Adipic acid is an important industrial chemical used in the synthesis of nylon-6,6. The commercial synthesis of adipic acid uses petroleum-derived benzene and releases significant quantities of greenhouse gases. Biocatalytic production of adipic acid from renewable feedstocks could potentially reduce the environmental damage and eliminate the need for fossil fuel precursors. Recently, we have demonstrated the first enzymatic hydrogenation of muconic acid to adipic acid using microbial enoate reductases (ERs) - complex iron-sulfur and flavin containing enzymes. In this work, we successfully expressed the Bacillus coagulans ER in a Saccharomyces cerevisiae strain producing muconic acid and developed a three-stage fermentation process enabling the synthesis of adipic acid from glucose. The ability to express active ERs and significant acid tolerance of S. cerevisiae highlight the applicability of the developed yeast strain for the biocatalytic production of adipic acid from renewable feedstocks.

Microbial metabolism can be harnessed to produce a broad range of industrially important chemicals. Often, three key process variables: Titer, Rate and Yield (TRY) are the target of metabolic engineering efforts to improve microbial hosts toward industrial production. Previous research into improving the TRY metrics have examined the efficacy of having distinct growth and production stages to achieve enhanced productivity. However, these studies assumed a switch from a maximum growth to a maximum production phenotype. Hence, phenotypes with intermediate growth and chemical production for the growth and production stages of two-stage processes are yet to be explored. The impact of reduced growth rates on substrate uptake adds to the need for intelligent choice of operating points while designing two-stage processes. In this work, we develop a computational framework that scans the phenotypic space of microbial metabolism to identify ideal growth and production phenotypic targets, to achieve optimal TRY targets. Using this framework, with Escherichia coli as a model organism, we compare two-stage processes that use dynamic pathway regulation, with one-stage processes that use static intervention strategies, for different bioprocess objectives. Our results indicate that two-stage processes with intermediate growth during the production stage always result in optimal TRY values even in cases where substrate uptake is limited due to reduced growth during chemical production. By analyzing the flux distributions for the production enhancing strategies, we identify key reactions and reaction subsystems that require perturbation to achieve a production phenotype for a wide range of metabolites in E. coli. Interestingly, flux perturbations that increase phosphoenolpyruvate and NADPH availability are enriched among these production phenotypes. Furthermore, reactions in the pentose phosphate pathway emerge as key control nodes that function together to increase the availability of precursors to most products in E. coli. The inherently modular nature of microbial metabolism results in common reactions and reaction subsystems that need to be regulated to modify microbes from their target of growth to the production of a diverse range of metabolites. Due to the presence of these common patterns in the flux perturbations, we propose the possibility of a universal production strain.

Metabolic engineers aim to genetically modify microorganisms to improve their ability to produce valuable compounds. Despite the prevalence of growth-coupled production processes, these strategies can significantly limit production rates. Instead, rates can be improved by decoupling and optimizing growth and production independently, and operating with a growth stage followed by a production stage. Here, we implement a bistable transcriptional controller to decouple and switch between these two states. We optimize the controller in anaerobic conditions, typical of industrial fermentations, to ensure stability and tight expression control, while improving switching dynamics. The stability of this controller can be maintained through a simulated seed train scale-up from 5 mL to 500 000 L, indicating industrial feasibility. Finally, we demonstrate a two-stage production process using our optimal construct to improve the instantaneous rate of lactate production by over 50%, motivating the use of these systems in broad metabolic engineering applications.

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Both Gram-positive and Gram-negative bacteria release nanosized extracellular vesicles called membrane vesicles (MVs, 20−400 nm), which have great potential in various biomedical applications due to their abilities to deliver effector molecules and induce therapeutic responses. To fully utilize bacterial MVs for therapeutic purposes, regulated and enhanced production of MVs would be highly advantageous. In this study, we developed a universal method to enhance MV yields in both G+/G− bacteria through an autonomous controlled peptidoglycan hydrolase (PGase) expression system. A significant increase (9.37-fold) of MV concentration was observed in engineered E. coli Nissle 1917 compared to the wild-type. With the help of this autonomous system, for the first time we experimentally confirmed horizontal gene transfer and nutrient acquisition in a cocultured bacterial consortium. Furthermore, the engineered probiotic E. coli strains with high yield of MVs showed higher activation of the innate immune responses in human embryonic kidney 293T (HEK293T) and human colorectal carcinoma cells (HCT116), thereby demonstrating the great potential of engineering probiotics in immunology and further living therapeutics in humans.