Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity
Optimal gene expression is central for the development of both bacterial expression systems for heterologous protein production, and microbial cell factories for industrial metabolite production. Our goal is to fulfill industry-level overproduction demands optimally, as measured by the following key...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/13/5859 |
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| author | Fernando N. Santos-Navarro Yadira Boada Alejandro Vignoni Jesús Picó |
| author_facet | Fernando N. Santos-Navarro Yadira Boada Alejandro Vignoni Jesús Picó |
| author_sort | Fernando N. Santos-Navarro |
| collection | DOAJ |
| description | Optimal gene expression is central for the development of both bacterial expression systems for heterologous protein production, and microbial cell factories for industrial metabolite production. Our goal is to fulfill industry-level overproduction demands optimally, as measured by the following key performance metrics: titer, productivity rate, and yield (TRY). Here we use a multiscale model incorporating the dynamics of (i) the cell population in the bioreactor, (ii) the substrate uptake and (iii) the interaction between the cell host and expression of the protein of interest. Our model predicts cell growth rate and cell mass distribution between enzymes of interest and host enzymes as a function of substrate uptake and the following main lab-accessible gene expression-related characteristics: promoter strength, gene copy number and ribosome binding site strength. We evaluated the differential roles of gene transcription and translation in shaping TRY trade-offs for a wide range of expression levels and the sensitivity of the TRY space to variations in substrate availability. Our results show that, at low expression levels, gene transcription mainly defined TRY, and gene translation had a limited effect; whereas, at high expression levels, TRY depended on the product of both, in agreement with experiments in the literature. |
| first_indexed | 2024-03-10T10:06:20Z |
| format | Article |
| id | doaj.art-32acfa7597c0494187cd00f01d03e635 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T10:06:20Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-32acfa7597c0494187cd00f01d03e6352023-11-22T01:31:49ZengMDPI AGApplied Sciences2076-34172021-06-011113585910.3390/app11135859Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and ProductivityFernando N. Santos-Navarro0Yadira Boada1Alejandro Vignoni2Jesús Picó3Synthetic Biology and Biosystems Control Laboratory, Institut d’Automática e Informática Industrial, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022 Valencia, SpainSynthetic Biology and Biosystems Control Laboratory, Institut d’Automática e Informática Industrial, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022 Valencia, SpainSynthetic Biology and Biosystems Control Laboratory, Institut d’Automática e Informática Industrial, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022 Valencia, SpainSynthetic Biology and Biosystems Control Laboratory, Institut d’Automática e Informática Industrial, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022 Valencia, SpainOptimal gene expression is central for the development of both bacterial expression systems for heterologous protein production, and microbial cell factories for industrial metabolite production. Our goal is to fulfill industry-level overproduction demands optimally, as measured by the following key performance metrics: titer, productivity rate, and yield (TRY). Here we use a multiscale model incorporating the dynamics of (i) the cell population in the bioreactor, (ii) the substrate uptake and (iii) the interaction between the cell host and expression of the protein of interest. Our model predicts cell growth rate and cell mass distribution between enzymes of interest and host enzymes as a function of substrate uptake and the following main lab-accessible gene expression-related characteristics: promoter strength, gene copy number and ribosome binding site strength. We evaluated the differential roles of gene transcription and translation in shaping TRY trade-offs for a wide range of expression levels and the sensitivity of the TRY space to variations in substrate availability. Our results show that, at low expression levels, gene transcription mainly defined TRY, and gene translation had a limited effect; whereas, at high expression levels, TRY depended on the product of both, in agreement with experiments in the literature.https://www.mdpi.com/2076-3417/11/13/5859metabolic synthetic engineeringhost-aware modelscell burdenbioreactor productionmulti-scale modelstiter-yield-rate |
| spellingShingle | Fernando N. Santos-Navarro Yadira Boada Alejandro Vignoni Jesús Picó Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity Applied Sciences metabolic synthetic engineering host-aware models cell burden bioreactor production multi-scale models titer-yield-rate |
| title | Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity |
| title_full | Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity |
| title_fullStr | Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity |
| title_full_unstemmed | Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity |
| title_short | Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity |
| title_sort | gene expression space shapes the bioprocess trade offs among titer yield and productivity |
| topic | metabolic synthetic engineering host-aware models cell burden bioreactor production multi-scale models titer-yield-rate |
| url | https://www.mdpi.com/2076-3417/11/13/5859 |
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