Metagenomics-Based Microbial Ecological Community Threshold and Indicators of Anthropogenic Disturbances in Estuarine Sediments.

Assessing the impacts of cumulative anthropogenic disturbances on estuarine ecosystem health is challenging. Using spatially distributed sediments from the Pearl River Estuary (PRE) in southern China, which are significantly influenced by anthropogenic activities, we demonstrated that metagenomics-based surveillance of benthic microbial communities is a robust approach to assess anthropogenic impacts on estuarine benthic ecosystems. Correlational and threshold analyses between microbial compositions and environmental conditions indicated that anthropogenic disturbances in the PRE sediments drove the taxonomic and functional variations in the benthic microbial communities. An ecological community threshold of anthropogenic disturbances was identified, which delineated the PRE sediments into two groups (H and L) with distinct taxa and functional traits. Group H, located nearshore and subjected to a higher level of anthropogenic disturbances, was enriched with pollutant degraders, putative human pathogens, fecal pollution indicators, and functional traits related to stress tolerance. In contrast, Group L, located offshore and subjected to a lower level of anthropogenic disturbances, was enriched with halotolerant and oligotrophic taxa and functional traits related to growth and resource acquisition. The machine learning random forest model identified a number of taxonomic and functional indicators that could differentiate PRE sediments between Groups H and L. The identified ecological community threshold and microbial indicators highlight the utility of metagenomics-based microbial surveillance in assessing the adverse impacts of anthropogenic disturbances in estuarine sediments, which can assist environmental management to better protect ecosystem health.

Screening of priority antibiotics in Chinese seawater based on the persistence, bioaccumulation, toxicity and resistance.

Antibiotics are emerging pollutants that have detrimental effects on both target and non-target organisms in the environment. However, current methods for environmental risk assessment primarily focus on the risk to non-target organisms in ecosystems, overlooking a crucial risk of antibiotics - the induction of resistance in targeted bacteria. To address this oversight, we have incorporated resistance (R) risk with persistence, bioaccumulation and toxicity (PBT) to establish a more comprehensive PBTR (persistence, bioaccumulation, toxicity, and resistance) framework for antibiotic-specific risk assessment. Using the PBTR framework, we evaluated 74 antibiotics detected in Chinese seawater from 2000 to 2021, and identified priority antibiotics. Our analysis revealed that the priority antibiotics with R risk accounted for the largest proportion (50% to 70%), followed by P risk (40% to 58%), T risk (16% to 35%) and B risk (0 to 13%). To further categorize these priority antibiotics, we assigned them a risk level according to their fulfillment of criteria related to P, B, T, and R. Antibiotics meeting all four indicators were classified as Grade I, representing the highest risk level. Grade II and Grade III were assigned to antibiotics meeting three or two indicators, respectively. Antibiotics meeting only one indicator were classified as Grade IV, representing the lowest risk level. The majority of priority antibiotics fell into Grade IV, indicating low risk (55% to 79%), followed by Grade III (16% to 45%). The highest risk antibiotic identified in this study was clindamycin (CLIN), categorized as Grade II, in the East China Sea. Our findings aligned with previous studies for 25 antibiotics, affirming the validity of the PBTR framework. Moreover, we identified 13 new priority antibiotics, highlighting the advancement of this approach. This study provides a feasible screening strategy and monitoring recommendations for priority antibiotics in Chinese seawater.

Wastewater treatment plant effluent discharge decreases bacterial community diversity and network complexity in urbanized coastal sediment.

The wastewater treatment plant (WWTP) effluent discharge affects the microorganisms in the receiving water bodies. Despite the ecological significance of microbial communities in pollutant degradation and element cycling, how the community diversity is affected by effluent remains obscure. Here, we compared the sediment bacterial communities exposed to different intensities of WWTP effluent discharge in Hangzhou Bay, China: i) a severely polluted area that receives effluent from an industrial WWTP, ii) a moderately polluted area that receives effluent from a municipal WWTP, and iii) less affected area that inner the bay. We found that the sediment bacterial diversity decreased dramatically with pollution levels of inorganic nutrients, heavy metals, and organic halogens. Microbial community assembly model analysis revealed increased environmental selection and decreased species migration rate in the severely polluted area, resulting in high phylogenetic clustering of the bacterial communities. The ecological networks were less complex in the two WWTP effluent receiving areas than in the inner bay area, as suggested by the smaller network size and lower modularity. Fewer negative network associations were detected in the severely (6.7%) and moderately (8.3%) polluted areas than in the less affected area (16.7%), indicating more collaborative inter-species behaviors are required under stressful environmental conditions. Overall, our results reveal the fundamental impacts of WWTP effluents on the ecological processes shaping coastal microbial communities and point to the potential adverse effects of diversity loss on ecosystem functions.

Insights into the distribution, partitioning and influencing factors of antibiotics concentration and ecological risk in typical bays of the East China Sea.

In order to obtain in-depth insight of the behavioral fate and ecological risks of antibiotics in coastal environment, this study investigated the distribution, partitioning and primary influencing factors of antibiotics in water and sediment in the East China Sea. After quantification of 77 target antibiotics in 6 categories, ten antibiotics were detected simultaneously with a detection frequency >50.0% in water and sediment; the concentrations of these ten antibiotics were 0.1-1508.0 ng L-1 and 0.01-9.4 ng g-1 in water and dry sediment, respectively. Sulfadiazine and Azithromycin (Pseudo partitioning coefficient were 28-3814 L kg-1 and 21-2405 L kg-1, respectively.) had the largest partitioning coefficient between sediment and water. In addition, pseudo partitioning coefficient of Sulfadiazine and Clindamycin were higher than the values of corresponding equilibrium partitioning constant (Kd), which would likely cause them to re-release from sediment to water. Compared to the physiochemical properties of the sediment, water quality has a greater impact on antibiotic partitioning. We found that the partitioning of antibiotics was significantly positively correlated with salinity, suspended solids, pH, NH4+-N and Zn; and negatively correlated with temperature, dissolved oxygen, PO43-, chemical oxygen demand, NO3--N, oil, Cu and Cd. The ecological risks of antibiotics in water and sediment were also evaluated for revealing their relationship with the concentration partitioning of antibiotics. Results showed that the target antibiotics mainly pose ecological risks to Daphnia with low and median chronic toxicity risk rather than fish and green algae. The antibiotics in sediment were more chronically toxic to Daphnia than that in water. The risk quotient ratio of sediment and water (RQs/RQw) ranged from 0 to 1154.0, which were exactly opposite of the values of organic carbon normalized partition coefficient (Koc), suggesting that the physical properties of antibiotics drove the ecological risk allocation of antibiotics in sediment and water.

Fate of antibiotics in engineered wastewater systems and receiving water environment: A case study on the coast of Hangzhou Bay, China.

The occurrence of man-made antibiotics in natural environment has aroused attentions from both scientists and publics. However, few studies tracked antibiotics from their production site to the end of disposal environment. Taking the coastal region of Hangzhou Bay as the study area, the fate of 77 antibiotics from 6 categories in two-step wastewater treatment plants (WTPs, i.e. pharmaceutical WTP and integrated WTP) was focused; and the antibiotics in both dissolved and adsorbed phases were investigated simultaneously in this study. The ubiquitous occurrence of antibiotics was observed in the two-step WTPs, with antibiotic concentrations following the order of PWTP (LOQ - 1.0 × 105 ng·L-1) > IWTPi (for industrial wastewater treatment, LOQ - 3.7 × 103 ng·L-1) > IWTPd (for domestic sewage treatment, LOQ - 1.3 × 103 ng·L-1). And the types of antibiotics detected in excess sludge and suspended particles were in accordance with those in wastewater. Quinolones were invariably dominant in both dissolved and adsorbed fractions. High removal efficiencies (median values >50.0%) were acquired for the dissolved quinolones (except for DFX), tetracyclines, ß-lactams, and lincosamides. Anaerobic/anoxic/oxic achieved the highest aqueous removal of antibiotics among the investigated treatment technologies in the three WTPs. PWTP and IWTP removed 9797 and 487 g·d-1 of antibiotics, respectively; and a final effluent with 126.4 g·d-1 of antibiotics was discharged into the effluent-receiving area (ERA) of Hangzhou Bay. Source apportionment analysis demonstrated that the effluents of IWTPd and IWTPd contributed respectively 39.3% and 8.9% to the total antibiotics in the ERA. The results illustrate quantitatively the antibiotic flows from engineered wastewater systems to natural water environment, on the basis of which the improvements of wastewater treatment technologies and discharge management would be put forward.

Identification of the priority antibiotics based on their detection frequency, concentration, and ecological risk in urbanized coastal water.

Antibiotics have raised significant concern as emerging pollutants for their increasing consumption, persistent input, and potential threat to ecological environment. Due to low concentrations and various types in coastal water, simultaneous quantification of all kinds of antibiotics is time-consuming and costly. In order to make antibiotic regular monitoring in coastal water possible, identifying the priority antibiotics in the environment is essential. Here, a method for screening the priority antibiotics in coastal water was proposed, considering individual antibiotic concentration, the positive correlation between individual and total antibiotic concentration, the detection frequency, and obvious ecological risk. Taking coastal water of the East China Sea as an example, on a list of 77 target antibiotics, 7 (SMX, TMP, SCP, SMP, CNX, ATM, and ETM) and 4 (SMX, SCP, SMP, and CNX) antibiotics were selected to be the priority antibiotics in 2017 and 2018, respectively. Furthermore, the 4 priority antibiotics in 2018 were all involved in the 7 priority antibiotics in 2017. The sum of the priority antibiotic concentrations accounted for 0.8% and 23.2% of total antibiotic concentrations, and the sum of their RQ accounted for 69.2% and 66.8% of total RQ values in 2017 and 2018, respectively. Among the above 7 priority antibiotics, ATM is mainly used in human clinical, SMX, SCP, and SMP are mainly consumed in veterinary medicine, TMP, CNX, and ETM are commonly used for humans and animals. The proposed method might provide an important reference for the monitoring and management of antibiotic pollution in coastal water.

Antibiotics in coastal water and sediments of the East China Sea: Distribution, ecological risk assessment and indicators screening.

The distribution of 77 antibiotics in the coastal water and sediment from 3 bays of the East China Sea was investigated. There were 43 and 25 antibiotics detected with total concentrations of 30.8-2106.1 ng/L and 2.2-99.9 ng/g in water and sediment, respectively. Approximately 83.0% and 85.4% of the individual antibiotic concentrations were lower than 5.0 ng/L in water and 1.0 ng/g in sediment. Clindamycin (1.2-1507.9 ng/L, mean 183.8 ng/L) and erythromycin (ND-45.2 ng/g, mean 3.4 ng/g) were the most abundant in water and sediment, respectively. Ecological risk assessment revealed that the joint toxicity was enhanced when multiple antibiotics were present simultaneously. A decrease in the total antibiotic concentration and the ecological risk in water was observed from nearshore to offshore. Three antibiotics (sulfamethoxypyridazine, sulfamethoxazole and cinoxacin) were selected to be prioritized based on ecological risks for antibiotics monitoring and management of the coastal water in the East China Sea.