Identification of a metagenome-derived prephenate dehydrogenase gene from an alkaline-polluted soil microorganism

Characterization of a metagenome-derived protease from contaminated agricultural soil microorganisms and its random mutagenesis

Proteases are typical key enzymes that hydrolyze proteins into amino acids and peptides. Numerous proteases have been studied, but the discovery of metagenome-derived proteases is still significant for both commercial applications and basic research. An unexplored protease gene sep1A was identified by function-based screening from a plasmid metagenomic library derived from uncultured contaminated agricultural soil microorganisms. The putative protease gene was subcloned into pET-32a (+) vector and overexpressed in E. coli BL21(DE3) pLysS, then the recombinant protein was purified to homogeneity. The detailed biochemical characterization of the Sep1A protein was performed, including its molecular characterization, specific activity, pH-activity profile, metal ion-activity profile, and enzyme kinetic assays. Furthermore, the protein engineering approach of random mutagenesis via error-prone PCR was applied on the original Sep1A protein. Biochemical characterization demonstrated that the purified recombinant Ep48 protein could hydrolyze casein. Compared with the original Sep1A protein, the best variant of Ep48 in the random mutagenesis library, with the Gln307Leu and Asp391Gly changes, exhibited 2.62-fold activity at the optimal reaction conditions of 50 °C and pH 9.0. These results are the first step toward a better understanding of the properties of Sep1A protein. Protein engineering with error-prone PCR paves the way toward the metagenome-derived genes for biotechnological applications.

A novel D-amino acid oxidase from a contaminated agricultural soil metagenome and its characterization

A novel D-amino acid oxidase (DAAO) gene designated as daoE was cloned by the sequence-based screening of a plasmid metagenomic library of uncultured microorganisms from contaminated agricultural soil. The deduced amino acid sequence comparison and phylogenetic analysis indicated that daoE and other putative DAAOs are closely related. The putative DAAO gene was subcloned into a pETBlue-2 vector and overexpressed in Escherichia coli Tunner(DE3)pLacI. The recombinant protein was purified to homogeneity. The maximum activity of DaoE protein occurred at pH 8.0 and 37 °C. DaoE recombinant protein had an apparent K m of 2.96 mM, V max of 0.018 mM/min, k cat of 10.9/min, and k cat/K m of 1.16 × 10(4)/mol/min. The identification of this novel DAAO gene demonstrated the importance of metagenomic libraries in exploring new D-amino acid oxidases from environmental microorganisms to optimize their applications.

Synthetic biology approaches to improve biocatalyst identification in metagenomic library screening

There is a growing demand for enzymes with improved catalytic performance or tolerance to process-specific parameters, and biotechnology plays a crucial role in the development of biocatalysts for use in industry, agriculture, medicine and energy generation. Metagenomics takes advantage of the wealth of genetic and biochemical diversity present in the genomes of microorganisms found in environmental samples, and provides a set of new technologies directed towards screening for new catalytic activities from environmental samples with potential biotechnology applications. However, biased and low level of expression of heterologous proteins in Escherichia coli together with the use of non-optimal cloning vectors for the construction of metagenomic libraries generally results in an extremely low success rate for enzyme identification. The bottleneck arising from inefficient screening of enzymatic activities has been addressed from several perspectives; however, the limitations related to biased expression in heterologous hosts cannot be overcome by using a single approach, but rather requires the synergetic implementation of multiple methodologies. Here, we review some of the principal constraints regarding the discovery of new enzymes in metagenomic libraries and discuss how these might be resolved by using synthetic biology methods.