A Synthetic Genetic Edge Detection Program

By Jeffrey J. Tabor, Howard M. Salis, Zachary Booth Simpson, Aaron Chevalier, Anselm Levskaya, Edward M. Marcotte, Christopher A. Voigt, A. Ellington. Cell, 2009

490 citations recorded by the source corpus.

Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d7d7d673ecc41bf87ec773f5698d548359b51569

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Citations in the corpus

Stem Cell Organoid Engineering (2016, unknown): “(Tabor et al., 2009), an achievement that can potentially one day be incorporated in organoid systems to direct cellular organization.”
Biomolecular computing systems: principles, progress and potential (2012, methodology): “Studies have shown that signalling processes such as mating and osmolarity pathways in yeast 94 and two-component signalling in bacteria 89,95 can be rewired.”
Synthetic biology: applications come of age (2010, methodology): “Using a synthetic hybrid approach, Voigt and colleague”
Automated Design of Synthetic Ribosome Binding Sites to Precisely Control Protein Expression (2009, background): “Generation and selection of a sequence library can become impractical as the number of participating proteins increases, especially if measuring the function requires a low-throughput assay or screen 6.”
The ribosome binding site calculator. (2011, background): “Genetic circuits have been engineered to exhibit bistability, oscillations, pattern formation, traveling waves, and Boolean logic (Danino et al., 2010; Ellis et al., 2009; Khalil and Collins, 2010; Lu et al., 2009; Purnick and Weiss, 2009; Stricker et al., 2008; Tabor et al., 2009).”