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A Formalized Design Process for Bacterial Consortia That Perform Logic Computing

Overview of attention for article published in PLOS ONE, February 2013
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Title
A Formalized Design Process for Bacterial Consortia That Perform Logic Computing
Published in
PLOS ONE, February 2013
DOI 10.1371/journal.pone.0057482
Pubmed ID
Authors

Weiyue Ji, Handuo Shi, Haoqian Zhang, Rui Sun, Jingyi Xi, Dingqiao Wen, Jingchen Feng, Yiwei Chen, Xiao Qin, Yanrong Ma, Wenhan Luo, Linna Deng, Hanchi Lin, Ruofan Yu, Qi Ouyang

Abstract

The concept of microbial consortia is of great attractiveness in synthetic biology. Despite of all its benefits, however, there are still problems remaining for large-scaled multicellular gene circuits, for example, how to reliably design and distribute the circuits in microbial consortia with limited number of well-behaved genetic modules and wiring quorum-sensing molecules. To manage such problem, here we propose a formalized design process: (i) determine the basic logic units (AND, OR and NOT gates) based on mathematical and biological considerations; (ii) establish rules to search and distribute simplest logic design; (iii) assemble assigned basic logic units in each logic operating cell; and (iv) fine-tune the circuiting interface between logic operators. We in silico analyzed gene circuits with inputs ranging from two to four, comparing our method with the pre-existing ones. Results showed that this formalized design process is more feasible concerning numbers of cells required. Furthermore, as a proof of principle, an Escherichia coli consortium that performs XOR function, a typical complex computing operation, was designed. The construction and characterization of logic operators is independent of "wiring" and provides predictive information for fine-tuning. This formalized design process provides guidance for the design of microbial consortia that perform distributed biological computation.

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Geographical breakdown

Country Count As %
United States 3 4%
Colombia 1 1%
Austria 1 1%
Belgium 1 1%
United Kingdom 1 1%
Spain 1 1%
China 1 1%
Unknown 74 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 30%
Researcher 16 19%
Student > Bachelor 13 16%
Student > Master 12 14%
Student > Doctoral Student 4 5%
Other 7 8%
Unknown 6 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 49%
Biochemistry, Genetics and Molecular Biology 13 16%
Engineering 11 13%
Computer Science 6 7%
Immunology and Microbiology 2 2%
Other 3 4%
Unknown 7 8%