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- Rugbjerg, Peter, 1988, et al.
(author)
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The future of self-selecting and stable fermentations
- 2020
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In: Journal of Industrial Microbiology and Biotechnology. - : Oxford University Press (OUP). - 1367-5435 .- 1476-5535. ; 47:11, s. 993-1004
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Research review (peer-reviewed)abstract
- Unfavorable cell heterogeneity is a frequent risk during bioprocess scale-up and characterized by rising frequencies of low-producing cells. Low-producing cells emerge by both non-genetic and genetic variation and will enrich due to their higher specific growth rate during the extended number of cell divisions of large-scale bioproduction. Here, we discuss recent strategies for synthetic stabilization of fermentation populations and argue for their application to make cell factory designs that better suit industrial needs. Genotype-directed strategies leverage DNA-sequencing data to inform strain design. Self-selecting phenotype-directed strategies couple high production with cell proliferation, either by redirected metabolic pathways or synthetic product biosensing to enrich for high-performing cell variants. Evaluating production stability early in new cell factory projects will guide heterogeneity-reducing design choices. As good initial metrics, we propose production half-life from standardized serial-passage stability screens and production load, quantified as production-associated percent-wise growth rate reduction. Incorporating more stable genetic designs will greatly increase scalability of future cell factories through sustaining a high-production phenotype and enabling stable long-term production.
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| 2. |
- Torello Pianale, Luca, 1995, et al.
(author)
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Exploring Microbial Robustness for a Sustainable and Efficient Bioproduction
- 2020
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Conference paper (other academic/artistic)abstract
- Efficient microbial cell factories that produce valuable compounds are gaining increasing interest as one path towards a more sustainable economy. Therefore, there is an increasing need for robust microorganisms which can optimally perform even in harsh and challenging industrial conditions. The identification of robustness traits is crucial to improve the already-existing strains and develop new, better ones. Here, different approaches to study microbial robustness are presented. First, single-cell analysis in a cell population might give some insights on the development of more robust sub-populations. Physiological parameters (such as intracellular pH, fluxes, redox balance, etc.) and morphologic features were monitored with fluorescent biosensors and tagged proteins to study the single-cell status. Moreover, a barcoding technique will be used to discover and underline patterns in the development of population dynamics during the different industrial processes. Furthermore, an objective method to quantify robustness was developed for selection of useful strains and a large dataset was analysed to find predictive parameters for robustness. All together, these tools will give the possibility to identify robustness traits and understand robustness leading to improved industrial strains and processes.
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