Gel-based proteomics as a tool for increased recovery of extra heavy crude oil
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Two-thirds of the world s remaining oil reserves are made up of heavy and extra heavy crude oils (EHOs). EHOs have a high viscosity due to their complex chemical structure. Production, transport and refining of these are therefore expensive, both from an economic and from an environmental view. Hence, the petroleum industry is seeking improved methods for extraction and upgrading. A proposed method is to take advantage of microorganisms that are adapted to the harsh conditions in the reservoirs, and have the ability to digest components from EHOs, thus making these oils less viscous. To use such organisms, understanding the metabolic pathways responsible for these changes is of high interest. Proteomic approaches have the technology to separate proteins and in so doing making them available for identification. A recently developed field of metaproteomics enables all proteins recovered directly from an environmental sample to be analyzed as one large unit. Two-dimensional difference gel electrophoresis (DIGE) allows for semi-quantitative protein expression analysis of up to three protein samples simultaneously on the same gel, and with statistical analysis, proteins of interest can be marked for identification. Bioconversion experiments were carried out with the purpose of identifying enzymes and metabolic pathways from the metaproteome of a microbial community using DIGE. Microbial consortium, obtained from an environmental sample collected near one of Statoil ASA s oil fields, was grown on EHOs in an aqueous minimal mineral (MM) medium. Four replicate shaker flasks were prepared for each day of sampling performed after the 1st, 2nd, 3rd or 7th day of bioconversion. Upon sampling, proteins from the lyophilized growth medium were phenol extracted followed by methanol/ammonium-acetate precipitation and resuspended in lysis buffer. One-dimensional gel electrophoresis (1-D GE) was performed to ensure presence of proteins, and Bradford assay was used to quantify proteins in the samples. An internal standard together with two different samples were stained and pooled prior to DIGE. The resulting gels were scanned and analyzed using statistical software for proteomic data. Using the same software, results from this experiment were compared with an analogous experiment using an enriched mineral medium with acetate and yeast extract (MMAcYE) EHOs exposed to microorganisms became to a varying degree emulsified in the growth medium. Overall, the protein content in the water phase was low. From ANOVA calculations, a total of 332 spots were detected on the reference gel of which 25 spots had a p-value of <0.05 and seven spots with the cut-off values of p <0.5 and >2 fold change in spot volume throughout bioconversion. This low number of spots indicated high variance between replicates and that few proteins had a significant average up/down regulation of expression profile between days of sampling. According to the power analysis where 0.80 is considered an acceptable value, a sample size of 33 replicates was necessary to find a significant difference between groups. Based on these statistical calculations further identification of spots was not performed. Still, as the oil s appearance was clearly changing during bioconversion, further work could give valuable information. An earlier performed DIGE experiment using MMAcYE gave a total of 612 spots of which 377 spots had a p-value of <0.05. A total of 38 proteins were identified using MALDI-ToF/ToF MS. By comparing these two experiments, nine of the spots with protein identification were found on the MM gels, indicating similar protein. Spot pattern between the experiments is also similar.