Two-Step Bio-Based Production of Heme: In Vivo Cell Cultivation Followed by In Vitro Enzymatic Conversion
Bibliographic record
Abstract
Heme is a chemical compound crucial for various biological processes and industrial applications. However, the microbial production of heme is often limited by its intracellular accumulation and associated toxicity. To address this, we employed a two-step approach involving in vivo cell cultivation for the production of a heme precursor (coproporphyrin III or coproheme) followed by its in vitro conversion(s) to heme. For the first step, we engineered Escherichia coli strains by implementing the coproporphyrin-dependent (CPD) pathway for bacterial cell cultivation, extracellularly producing up to 251 mg/L coproporphyrin III and 85 mg/L coproheme, respectively. For the second step, we cloned the hemH and hemQ genes for expression in E. coli, and the expressed gene products, i.e., coproheme decarboxylase (ChdC/HemH) and heme synthase (HemQ), were purified. Using the purified enzymes with modulated reaction conditions, we achieved up to a 77.2% yield to convert coproporphyrin III to coproheme and a 45.8% yield to convert coproheme to heme. This in vitro approach not only bypassed the intracellular toxicity constraint associated with in vivo cell cultivation but also enabled precise reaction control, leading to a higher efficiency and yield for heme (and coproheme) production. By applying novel strategies in strain engineering and bioprocessing to overcome inherent bioprocess challenges, this study paves the way for industrial biotechnology for the sustainable, efficient, and even large-scale bio-based production of heme.
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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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".