油类型和温度依赖性生物降解动力学——通过多元分析结合化学和微生物群落数据。
Oil type and temperature dependent biodegradation dynamics - Combining chemical and microbial community data through multivariate analysis.
机构信息
SINTEF Ocean, Environment and New Resources, Brattørkaia 17C, 7010, Trondheim, Norway.
Department Clinical and Molecular Medicine, The Norwegian University of Science and Technology, 7491, Trondheim, Norway.
出版信息
BMC Microbiol. 2018 Aug 7;18(1):83. doi: 10.1186/s12866-018-1221-9.
BACKGROUND
This 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.
RESULTS
PCA 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%).
CONCLUSIONS
In 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.
背景
本研究采用比较多元方法研究化学分散油的生物降解。采用这种方法的依据是数据的固有复杂性以及在比较具有不同采样点的多个实验时所面临的挑战，因为这些实验需要推断相关性并可视化具有大量变量的多个数据集。我们的目的是通过从不一致的采样时间点创建模拟数据集，确定微生物群落组成、单个石油烃的化学变化、油类型和温度之间的新关联。用新采集的挪威海水进行了四个不同的培养实验，其中分别加入了用 Corexit 9500 分散的 Grane 和 Troll 油。培养在 5°C 和 13°C 两个不同温度下进行，持续 64 天。
结果
对模型化化学数据集的 PCA 分析和计算半衰期揭示了温度和油类型对个别烃类生物降解的差异。在 5°C 时，与轻 Troll 油相比，重 Grane 油中的大多数正构烷烃更快地生物降解。对模型化微生物群落数据集的 PCA 分析揭示了温度和油类型之间的差异，尤其是在低温下。对于两种油，冷培养（5°C）中 Colwelliaceae 和 Oceanospirillaceae 比暖培养（13°C）更突出。总体而言，Colwelliaceae、Oceanospirillaceae、Flavobacteriaceae、Rhodobacteraceae、Alteromonadaceae 和 Piscirickettsiaceae 在两个温度和两种油类型中始终占据微生物群落的主导地位。还鉴定出其他已知包含石油降解细菌的科，如 Alcanivoracaceae、Methylophilaceae、Sphingomonadaceae 和 Erythrobacteraceae，但它们在分散油培养物中的丰度都很低（<1%）。
结论
在本研究中，我们的目标是引入一种比较多元方法来研究分散油的生物降解，包括为了提高数据分辨率和可比性而对数据集进行曲线拟合模型。通过应用这些方法，我们展示了不同温度和油类型如何影响具有不一致采样点的培养物中油的生物降解。聚类分析进一步揭示了温度和油类型如何影响单个化合物的消耗和微生物群落组成。最后，降解菌群落与单个化合物数据的相关性分析揭示了在生物降解研究中通常用于微生物群落数据的丰度截止值下的复杂性。
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