Microbial community structure is affected by both natural processes and human activities. In coastal area, anthropegenetic activity can usually lead to the discharge of the effluent from wastewater treatment plant (WWTP) to sea, and thus the water quality chronically turns worse and marine ecosystem becomes unhealthy. Microorganisms play key roles in pollutants degradation and ecological restoration; however, there are few studies about how the WWTP effluent disposal influences coastal microbial communities. In this study, sediment samples were collected from two WWTP effluent-receiving areas (abbreviated as JX and SY) in Hangzhou Bay. First, based on the high-throughput sequencing of 16S rRNA gene, microbial community structure was analyzed. Secondly, several statistical analyses were conducted to reveal the microbial community characteristics in response to the effluent disposal. Using PCoA, the significant difference of in microbial community structure was determined between JX and SY; using RDA, water COD and temperature, and sediment available phosphate and ammonia nitrogen were identified as the key environmental factors for the community difference; using LDA effect size analysis, the most distinctive microbes were found and their correlations with environmental factors were investigated; and according to detrended beta-nearest-taxon-index, the sediment microbial communities were found to follow “niche theory”. An interesting and important finding was that in SY that received more and toxic COD, many distinctive microbes were related to the groups that were capable of degrading toxic organic pollutants. This study provides a clear illustration of eco-environmental deterioration under the long-term human pressure from the view of microbial ecology.
Current technologies could identify the abundance and functions of specific microbes, and evaluate their individual effects on microbial ecology. However, these microbes interact with each other, as well as environmental factors, in the form of complex network. Determination of their combined ecological influences remains a challenge. In this study, we developed a tripartite microbial-environment network (TMEN) analysis method that integrates microbial abundance, metabolic function, and environmental data as a tripartite network to investigate the combined ecological effects of microbes. Applying TMEN to analyzing the microbial-environment community structure in the sediments of Hangzhou Bay, one of the most seriously polluted coastal areas in China, we found that microbes were well-organized into 4 bacterial communities and 9 archaeal communities. The total organic carbon, sulfate, chemical oxygen demand, salinity, and nitrogen-related indexes were detected as crucial environmental factors in the microbial-environmental network. With close interactions with these environmental factors, Nitrospirales and Methanimicrococcu were identified as hub microbes with connection advantage. Our TMEN method could close the gap between lack of efficient statistical and computational approaches and the booming of large-scale microbial genomic and environmental data. Based on TMEN, we discovered a potential microbial ecological mechanism that crucial species with significant influence on the microbial community ecology would possess one or two of the community advantages for enhancing their ecological status and essentiality, including abundance advantage and connection advantage.
The coastal area of the East China Sea has experienced rapid urbanization and industrialization in China since 1980s, resulting in severe pollution of its environments. Antibiotic resistance genes (ARGs) are regarded as a kind of emerging pollutant with potential high risk. The sediment samples were collected from Hangzhou Bay (HB), Xiangshan Bay (XB), and Taizhou Bay (TB) to investigate the spatial occurrence and distribution of 27 ARGs and class I integron–integrase gene (intI1) in the coastal area of the East China Sea. The PCR results showed the frequent presence of 11 ARGs and intI1 in the sediments of the three bays. The qPCR results further showed that sulfonamide resistance was the most prevalent ARG type and antibiotic target replacement and protection were the most important resistance mechanisms in the sediments. Regarding the subtype of ARGs, sulI, tetW, and dfrA13 were the most abundant ARGs, in which sulI was higher in TB (based on both the absolute and relative abundances) and dfrA13 was higher in HB (based on the relative abundances). The network analysis revealed that intI1 had significant correlations with tetC, sulI, sulII, and blaPSE-1. Oil was the key connected factor, which had positive connections with sulI, sulII, and blaPSE-1. In addition, the joint effect of heavy metals and nutrients & organic pollutants might be crucial for the fate of ARGs in the coastal sediments.
Coastal estuaries and bays are exposed to both natural and anthropogenic environmental changes, inflicting intensive stress on the microbial communities inhabiting these areas. However, it remains unclear how microbial community diversity and their eco-functions are affected by anthropogenic disturbances rather than natural environmental changes. Here, we explored sediment microbial functional genes dynamics and community interaction networks in Hangzhou Bay (HZB), one of the most severely polluted bays on China’s eastern coast. The results indicated key microbial functional gene categories, including N, P, S, and aromatic compound metabolism, and stress response, displayed significant spatial dynamics along environmental gradients. Sensitive feedbacks of key functional gene categories to N and P pollutants demonstrated potential impacts of human-induced seawater pollutants to microbial functional capacity. Seawater ammonia and dissolved inorganic nitrogen (DIN) was identified as primary drivers in selecting adaptive populations and varying community composition. Network analysis revealed distinct modules that were stimulated in inner or outer bay. Importantly, the network keystone species, which played a fundamental role in community interactions, were strongly affected by N-pollutants. Our results provide a systematic understanding of the microbial compositional and functional dynamics in an urbanized coastal estuary, and highlighted the impact of human activities on these communities.
Antibiotic resistance genes (ARGs) are regarded as emerging contaminants related with human activities. Aquatic environments of an urban city are apt for the persistence and prevalence of ARGs. In this study, we investigated the occurrence and distribution of ARGs and integrase genes in the sediment samples collected from drinking water sources, urban rivers, and coastal areas of Zhuhai, China, in the dry and wet seasons of 2016. The results show that sulfonamide resistance gene of sulII was present at the highest detection frequency (85.71%); and its average concentrations were also the highest in both dry and wet seasons (3.78×107 and 9.04×107 copies/g sediment, respectively), followed by tetC, tetO, tetA, ermB, dfrA1, and blaPSE-1. Temporally, the concentrations of total ARGs in the wet season were likely higher than those in the dry season; and spatially, the concentrations of total ARGs in the drinking water sources were substantially lower than those in the urban rivers and nearby coastal areas, indicating the different degrees of anthropogenic impact and consequent health risks. Positive correlations were found between intI1 and each quantitative ARG in all wet season samples rather than dry season samples, which suggested higher temperature and more rain in summer might have positive influences on ARG dissemination, especially that mediated by intI1 gene and class I integrons.
Coastal ecosystem structures and functions are changing under natural and anthropogenic influences. In this study, surface sediment samples were collected from disturbed zone (DZ), near estuary zone (NEZ), and far estuary zone (FEZ) of Hangzhou Bay, one of the most seriously polluted bays in China. The bacterial community structures and predicted functions varied significantly in different zones. Firmicutes were found most abundantly in DZ, highlighting the impacts of anthropogenic activities. Sediment total phosphorus was most influential on the bacterial community structures. Predicted by PICRUSt analysis, DZ significantly exceeded FEZ and NEZ in the subcategory of Xenobiotics Biodegradation and Metabolism; and DZ enriched all the nitrate reduction related genes, except nrfA gene. Seawater salinity and inorganic nitrogen, respectively as the representative natural and anthropogenic factor, performed exact-oppositely in nitrogen metabolism functions. The changes of bacterial community compositions and predicted functions provide a new insight into human-induced pollution impacts on coastal ecosystem.
Cell-associated ARGs in wastewater treatment plants (WWTPs) has been concerned, however, cell-free ARGs in WWTPs was rarely studied. In this study, the abundances of four representative ARGs, sulII, tetC, blaPSE‑1,and ermB, in a large municipal WWTP were investigated in both cell-associated and cell-free fractions. Cell-associated ARGs was the dominant ARGs fraction in the raw wastewater. After biological treatment, sludge settling, membrane filtration, and disinfection, cell-associated ARGs were substantially reduced, though the ratios of ARG/16S rRNA gene were increased with disinfection. Cell-free ARGs persisted in the WWTP with a removal of 0.36 log to 2.68 logs, which was much lower than the removal of cell-associated ARGs (3.21 logs to 4.14 logs). Therefore, the abundance ratio of cell-free ARGs to cell-associated ARGs increased from 0.04−1.59% to 2.00−1895.08% along the treatment processes. After 25-day-storage, cell-free ARGs in both biological effluent and disinfection effluent increased by 0.14 log to 1.99 logs and 0.12 log to 1.77 logs respectively, reflecting the persistence and low decay rate of cell-free ARGs in the discharge water. Therefore, cell-free ARGs might be a kind of important but previously neglected pollutant from WWTPs, which added potential risks to the effluent receiving environments.
Coastal areas are land–sea transitional zones with complex natural and anthropogenic disturbances. Microorganisms in coastal sediments adapt to such disturbances both individually and as a community. The microbial community structure changes spatially and temporally under environmental stress. In this study, we investigated the microbial community structure in the sediments of Hangzhou Bay, a seriously polluted bay in China. In order to identify the roles and contribution of all microbial taxa, we set thresholds as 0.1% for rare taxa and 1% for abundant taxa, and classified all operational taxonomic units into six exclusive categories based on their abundance. The results showed that the key taxa in differentiating the communities are abundant taxa (AT), conditionally abundant taxa (CAT), and conditionally rare or abundant taxa (CRAT). A large population in conditionally rare taxa (CRT) made this category collectively significant in differentiating the communities. Both bacteria and archaea demonstrated a distance decay pattern of community similarity in the bay, and this pattern was strengthened by rare taxa, CRT and CRAT, but weakened by AT and CAT. This implied that the low abundance taxa were more deterministically distributed, while the high abundance taxa were more ubiquitously distributed.