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Cited by 397

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

A sensing array of radically coupled genetic ‘biopixels’

Open access
Prindle, Arthur, Samayoa, Phillip, Razinkov, Ivan, Danino, Tal, Tsimring, Lev S., Hasty, Jeff·2012·Nature

Abstract

Although there has been considerable progress in the development of engineering principles for synthetic biology, a substantial challenge is the construction of robust circuits in a noisy cellular environment. Such an environment leads to considerable intercellular variability in circuit behaviour, which can hinder functionality at the colony level. Here we engineer the synchronization of thousands of oscillating colony ‘biopixels’ over centimetre-length scales through the use of synergistic intercellular coupling involving quorum sensing within a colony and gas-phase redox signalling between colonies. We use this platform to construct a liquid crystal display (LCD)-like macroscopic clock that can be used to sense arsenic via modulation of the oscillatory period. Given the repertoire of sensing capabilities of bacteria such as Escherichia coli, the ability to coordinate their behaviour over large length scales sets the stage for the construction of low cost genetic biosensors that are capable of detecting heavy metals and pathogens in the field.

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Crossref · 10.1038/nature10722

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Metadata

Authors
Prindle, A., Samayoa, P., Razinkov, I., Danino, T., Tsimring, L. S., & Hasty, J.
Venue
Nature
Published
2011-12-18
Volume
481
Issue
7379
Pages
39-44
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2141564052
Cited by
397
References
4
FWCI
11.52
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A sensing array of radically coupled genetic ‘biopixels’. https://app.cochat.ai/papers/10.1038/nature10722
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Prindle, A., Samayoa, P., Razinkov, I., Danino, T., Tsimring, L. S., & Hasty, J. (2012). A sensing array of radically coupled genetic ‘biopixels’. Nature. https://doi.org/10.1038/nature10722

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.