 1.15 ± 0.02 g/L. By expressing a heterologous gene, pyc, in the engineered E. coli, the accumulation of intracellular oxaloacetate remarkably improved, leading to glyoxylate production of up to 2.42 ± 0.00 g/L with specific productivity at 4.22 ± 0.09 g/g-cell. To date, this is the highest reported titer and specific productivity of glyoxylate in E. coli.
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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) | 0.000 | 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 | 0.001 |
| 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 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".