Microbial communities occur in almost every habitat. To evaluate the homeostasis disruption of in situ microbiomes, dredged sediments from Guanabara Bay-Brazil (GB) were mixed with sediments from outside of the bay (D) in three different proportions (25%, 50%, and 75%) which we called GBD25, GBD50, and GBD75. Grain size, TOC, and metals—as indicators of complex contamination—dehydrogenase (DHA) and esterase enzymes (EST)—as indicators of microbial community availability—were determined. Microbial community composition was addressed by amplifying the 16S rRNA gene for DGGE analysis and sequencing using MiSeq platform (Illumina).We applied the quality ratio index (QR) to the GB, D, and every GBD mixture to integrate geochemical parameters with our microbiome data. QR indicated high environmental risk for GB and every GBD mixture, and low risk for D. The community shifted from aerobic to anaerobic profile, consistent with the characteristics of GB. Sample D was dominated by JTB255 marine benthic group, related to low impacted areas. Milano-WF1B-44 was the most representative of GB, often found in anaerobic and sulfur enriched environments. In GBD, the denitrifying sulfur-oxidizing bacteria, Sulfurovum, was the most representative, typically found in suboxic or anoxic niches. The canonical correspondence analysis was able to explain 60% of the community composition variation and exhibit the decrease of environmental quality as the contamination increases. Physiological and taxonomic shifts of the microbial assemblage in sediments were inferred by QR, which was suitable to determine sediment risk. The study produced sufficient information to improve the dredging plan and management.

中文翻译：

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在富营养化海湾疏of的沉积物暴露下，微生物群落转移。

几乎每个栖息地都有微生物群落。为了评估原位微生物群的稳态破坏，将瓜纳巴拉湾-巴西（GB）的疏sediment沉积物与海湾（D）外的沉积物按三种不同的比例（25％，50％和75％）混合GBD25，GBD50和GBD75。确定了作为复杂污染指标的粒度，TOC和金属，即作为微生物群落可用性的指标的脱氢酶（DHA）和酯酶（EST）。通过使用MiSeq平台（Illumina）扩增用于DGGE分析和测序的16S rRNA基因来解决微生物群落组成，我们将质量比指数（QR）应用于GB，D和每种GBD混合物，以将地球化学参数与我们的微生物组数据整合。QR表示GB和每种GBD混合物的环境风险较高，而D的风险较低。社区从有氧模式转变为厌氧模式，这与GB的特征一致。样品D以JTB255海洋底栖动物群，与低影响地区有关。Milano-WF1B-44是GB的最典型代表，通常在厌氧和富硫环境中发现。在GBD中，反硝化的硫氧化细菌，Sulfurovum是最典型的代表，通常发现于低氧或缺氧的生态位中。典范对应分析能够解释60％的群落组成变化，并显示随着污染的增加环境质量下降。QR推断出沉积物中微生物组合的生理学和生物分类学变化，适用于确定沉积物风险。该研究产生了足够的信息来改善疏the计划和管理。