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Metabolic engineering of yeast for the production of carbohydrate-derived foods and chemicals from C1–3 molecules

Nature Catalysis volume 7, pages 21–34 (2024)Cite this article

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Abstract

The increase in population-related and environmental issues has emphasized the need for more efficient and sustainable production strategies for foods and chemicals. Carbohydrates are macronutrients sourced from crops and undergone transformation into various products ranging from foods to chemicals. Continuous efforts have led to the identification of a promising hybrid system that couples the electrochemical reduction of CO2 to intermediates containing one to three carbons (C1–3) with the transformation of the intermediates using engineered microorganisms into valuable products. Here we use yeast to transform C1–3 substrates into glucose and structurally tailored glucose derivatives, such as the sugar alcohol myo-inositol, the amino monosaccharide glucosamine, the disaccharide sucrose and the polysaccharide starch. By metabolic rewiring and mitigation of glucose repression, the titre of glucose and sucrose reached dozens of grams per litre. These results provide directions for microbial sugar-derived foods and chemicals production from renewable reduced CO2-based feedstocks.

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Fig. 1: Roadmap for production of glucose-derived chemicals from renewable electricity-driven substrates.
Fig. 2: Biorefinery of renewable raw materials from C1–3 substrates.
Fig. 3: Production of monosaccharide derivatives.
Fig. 4: Production of oligosaccharide and polysaccharide derivatives.
Fig. 5: Metabolic rewiring of S. cerevisiae for glucose overproduction.
Fig. 6: Fed-batch fermentation of C1–3 substrates by engineered strains.

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Acknowledgements

This work was financially supported by the National Key Research and Development Program of China (grant no. 2020YFA0907800 to T.Y.), the National Natural Science Foundation of China (grant no. 32071416 to T.Y. and 22308369 to W.C.), the Shenzhen Institute of Synthetic Biology Scientific Research Program (grant no. JCHZ20200003 to T.Y.), Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines (grant no. ZDSYS20210623091810032 to T.Y.), Key-Area Research and Development Program of Guangdong Province (grant no. 2022B1111080005 to T.Y.), the Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDB0480000 to T.Y.), the National Key Research and Development Program of China (grant no. 2021YFA0911000 to T.Y.), CAS Project for Young Scientists in Basic Research (YSBR-051 to J.Z.), the China Postdoctoral Science Foundation (grant no. 2020M682973 to S.G.) and Guangdong Basic and Applied Basic Research Foundation (grant no. 2020A1515110927 to S.G.). We acknowledge the related fundings supported by China Merchants Research Institute of Advanced Technology Company Limited and China BlueChemical Ltd. We acknowledge the Shenzhen Infrastructure for Synthetic Biology for instrument support and technical assistance with plasmid construction. We thank X. Zhang and L. Xia for critical discussion, and the SIAT Mass Spectrometry Infrastructure for assistance with metabolite analysis.

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  1. These authors contributed equally: Hongting Tang, Lianghuan Wu, Shuyuan Guo.

Authors and Affiliations

  1. Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Key Laboratory of Quantitative Synthetic Biology, Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Hongting Tang, Lianghuan Wu, Shuyuan Guo, Wenbing Cao, Wenhui Ma, Xiang Wang, Junfeng Shen, Menglin Wang, Qiannan Zhang, Xiaozhou Luo, Jay D. Keasling & Tao Yu

  2. Hefei National Research Center for Physical Sciences at the Microscale, Key Laboratory of Strongly-Coupled Quantum Matter Physics of Chinese Academy of Sciences, Key Laboratory of Surface and Interface Chemistry and Energy Catalysis of Anhui Higher Education Institutes, Department of Chemical Physics, University of Science and Technology of China, Hefei, China

    Menglin Wang & Jie Zeng

  3. School of Food Science and Engineering, South China University of Technology, Guangzhou, China

    Mingtao Huang

  4. Joint BioEnergy Institute, Emeryville, CA, USA

    Jay D. Keasling

  5. Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Jay D. Keasling

  6. Department of Chemical and Biomolecular Engineering & Department of Bioengineering, University of California, Berkeley, CA, USA

    Jay D. Keasling

  7. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark

    Jay D. Keasling

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  1. Hongting Tang
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Contributions

T.Y. and J.D.K. conceived this study. H.T., L.W. and S.G. designed and performed most of the experiments, analysed the data and drafted the manuscript. W.M., X.W. and J.S. assisted with the experiments and products detection. W.C. assisted with data analysis and interpretation. M.W., Q.Z., X.L. and J.Z. contributed to the manuscript revision. T.Y., J.D.K. and M.H. revised the manuscript. All authors revised and approved the manuscript.

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Correspondence to Jay D. Keasling or Tao Yu.

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Competing interests

J.D.K. has a financial interest in Amyris, Lygos, Demetrix, Napigen, Maple Bio, Apertor Labs, Zero Acre Farms, Berkeley Yeast and Ansa Biotechnology. X.L. has a financial interest in Demetrix and Synceres. All other authors declare no competing interests.

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Nature Catalysis thanks Yong-Cheol Park, Rodrigo Ledesma-Amaro and Tianwei Tan for their contribution to the peer review of this work.

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Tang, H., Wu, L., Guo, S. et al. Metabolic engineering of yeast for the production of carbohydrate-derived foods and chemicals from C1–3 molecules. Nat Catal 7, 21–34 (2024). https://doi.org/10.1038/s41929-023-01063-7

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