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Improved production of Taxol® precursors in S. cerevisiae using combinatorial in silico design and metabolic engineering.
Malci, Koray; Santibáñez, Rodrigo; Jonguitud-Borrego, Nestor; Santoyo-Garcia, Jorge H; Kerkhoven, Eduard J; Rios-Solis, Leonardo.
Affiliation
  • Malci K; Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BF, UK. k.malci@imperial.ac.uk.
  • Santibáñez R; Centre for Engineering Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BF, UK. k.malci@imperial.ac.uk.
  • Jonguitud-Borrego N; Department of Bioengineering, Imperial College London, London, SW7 2AZ, UK. k.malci@imperial.ac.uk.
  • Santoyo-Garcia JH; Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0760, USA.
  • Kerkhoven EJ; Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BF, UK.
  • Rios-Solis L; Centre for Engineering Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BF, UK.
Microb Cell Fact ; 22(1): 243, 2023 Nov 29.
Article in En | MEDLINE | ID: mdl-38031061
BACKGROUND: Integrated metabolic engineering approaches that combine system and synthetic biology tools enable the efficient design of microbial cell factories for synthesizing high-value products. In this study, we utilized in silico design algorithms on the yeast genome-scale model to predict genomic modifications that could enhance the production of early-step Taxol® in engineered Saccharomyces cerevisiae cells. RESULTS: Using constraint-based reconstruction and analysis (COBRA) methods, we narrowed down the solution set of genomic modification candidates. We screened 17 genomic modifications, including nine gene deletions and eight gene overexpressions, through wet-lab studies to determine their impact on taxadiene production, the first metabolite in the Taxol® biosynthetic pathway. Under different cultivation conditions, most single genomic modifications resulted in increased taxadiene production. The strain named KM32, which contained four overexpressed genes (ILV2, TRR1, ADE13, and ECM31) involved in branched-chain amino acid biosynthesis, the thioredoxin system, de novo purine synthesis, and the pantothenate pathway, respectively, exhibited the best performance. KM32 achieved a 50% increase in taxadiene production, reaching 215 mg/L. Furthermore, KM32 produced the highest reported yields of taxa-4(20),11-dien-5α-ol (T5α-ol) at 43.65 mg/L and taxa-4(20),11-dien-5-α-yl acetate (T5αAc) at 26.2 mg/L among early-step Taxol® metabolites in S. cerevisiae. CONCLUSIONS: This study highlights the effectiveness of computational and integrated approaches in identifying promising genomic modifications that can enhance the performance of yeast cell factories. By employing in silico design algorithms and wet-lab screening, we successfully improved taxadiene production in engineered S. cerevisiae strains. The best-performing strain, KM32, achieved substantial increases in taxadiene as well as production of T5α-ol and T5αAc. These findings emphasize the importance of using systematic and integrated strategies to develop efficient yeast cell factories, providing potential implications for the industrial production of high-value isoprenoids like Taxol®.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Paclitaxel / Diterpenes Language: En Journal: Microb Cell Fact Journal subject: BIOTECNOLOGIA / MICROBIOLOGIA Year: 2023 Document type: Article Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Paclitaxel / Diterpenes Language: En Journal: Microb Cell Fact Journal subject: BIOTECNOLOGIA / MICROBIOLOGIA Year: 2023 Document type: Article Country of publication: United kingdom