Minimal genetic device with multiple tunable functions
Bibliographic record
Abstract
The ability to design artificial genetic devices with predictable functions is critical to the development of synthetic biology. Given the highly variable requirements of biological designs, the ability to tune the behavior of a genetic device is also of key importance; such tuning will allow devices to be matched with other components into larger systems, and to be shifted into the correct parameter regimes to elicit desired behaviors. Here, we have developed a minimal synthetic genetic system that acts as a multifunction, tunable biodevice in the bacterium Escherichia coli. First, it acts as a biochemical AND gate, sensing the extracellular small molecules isopropyl β-D -1-thiogalactopyranoside and anhydrotetracycline as two input signals and expressing enhanced green fluorescent protein as an output signal. Next, the output signal of the AND gate can be amplified by the application of another extracellular chemical, arabinose. Further, the system can generate a wide range of chemically tunable single input-output response curves, without any genetic alteration of the circuit, by varying the concentrations of a set of extracellular small molecules. We have developed and parameterized a simple transfer function model for the system, and shown that the model successfully explains and predicts the quantitative relationships between input and output signals in the system.
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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".