Merging automation and fundamental discovery into the design-build-test-learn cycle of nontraditional microbes

Trends Biotechnol. 2022 Oct;40(10):1148-1159. doi: 10.1016/j.tibtech.2022.03.004. Epub 2022 Apr 8.

Abstract

Major advances toward a bio-based industry enabled cost-efficient bioproduction of multiple chemicals, yet successful industrial processes are relatively scarce and limited to the use of few workhorse microbes as hosts. An in-depth understanding of the physiology and metabolism of nontraditional microorganisms is key to unleash their biotechnological potential. The inception of biofoundries multiplied the capacity of constructing and testing a large number of microbial strains tailored for bioproduction - and we argue that automation workflows therein can be adapted to gain fundamental knowledge of nontraditional hosts. Here, we propose a 'metabolism-centric' approach to the design-build-test-learn cycle of synthetic biology, supported by multi-omic analyses, to facilitate the deployment of microbial cell factories designed for bioproduction beyond the typical landscape of target products.

Keywords: DBTL cycle; automation; biofoundry; metabolic engineering; microbial host; synthetic biology; synthetic metabolism.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Automation
  • Biotechnology
  • Metabolic Engineering*
  • Synthetic Biology*