Genome repository of oil systems: An interactive and searchable database that expands the catalogued diversity of crude oil‐associated microbes

Abstract

Summary Microbial communities ultimately control the fate of petroleum hydrocarbons (PHCs) that enter the natural environment, but the interactions of microbes with PHCs and the environment are highly complex and poorly understood. Genome‐resolved metagenomics can help unravel these complex interactions. However, the lack of a comprehensive database that integrates existing genomic/metagenomic data from oil environments with physicochemical parameters known to regulate the fate of PHCs currently limits data analysis and interpretations. Here, we curated a comprehensive, searchable database that documents microbial populations in natural oil ecosystems and oil spills, along with available underlying physicochemical data, geocoded via geographic information system to reveal their geographic distribution patterns. Analysis of the ~2000 metagenome‐assembled genomes (MAGs) available in the database revealed strong ecological niche specialization within habitats. Over 95% of the recovered MAGs represented novel taxa underscoring the limited representation of cultured organisms from oil‐contaminated and oil reservoir ecosystems. The majority of MAGs linked to oil‐contaminated ecosystems were detectable in non‐oiled samples from the Gulf of Mexico but not in comparable samples from elsewhere, indicating that the Gulf is primed for oil biodegradation. The repository should facilitate future work toward a predictive understanding of the microbial taxa and their activities that control the fate of oil spills.

A novel, divergent alkane monooxygenase (alkB) clade involved in crude oil biodegradation

“…Crude oil composition is highly complex, depending on the reservoir source and its underlying biogeochemistry (Overton et al ., 2016). However, once the crude oil is released into to the environment, its components undergo rapid changes, which are highly dependent on the in situ physicochemical conditions, most notably prevailing temperatures, level of sunlight and microbial biotransformation (Prince et al ., 2010; Shao and Wang, 2013; Lea‐Smith et al ., 2015; Karthikeyan et al ., 2020a). Following the Deepwater Horizon (DWH) accident in April of 2010, massive amounts of crude oil were released into the Gulf of Mexico (GoM) in a short period of time (McNutt et al ., 2012; Reddy et al ., 2012).…”

“…Most of the earlier studies describing alkB sequences and their phylogenetic distribution across clades were elucidated using previously characterized isolated organisms or through targeted amplicon PCR efforts based on primers from isolate genomes (Wang et al ., 2010; Shao and Wang, 2013; Smith et al ., 2013; (Nie et al ., 2014). Yet, recent work has shown that the great majority of the microbial populations responding to crude oil, especially in coastal habitats affected by the DWH spill (>95% of the total), represent novel taxa not closely related to the previously isolated organisms (Karthikeyan et al ., 2020a). Previous oligotyping‐based studies also indicated that diverse taxa from the rare biosphere dominated the microbial community associated with the deep‐sea plume (Kleindienst et al ., 2015).…”

MAGNETO: an automated workflow for genome-resolved metagenomics

“…Historically, metagenomic compositional distances have mainly been used to compare metagenomic samples (30) or MAGs (14), but not to actually guide the co-assembly process. Though, a few recent studies have started to use metagenomic-based distances combined with clustering to guide the co-assembly process of metagenomes (31, 32, 33), while another study has used metagenomic distances to guide the co-binning (or co-mapping) process (34). Here, we computed distances between metagenomes using Simka (35), and identified optimal clustering solutions using the Silhouette index (36) to delineate unsupervised sets of samples to co-assemble.…”

Bacteria From the Southern Gulf of Mexico: Baseline, Diversity, Hydrocarbon-Degrading Potential and Future Applications

“…When published, the tool will be the first system capable of exploring metagenomic information related to the microbial diversity and metabolic potential of the sGoM. This system may complement other tools such as the GROS database, which gathers sequenced genomes with hydrocarbon-degrading capabilities (Karthikeyan et al, 2020).…”