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A metagenomic study revealing unexpectedly diverse functional groups in microbial communities of deep-ground oil

ABSTRACT: Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples.

ORGANISM(S): uncultured bacterium Bacteria

PROVIDER: GSE55293 | GEO | 2016/04/01

SECONDARY ACCESSION(S): PRJNA239233

REPOSITORIES: GEO

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Project description:Time is often not characterized as a variable in ecotoxicogenomic studies. In this study, the temporal kinetics in gene expression were determined during exposure to crude oil and a subsequent recovery period. Juvenile rainbow trout, Oncorhynchus mykiss, were exposed for 96 hours to the water accomodated fractions of 0.4, 2 or 10 mg l-1 crude oil loadings. Following 96 h of exposure, fish were transferred to recovery tanks for 96 h. Gill and liver samples were collected after 24 and 96 h of exposure, and after 96 h of recovery for RNA extraction and microarray analysis. Fluorescently labeled cDNA was hybridized against matched controls, using salmonid cDNA arrays. Each exposure scenario generated unique patterns of altered gene expression. More genes responded to crude oil in the gill than in liver. In the gill, 1137 genes had altered expression at 24 hours, 2003 genes had altered expression levels at 96 h of exposure, yet by 96 h of recovery, no genes were significant ly altered in expression. The Gene Ontology terms associated with gill-responsive genes implicated membrane narcosis, a toxic mechanism for crude oil. By contrast, in the liver at 10 mg l-1, only five genes were changed at 24 h, yet 192 genes had altered expression after 96 h recovery. At 2 mg l-1 in the liver, many genes had altered regulation at all three timepoints. The 0.4 mg l-1 loading also showed 289 genes upregulated at 24 h after exposure. The Gene Ontology terms associated with altered expression in the liver suggested that the processes of protein synthesis, xenobiotic metabolism, and oxidoreductase activity were altered. The concentration-responsive expression profile of cytochrome P450 1A, a biomarker for oil exposure, did not predict the majority of gene expression profiles in any tissue or dose, since direct relationships with dose were not observed for most genes. While the genes and their associated functions agree with known modes of toxic action for crude oil, the gene lists obtained do not agree with our previously published work, presumably due to array analysis procedures. These results demonstrate that changes in gene expression with time and dose should be characterized in controlled laboratory settings before responses from field collected organisms are interpreted, and that processes for analyzing microarray data need to be developed such that standardized gene lists are developed, or that analysis is gene list independent before arrays are as a monitoring tool.

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A metagenomic study revealing unexpectedly diverse functional groups in microbial communities of deep-ground oil

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