IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v7y2016i1d10.1038_ncomms12971.html
   My bibliography  Save this article

Forward design of a complex enzyme cascade reaction

Author

Listed:
  • Christoph Hold

    (Department of Biosystems Science and Engineering)

  • Sonja Billerbeck

    (Department of Biosystems Science and Engineering
    Present address: Department of Systems Biology, Columbia University, 1130 St Nicholas Avenue, New York, New York 10032, USA)

  • Sven Panke

    (Department of Biosystems Science and Engineering)

Abstract

Enzymatic reaction networks are unique in that one can operate a large number of reactions under the same set of conditions concomitantly in one pot, but the nonlinear kinetics of the enzymes and the resulting system complexity have so far defeated rational design processes for the construction of such complex cascade reactions. Here we demonstrate the forward design of an in vitro 10-membered system using enzymes from highly regulated biological processes such as glycolysis. For this, we adapt the characterization of the biochemical system to the needs of classical engineering systems theory: we combine online mass spectrometry and continuous system operation to apply standard system theory input functions and to use the detailed dynamic system responses to parameterize a model of sufficient quality for forward design. This allows the facile optimization of a 10-enzyme cascade reaction for fine chemical production purposes.

Suggested Citation

  • Christoph Hold & Sonja Billerbeck & Sven Panke, 2016. "Forward design of a complex enzyme cascade reaction," Nature Communications, Nature, vol. 7(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12971
    DOI: 10.1038/ncomms12971
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms12971
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms12971?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bob Sluijs & Tao Zhou & Britta Helwig & Mathieu G. Baltussen & Frank H. T. Nelissen & Hans A. Heus & Wilhelm T. S. Huck, 2024. "Iterative design of training data to control intricate enzymatic reaction networks," Nature Communications, Nature, vol. 15(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12971. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.