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Computational Approaches to Design and Test Plant Synthetic Metabolic Pathways

  • Successfully designed and implemented plant-specific synthetic metabolic pathways hold promise to increase crop yield and nutritional value. Advances in synthetic biology have already demonstrated the capacity to design artificial biological pathways whose behavior can be predicted and controlled in microbial systems. However, the transfer of these advances to model plants and crops faces the lack of characterization of plant cellular pathways and increased complexity due to compartmentalization and multicellularity. Modern computational developments provide the means to test the feasibility of plant synthetic metabolic pathways despite gaps in the accumulated knowledge of plant metabolism. Here, we provide a succinct systematic review of optimization-based and retrobiosynthesis approaches that can be used to design and in silico test synthetic metabolic pathways in large-scale plant context-specific metabolic models. In addition, by surveying the existing case studies, we highlight the challenges that these approaches face whenSuccessfully designed and implemented plant-specific synthetic metabolic pathways hold promise to increase crop yield and nutritional value. Advances in synthetic biology have already demonstrated the capacity to design artificial biological pathways whose behavior can be predicted and controlled in microbial systems. However, the transfer of these advances to model plants and crops faces the lack of characterization of plant cellular pathways and increased complexity due to compartmentalization and multicellularity. Modern computational developments provide the means to test the feasibility of plant synthetic metabolic pathways despite gaps in the accumulated knowledge of plant metabolism. Here, we provide a succinct systematic review of optimization-based and retrobiosynthesis approaches that can be used to design and in silico test synthetic metabolic pathways in large-scale plant context-specific metabolic models. In addition, by surveying the existing case studies, we highlight the challenges that these approaches face when applied to plants. Emphasis is placed on understanding the effect that metabolic designs can have on native metabolism, particularly with respect to metabolite concentrations and thermodynamics of biochemical reactions. In addition, we discuss the computational developments that may help to transform the identified challenges into opportunities for plant synthetic biology.show moreshow less

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Metadaten
Author details:Anika KükenORCiD, Zoran NikoloskiORCiDGND
DOI:https://doi.org/10.1104/pp.18.01273
ISSN:0032-0889
ISSN:1532-2548
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/30647083
Title of parent work (English):Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants
Publisher:American Society of Plant Physiologists
Place of publishing:Rockville
Publication type:Article
Language:English
Date of first publication:2019/01/15
Publication year:2019
Release date:2021/03/26
Volume:179
Issue:3
Number of pages:13
First page:894
Last Page:906
Funding institution:Max Planck SocietyMax Planck Society
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
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