Digital and analog gene circuits for biotechnology
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Lu_Digital and.pdf
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1.17 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Lu, Timothy K.
Roquet, Nathaniel Bernard
Date Issued
May 2014
Journal
Biotechnology Journal
Publisher
Wiley Blackwell
Citation
Roquet, Nathaniel, and Timothy K. Lu. “Digital and Analog Gene Circuits for Biotechnology.” Biotechnology Journal 9, no. 5 (February 20, 2014): 597–608.
Version
Author's final manuscript
Abstract
Biotechnology offers the promise of valuable chemical production via microbial processing of renewable and inexpensive substrates. Thus far, static metabolic engineering strategies have enabled this field to advance industrial applications. However, the industrial scaling of statically engineered microbes inevitably creates inefficiencies due to variable conditions present in large-scale microbial cultures. Synthetic gene circuits that dynamically sense and regulate different molecules can resolve this issue by enabling cells to continuously adapt to variable conditions. These circuits also have the potential to enable next-generation production programs capable of autonomous transitioning between steps in a bioprocess. Here, we review the design and application of two main classes of dynamic gene circuits, digital and analog, for biotechnology. Within the context of these classes, we also discuss the potential benefits of digital-analog interconversion, memory, and multi-signal integration. Though synthetic gene circuits have largely been applied for cellular computation to date, we envision that utilizing them in biotechnology will enhance the efficiency and scope of biochemical production with living cells.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Synthetic Biology Center
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1002/biot.201300258
