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Detalle de: Computer-aided design for metabolic engineering

Title Computer-aided design for metabolic engineering
Abstract

The development and application of biotechnology-based strategies has had a great socio-economical impact and is likely to play a crucial role in the foundation of more sustainable and efficient industrial processes. Within biotechnology, metabolic engineering aims at the directed improvement of cellular properties, often with the goal of synthesizing a target chemical compound. The use of computer-aided design (CAD) tools, along with the continuously emerging advanced genetic engineering techniques have allowed metabolic engineering to broaden and streamline the process of heterologous compound-production. In this work, we review the CAD tools available for metabolic engineering with an emphasis, on retrosynthesis methodologies. Recent advances in genetic engineering strategies for pathway implementation and optimization are also reviewed as well as a range of bionalytical tools to validate in silico predictions. A case study applying retrosynthesis is presented as an experimental verification of the output from Retropath, the first complete automated computational pipeline applicable to metabolic engineering. Applying this CAD pipeline, together with genetic reassembly and optimization of culture conditions led to improved production of the plant flavonoid pinocembrin. Coupling CAD tools with advanced genetic engineering strategies and bioprocess optimization is crucial for enhanced product yields and will be of great value for the development of non-natural products through sustainable biotechnological processes.

Apa Reference Fernández-Castané, A., Fehér, T., Carbonell, P., Pauthenier, C., & Faulon, J.-L. (2014). Computer-aided design for metabolic engineering. Journal of Biotechnology, 192, 302–313. 10.1016/j.jbiotec.2014.03.029
Doi 10.1016/j.jbiotec.2014.03.029
Publication Date Dec 2014
Publication Type Article
Researcher Pablo Carbonell
Ontology Computational models and simulations
Research Groups Dynamics Biodesign Lab
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