Refactoring Ehrlich Pathway for High-Yield 2-Phenylethanol Production in Yarrowia lipolytica.

ACS synthetic biology(2020)

Cited 56|Views3
No score
Abstract
Efficient microbial synthesis of chemicals requires the coordinated supply of precursors and cofactors to maintain cell growth and product formation. Substrates with different entry points into the metabolic network have different energetic and redox statuses. Generally, substrate cofeeding could bypass the lengthy and highly regulated native metabolism and facilitates high carbon conversion rate. Aiming to efficiently synthesize the high-value rose-smell 2-phenylethanol (2-PE) in Y. lipolytica, we analyzed the stoichiometric constraints of the Ehrlich pathway and identified that the selectivity of the Ehrlich pathway and the availability of 2-oxoglutarate are the rate-limiting factors. Stepwise refactoring of the Ehrlich pathway led us to identify the optimal catalytic modules consisting of l-phenylalanine permease, ketoacid aminotransferase, phenylpyruvate decarboxylase, phenylacetaldehyde reductase, and alcohol dehydrogenase. On the other hand, mitochondrial compartmentalization of 2-oxoglutarate inherently creates a bottleneck for efficient assimilation of l-phenylalanine, which limits 2-PE production. To improve 2-oxoglutarate (aKG) trafficking across the mitochondria membrane, we constructed a cytosolic aKG source pathway by coupling a bacterial aconitase with a native isocitrate dehydrogenase (ylIDP2). Additionally, we also engineered dicarboxylic acid transporters to further improve the 2-oxoglutarate availability. Furthermore, by blocking the precursor-competing pathways and mitigating fatty acid synthesis, the engineered strain produced 2669.54 mg/L of 2-PE in shake flasks, a 4.16-fold increase over the starting strain. The carbon conversion yield reaches 0.702 g/g from l-phenylalanine, 95.0% of the theoretical maximal. The reported work expands our ability to harness the Ehrlich pathway for production of high-value aromatics in oleaginous yeast species.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined