MediaDB: A Database of Microbial Growth Conditions in Defined Media

Abstract

Isolating pure microbial cultures and cultivating them in the laboratory on defined media is used to more fully characterize the metabolism and physiology of organisms. However, identifying an appropriate growth medium for a novel isolate remains a challenging task. Even organisms with sequenced and annotated genomes can be difficult to grow, despite our ability to build genome-scale metabolic networks that connect genomic data with metabolic function. The scientific literature is scattered with information about defined growth media used successfully for cultivating a wide variety of organisms, but to date there exists no centralized repository to inform efforts to cultivate less characterized organisms by bridging the gap between genomic data and compound composition for growth media. Here we present MediaDB, a manually curated database of defined media that have been used for cultivating organisms with sequenced genomes, with an emphasis on organisms with metabolic network models. The database is accessible online, can be queried by keyword searches or downloaded in its entirety, and can generate exportable individual media formulation files. The data assembled in MediaDB facilitate comparative studies of organism growth media, serve as a starting point for formulating novel growth media, and contribute to formulating media for in silico investigation of metabolic networks. MediaDB is freely available for public use at https://mediadb.systemsbiology.net.

Correlating enzyme annotations with a large set of microbial growth temperatures reveals metabolic adaptations to growth at diverse temperatures

“…Several other resources provide similar data, but with a more limited scope. For example; BacDive (Söhngen et al 2014(Söhngen et al , 2015 contains growth temperatures for~10,000 species, MediaDB (Richards et al 2014) for less than 200 species and finally, the IJSEM phenotypic database provide the growth temperature for 4,365 strains, with the number of represented species being fewer (Barberán et al 2017) . There is a very high proportion of mesophilic organisms compared to thermophilic ones in the collected dataset ( Figure 1C).…”

“…The most comprehensive of these is BacDive (Söhngen et al 2014(Söhngen et al , 2015 which was created by digitizing and mining analog records containing microbial metadata (Reimer et al 2017) . Other resources include MediaDB, which offers a hand-curated database for microbial growth conditions (Richards et al 2014) . Records regarding the phenotypic and environmental tolerance for over 5,000 species has also been made available (Barberán et al 2017) .…”

Data-driven integration of genome-scale regulatory and metabolic network models

“…As many metabolic pathways are broadly conserved, these curated CBMs can serve as scaffolds for automated reconstruction of high-quality organism-specific CBMs for closely related organism using genomic information, conceivably making high-quality CBMs available for any sequenced organism, while minimizing the need for manual curation (Henry et al, 2010 ; Karp et al, 2010 ; Swainston et al, 2011 ; Agren et al, 2013 ; Benedict et al, 2014 ). Furthermore, computational tools and databases that facilitate automated identification of biomass components (Tervo and Reed, 2013 ) and minimal media composition (Richards et al, 2014 ) should further streamline this process.…”

Transparency in metabolic network reconstruction enables scalable biological discovery

“…Such computational approaches are significantly faster and less expensive than biochemical characterization [7]. They are also providing new resources facilitate cultivation of novel environmental isolates [8], and the scope of draft metabolic network coverage across the biome has increased much faster than wet lab characterization. If the distinction between reconstruction and model formulation can be strengthened and supported through software implementation, there is great opportunity for using both tasks to further advance rapid discovery of biological function.…”