[Bacterial Community Composition in Channel Sediment in Response to Mariculture Wastewater Drainage].

The impact of mariculture on the ecological environment of sediments in surrounding waters is intensely debated. Microbial communities are considered to be keystone indicators of lineage responses to changes in environmental quality. To examine the mariculture effects, we collected channel sediment from four sites in the culture area including oneintake canal, one outfall, and two outlet canals. On the basis of bacterial 16S rRNA gene and phospholipid fatty acid (PLFA) technology, we used Illumina MiSeq sequencing applied to the analysis results to explore the effects of mariculture wastewater drainage on the bacterial community structures in the sediment. The results revealed that Proteobacteria, including γ-Proteobacteria, δ-Proteobacteria, and α-Proteobacteria, were the dominant lineages of bacteria at the four sites. The microbial biomass of the sediment increased significantly owing to the effects of mariculture wastewater drainage. The relative abundance of Actinobacteria and ammoniated microorganisms decreased, whereas the relative abundance of Bacteroidetes increased. The results of non-metric multidimensional scaling (NMDS) analysis indicated that most of the sediment bacterial communities clustered by influent and effluent. The diversity indicated that the mariculture wastewater drainage decreased the bacterial diversity, and redundancy analysis (RDA) indicated that the most obvious correlation occurred between ammonia nitrogen and bacterial community structures. In summary, the mariculture wastewater drainage resulted in significant changes in the physical and chemical properties and structures of bacterial communities in the aquaculture channel sediment. This indicates that the long-term direct discharge of aquaculture wastewater would excessively contaminate a channel environment and might further pose a threat to the offshore ecological environment.

[Effects of Organic Pollutants on the Bacterioplankton Community in Hangzhou Bay].

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.