Proteins identified through predictive metagenomics as potential biomarkers for the detection of microbiologically influenced corrosion

Abstract

The unpredictability of microbial growth and subsequent localized corrosion of steel can cause significant cost for the oil and gas industry, due to production downtime, repair, and replacement. Despite a long tradition of academic research and industrial experience, microbial corrosion is not yet fully understood and thus not effectively controlled. In particular, biomarkers suitable for diagnosing microbial corrosion which abstain from the detection of the classic signatures of sulfate-reducing bacteria are urgently required. In this study, a natural microbial community was enriched anaerobically with carbon steel coupons and in the presence of a variety of physical and chemical conditions. With the characterization of the microbiome and of its functional properties inferred through predictive metagenomics, a series of proteins were identified as biomarkers in the water phase that could be correlated directly to corrosion. This study provides an opportunity for the further development of a protein-based biomarker approach for effective and reliable microbial corrosion detection and monitoring in the field.

Keywords: biomarkers; microbial corrosion; pipeline’s microbiome; predictive metagenomics; sulfate-reducing bacteria.