Succession in the petroleum reservoir microbiome through an oil field production lifecycle.

Subsurface petroleum reservoirs are an important component of the deep biosphere where indigenous microorganisms live under extreme conditions and in isolation from the Earth's surface for millions of years. However, unlike the bulk of the deep biosphere, the petroleum reservoir deep biosphere is subject to extreme anthropogenic perturbation, with the introduction of new electron acceptors, donors and exogenous microbes during oil exploration and production. Despite the fundamental and practical significance of this perturbation, there has never been a systematic evaluation of the ecological changes that occur over the production lifetime of an active offshore petroleum production system. Analysis of the entire Halfdan oil field in the North Sea (32 producing wells in production for 1-15 years) using quantitative PCR, multigenic sequencing, comparative metagenomic and genomic bins reconstruction revealed systematic shifts in microbial community composition and metabolic potential, as well as changing ecological strategies in response to anthropogenic perturbation of the oil field ecosystem, related to length of time in production. The microbial communities were initially dominated by slow growing anaerobes such as members of the Thermotogales and Clostridiales adapted to living on hydrocarbons and complex refractory organic matter. However, as seawater and nitrate injection (used for secondary oil production) delivered oxidants, the microbial community composition progressively changed to fast growing opportunists such as members of the Deferribacteres, Delta-, Epsilon- and Gammaproteobacteria, with energetically more favorable metabolism (for example, nitrate reduction, H2S, sulfide and sulfur oxidation). This perturbation has profound consequences for understanding the microbial ecology of the system and is of considerable practical importance as it promotes detrimental processes such as reservoir souring and metal corrosion. These findings provide a new conceptual framework for understanding the petroleum reservoir biosphere and have consequences for developing strategies to manage microbiological problems in the oil industry.

Complementary Microorganisms in Highly Corrosive Biofilms from an Offshore Oil Production Facility.

Offshore oil production facilities are frequently victims of internal piping corrosion, potentially leading to human and environmental risks and significant economic losses. Microbially influenced corrosion (MIC) is believed to be an important factor in this major problem for the petroleum industry. However, knowledge of the microbial communities and metabolic processes leading to corrosion is still limited. Therefore, the microbial communities from three anaerobic biofilms recovered from the inside of a steel pipe exhibiting high corrosion rates, iron oxide deposits, and substantial amounts of sulfur, which are characteristic of MIC, were analyzed in detail. Bacterial and archaeal community structures were investigated by automated ribosomal intergenic spacer analysis, multigenic (16S rRNA and functional genes) high-throughput Illumina MiSeq sequencing, and quantitative PCR analysis. The microbial community analysis indicated that bacteria, particularly Desulfovibrio species, dominated the biofilm microbial communities. However, other bacteria, such as Pelobacter, Pseudomonas, and Geotoga, as well as various methanogenic archaea, previously detected in oil facilities were also detected. The microbial taxa and functional genes identified suggested that the biofilm communities harbored the potential for a number of different but complementary metabolic processes and that MIC in oil facilities likely involves a range of microbial metabolisms such as sulfate, iron, and elemental sulfur reduction. Furthermore, extreme corrosion leading to leakage and exposure of the biofilms to the external environment modify the microbial community structure by promoting the growth of aerobic hydrocarbon-degrading organisms.

Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem.

We have constructed a conceptual model of biogeochemical cycles and metabolic and microbial community shifts within a hot spring ecosystem via coordinated analysis of the "Bison Pool" (BP) Environmental Genome and a complementary contextual geochemical dataset of ~75 geochemical parameters. 2,321 16S rRNA clones and 470 megabases of environmental sequence data were produced from biofilms at five sites along the outflow of BP, an alkaline hot spring in Sentinel Meadow (Lower Geyser Basin) of Yellowstone National Park. This channel acts as a >22 m gradient of decreasing temperature, increasing dissolved oxygen, and changing availability of biologically important chemical species, such as those containing nitrogen and sulfur. Microbial life at BP transitions from a 92 °C chemotrophic streamer biofilm community in the BP source pool to a 56 °C phototrophic mat community. We improved automated annotation of the BP environmental genomes using BLAST-based Markov clustering. We have also assigned environmental genome sequences to individual microbial community members by complementing traditional homology-based assignment with nucleotide word-usage algorithms, allowing more than 70% of all reads to be assigned to source organisms. This assignment yields high genome coverage in dominant community members, facilitating reconstruction of nearly complete metabolic profiles and in-depth analysis of the relation between geochemical and metabolic changes along the outflow. We show that changes in environmental conditions and energy availability are associated with dramatic shifts in microbial communities and metabolic function. We have also identified an organism constituting a novel phylum in a metabolic "transition" community, located physically between the chemotroph- and phototroph-dominated sites. The complementary analysis of biogeochemical and environmental genomic data from BP has allowed us to build ecosystem-based conceptual models for this hot spring, reconstructing whole metabolic networks in order to illuminate community roles in shaping and responding to geochemical variability.