Abstract
Metabolic engineering holds the promise to transform the chemical industry and to support the transition into a circular bioeconomy, by engineering cellular biocatalysts that efficiently convert sustainable substrates into desired products. However, despite decades of research, the potential of metabolic engineering has only been realized to a limited extent at the industrial level. To further realize its potential, it is essential to optimize the synthetic and native metabolic networks of cell factories at a system and genome-wide level. Here we discuss the tools and strategies enabling system-wide (semi-) rational engineering. Recent advances in genome-editing technologies enable directed genome-wide engineering in a growing number of relevant microorganisms. Such system-wide engineering can benefit from machine learning and other in silico design methods, and it needs to be integrated with efficient screening or selection approaches. These approaches are expected to realize the promise of next-generation cell factories for efficient, sustainable production of a wide range of products.
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Acknowledgements
We thank R. van Kranenburg and E. Orsi for critical reading of this manuscript. S.Y., N.J.C. and J.v.d.O. acknowledge the support of the Dutch Research Council (NWO) via the Gravitation Project BaSyC (024.003.019) and Spinoza (SPI 93-537), awarded to J.v.d.O. In addition, N.J.C. acknowledges support from his NWO Veni fellowship (VI.Veni.192.156). Funding for this research was also provided by the US Department of Energy (DOE) under grant no. DE-FG02-02ER63445 and by the National Science Foundation (NSF) award no. 2123243 (both to G.M.C.). A.N. was supported by the EMBO LTF 160-2019 Long-Term fellowship.
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J.v.d.O. is included as inventor on several CRISPR-related patents and is scientific advisor of NTrans Technologies, Scope Biosciences and Hudson River Biotechnology. G.M.C. is a founder of companies in which he has related financial interests: ReadCoor, EnEvolv and 64x Bio. For a complete list of G.M.C.’s financial interests, see also https://arep.med.harvard.edu/gmc/tech.html. A.N. is an inventor on a patent related to directed evolution with random genomic mutations (DIvERGE) (US patent 10669537B2: Mutagenizing intracellular nucleic acids). The remaining authors declare no competing interests.
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Yilmaz, S., Nyerges, A., van der Oost, J. et al. Towards next-generation cell factories by rational genome-scale engineering. Nat Catal 5, 751–765 (2022). https://doi.org/10.1038/s41929-022-00836-w
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DOI: https://doi.org/10.1038/s41929-022-00836-w
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