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

• Published in: Nature communications Vol. 6; no. 1; p. 8493
• Main Authors: Oberhardt, Matthew A., Zarecki, Raphy, Gronow, Sabine, Lang, Elke, Klenk, Hans-Peter, Gophna, Uri, Ruppin, Eytan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13-10-2015; Nature Publishing Group; Nature Pub. Group
• Subjects: 631/1647/48; 631/326/88; Culture Media; Culture Techniques; Databases as Topic; Humanities and Social Sciences; multidisciplinary; Natural Language Processing; Phylogeny; Science; Science (multidisciplinary)
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms9493

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.
Culturing new microorganisms requires a great deal of experience, and trial and error. Here, the authors build a database of >3,300 culturing media recipes and >18,000 microbial species that allows the prediction of appropriate media recipes for the growth of new microbes based on their 16S rDNA sequences.