Optogenetic Control of Heterologous Metabolism in <i>E. 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
Multiobjective optimization of microbial chassis for the production of xenobiotic compounds requires the implementation of metabolic control strategies that permit dynamic distribution of cellular resources between biomass and product formation. We addressed this need in a previous study by engineering the T7 RNA polymerase to be thermally responsive. The modified polymerase is activated only after the temperature of the host cell falls below 18 °C, and Escherichia coli cells that employ the protein to transcribe the heterologous lycopene biosynthetic pathway exhibit impressive improvements in productivity. We have expanded our toolbox of metabolic switches in the current study by engineering a version of the T7 RNA polymerase that drives the transition between biomass and product formation upon stimulation with red light. The engineered polymerase is expressed as two distinct polypeptide chains. Each chain comprises one of two photoactive components from Arabidopsis thaliana, phytochrome B (PhyB) and phytochrome-integrating factor 3 (PIF3), as well as the N- or C-terminus domains of both, the vacuolar ATPase subunit (VMA) intein of Saccharomyces cerevisiae and the polymerase. Red light drives photodimerization of PhyB and PIF3, which then brings together the N- and C-terminus domains of the VMA intein. Trans-splicing of the intein follows suit and produces an active form of the polymerase that subsequently transcribes any sequence that is under the control of a T7 promoter. The photodimerization also involves a third element, the cyanobacterial chromophore phycocyanobilin (PCB), which too is expressed heterologously by E. coli. We deployed this version of the T7 RNA polymerase to control the production of lycopene in E. coli and observed tight control of pathway expression. We tested a variety of expression configurations to identify one that imposes the lowest metabolic burden on the strain, and we subsequently optimized key parameters such as the source, moment, and duration of photostimulation. We also identified targets for future refinement of the circuit. In summary, our work is a significant advance for the field and greatly expands on previous work by other groups that have used optogenetic circuits to control heterologous metabolism in prokaryotic hosts.
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.
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