Single-Cell-Based Screening and Engineering of d-Amino Acid Amidohydrolases Using Artificial Amidophenol Substrates and Microbial Biosensors

Mechanism-Guided Computational Design Drives meso-Diaminopimelate Dehydrogenase to Efficient Synthesis of Aromatic d-amino Acids

Aromatic d-amino acids (d-AAs) play a pivotal role as important chiral building blocks and key intermediates in fine chemical and drug synthesis. Meso-diaminopimelate dehydrogenase (DAPDH) serves as an excellent biocatalyst in the synthesis of d-AAs and their derivatives. However, its strict substrate specificity and the lack of efficient engineering methods have hindered its widespread application. Therefore, this study aims to elucidate the catalytic mechanism underlying DAPDH from Proteus vulgaris (PvDAPDH) through the examination of its crystallographic structure, computational simulations of potential energies and molecular dynamics simulations, and site-directed mutagenesis. Mechanism-guided computational design showed that the optimal mutant PvDAPDH-M3 increased specific activity and catalytic efficiency (kcat/Km) for aromatic keto acids up to 124-fold and 92.4-fold, respectively, compared to that of the wild type. Additionally, it expanded the substrate scope to 10 aromatic keto acid substrates. Finally, six high-value-added aromatic d-AAs and their derivatives were synthesized using a one-pot three-enzyme cascade reaction, exhibiting a good conversion rate ranging from 32 to 84% and excellent stereoselectivity (enantiomeric excess >99%). These findings provide a potential synthetic pathway for the green industrial production of aromatic d-AAs.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

Production of hydroxytyrosol through whole-cell bioconversion from L-DOPA using engineered Escherichia coli

Hydroxytyrosol (HT), a polyphenolic molecule of high value, is used in the nutraceutical, cosmetic, food, and livestock nutrition industries. As a natural product, HT is chemically manufactured or extracted from olives; nevertheless, the increasing demand mandates the exploration and development of alternative sources, such as heterologous production by recombinant bacteria. In order to achieve this purpose, we have molecularly modified Escherichia coli to carry two plasmids. For conversion of L-DOPA (Levodopa) into HT efficiently, it is necessary to enhance the expression of DODC (DOPA decarboxylase), ADH (alcohol dehydrogenases), MAO (Monoamine oxidase) and GDH (glucose dehydrogenases). The step that significantly affects the rate of ht biosynthesis is likely to be associated with the reaction facilitated by DODC enzymatic activity, as suggested by the result of in vitro catalytic experiment and HPLC. Then Pseudomonas putida, Sus scrofa, Homo sapiens and Levilactobacillus brevis DODC were taken into comparsion. The DODC from H. sapiens is superior to that of P. putida, S. scrofa or L. brevis for HT production. Seven promoters were introduced to increase the expression levels of catalase (CAT) to remove the byproduct H₂O₂ and optimized coexpression strains were obtained after screening. After the 10-hour operation, the optimized whole-cell biocatalyst produced HT at a maximum titer of 4.84 g/L with over 77.5% molar substrate conversion rate.

Enzyme directed evolution using genetically encodable biosensors

Directed evolution has been remarkably successful in identifying enzyme variants with new or improved properties, such as altered substrate scope or novel reactivity. Genetically encodable biosensors (GEBs), which convert the concentration of a small molecule ligand into an easily detectable output signal, have seen increasing application to enzyme directed evolution in the last decade. GEBs enable the use of high-throughput methods to assess enzyme activity of very large libraries, which can accelerate the search for variants with desirable activity. Here, we review different classes of GEBs and their properties in the context of enzyme evolution, how GEBs have been integrated into directed evolution workflows, and recent examples of enzyme evolution efforts utilizing GEBs. Finally, we discuss the advantages, challenges, and opportunities for using GEBs in the directed evolution of enzymes.