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.
journal_name
Nat Communjournal_title
Nature communicationsauthors
Oberhardt MA,Zarecki R,Gronow S,Lang E,Klenk HP,Gophna U,Ruppin Edoi
10.1038/ncomms9493subject
Has Abstractpub_date
2015-10-13 00:00:00pages
8493issn
2041-1723pii
ncomms9493journal_volume
6pub_type
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