Strain engineering for high‐level 5‐aminolevulinic acid production in <i>Escherichia coli</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Herein, we report the development of a microbial bioprocess for high‐level production of 5‐aminolevulinic acid (5‐ALA), a valuable non‐proteinogenic amino acid with multiple applications in medical, agricultural, and food industries, using Escherichia coli as a cell factory. We first implemented the Shemin (i.e., C4) pathway for heterologous 5‐ALA biosynthesis in E. coli . To reduce, but not to abolish, the carbon flux toward essential tetrapyrrole/porphyrin biosynthesis, we applied clustered regularly interspersed short palindromic repeats interference (CRISPRi) to repress hemB expression, leading to extracellular 5‐ALA accumulation. We then applied metabolic engineering strategies to direct more dissimilated carbon flux toward the key precursor of succinyl‐CoA for enhanced 5‐ALA biosynthesis. Using these engineered E. coli strains for bioreactor cultivation, we successfully demonstrated high‐level 5‐ALA biosynthesis from glycerol (~30 g L −1 ) under both microaerobic and aerobic conditions, achieving up to 5.95 g L −1 (36.9% of the theoretical maximum yield) and 6.93 g L −1 (50.9% of the theoretical maximum yield) 5‐ALA, respectively. This study represents one of the most effective bio‐based production of 5‐ALA from a structurally unrelated carbon to date, highlighting the importance of integrated strain engineering and bioprocessing strategies to enhance bio‐based production.
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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 | 0.000 | 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 | 0.000 | 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 it