Transfer of organisms with ships' ballast water is recognized as a major pathway of non-indigenous species introduction and addressed in a few recent legislative initiatives. Among other they imply scientific and technical research and monitoring to be conducted in a efficient and reliable way. The recent development of DNA barcoding and metabarcoding technologies opens new opportunities for biodiversity and biosecurity surveillance. In the current study, the performance of metabarcoding approach was assessed in comparison to the conventional (visual) observations, during the en route experimental ballast water survey. Opportunities and limitations of the molecular method were identified from taxonomical datasets rendered by two molecular markers of different degree of universality - the universal cytochrome oxydase sub-unit I gene and a fragment of RuBisCO gene. The cost-efficacy and possible improvements of these methods are discussed for the further successful development and implementation of the approach in ballast water control and NIS surveillance.

Oil biodegradation as a weathering process has been extensively investigated over the years, especially after the Deepwater Horizon blowout. In this study, we performed microcosm experiments at 5 °C with chemically dispersed oil in non-amended seawater. We link biodegradation processes with microbial community and metagenome dynamics and explain the succession based on substrate specialization. Reconstructed genomes and 16S rRNA gene analysis revealed that Bermanella and Zhongshania were the main contributors to initial n-alkane breakdown, while subsequent abundances of Colwellia and microorganisms closely related to Porticoccaceae were involved in secondary n‑alkane breakdown and beta‑oxidation. Cycloclasticus, Porticoccaceae and Spongiiabcteraceae were associated with degradation of mono- and poly-cyclic aromatics. Successional pattern of genes coding for hydrocarbon degrading enzymes at metagenome level, and reconstructed genomic content, revealed a high differentiation of bacteria involved in hydrocarbon biodegradation. A cooperation among oil degrading microorganisms is thus needed for the complete substrate transformation.

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BackgroundThis study investigates a comparative multivariate approach for studying the biodegradation of chemically dispersed oil. The rationale for this approach lies in the inherent complexity of the data and challenges associated with comparing multiple experiments with inconsistent sampling points, with respect to inferring correlations and visualizing multiple datasets with numerous variables. We aim to identify novel correlations among microbial community composition, the chemical change of individual petroleum hydrocarbons, oil type and temperature by creating modelled datasets from inconsistent sampling time points. Four different incubation experiments were conducted with freshly collected Norwegian seawater and either Grane and Troll oil dispersed with Corexit 9500. Incubations were conducted at two different temperatures (5 °C and 13 °C) over a period of 64 days.ResultsPCA analysis of modelled chemical datasets and calculated half-lives revealed differences in the biodegradation of individual hydrocarbons among temperatures and oil types. At 5 °C, most n-alkanes biodegraded faster in heavy Grane oil compared to light Troll oil. PCA analysis of modelled microbial community datasets reveal differences between temperature and oil type, especially at low temperature. For both oils, Colwelliaceae and Oceanospirillaceae were more prominent in the colder incubation (5 °C) than the warmer (13 °C). Overall, Colwelliaceae, Oceanospirillaceae, Flavobacteriaceae, Rhodobacteraceae, Alteromonadaceae and Piscirickettsiaceae consistently dominated the microbial community at both temperatures and in both oil types. Other families known to include oil-degrading bacteria were also identified, such as Alcanivoracaceae, Methylophilaceae, Sphingomonadaceae and Erythrobacteraceae, but they were all present in dispersed oil incubations at a low abundance (< 1%).ConclusionsIn the current study, our goal was to introduce a comparative multivariate approach for studying the biodegradation of dispersed oil, including curve-fitted models of datasets for a greater data resolution and comparability. By applying these approaches, we have shown how different temperatures and oil types influence the biodegradation of oil in incubations with inconsistent sampling points. Clustering analysis revealed further how temperature and oil type influence single compound depletion and microbial community composition. Finally, correlation analysis of degraders community, with single compound data, revealed complexity beneath usual abundance cut-offs used for microbial community data in biodegradation studies.Electronic supplementary materialThe online version of this article (10.1186/s12866-018-1221-9) contains supplementary material, which is available to authorized users.