ArticleScientific reports2017
Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
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- Dataset characterising dominant bacterial phylotypes across animal manure-enriched composting microcosms for crude oil waste sludge bioremediation.Data in brief · 2026Article
- The hydrocarbon-degrading bacteria and fungi in oil contaminated soils of Kazakhstan: microbiome composition, enrichment, isolation and bioremediation potential.Environmental microbiome · 2026Article
- Machine learning approaches for data-driven hydrocarbon bioaugmentation and phytoremediation: the role of multi-omics insights.Frontiers in microbiology · 2026Review
- Functional prediction based on 16S rRNA metagenome data from bacterial microbiota associated with macroalgae from the Peruvian coast.Scientific reports · 2024Article
- Effect of ocean acidification on the growth, response and hydrocarbon degradation of coccolithophore-bacterial communities exposed to crude oil.Scientific reports · 2023Article
- Understanding microbiome dynamics via interpretable graph representation learning.Scientific reports · 2023Article
- Functional Prediction of Microbial Communities in Sediment Microbial Fuel Cells.Bioengineering (Basel, Switzerland) · 2023Article
- Metataxonomic Characterization of Enriched Consortia Derived from Oil Spill-Contaminated Sites in Guimaras, Philippines, Reveals Major Role ofInternational journal of microbiology · 2023Article
- Temperature dependence of nitrification in a membrane-aerated biofilm reactor.Frontiers in microbiology · 2023Article
- Pathogenic and Endosymbiotic Bacteria and Their Associated Antibiotic Resistance Biomarkers inPathogens (Basel, Switzerland) · 2022Article
- Effects of heavy metals on bacterial community structures in two lead-zinc tailings situated in northwestern China.Archives of microbiology · 2021Article
- Exploring the diversity and hydrocarbon bioremediation potential of microbial community in the waste sludge of Duliajan oil field, Assam, India.Environmental science and pollution research international · 2021Article
- Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap.Molecular ecology · 2021Review
- Petroleum contamination significantly changes soil microbial communities in three oilfield locations in Delta State, Nigeria.Environmental science and pollution research international · 2021Article
- Impact of diesel and biodiesel contamination on soil microbial community activity and structure.Scientific reports · 2021Article
- A Comparative Taxonomic Profile of Microbial Polyethylene and Hydrocarbon-Degrading Communities in Diverse Environments.Iranian journal of biotechnology · 2021Article
- Harnessing the Potential of Native Microbial Communities for Bioremediation of Oil Spills in the Iberian Peninsula NW Coast.Frontiers in microbiology · 2021Article
- Assessment of Biological Contribution to Natural Recovery of Anthropized Freshwater Sediments From Argentina: Autochthonous Microbiome Structure and Functional Prediction.Frontiers in microbiology · 2021Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbial remediation of oil polluted habitats remains one of the foremost methods for restoration of petroleum hydrocarbon contaminated environments. The development of effective bioremediation strategies however, require an extensive understanding of the resident microbiome of these habitats. Recent developments such as high-throughput sequencing has greatly facilitated the advancement of microbial ecological studies in oil polluted habitats. However, effective interpretation of biological characteristics from these large datasets remain a considerable challenge. In this study, we have implemented recently developed bioinformatic tools for analyzing 65 16S rRNA datasets from 12 diverse hydrocarbon polluted habitats to decipher metagenomic characteristics of the resident bacterial communities. Using metagenomes predicted from 16S rRNA gene sequences through PICRUSt, we have comprehensively described phylogenetic and functional compositions of these habitats and additionally inferred a multitude of metagenomic features including 255 taxa and 414 functional modules which can be used as biomarkers for effective distinction between the 12 oil polluted sites. Additionally, we show that significantly over-represented taxa often contribute to either or both, hydrocarbon degradation and additional important functions. Our findings reveal significant differences between hydrocarbon contaminated sites and establishes the importance of endemic factors in addition to petroleum hydrocarbons as driving factors for sculpting hydrocarbon contaminated bacteriomes.
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