Microbiologically influenced corrosion (MIC) or biocorrosion is a complex biological and physicochemical process, Strategies for monitoring MIC are frequently based on microbial cultivation methods, while microbiological molecular methods (MMM) are not well-established in the oil industry in Brazil. Thus, there is a high demand for the development of effective protocols for monitoring biocorrosion with MMM. The main aim of our study was to analyze the physico-chemi- cal features of microbial communities occurring in produced water (PW) and in enrichment cultures in oil pipelines of the petroleum industry. In order to obtain strictly comparable results, the same samples were used for both culturing and metabarcoding. PW samples displayed higher phylogenetic diversity of bacteria and archaea whereas PW enrichments cultures showed higher dominance of bacterial MIC-associated genera. All samples had a core community composed of 19 distinct genera, with MIC-associated Desulfovibrio as the dominant genus. We observed significant associations between the PW and cultured PW samples, with a greater number of associations found between the cultured sulfate-reducing bacteria (SRB) samples and the uncultured PW samples. When evaluating the correlation between the physicochemical characteristics of the environment and the microbiota of the uncultivated samples, we suggest that the occurrence of anaerobic digestion metabolism can be characterized by well-defined phases. Therefore, the detection of microorganisms in uncultured PW by metabarcoding, along with physi-cochemical characterization, can be a more efficient method compared to the culturing method, as it is a less laborious and cost-effective method for monitoring MIC microbial agents in oil industry facilities.

Characterizing metabolically active microorganisms using RNA-based methods is a crucial tool for monitoring and mitigating operational issues, such as oil biodegradation and biocorrosion of pipelines in the oil and gas industry. Our review, a pioneering study, addresses the main methods used to preserve, isolate, and sequence RNA from oilfield samples and describes the most abundant metabolically active genera studied. Using the MEDLINE/PubMed, PubMed Central, Scopus, and Web of Science databases, 2.561 potentially eligible records were identified. After screening, 20 studies were included in our review, underscoring the scarcity of studies related to the subject. Data were extracted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). These studies evaluated different samples, including produced water (PW), injection water (IW), solid deposits (SD), oil (OIL), and oily sludge (OS) collected from oilfields located in Australia, China, India, Mexico, and the United Arab Emirates. Environmental samples accounted for 55% of the studies, while enriched cultures and microbial consortia represented 35% and 15% of studies, respectively. PW was the most frequently studied sample, comprising 72% of all samples. Filtration and centrifugation were the only processes employed to concentrate the biomass present in samples. For RNA preservation, the most used method was a solution composed of 95:5 v/v ethanol/TRIzol, while for RNA isolation, the TRIzol reagent was the most cited. The Sanger sequencing method was used in all studies evaluating functional genes (alkB, dsrA, aprA, assA, and mcrA), and the Next-Generation Sequencing (NGS) method was employed in studies for sequencing transcripts of the 16S rRNA gene and metatranscriptomes. Pseudomonas (16S rRNA = PW: 2%; IW: 8%; metatranscriptome = PW: 20%) and Acinetobacter (16S rRNA = PW: 1%; IW: 4%; metatranscriptome = PW: 17%) were the most abundant genera. This study outlined the primary methods employed in researching metabolically active microorganisms. These data provide a foundation for future research. However, it is essential to note that we cannot yet determine the most effective method. We hope that this study will inspire further research related to the standardization of RNA preservation, extraction, and sequencing methods and significantly contribute to our understanding of active microbial communities in oilfields.