Beyond CEN.PK - parallel engineering of selected S. cerevisiae strains reveals that superior chassis strains require different engineering approaches for limonene production
IF 6.8 1区 生物学Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Yanmei Zhu , Sasha Yogiswara , Anke Willekens , Agathe Gérardin , Rob Lavigne , Alain Goossens , Vitor B. Pinheiro , Zongjie Dai , Kevin J. Verstrepen
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引用次数: 0
Abstract
Genetically engineered microbes are increasingly utilized to produce a broad range of high-value compounds. However, most studies start with only a very narrow group of genetically tractable type strains that have not been selected for maximum titers or industrial robustness. In this study, we used high-throughput screening and parallel metabolic engineering to identify and optimize Saccharomyces cerevisiae chassis strains for the production of limonene, a monoterpene with applications in flavors, fragrances, and biofuels. We screened 921 genetically and phenotypically distinct S. cerevisiae strains for limonene tolerance and lipid content to identify optimal chassis strains for precision fermentation of limonene. In parallel, we also evaluated 16 different plant limonene synthases. Our results revealed that two of the selected strains showed approximately a 2-fold increase in titers compared to CEN.PK2-1C, the type strain that is often used as a chassis for limonene production, with the same genetic modifications in the mevalonate pathway. Intriguingly, the most effective engineering strategy proved strain-specific. Metabolic profiling revealed that this difference is likely explained by differences in native mevalonate production. Ultimately, by using strain-specific engineering strategies, we achieved 844 mg/L in a new strain, 40 % higher than the titer (605 mg/L) achieved by CEN.PK2-1C. Our findings demonstrate the potential of leveraging genetic diversity in S. cerevisiae for monoterpene bioproduction and highlight the necessity for tailoring metabolic engineering strategies to specific strains.
期刊介绍:
Metabolic Engineering (MBE) is a journal that focuses on publishing original research papers on the directed modulation of metabolic pathways for metabolite overproduction or the enhancement of cellular properties. It welcomes papers that describe the engineering of native pathways and the synthesis of heterologous pathways to convert microorganisms into microbial cell factories. The journal covers experimental, computational, and modeling approaches for understanding metabolic pathways and manipulating them through genetic, media, or environmental means. Effective exploration of metabolic pathways necessitates the use of molecular biology and biochemistry methods, as well as engineering techniques for modeling and data analysis. MBE serves as a platform for interdisciplinary research in fields such as biochemistry, molecular biology, applied microbiology, cellular physiology, cellular nutrition in health and disease, and biochemical engineering. The journal publishes various types of papers, including original research papers and review papers. It is indexed and abstracted in databases such as Scopus, Embase, EMBiology, Current Contents - Life Sciences and Clinical Medicine, Science Citation Index, PubMed/Medline, CAS and Biotechnology Citation Index.