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[Effects of Organic Pollutants on the Bacterioplankton Community in Hangzhou Bay]
Li-Xia Xuan1, Wen-Fang Dai1,2, Wei-Na Yu1,2
1School of Marine Sciences, Ningbo University, Ningbo 315211, China.
Abstract:
Hangzhou Bay suffers from intensive anthropogenic disturbances and a huge amount of terrestrial inputs, and thus has become one of the most seriously contaminated coastal zones in China. There is evidence that microbes play a dominant role in pollutant biodegradation and serve as biomarkers for pollution levels. However, it remains unclear how the bacterioplankton communities respond to organic contaminants. To fill this knowledge gap, we collected surface water samples (0.5 m below the surface layer) from 13 sites across Hangzhou Bay and 8 control sites across its adjacent offshore areas. Using Illumina sequencing based on analysis of the bacterial 16S rRNA gene, we explored the effects of increasing organic pollution levels on the bacterioplankton community compositions (BCCs). The results revealed that the organic pollution level (A) in Hangzhou Bay (13.2±1.6) was significantly (P<0.001) higher than in the control zone (5.4±3.0). The distribution and diversity of bacterioplankton communities were significantly distinct between the two zones. The dominant bacterioplankton lineages in Hangzhou Bay were γ-Proteobacteria (24.4%±5.5%), α-Proteobacteria (16.5%±7.7%), and Planctomycetes (13.9%±8.6%), whereas those in the adjacent zones were Cyanobacteria (20.1%±7.5%), Bacteroidetes (18.4%±1.5%), Actinobacteria (17.5%±4.2%), γ-Proteobacteria (16.6%±1.2%), and α-Proteobacteria (14.3%±1.7%). Multivariate regression tree (MRT) analysis showed that the bacterioplankton community diversity was primarily affected by suspended particulates (SP), nitrite, oil, and organic pollutants, which respectively explained 22.0%, 6.5%, 6.0%, and 5.5% of the variance in diversity. Redundancy analysis (RDA) illustrated that the bacterioplankton community distribution was controlled by organic pollutants, COD, Chla, TN, nitrate, and salinity, which cumulatively governed 71.0% of the variation in BCCs. Organic pollutants alone controlled 6.5% variance, which was higher than any other single factor. Additionally, 35 sensitive species were identified via the indicator value method and their relative abundances were significantly associated (P<0.05 in each case) with the organic pollution level, thereby indicating their potential for evaluating coastal pollution. Collectively, our work demonstrates that BCCs are sensitive to coastal pollution and provides biomarkers for elevated pollution levels.
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