Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2014 Dec 16;111(50):17803-8. doi: 10.1073/pnas.1409523111. Epub 2014 Dec 1.

Evolution-guided optimization of biosynthetic pathways.

Author information

1
Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115; Department of Genetics, Harvard Medical School, Boston, MA 02115; and sraman@genetics.med.harvard.edu.
2
Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115; School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02143.
3
Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115; Department of Genetics, Harvard Medical School, Boston, MA 02115; and.

Abstract

Engineering biosynthetic pathways for chemical production requires extensive optimization of the host cellular metabolic machinery. Because it is challenging to specify a priori an optimal design, metabolic engineers often need to construct and evaluate a large number of variants of the pathway. We report a general strategy that combines targeted genome-wide mutagenesis to generate pathway variants with evolution to enrich for rare high producers. We convert the intracellular presence of the target chemical into a fitness advantage for the cell by using a sensor domain responsive to the chemical to control a reporter gene necessary for survival under selective conditions. Because artificial selection tends to amplify unproductive cheaters, we devised a negative selection scheme to eliminate cheaters while preserving library diversity. This scheme allows us to perform multiple rounds of evolution (addressing ∼10(9) cells per round) with minimal carryover of cheaters after each round. Based on candidate genes identified by flux balance analysis, we used targeted genome-wide mutagenesis to vary the expression of pathway genes involved in the production of naringenin and glucaric acid. Through up to four rounds of evolution, we increased production of naringenin and glucaric acid by 36- and 22-fold, respectively. Naringenin production (61 mg/L) from glucose was more than double the previous highest titer reported. Whole-genome sequencing of evolved strains revealed additional untargeted mutations that likely benefit production, suggesting new routes for optimization.

KEYWORDS:

biosynthetic pathways; evolution; metabolic engineering; sensors; synthetic biology

PMID:
25453111
PMCID:
PMC4273373
DOI:
10.1073/pnas.1409523111
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center