Literature DB >> 33956071

The Design-Build-Test-Learn cycle for metabolic engineering of Streptomycetes.

Christopher M Whitford1, Pablo Cruz-Morales2,3,4, Jay D Keasling1,2,3,4,5,6, Tilmann Weber1.   

Abstract

Streptomycetes are producers of a wide range of specialized metabolites of great medicinal and industrial importance, such as antibiotics, antifungals, or pesticides. Having been the drivers of the golden age of antibiotics in the 1950s and 1960s, technological advancements over the last two decades have revealed that very little of their biosynthetic potential has been exploited so far. Given the great need for new antibiotics due to the emerging antimicrobial resistance crisis, as well as the urgent need for sustainable biobased production of complex molecules, there is a great renewed interest in exploring and engineering the biosynthetic potential of streptomycetes. Here, we describe the Design-Build-Test-Learn (DBTL) cycle for metabolic engineering experiments in streptomycetes and how it can be used for the discovery and production of novel specialized metabolites.
© 2021 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Entities:  

Keywords:  DBTL; Streptomyces; metabolic engineering; secondary metabolite; specialized metabolite

Mesh:

Substances:

Year:  2021        PMID: 33956071     DOI: 10.1042/EBC20200132

Source DB:  PubMed          Journal:  Essays Biochem        ISSN: 0071-1365            Impact factor:   8.000


  4 in total

1.  Evolutionary Genome Mining for the Discovery and Engineering of Natural Product Biosynthesis.

Authors:  Marc G Chevrette; Nelly Selem-Mojica; César Aguilar; Kristin Labby; Edder D Bustos-Diaz; Jo Handelsman; Francisco Barona-Gómez
Journal:  Methods Mol Biol       Date:  2022

Review 2.  Synthetic Biology Tools for Engineering Microbial Cells to Fight Superbugs.

Authors:  Angel León-Buitimea; Francisco de Jesús Balderas-Cisneros; César Rodolfo Garza-Cárdenas; Javier Alberto Garza-Cervantes; José Rubén Morones-Ramírez
Journal:  Front Bioeng Biotechnol       Date:  2022-05-04

Review 3.  Natural product drug discovery in the artificial intelligence era.

Authors:  F I Saldívar-González; V D Aldas-Bulos; J L Medina-Franco; F Plisson
Journal:  Chem Sci       Date:  2021-12-13       Impact factor: 9.825

Review 4.  Genome mining for drug discovery: progress at the front end.

Authors:  Richard H Baltz
Journal:  J Ind Microbiol Biotechnol       Date:  2021-12-23       Impact factor: 4.258

  4 in total

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