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Genome-Resolved Metagenomics Enables Method Optimization for Microbiological Oilfield Monitoring

The oil and gas industry’s efforts to characterize microbial communities in oilfield process fluids has shed increasing light on the influence of bacteria and archaea on hydrocarbon production. Notably topside or downhole water contamination by prokaryotes such as sulfate-reducing bacteria acid-producing bacteria and/or other halophiles can negatively impact asset integrity and reduce the quality and/or quantity of produced oil and gas. Molecular microbiology methods have contributed to our understanding of these complex processes by providing unprecedented resolution of resident microbial communities. However a lack of methodological consistency among industry and academic laboratories studying microbiological processes in oilfield systems has precluded the industry’s ability to discern broad cause-and-effect trends or compare results across laboratories. For example there exists no standard primer set for 16S rRNA gene amplicon sequencing agreed upon by the oil and gas community.Recently Dow Microbial Control and The Ohio State University partnered to perform a comprehensive microbial audit of multiple unconventional upstream operations. Over the course of the audit samples were systematically taken during drilling throughout completions and periodically over the first year of production. Produced water samples were submitted for whole-genome metagenomic sequencing and assembly with near-complete genomes for input microbes and reservoir-colonizing microbes subsequently resolved. By creating this genome-resolved metagenomic dataset we removed the PCR bias of any given 16S primer set allowing for comparison and curation of common 16S rRNA gene primer sets and elucidation of the most appropriate sequencing methodology for oilfield samples. Ultimately the use of validated molecular microbiological methods among the oilfield industry will more quickly advance our understanding of microbiological processes in these systems.

Product Number: 51319-13442-SG
Author: Joseph Moore
Publication Date: 2019
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