Engineered poplar for bioproduction of the triterpene squalene
Bibliographic record
Abstract
Building sustainable platforms to produce biofuels and specialty chemicals has become an increasingly important strategy to supplement and replace fossil fuels and petrochemical-derived products. Terpenoids are the most diverse class of natural products that have many commercial roles as specialty chemicals. Poplar is a fast growing, biomassdense bioenergy crop with many species known to produce large amounts of the hemiterpene isoprene, suggesting an inherent capacity to produce significant quantities of other terpenes. Here we aimed to engineer poplar with optimized pathways to produce squalene, a triterpene commonly used in cosmetic oils, a potential biofuel candidate, and the precursor to the further diversified classes of triterpenoids and sterols. The squalene production pathways were either re-targeted from the cytosol to plastids or co-produced with lipid droplets in the cytosol. Squalene and lipid droplet co-production appeared to be toxic, which we hypothesize to be due to disruption of adventitious root formation, suggesting a need for tissue specific production. Plastidial squalene production enabled up to 0.63 mg/g fresh weight in leaf tissue, which also resulted in reductions in isoprene emission and photosynthesis. These results were also studied through a technoeconomic analysis, providing further insight into developing poplar as a production host.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".