The bio‐based production of added‐value compounds (with applications as pharmaceuticals, biofuels, food ingredients, and building blocks) using bacterial platforms is a well‐established industrial activity. The design and construction of microbial cell factories (MCFs) with robust and stable industrially relevant phenotypes, however, remains one of the biggest challenges of contemporary biotechnology. In this review, traditional and cutting‐edge approaches for optimizing the performance of MCFs for industrial bioprocesses, rooted on the engineering principle of natural evolution (i.e., genetic variation and selection), are discussed. State‐of‐the‐art techniques to manipulate and increase genetic variation in bacterial populations and to construct combinatorial libraries of strains, both globally (i.e., genome level) and locally (i.e., individual genes or pathways, and entire sections and gene clusters of the bacterial genome) are presented. Cutting‐edge screening and selection technologies applied to isolate MCFs displaying enhanced phenotypes are likewise discussed. The review article is closed by presenting future trends in the design and construction of a new generation of MCFs that will contribute to the long‐sought‐after transformation from a petrochemical industry to a veritable sustainable bio‐based industry.
Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost-effectiveness expectations. In this study, we explore the bioproduction of D-psicose, also known as D-allulose, a rare non-toxic sugar and a sweetener present in nature in low amounts. D-psicose has interesting properties and seemingly the ability to fight against obesity and type 2 diabetes. We developed a biosensor-based enzyme screening approach as a tool for enzyme selection that we benchmarked with the Clostridium cellulolyticum D-psicose 3-epimerase for the production of D-psicose from D-fructose. For this purpose, we constructed and characterized seven psicose responsive biosensors based on previously uncharacterized transcription factors and either their predicted promoters or an engineered promoter. In order to standardize our system, we created the Universal Biosensor Chassis, a construct with a highly modular architecture that allows rapid engineering of any transcription factor-based biosensor. Among the seven biosensors, we chose the one displaying the most linear behavior and the highest increase in fluorescence fold change. Next, we generated a library of D-psicose 3-epimerase mutants by error-prone PCR and screened it using the biosensor to select gain of function enzyme mutants, thus demonstrating the framework’s efficiency.
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