Abstract
Bioactive compounds and enzymes with tolerance to process-specific parameters or improved catalytic performance play a crucial role in the development of applications in the chemical and pharmaceutical industry or energy production. Metagenomics takes advantage of the wealth of biochemical diversity present in the genomes of microorganisms found in environmental samples and provides a set of new technologies directed toward screening for new genes with potential in biotechnological applications. However, despite the vast number of published successful studies using this approach, metagenomic strategies typically have low rates of target discovery, and a number of issues need to be addressed in order to improve the screening efficiency of metagenomic libraries. Current limitations include biases imposed by expression in foreign host organisms, low vector performance in particular hosts, and the absence of suitable screening strategies for many targets. These restrictions cannot be overcome by using a single approach but rather require the synergetic implementation of multiple methodologies. In this chapter, we review some of the principal constraints regarding the discovery of new genes with potential use in biotechnology in metagenomic libraries and discuss how these might be resolved using synthetic biology methods. In addition, we review the state of art of synthetic biology approaches directed to improve the recovery of target genes in metagenomic screenings.
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Acknowledgments
The study was supported by the National Council of Technological and Scientific Development (CNPq 472893/2013-0 and 441833/2014-4) and by the Sao Paulo State Foundation (FAPESP, grant number 2015/04309-1 and 2012/21922-8). MEG was a beneficiary of a CNPq Young Talent Fellowship (CNPq 370630/2013-0). Authors have no conflict of interest to declare.
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Alves, L.d.F., Silva-Rocha, R., Guazzaroni, ME. (2017). Enhancing Metagenomic Approaches Through Synthetic Biology. In: Charles, T., Liles, M., Sessitsch, A. (eds) Functional Metagenomics: Tools and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-61510-3_5
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