Dataset Information

Evolution-guided optimization of biosynthetic pathways.

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.

SUBMITTER: Raman S

PROVIDER: S-EPMC4273373 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Evolution-guided optimization of biosynthetic pathways.

Raman Srivatsan S Rogers Jameson K JK Taylor Noah D ND Church George M GM

Proceedings of the National Academy of Sciences of the United States of America 20141201 50

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 tar ...[more]

PMID: 25453111

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Project description:BACKGROUND: The lysine, threonine, and methionine biosynthetic pathways share the three initial enzymatic steps, which are referred to as the Common Pathway (CP). In Escherichia coli three different aspartokinases (AKI, AKII, AKIII, the products of thrA, metL and lysC, respectively) can perform the first step of the CP. Moreover, two of them (AKI and AKII) are bifunctional, carrying also homoserine dehydrogenasic activity (hom product). The second step of the CP is catalyzed by a single aspartate semialdehyde dehydrogenase (ASDH, the product of asd). Thus, in the CP of E. coli while a single copy of ASDH performs the same reaction for three different metabolic routes, three different AKs perfom a unique step. Why and how such a situation did emerge and maintain? How is it correlated to the different regulatory mechanisms acting on these genes? The aim of this work was to trace the evolutionary pathway leading to the extant scenario in proteobacteria. RESULTS: The analysis of the structure, organization, phylogeny, and distribution of ask and hom genes revealed that the presence of multiple copies of these genes and their fusion events are restricted to the gamma-subdivision of proteobacteria. This allowed us to depict a model to explain the evolution of ask and hom according to which the fused genes are the outcome of a cascade of gene duplication and fusion events that can be traced in the ancestor of gamma-proteobacteria. Moreover, the appearance of fused genes paralleled the assembly of operons of different sizes, suggesting a strong correlation between the structure and organization of these genes. A statistic analysis of microarray data retrieved from experiments carried out on E. coli and Pseudomonas aeruginosa was also performed. CONCLUSION: The integration of data concerning gene structure, organization, phylogeny, distribution, and microarray experiments allowed us to depict a model for the evolution of ask and hom genes in proteobacteria and to suggest a biological significance for the extant scenario.

Dataset Information

Evolution-guided optimization of biosynthetic pathways.

Publications

Evolution-guided optimization of biosynthetic pathways.

Similar Datasets

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