Synthetic metabolism for biohalogenation.

The pressing need for novel bioproduction approaches faces a limitation in the number and type of molecules accessed through synthetic biology. Halogenation is widely used for tuning physicochemical properties of molecules and polymers, but traditional halogenation chemistry often lacks specificity and generates harmful by-products. Here, we pose that deploying synthetic metabolism tailored for biohalogenation represents an unique opportunity towards economically attractive and environmentally friendly organohalide production. On this background, we discuss growth-coupled selection of functional metabolic modules that harness the rich repertoire of biosynthetic and biodegradation capabilities of environmental bacteria for in vivo biohalogenation. By rationally combining these approaches, the chemical landscape of living cells can accommodate bioproduction of added-value organohalides which, as of today, are obtained by traditional chemistry.

Spatiotemporal Manipulation of the Mismatch Repair System of Pseudomonas putida Accelerates Phenotype Emergence.

The development of complex phenotypes in industrially relevant bacteria is a major goal of metabolic engineering, which encompasses the implementation of both rational and random approaches. In the latter case, several tools have been developed toward increasing mutation frequencies, yet the precise control of mutagenesis processes in cell factories continues to represent a significant technical challenge. Pseudomonas species are endowed with one of the most efficient DNA mismatch repair (MMR) systems found in the bacterial domain. Here, we investigated if the endogenous MMR system could be manipulated as a general strategy to artificially alter mutation rates in Pseudomonas species. To bestow a conditional mutator phenotype in the platform bacterium Pseudomonas putida, we constructed inducible mutator devices to modulate the expression of the dominant-negative mutLE36K allele. Regulatable overexpression of mutLE36K in a broad-host-range, easy-to-cure plasmid format resulted in a transitory inhibition of the MMR machinery, leading to a significant increase (up to 438-fold) in DNA mutation frequencies and a heritable fixation of mutations in the genome. Following such an accelerated mutagenesis-followed by selection approach, three phenotypes were successfully evolved: resistance to antibiotics streptomycin and rifampicin (either individually or combined) and reversion of a synthetic uracil auxotrophy. Thus, these mutator devices could be applied to accelerate the evolution of metabolic pathways in long-term evolutionary experiments, alternating cycles of (inducible) mutagenesis coupled to selection schemes toward the desired phenotype(s).

Evolutionary Approaches for Engineering Industrially Relevant Phenotypes in Bacterial Cell Factories.

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.

Biosensor-based enzyme engineering approach applied to psicose biosynthesis.

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.