Metabolomic and metagenomic analysis of two crude oil production pipelines experiencing differential rates of corrosion

Corrosion processes in two North Sea oil production pipelines were studied by analyzing pig envelope samples via metagenomic and metabolomic techniques. Both production systems have similar physico-chemical properties and injection waters are treated with nitrate, but one pipeline experiences severe corrosion and the other does not. Early and late pigging material was collected to gain insight into the potential causes for differential corrosion rates. Metabolites were extracted and analyzed via ultra-high performance liquid chromatography/high-resolution mass spectrometry with electrospray ionization (ESI) in both positive and negative ion modes. Metabolites were analyzed by comparison with standards indicative of aerobic and anaerobic hydrocarbon metabolism and by comparison to predicted masses for KEGG metabolites. Microbial community structure was analyzed via 16S rRNA gene qPCR, sequencing of 16S PCR products, and MySeq Illumina shotgun sequencing of community DNA. Metagenomic data were used to reconstruct the full length 16S rRNA genes and genomes of dominant microorganisms. Sequence data were also interrogated via KEGG annotation and for the presence of genes related to terminal electron accepting (TEA) processes as well as aerobic and anaerobic hydrocarbon degradation. Significant and distinct differences were observed when comparing the ‘high corrosion’ (HC) and the ‘low corrosion’ (LC) pipeline systems, especially with respect to the TEA utilization potential. The HC samples were dominated by sulfate-reducing bacteria (SRB) and archaea known for their ability to utilize simple carbon substrates, whereas LC samples were dominated by pseudomonads with the genetic potential for denitrification and aerobic hydrocarbon degradation. The frequency of aerobic hydrocarbon degradation genes was low in the HC system, and anaerobic hydrocarbon degradation genes were not detected in either pipeline. This is in contrast with metabolite analysis, which demonstrated the presence of several succinic acids in HC samples that are diagnostic of anaerobic hydrocarbon metabolism. Identifiable aerobic metabolites were confined to the LC samples, consistent with the metagenomic data. Overall, these data suggest that corrosion management might benefit from a more refined understanding of microbial community resilience in the face of disturbances such as nitrate treatment or pigging, which frequently prove insufficient to alter community structure toward a stable, less-corrosive assemblage.This work was supported in part by grants from the University of Oklahoma Biocorrosion Center, the National Science Foundation (OCE 1634630 and MCB 1329890) and BP (The Gulf of Mexico Research Initiative, Project No. 130206). The instrumentation for the metabolomic analysis was funded by ONR through a DURIP grant (Award no. N000140910797), and the method development by ONR through a MURI grant (Award no. N000141010946).Ye

Some memories are odder than others : Judgments of episodic oddity violate known decision rules

Current decision models of recognition memory are based almost entirely on one paradigm, single item old/new judgments accompanied by confidence ratings. This task results in receiver operating characteristics (ROCs) that are well fit by both signal-detection and dual-process models. Here we examine an entirely new recognition task, the judgment of episodic oddity, whereby participants select the mnemonically odd members of triplets (e.g., a new item hidden among two studied items). Using the only two known signal-detection rules of oddity judgment derived from the sensory perception literature, the unequal variance signal-detection model predicted that an old item among two new items would be easier to discover than a new item among two old items. In contrast, four separate empirical studies demonstrated the reverse pattern: triplets with two old items were the easiest to resolve. This finding was anticipated by the dual-process approach as the presence of two old items affords the greatest opportunity for recollection. Furthermore, a bootstrap-fed Monte Carlo procedure using two independent datasets demonstrated that the dual-process parameters typically observed during single item recognition correctly predict the current oddity findings, whereas unequal variance signal-detection parameters do not. Episodic oddity judgments represent a case where dual- and single-process predictions qualitatively diverge and the findings demonstrate that novelty is "odder" than familiarity.PreprintPeer reviewe

Metabolomic and Metagenomic Analysis of Two Crude Oil Production Pipelines Experiencing Differential Rates of Corrosion

Corrosion processes in two North Sea oil production pipelines were studied by analyzing pig envelope samples via metagenomic and metabolomic techniques. Both production systems have similar physico-chemical properties and injection waters are treated with nitrate, but one pipeline experiences severe corrosion and the other does not. Early and late pigging material was collected to gain insight into the potential causes for differential corrosion rates. Metabolites were extracted and analyzed via ultra-high performance liquid chromatography/high-resolution mass spectrometry with electrospray ionization (ESI) in both positive and negative ion modes. Metabolites were analyzed by comparison with standards indicative of aerobic and anaerobic hydrocarbon metabolism and by comparison to predicted masses for KEGG metabolites. Microbial community structure was analyzed via 16S rRNA gene qPCR, sequencing of 16S PCR products, and MySeq Illumina shotgun sequencing of community DNA. Metagenomic data were used to reconstruct the full length 16S rRNA genes and genomes of dominant microorganisms. Sequence data were also interrogated via KEGG annotation and for the presence of genes related to terminal electron accepting (TEA) processes as well as aerobic and anaerobic hydrocarbon degradation. Significant and distinct differences were observed when comparing the 'high corrosion' (HC) and the 'low corrosion' (LC) pipeline systems, especially with respect to the TEA utilization potential. The HC samples were dominated by sulfate-reducing bacteria (SRB) and archaea known for their ability to utilize simple carbon substrates, whereas LC samples were dominated by pseudomonads with the genetic potential for denitrification and aerobic hydrocarbon degradation. The frequency of aerobic hydrocarbon degradation genes was low in the HC system, and anaerobic hydrocarbon degradation genes were not detected in either pipeline. This is in contrast with metabolite analysis, which demonstrated the presence of several succinic acids in HC samples that are diagnostic of anaerobic hydrocarbon metabolism. Identifiable aerobic metabolites were confined to the LC samples, consistent with the metagenomic data. Overall, these data suggest that corrosion management might benefit from a more refined understanding of microbial community resilience in the face of disturbances such as nitrate treatment or pigging, which frequently prove insufficient to alter community structure toward a stable, less-corrosive assemblage