Narrowing the gap between the promise and reality of polyketide synthases as a synthetic biology platform

Sean Poust; Andrew Hagen; Leonard Katz; Jay D Keasling

doi:10.1016/j.copbio.2014.04.011

Narrowing the gap between the promise and reality of polyketide synthases as a synthetic biology platform

Curr Opin Biotechnol. 2014 Dec:30:32-9. doi: 10.1016/j.copbio.2014.04.011. Epub 2014 May 6.

Authors

Sean Poust¹, Andrew Hagen², Leonard Katz³, Jay D Keasling⁴

Affiliations

¹ Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94270, USA; Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA.
² Department of Plant & Microbial Biology, University of California, Berkeley, CA 94270, USA; Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Synthetic Biology Engineering Research Center, 5885 Hollis Street, Emeryville, CA 94608, USA.
³ QB3 Institute, University of California, Berkeley, CA 94270, USA; Synthetic Biology Engineering Research Center, 5885 Hollis Street, Emeryville, CA 94608, USA.
⁴ Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94270, USA; Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; QB3 Institute, University of California, Berkeley, CA 94270, USA; Synthetic Biology Engineering Research Center, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Bioscience Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94270, USA. Electronic address: keasling@berkeley.edu.

PMID: 24816568
DOI: 10.1016/j.copbio.2014.04.011

Abstract

Engineering modular polyketide synthases (PKSs) has the potential to be an effective methodology to produce existing and novel chemicals. However, this potential has only just begun to be realized. We propose the adoption of an iterative design-build-test-learn paradigm to improve PKS engineering. We suggest methods to improve engineered PKS design by learning from laboratory-based selection; adoption of DNA design software and automation to build constructs and libraries more easily; tools for the expression of engineered proteins in a variety of heterologous hosts; and mass spectrometry-based high-throughput screening methods. Finally, lessons learned during iterations of the design-build-test-learn cycle can serve as a knowledge base for the development of a single retrosynthesis algorithm usable by both PKS experts and non-experts alike.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Algorithms
Biotechnology / methods*
Escherichia coli / metabolism
Polyketide Synthases / chemistry*
Polyketide Synthases / genetics
Polyketide Synthases / metabolism
Protein Engineering*
Synthetic Biology / methods

Substances

Polyketide Synthases