IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v6y2015i1d10.1038_ncomms9493.html
   My bibliography  Save this article

Harnessing the landscape of microbial culture media to predict new organism–media pairings

Author

Listed:
  • Matthew A. Oberhardt

    (Blavatnik School of Computer Sciences and Sackler School of Medicine, Tel Aviv University
    Faculty of Life Sciences, Tel Aviv University
    Center for Bioinformatics and Computational Biology (CBCB), and University of Maryland, Institute of Advanced Computer Science (UMIACS), University of Maryland, College Park)

  • Raphy Zarecki

    (Blavatnik School of Computer Sciences and Sackler School of Medicine, Tel Aviv University)

  • Sabine Gronow

    (Leibniz Institute DSMZ—German Collection of Microorganisms and Cell Cultures)

  • Elke Lang

    (Leibniz Institute DSMZ—German Collection of Microorganisms and Cell Cultures)

  • Hans-Peter Klenk

    (School of Biology, Newcastle University)

  • Uri Gophna

    (Faculty of Life Sciences, Tel Aviv University)

  • Eytan Ruppin

    (Blavatnik School of Computer Sciences and Sackler School of Medicine, Tel Aviv University
    Center for Bioinformatics and Computational Biology (CBCB), and University of Maryland, Institute of Advanced Computer Science (UMIACS), University of Maryland, College Park)

Abstract

Culturing microorganisms is a critical step in understanding and utilizing microbial life. Here we map the landscape of existing culture media by extracting natural-language media recipes into a Known Media Database (KOMODO), which includes >18,000 strain–media combinations, >3300 media variants and compound concentrations (the entire collection of the Leibniz Institute DSMZ repository). Using KOMODO, we show that although media are usually tuned for individual strains using biologically common salts, trace metals and vitamins/cofactors are the most differentiating components between defined media of strains within a genus. We leverage KOMODO to predict new organism–media pairings using a transitivity property (74% growth in new in vitro experiments) and a phylogeny-based collaborative filtering tool (83% growth in new in vitro experiments and stronger growth on predicted well-scored versus poorly scored media). These resources are integrated into a web-based platform that predicts media given an organism’s 16S rDNA sequence, facilitating future cultivation efforts.

Suggested Citation

  • Matthew A. Oberhardt & Raphy Zarecki & Sabine Gronow & Elke Lang & Hans-Peter Klenk & Uri Gophna & Eytan Ruppin, 2015. "Harnessing the landscape of microbial culture media to predict new organism–media pairings," Nature Communications, Nature, vol. 6(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9493
    DOI: 10.1038/ncomms9493
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms9493
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms9493?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
    ---><---

    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:6:y:2015:i:1:d:10.1038_ncomms9493. 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.