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

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 Commun

journal_title

Nature communications

authors

Oberhardt MA,Zarecki R,Gronow S,Lang E,Klenk HP,Gophna U,Ruppin E

doi

10.1038/ncomms9493

subject

Has Abstract

pub_date

2015-10-13 00:00:00

pages

8493

issn

2041-1723

pii

ncomms9493

journal_volume

6

pub_type

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