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The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology
- Source :
- Sandberg, T E, Salazar, M J, Weng, L L, Palsson, B O & Feist, A M 2019, ' The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology ', Metabolic Engineering, vol. 56, pp. 1-16 . https://doi.org/10.1016/j.ymben.2019.08.004, Metab Eng
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Harnessing the process of natural selection to obtain and understand new microbial phenotypes has become increasingly possible due to advances in culturing techniques, DNA sequencing, bioinformatics, and genetic engineering. Accordingly, Adaptive Laboratory Evolution (ALE) experiments represent a powerful approach to both investigate the evolutionary forces influencing strain phenotypes, performance, and stability, and to acquire production strains that contain beneficial mutations. In this review, we summarize and categorize the applications of ALE to various aspects of microbial physiology pertinent to industrial bioproduction by collecting case studies that highlight the multitude of ways in which evolution can facilitate the strain construction process. Further, we discuss principles that inform experimental design, complementary approaches such as computational modeling that help maximize utility, and the future of ALE as an efficient strain design and build tool driven by growing adoption and improvements in automation.
- Subjects :
- 0303 health sciences
Natural selection
030306 microbiology
Computer science
business.industry
Process (engineering)
Bioengineering
Industrial biotechnology
Models, Biological
Applied Microbiology and Biotechnology
Automation
Article
Microbial Physiology
Industrial Microbiology
03 medical and health sciences
Metabolic Engineering
Biochemical engineering
Directed Molecular Evolution
Microorganisms, Genetically-Modified
business
030304 developmental biology
Biotechnology
Subjects
Details
- ISSN :
- 10967176
- Volume :
- 56
- Database :
- OpenAIRE
- Journal :
- Metabolic Engineering
- Accession number :
- edsair.doi.dedup.....1aa8ccc35bc3cc06dcbf244584ad99c5
- Full Text :
- https://doi.org/10.1016/j.ymben.2019.08.004