A multilevel approach was implemented in Saccharomyces cerevisiae to optimize the precursor module of the aromatic amino acid biosynthesis pathway, which is a rich resource for synthesizing a great variety of chemicals ranging from polymer precursor, to nutraceuticals and pain-relief drugs. To facilitate the discovery of novel targets to enhance the pathway flux, we incorporated the computational tool YEASTRACT for predicting novel transcriptional repressors and OptForce strain-design for identifying non-intuitive pathway interventions. The multilevel approach consisted of (i) relieving the pathway from strong transcriptional repression, (ii) removing competing pathways to ensure high carbon capture, and (iii) rewiring precursor pathways to increase the carbon funneling to the desired target. The combination of these interventions led to the establishment of a S. cerevisiae strain with shikimic acid (SA) titer reaching as high as 2.5gL-1, 7-fold higher than the base strain. Further expansion of the platform led to the titer of 2.7gL-1 of muconic acid (MA) and its intermediate protocatechuic acid (PCA) together. Both the SA and MA production platforms demonstrated increases in titer and yield nearly 300% from the previously reported, highest-producing S. cerevisiae strains. Further examination elucidated the diverged impacts of disrupting the oxidative branch (ZWF1) of the pentose phosphate pathway on the titers of desired products belonging to different portions of the pathway. The investigation of other non-intuitive interventions like the deletion of the Pho13 enzyme also revealed the important role of the transaldolase in determining the fate of the carbon flux in the pathways of study. This integrative approach identified novel determinants at both transcriptional and metabolic levels that constrain the flux entering the aromatic amino acid pathway. In the future, this platform can be readily used for engineering the downstream modules toward the production of important plant-sourced aromatic secondary metabolites.
Keywords: Aromatic amino acid pathway; Computational strain design; Muconic acid; Multilevel metabolic engineering; Shikimic acid; Transcriptional regulation.
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