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Abstract

In the present there is a great necessity of suitable biocatalysts with high process performance, as a “greener” complementary alternative to the chemical synthesis. It is expected that in the coming decade, up to 40% of bulk chemical synthesis processes could be substituted by enzymatic catalysis. The identification and optimization of an appropriate enzyme represent important requirements to obtain a successful and efficient enzymatic process. In this context, the establishment of enzymatic processes in the industry is mainly a problem of finding and optimizing new enzymes. In this sense, nature is the richest reservoir from which enzymes can be isolated because they are continuously changing and evolving as a consequence of natural processes of selection. We are now taking advantages of sequencing and extensive screening technologies to develop enzyme discovery strategies and to identify microbial enzymes with improved and unusual activities and specificities. These approaches, in combination with modern protein engineering methods and distinct combinatorial and rational methods, will increase our chances to generate new stabilized biocatalysts that fit industrial requirements. Here, we review the methodologies, obstacles, and solving problems around metagenomics investigations to screen for enzymes with activities of interest.

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Acknowledgments

The authors gratefully acknowledge the financial support provided by the European Community project KILL-SPILL (FP7-KBBE-2012-312139) European Union’s Horizon 2020 Project INMARE (grant agreement No 634486. This work was further funded by grants BIO2011-25012, PCIN-2014-107, and BIO2014-54494-R from the Spanish Ministry of Economy and Competitiveness. The present investigation was funded by the Spanish Ministry of Economy and Competitiveness, the UK Biotechnology and Biological Sciences Research Council (BBSRC) (Grant Nr BB/MO29085/1) within the ERA NET-IB2 program, grant number ERA-IB-14-030. MF gratefully acknowledges the financial support provided by the European Regional Development Fund (ERDF).

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Correspondence to Peter N. Golyshin .

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Distaso, M.A., Tran, H., Ferrer, M., Golyshin, P.N. (2017). Metagenomic Mining of Enzyme Diversity. In: Lee, S. (eds) Consequences of Microbial Interactions with Hydrocarbons, Oils, and Lipids: Production of Fuels and Chemicals. Handbook of Hydrocarbon and Lipid Microbiology . Springer, Cham. https://doi.org/10.1007/978-3-319-50436-0_216

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