2004
DOI: 10.1073/pnas.0306484101
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Design of artificial cell–cell communication using gene and metabolic networks

Abstract: Artificial transcriptional networks have been used to achieve novel, nonnative behavior in bacteria. Typically, these artificial circuits are isolated from cellular metabolism and are designed to function without intercellular communication. To attain concerted biological behavior in a population, synchronization through intercellular communication is highly desirable. Here we demonstrate the design and construction of a gene-metabolic circuit that uses a common metabolite to achieve tunable artificial cell-ce… Show more

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Cited by 152 publications
(92 citation statements)
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“…Previous efforts achieved such coordination by taking existing quorum sensing (QS) components from a source host, Vibrio fischeri, and integrating them into a target host, Escherichia coli (5,7,8). The work of Bulter et al (11) in this issue of PNAS describes a new form of engineering cell-cell communication based on manipulating metabolic pathways. Specifically, the authors engineered the nitrogen regulation system and the acetate pathway in E. coli.…”
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confidence: 99%
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“…Previous efforts achieved such coordination by taking existing quorum sensing (QS) components from a source host, Vibrio fischeri, and integrating them into a target host, Escherichia coli (5,7,8). The work of Bulter et al (11) in this issue of PNAS describes a new form of engineering cell-cell communication based on manipulating metabolic pathways. Specifically, the authors engineered the nitrogen regulation system and the acetate pathway in E. coli.…”
mentioning
confidence: 99%
“…Acetyl phosphate transfers its phosphate group to NR I , a transcriptional regulator of glnAp2 promoter (12). As a result, NR I ϳP dimerizes, binds the glnAp2 promoter at two enhancer regions, and activates transcription of GFP in the engineered system (11). Through the above processes, the cytoplasmic level of NR I ϳP reflects the extracellular acetate concentration, which in turn correlates to cell density.…”
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confidence: 99%
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