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

Angel Goni-Moreno*, Pablo Ivan Nikel

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

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.
Original languageEnglish
Article number40
JournalFrontiers in Bioengineering and Biotechnology
Volume7
Number of pages6
ISSN2296-4185
DOIs
Publication statusPublished - 2019

Keywords

  • biocomputing
  • synthetic biology
  • metabolic engineering
  • boolean logic
  • genetic circuits
  • metabolic networks

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