Microbial photoproduction of n-heptane
Bibliographic record
Abstract
The photoenzyme fatty acid photodecarboxylase (FAP) has emerged as a promising catalyst for the redox-neutral biological production of hydrocarbons. Previous studies have shown that FAP can efficiently convert medium-chain fatty acids such as n-octanoic acid into hydrocarbons, outperforming its natural long-chain fatty acid substrates (C16-C18). Such observation expands the potential applications of FAP to include solvents and jet fuels. However, the limited availability of natural sources of n-octanoic acid poses a challenge to the industrial implementation of n-heptane bioproduction. This study investigates the hydrocarbon synthesis capacity of an E. coli strain that expresses FAP and produces n-octanoic acid, the precursor to n-heptane, via a specific octanoyl-ACP thioesterase. Several FAPs and thioesterases were tested. A blue light-inducible promoter ensured high expression of both enzymes, eliminating the need for chemical inducers. Fusion of FAP with thioredoxin increased n-heptane production 12-fold. Using a co-cultivation strategy, where one strain produces n-octanoic acid and another strain converts it to n-heptane, increased hydrocarbon production 14-fold compared to co-expressing FAP and thioesterase. Co-cultures operated in batch mode in 100-mL photobioreactors enabled the recovery of >90%-pure n-heptane, yielding 272 mg·L-1 over 56 h. This work lays the foundation for the development of an industrial bioproduction of n-heptane.
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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) | 0.000 | 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 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".