Synthetic Evolution of Metabolic Productivity Using Biosensors

Synthetic Evolution of Metabolic Productivity Using Biosensors Synthetic biology has progressed to the point where genes that encode whole metabolic pathways and even genomes can be manufactured and brought to life. This impressive ability to synthesise and assemble DNA is not yet matched by an ability to predictively engineer biology. These difficulties exist because biological systems are often overwhelmingly complex, having evolved to facilitate growth and survival rather than specific engineering objectives such as the optimisation of biochemical production. A promising and revolutionary solution to this problem is to harness the process of evolution to create microbial strains with desired properties. The tools of systems biology can then be applied to understand the principles of biological design, bringing synthetic biology closer to becoming a predictive engineering discipline. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Trends in Biotechnology Elsevier

Synthetic Evolution of Metabolic Productivity Using Biosensors

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Publisher
Elsevier
Copyright
Copyright © 2016 Elsevier Ltd
ISSN
0167-7799
D.O.I.
10.1016/j.tibtech.2016.02.002
Publisher site
See Article on Publisher Site

Abstract

Synthetic biology has progressed to the point where genes that encode whole metabolic pathways and even genomes can be manufactured and brought to life. This impressive ability to synthesise and assemble DNA is not yet matched by an ability to predictively engineer biology. These difficulties exist because biological systems are often overwhelmingly complex, having evolved to facilitate growth and survival rather than specific engineering objectives such as the optimisation of biochemical production. A promising and revolutionary solution to this problem is to harness the process of evolution to create microbial strains with desired properties. The tools of systems biology can then be applied to understand the principles of biological design, bringing synthetic biology closer to becoming a predictive engineering discipline.

Journal

Trends in BiotechnologyElsevier

Published: May 1, 2016

References

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