IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-19124-x.html
   My bibliography  Save this article

Exploring the synthetic biology potential of bacteriophages for engineering non-model bacteria

Author

Listed:
  • Eveline-Marie Lammens

    (KU Leuven)

  • Pablo Ivan Nikel

    (Technical University of Denmark)

  • Rob Lavigne

    (KU Leuven)

Abstract

Non-model bacteria like Pseudomonas putida, Lactococcus lactis and other species have unique and versatile metabolisms, offering unique opportunities for Synthetic Biology (SynBio). However, key genome editing and recombineering tools require optimization and large-scale multiplexing to unlock the full SynBio potential of these bacteria. In addition, the limited availability of a set of characterized, species-specific biological parts hampers the construction of reliable genetic circuitry. Mining of currently available, diverse bacteriophages could complete the SynBio toolbox, as they constitute an unexplored treasure trove for fully adapted metabolic modulators and orthogonally-functioning parts, driven by the longstanding co-evolution between phage and host.

Suggested Citation

  • Eveline-Marie Lammens & Pablo Ivan Nikel & Rob Lavigne, 2020. "Exploring the synthetic biology potential of bacteriophages for engineering non-model bacteria," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-19124-x
    DOI: 10.1038/s41467-020-19124-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-19124-x
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-020-19124-x?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. Jan Zrimec & Xiaozhi Fu & Azam Sheikh Muhammad & Christos Skrekas & Vykintas Jauniskis & Nora K. Speicher & Christoph S. Börlin & Vilhelm Verendel & Morteza Haghir Chehreghani & Devdatt Dubhashi & Ver, 2022. "Controlling gene expression with deep generative design of regulatory DNA," Nature Communications, Nature, vol. 13(1), pages 1-17, 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:11:y:2020:i:1:d:10.1038_s41467-020-19124-x. 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.