Design and implementation of a transmitter-receiver genetic circuit
Bibliographic record
Abstract
Summary form only given. A prototype of a transmitter-receiver genetic circuit was designed and constructed. This design allows the transmission of signals between Gram-positive bacteria (Streptococcus mutans) and Gram-negative bacteria (Vibrio harveyi). AutoInducer-2 (AI-2) is used as the signaling molecule. For the transmitter circuit, we created a plasmid that contained a luxS gene (responsible for AI-2 synthesis) and an inducible promoter. This plasmid was inserted into S. mutans to form the transmitter cells. The transmitter activity can be modulated. Glucose lowers luxS gene expression, thus reducing AI-2 production. Raffinose activates the promoter, leading to an increase in AI-2 production. The receiver detects the signal produced by the transmitter. Vibrio harveyi BB170 was used as the receiver. This strain of bacteria lacks the gene to produce AI-2, but it has the receptor for AI-2 detection. When the bacteria detect AI-2, they produce luciferase, leading to light production. The circuit was tested by examining the luxS gene expression in the transmitter cells and the luminescence level of the receiver cells. First, the luxS gene expression of the transmitter was investigated. The transmitter cells were cultured with a supplement of either glucose (i.e. transmitter "off") or raffinose ("on") until they reached mid-log phase. The luxS expression levels in the activated cells were 10-fold higher than those in the repressed cells. The impact of different sugars (glucose and raffinose) on cell growth was examined. The measured doubling time for the cells in each of raffinose and glucose was 63.76plusmn0.30 and 67.59plusmn0.34 minutes, respectively. The similarity of the doubling times suggested that the sugars had no effect on normal cell growth. The behaviour of the receiver was then investigated. The receiver cells were exposed to the supernatant of the transmitter cells to test their AI-2 detection capability. The supernatant of mid-log phase transmitter cells was collected by removing the cells through centrifugation followed by filtration. The luminescence level of the receivers was measured hourly for five hours. A five-fold luminescence signal increase was observed after four hours of incubation with the supernatant. The underlying mechanism of this delay in the receiver response time is unclear. A computational approach was used to investigate the cause of the delay. A stochastic model of the receiver cells was developed based on Gillespie's algorithm. Our simulation yielded a receiver response time of just less than two hours. This is the first study on synthetic interspecies communication. The ability to communicate between species will be a valuable tool for the creation of larger engineered systems
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".