MétaCan
Menu
Back to cohort
Record W2543987543 · doi:10.1109/bmn.2006.330882

Design and implementation of a transmitter-receiver genetic circuit

2006· article· en· W2543987543 on OpenAlexaff
YL Yip, Céline M. Lévesque, Dennis G. Cvitkovitch, Stella M. Davies

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVibrio harveyiTransmitterRaffinosePlasmidBiologyMicrobiologyMolecular biologyCell biologyVibrioGeneBacteriaBiochemistryGeneticsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

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

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.012
GPT teacher head0.269
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicbioluminescence and chemiluminescence researchFrench-language works237,207