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Journal article

High-Performance Biocomputing in Synthetic Biology-Integrated Transcriptional and Metabolic Circuits

From

Newcastle University1

Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark2

Research Groups, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark3

Systems Environmental Microbiology, Research Groups, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark4

Biocomputing uses molecular biology parts as the hardware to implement computational devices. By following pre-defined rules, often hard-coded into biological systems, these devices are able to process inputs and return outputs-thus computing information. Key to the success of any biocomputing endeavor is the availability of a wealth of molecular tools and biological motifs from which functional devices can be assembled.

Synthetic biology is a fabulous playground for such purpose, offering numerous genetic parts that allow for the rational engineering of genetic circuits that mimic the behavior of electronic functions, such as logic gates. A grand challenge, as far as biocomputing is concerned, is to expand the molecular hardware available beyond the realm of genetic parts by tapping into the host metabolism.

This objective requires the formalization of the interplay of genetic constructs with the rest of the cellular machinery. Furthermore, the field of metabolic engineering has had little intersection with biocomputing thus far, which has led to a lack of definition of metabolic dynamics as computing basics.

In this perspective article, we advocate the conceptualization of metabolism and its motifs as the way forward to achieve whole-cell biocomputations. The design of merged transcriptional and metabolic circuits will not only increase the amount and type of information being processed by a synthetic construct, but will also provide fundamental control mechanisms for increased reliability.

Language: English
Publisher: Frontiers Media S.A.
Year: 2019
Pages: 40
ISSN: 22964185
Types: Journal article
DOI: 10.3389/fbioe.2019.00040
ORCIDs: Nikel, Pablo Ivan

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