Project description: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. From the Qinghai Oilfield located in the Tibetan Plateau, northwest China, oil production mixtures were taken from four oil production wells (No. 813, 516, 48 and 27) and one injection well (No. 517) in the Yue-II block. The floating oil and water phases of the production mixtures were separated overnight by gravitational separation. Subsequently, the microbial community and the characteristics of the water solution (W813, W516, W48, and W27) and floating crude oil (O813, O516, O48, and O27) samples were analyzed. A similar analysis was performed with the injection water solution (W517).
Project description: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.
2016-04-01 | GSE55293 | GEO
Project description:metagenome of production water from oil reservoirs
| PRJNA556933 | ENA
Project description:Seasonal succession of microbial community co-occurrence patterns and community assembly mechanism in coal mining subsidence lakes
Project description:The gut microbiome is known to be sensitive to changes in the immune system, especially during autoimmune diseases such as Multiple Sclerosis (MS). Our study examines the changes to the gut microbiome that occur during Experimental Autoimmune Encephalomyelitis (EAE), an animal model for MS. We collected fecal samples at key stages of EAE progression and quantified microbial abundances with 16S V4 amplicon sequencing. Our analysis of the data suggests that commensal Lactobacillaceae fall in abundance during EAE while other commensal populations belonging to the Clostridiaceae, Ruminococcaceae, and Peptostreptococcaceae families expand. Community analysis with microbial co-occurrence networks points to these three taxa as mediators of gut microbiome dysbiosis. We also employed PICRUSt2 to impute MetaCyc Enzyme Consortium (EC) pathway abundances from the original microbial abundance data. From this analysis, we found that a number of imputed EC pathways responsible for the production of compounds with indole groups are enriched in mice undergoing EAE. Our analysis and interpretation of results provides a detailed picture of the changes to the gut microbiome that are occurring throughout the course of EAE disease progression.