IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-18302-1.html
   My bibliography  Save this article

Engineered systems of inducible anti-repressors for the next generation of biological programming

Author

Listed:
  • Thomas M. Groseclose

    (School of Chemical & Biomolecular Engineering)

  • Ronald E. Rondon

    (School of Chemical & Biomolecular Engineering)

  • Zachary D. Herde

    (School of Chemical & Biomolecular Engineering)

  • Carlos A. Aldrete

    (School of Chemical & Biomolecular Engineering)

  • Corey J. Wilson

    (School of Chemical & Biomolecular Engineering)

Abstract

Traditionally engineered genetic circuits have almost exclusively used naturally occurring transcriptional repressors. Recently, non-natural transcription factors (repressors) have been engineered and employed in synthetic biology with great success. However, transcriptional anti-repressors have largely been absent with regard to the regulation of genes in engineered genetic circuits. Here, we present a workflow for engineering systems of non-natural anti-repressors. In this study, we create 41 inducible anti-repressors. This collection of transcription factors respond to two distinct ligands, fructose (anti-FruR) or D-ribose (anti-RbsR); and were complemented by 14 additional engineered anti-repressors that respond to the ligand isopropyl β-d-1-thiogalactopyranoside (anti-LacI). In turn, we use this collection of anti-repressors and complementary genetic architectures to confer logical control over gene expression. Here, we achieved all NOT oriented logical controls (i.e., NOT, NOR, NAND, and XNOR). The engineered transcription factors and corresponding series, parallel, and series-parallel genetic architectures represent a nascent anti-repressor based transcriptional programming structure.

Suggested Citation

  • Thomas M. Groseclose & Ronald E. Rondon & Zachary D. Herde & Carlos A. Aldrete & Corey J. Wilson, 2020. "Engineered systems of inducible anti-repressors for the next generation of biological programming," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18302-1
    DOI: 10.1038/s41467-020-18302-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-18302-1
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-020-18302-1?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. Yang Gao & Yuchen Zhou & Xudong Ji & Austin J. Graham & Christopher M. Dundas & Ismar E. Miniel Mahfoud & Bailey M. Tibbett & Benjamin Tan & Gina Partipilo & Ananth Dodabalapur & Jonathan Rivnay & Ben, 2024. "A hybrid transistor with transcriptionally controlled computation and plasticity," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Brian D. Huang & Dowan Kim & Yongjoon Yu & Corey J. Wilson, 2024. "Engineering intelligent chassis cells via recombinase-based MEMORY circuits," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    3. Brian D. Huang & Thomas M. Groseclose & Corey J. Wilson, 2022. "Transcriptional programming in a Bacteroides consortium," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    4. Andrew E. Short & Dowan Kim & Prasaad T. Milner & Corey J. Wilson, 2023. "Next generation synthetic memory via intercepting recombinase function," Nature Communications, Nature, vol. 14(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_s41467-020-18302-1. 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.