Corrosion-influencing microorganisms in petroliferous regions on a global scale: systematic review, analysis, and scientific synthesis of 16S amplicon metagenomic studies

Author:

Dutra Joyce1,Gomes Rosimeire1,Yupanqui García Glen Jasper2,Romero-Cale Danitza Xiomara3,Santos Cardoso Mariana2,Waldow Vinicius4ORCID,Groposo Claudia5,Akamine Rubens N.4ORCID,Sousa Maira4,Figueiredo Henrique6,Azevedo Vasco7ORCID,Góes-Neto Aristóteles7ORCID

Affiliation:

1. Graduate Program in Microbiology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

2. Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

3. Graduate Program in Biotechnology, State University of Feira de Santana, Feira de Santana, Bahia, Brazil

4. Petrobras Research and Development Center (CENPES), Petrobras, Rio de Janeiro, Rio de Janeiro, Brazil

5. Petrobras, Criciúma, Santa Catarina, Brazil

6. Veterinary School, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

7. Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

Abstract

The objective of the current systematic review was to evaluate the taxonomic composition and relative abundance of bacteria and archaea associated with the microbiologically influenced corrosion (MIC), and the prediction of their metabolic functions in different sample types from oil production and transport structures worldwide. To accomplish this goal, a total of 552 published studies on the diversity of microbial communities using 16S amplicon metagenomics in oil and gas industry facilities indexed in Scopus, Web of Science, PubMed and OnePetro databases were analyzed on 10th May 2021. The selection of articles was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only studies that performed amplicon metagenomics to obtain the microbial composition of samples from oil fields were included. Studies that evaluated oil refineries, carried out amplicon metagenomics directly from cultures, and those that used DGGE analysis were removed. Data were thoroughly investigated using multivariate statistics by ordination analysis, bivariate statistics by correlation, and microorganisms’ shareability and uniqueness analysis. Additionally, the full deposited databases of 16S rDNA sequences were obtained to perform functional prediction. A total of 69 eligible articles was included for data analysis. The results showed that the sulfidogenic, methanogenic, acid-producing, and nitrate-reducing functional groups were the most expressive, all of which can be directly involved in MIC processes. There were significant positive correlations between microorganisms in the injection water (IW), produced water (PW), and solid deposits (SD) samples, and negative correlations in the PW and SD samples. Only the PW and SD samples displayed genera common to all petroliferous regions, Desulfotomaculum and Thermovirga (PW), and Marinobacter (SD). There was an inferred high microbial activity in the oil fields, with the highest abundances of (i) cofactor, (ii) carrier, and (iii) vitamin biosynthesis, associated with survival metabolism. Additionally, there was the presence of secondary metabolic pathways and defense mechanisms in extreme conditions. Competitive or inhibitory relationships and metabolic patterns were influenced by the physicochemical characteristics of the environments (mainly sulfate concentration) and by human interference (application of biocides and nutrients). Our worldwide baseline study of microbial communities associated with environments of the oil and gas industry will greatly facilitate the establishment of standardized approaches to control MIC.

Funder

PETROBRAS

Graduate Programs of Microbiology and Bioinformatics

Pro-Rectory of Research of the Universidade Federal de Minas Gerais

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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