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- Olsson, Lisbeth, 1963, et al.
(författare)
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Microbial robustness in bioprocesses
- 2023
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Yeast is broadly exploited for industrial use, and strains are constantly improved to meet the requirements to produce the targeted product with high yield, productivity and titer. Successful strains have consistent performance also in presence of different perturbations, i.e. their performance is robust. The concept of microbial robustness will be discussed and contrasted to tolerance toward specific stresses. Furthermore, a method to quantitatively assess microbial robustness will be presented. This method allows a high throughput evaluation, in a perturbation space where different cellular function can form the basis for the evaluation. Another important tool box to examine intracellular status in face of pertubations are biosensors. Examples of applying these two methodologies towards microbial robustness will be discussed. We have used the tools to scale down bioprocesses and their perturbation, to follow adaptive laboratory evolution and to gain understanding of subpopulations.
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| 2. |
- Torello Pianale, Luca, 1995, et al.
(författare)
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Four ways of implementing robustness quantification in strain characterisation
- 2023
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Ingår i: Biotechnology for Biofuels and Bioproducts. - 2731-3654. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background. In industrial bioprocesses, microorganisms are generally selected based on performance, whereas robustness, i.e., the ability of a system to maintain a stable performance, has been overlooked due to the challenges in its quantification and implementation into routine experimental procedures. This work presents four ways of implementing robustness quantification during strain characterisation. One Saccharomyces cerevisiae laboratory strain (CEN.PK113-7D) and two industrial strains (Ethanol Red and PE2) grown in seven different lignocellulosic hydrolysates were assessed for growth-related functions (specific growth rate, product yields, etc.) and eight intracellular parameters (using fluorescent biosensors). Results. Using flasks and high-throughput experimental setups, robustness was quantified in relation to: (i) stability of growth functions in response to the seven hydrolysates; (ii) stability of growth functions across different strains to establish the impact of perturbations on yeast metabolism; (iii) stability of intracellular parameters over time; (iv) stability of intracellular parameters within a cell population to indirectly quantify population heterogeneity. Ethanol Red was the best-performing strain under all tested conditions, achieving the highest growth function robustness. PE2 displayed the highest population heterogeneity. Moreover, the intracellular environment varied in response to non-woody or woody lignocellulosic hydrolysates, manifesting increased oxidative stress and unfolded protein response, respectively. Conclusions. Robustness quantification is a powerful tool for strain characterisation as it offers novel information on physiological and biochemical parameters. Owing to the flexibility of the robustness quantification method, its implementation was successfully validated at single-cell as well as high-throughput levels, showcasing its versatility and potential for several applications.
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| 3. |
- Torello Pianale, Luca, 1995, et al.
(författare)
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ScEnSor Kit for Saccharomyces cerevisiae Engineering and Biosensor-Driven Investigation of the Intracellular Environment
- 2023
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Ingår i: ACS Synthetic Biology. - 2161-5063. ; 12:8, s. 2493-2497
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Tidskriftsartikel (refereegranskat)abstract
- In this study, the three-step build-transform-assess toolbox for real-time monitoring of the yeast intracellular environment has been expanded and upgraded to the two-module ScEnSor (S. cerevisiae Engineering + Biosensor) Kit. The Biosensor Module includes eight fluorescent reporters for the intracellular environment; three of them (unfolded protein response, pyruvate metabolism, and ethanol consumption) were newly implemented to complement the original five. The Genome-Integration Module comprises a set of backbone plasmids for the assembly of 1-6 transcriptional units (each consisting of promoter, coding sequence, and terminator) for efficient marker-free single-locus genome integration (in HO and/or X2 loci). Altogether, the ScEnSor Kit enables rapid and easy construction of strains with new transcriptional units as well as high-throughput investigation of the yeast intracellular environment.
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