RT Journal Article
SR Electronic
T1 Genome Repository of Oiled Systems (GROS): an interactive and searchable database that expands the catalogued diversity of crude oil-associated microbes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 838573
DO 10.1101/838573
A1 Smruthi Karthikeyan
A1 Luis M. Rodriguez-R
A1 Patrick Heritier-Robbins
A1 Janet K. Hatt
A1 Markus Huettel
A1 Joel E. Kostka
A1 Konstantinos T. Konstantinidis
YR 2019
UL http://biorxiv.org/content/early/2019/11/12/838573.abstract
AB Indigenous microbial communities ultimately control the fate of petroleum hydrocarbons (PHCs) that enters the natural environment through natural seeps or accidental oil spills, but the interactions among microbes and with their chemical environment during oil biodegradation are highly complex and poorly understood. Genome-resolved metagenomics have the potential to help in unraveling these complex interactions. However, the lack of a comprehensive database that integrates existing genomic/metagenomic data from oiled environments with physicochemical parameters known to regulate the fate of PHCs currently limits data analysis and interpretations. Here, we present a curated, comprehensive, and searchable database that documents microbial populations in oiled ecosystems on a global scale, along with underlying physicochemical data, geocoded via GIS to reveal geographic distribution patterns of the populations. Analysis of the ~2,000 metagenome-assembled genomes (MAGs) available in the database revealed strong ecological niche specialization within habitats e.g., specialization to coastal sediments vs. water-column vs. deep-sea sediments. Over 95% of the recovered MAGs represented novel and uncultured species underscoring the limited representation of cultured organisms from oil-contaminated and oil reservoir ecosystems. The majority of MAGs linked to oiled ecosystems are members of the rare biosphere in non-oiled samples, except for the Gulf of Mexico (GoM) which appears to be primed for oil biodegradation. GROS should facilitate future work toward a more predictive understanding of the microbial taxa and their activities that control the fate of oil spills as well as serve as a model approach for building similar resources for additional environmental processes and omic data of interest.