Strain engineering and bioprocessing strategies for biobased production of porphobilinogen in Escherichia coli
Bibliographic record
Abstract
Abstract Strain engineering and bioprocessing strategies were applied for biobased production of porphobilinogen (PBG) using Escherichia coli as the cell factory. The non-native Shemin/C4 pathway was first implemented by heterologous expression of hemA from Rhodopseudomonas spheroids to supply carbon flux from the natural tricarboxylic acid (TCA) pathways for PBG biosynthesis via succinyl-CoA. Metabolic strategies were then applied for carbon flux direction from the TCA pathways to the C4 pathway. To promote PBG stability and accumulation, Clustered Regularly Interspersed Short Palindromic Repeats interference (CRISPRi) was applied to repress hemC expression and, therefore, reduce carbon flowthrough toward porphyrin biosynthesis with minimal impact to cell physiology. To further enhance PBG biosynthesis and accumulation under the hemC-repressed genetic background, we further heterologously expressed native E. coli hemB. Using these engineered E. coli strains for bioreactor cultivation based on ~ 30 g L−1 glycerol, we achieved high PBG titers up to 209 mg L−1, representing 1.73% of the theoretical PBG yield, with improved PBG stability and accumulation. Potential biochemical, genetic, and metabolic factors limiting PBG production were systematically identified for characterization. Graphical Abstract
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".