Synthetic Evolution of Metabolic Productivity Using Biosensors

Thomas C Williams; Isak S Pretorius; Ian T Paulsen

doi:10.1016/j.tibtech.2016.02.002

Synthetic Evolution of Metabolic Productivity Using Biosensors

Trends Biotechnol. 2016 May;34(5):371-381. doi: 10.1016/j.tibtech.2016.02.002. Epub 2016 Mar 3.

Authors

Thomas C Williams¹, Isak S Pretorius¹, Ian T Paulsen²

Affiliations

¹ Department of Chemistry and Biomolecular Sciences, Macquarie University, NSW, Australia.
² Department of Chemistry and Biomolecular Sciences, Macquarie University, NSW, Australia. Electronic address: ian.paulsen@mq.edu.au.

PMID: 26948437
DOI: 10.1016/j.tibtech.2016.02.002

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.

Keywords: Saccharomyces cerevisiae; adaptive laboratory evolution; biosensing; genome engineering; metabolic engineering; synthetic biology; yeast.

Publication types

Review

MeSH terms

Biosensing Techniques
Escherichia coli / genetics
Escherichia coli / metabolism
Metabolic Engineering / methods*
Metabolic Networks and Pathways
Saccharomyces cerevisiae / genetics
Saccharomyces cerevisiae / metabolism
Synthetic Biology / methods*
Systems Biology / methods*