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Combinatorial assembly platform enabling engineering of genetically stable metabolic pathways in cyanobacteria

Taylor, George M.; Hitchcock, Andrew; Heap, John T

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Authors

George M. Taylor

Andrew Hitchcock

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JOHN HEAP JOHN.HEAP@NOTTINGHAM.AC.UK
Associate Professor



Abstract

Cyanobacteria are simple, efficient, genetically-tractable photosynthetic microorganisms which in principle represent ideal biocatalysts for CO2 capture and conversion. However, in practice, genetic instability and low productivity are key, linked problems in engineered cyanobacteria. We took a massively parallel approach, generating and characterising libraries of synthetic promoters and RBSs for the cyanobacterium Synechocystis sp. PCC 6803, and assembling a sparse combinatorial library of millions of metabolic pathway-encoding construct variants. Genetic instability was observed for some variants, which is expected when variants cause metabolic burden. Surprisingly however, in a single combinatorial round without iterative optimisation, 80% of variants chosen at random and cultured photoautotrophically over many generations accumulated the target terpenoid lycopene from atmospheric CO2, apparently overcoming genetic instability. This large-scale parallel metabolic engineering of cyanobacteria provides a new platform for development of genetically stable cyanobacterial biocatalysts for sustainable light-driven production of valuable products directly from CO2, avoiding fossil carbon or competition with food production.

Citation

Taylor, G. M., Hitchcock, A., & Heap, J. T. (2021). Combinatorial assembly platform enabling engineering of genetically stable metabolic pathways in cyanobacteria. Nucleic Acids Research, 49(21), e123-e123. https://doi.org/10.1093/nar/gkab791

Journal Article Type Article
Acceptance Date Aug 28, 2021
Online Publication Date Sep 23, 2021
Publication Date Dec 2, 2021
Deposit Date Sep 9, 2021
Publicly Available Date Mar 29, 2024
Journal Nucleic Acids Research
Print ISSN 0305-1048
Electronic ISSN 1362-4962
Publisher Oxford University Press (OUP)
Peer Reviewed Peer Reviewed
Volume 49
Issue 21
Pages e123-e123
DOI https://doi.org/10.1093/nar/gkab791
Keywords Genetics
Public URL https://nottingham-repository.worktribe.com/output/6189036
Publisher URL https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab791/6374482

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