Domestic and industrial wastewater treatment plants (WWTPs) are facing formidable challenges in effectively eliminating emerging pollutants and conventional nutrients. In microbiome engineering, two approaches have been developed: a top-down method focusing on domesticating seed microbiomes into engineered ones, and a bottom-up strategy that synthesizes engineered microbiomes from microbial isolates. However, these approaches face substantial hurdles that limit their real-world applicability in wastewater treatment engineering. Addressing this gap, we propose the creation of a Global WWTP Microbiome-based Integrative Information Platform, inspired by the untapped microbiome and engineering data from WWTPs and advancements in artificial intelligence (AI). This open platform integrates microbiome and engineering information globally and utilizes AI-driven tools for identifying seed microbiomes for new plants, providing technical upgrades for existing facilities, and deploying microbiomes for accidental pollution remediation. Beyond its practical applications, this platform has significant scientific and social value, supporting multidisciplinary research, documenting microbial evolution, advancing Wastewater-Based Epidemiology, and enhancing global resource sharing. Overall, the platform is expected to enhance WWTPs’ performance in pollution control, safeguarding a harmonious and healthy future for human society and the natural environment.

抗生素耐药性在环境中的发展和传播对人体健康造成潜在风险。随着高通量测序技术和生物信息学方法的不断发展，宏基因组学技术被广泛应用于不同环境样本的抗生素耐药组研究。本文介绍了两种针对环境耐药组筛查的宏基因组学分析方法，总结了当前主流的生物信息学软件和数据库，并阐述了环境耐药组的风险评估框架和基于宏基因组学技术的相关实践，以期为环境耐药组的监测、风险评估和管控提供可行的路线图。

Antimicrobial resistance (AMR) has emerged as a significant challenge in human health. Wastewater treatment plants (WWTPs), acting as a link between human activities and the environment, create ideal conditions for the selection and spread of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). Unfortunately, current treatment processes are ineffective in removing ARGs, resulting in the release of large quantities of ARB and ARGs into the aquatic environment through WWTP effluents. This, in turn, leads to their dispersion and potential transmission to human through water and the food chain. To safeguard human and environmental health, it is crucial to comprehend the mechanisms by which WWTP effluent discharge influences the distribution and diffusion of ARGs in downstream waterbodies. In this study, we examine the latest researches on the antibiotic resistome in various waterbodies that have been exposed to WWTP effluent, highlighting the key influencing mechanisms. Furthermore, recommendations for future research and management strategies to control the dissemination of ARGs from WWTPs to the environment are provided, with the aim to achieve the “One Health” objective.

Wastewater treatment plants (WWTPs) effluent often contains a significant amount of residual organic pollutants and nutrients, causing disturbance to the coastal effluent receiving areas (ERA). Microbial communities in coastal ERA sediments may benefit from the coexistence of organic pollutants and nutrients, promoting the emergence of versatile taxa that are capable of eliminating these substances simultaneously. However, the identification and exploration of versatile taxa in natural environments under anthropogenic disturbances remain largely uncharted territory. In this study, we specifically focused on the versatile taxa coupled by the degradation of aromatic compounds (ACs) and denitrification, using Hangzhou Bay in China as our study area. We explored how WWTPs effluent disturbance would affect the versatile taxa, and particularly examined the role of disturbance intensity in shaping their composition. Intriguingly, we found that versatile taxa were mainly derived from denitrifiers like Pseudomonas, suggesting the fulfilled potential of denitrifiers regarding ACs degradation. We also discovered that moderate disturbance stimulated the diversity of versatile taxa, resulting in strengthened functional redundancy. Through correlation network analysis, we further demonstrated that moderate disturbance enhanced the community-level cooperation. Thus, moderate disturbance serves as a catalyst for versatile taxa to maintain community function, making them more resilient to effluent disturbances. Additionally, we identified COD and NO3−-N concentrations as significant environmental factors influencing the versatile taxa. Overall, our findings reveal the role of effluent disturbances in the promotion of versatile taxa, and highlight moderate disturbance can foster more robust versatile taxa that are better equipped to handle effluent disturbances.

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.

随着现代城市和工商业的快速发展，污水处理厂成为保护水环境的重要设施，然而污水处理厂的尾水排放仍然对受纳水体产生不利影响。沿海地区的污水处理厂长期将尾水排入近海，引起海水水质变差，但是近海环境微生物对污染的响应尚不清晰。本研究选择我国污染形势严峻的杭州湾北岸、南岸各一片纳污区（简称JX 和SY）为研究对象，进行环境质量调查，并对沉积物微生物群落进行宏基因组测序，分析不同类型的废水排放对纳污区微生物群落结构和功能的潜在影响。研究结果表明，陆源废水排放对纳污区沉积物的微生物群落产生影响。JX和SY群落的物种组成和多样性存在差异，造成这种差异的关键环境因子为水中COD以及水深；JX和SY群落的碳代谢功能也存在差异，JX群落中与甲烷代谢相关的功能基因丰度更高，而SY群落中与糖异生途径相关的功能基因丰度更高，主要影响因子为水中COD和沉积物中TOC及石油类。上述结果对纳污海域的环境管理具有重要意义，并为完善污水处理厂排放标准提供了科学依据。

污水处理厂是向水环境中传播抗生素抗性基因(antibiotic resistance genes， ARGs)的热点。与城镇污水相比，工业园区废水成分复杂、污染物浓度高，更有利于ARGs的增殖和扩散。为探究不同类型废水环境的ARGs组成特征和潜在的传播风险，采用宏基因组学技术分别对城镇生活污水处理系统(W1-SD)、工业园区废水处理系统(W1-SI)和2个城镇综合污水处理系统(W2-LH1和W2-LH2)进行取样调查。结果显示，多重耐药类、磺胺类、氨基糖苷类和杆菌肽类抗性基因是废水环境中的主要耐药类型，Ⅰ型整合子、转座酶基因等可移动遗传元件(MGEs)对sul1、aadA和ereA等基因亚型的增殖扩散发挥了关键作用，通过序列分型发现质粒型ARGs的相对丰度更高，尤其是在进水样品中，氨基糖苷类和磺胺类等抗性基因是主要的质粒型ARGs；污水处理过程削减了ARGs多样性，且经过二次沉淀工艺，ARGs丰度均明显降低，但在W1-SI和W2-LH2中，后续的深度处理工艺又使ARGs丰度升高；与城镇污水处理系统相比，W1-SI的ARGs组成更为稳定，最终排水中富集了较高丰度的质粒型ARGs，同时识别到了高频率的潜在水平基因转移事件和2条携带多种抗性基因的重叠群序列(contigs)，表明工业园区废水排放具有更高的ARGs传播风险。本研究丰富了不同类型废水环境耐药基因组的已有认知，为有效管控废水排放特别是工业园区废水排放的健康风险提供了科学依据。

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.

Wastewater treatment plants (WWTPs) have been regarded as an important source of antibiotic resistance genes (ARGs) in environment, but out of municipal domestic WWTPs, few evidences show how environment is affected by industrial WWTPs. Here we chose Hangzhou Bay (HZB), China as our study area, where land-based municipal and industrial WWTPs discharged their effluent into the bay for decades. We adopted high-throughput metagenomic sequencing to examine the antibiotic resistome of the WWTP effluent and coastal sediment samples. And we proposed a conceptual framework for the assessment of antibiotic resistome risk, and a new bioinformatic pipeline for the evaluation of the potential horizontal gene transfer (HGT) frequency. Our results revealed that the diversity and abundance of ARGs in the WWTP’s effluent were significantly higher than those in the sediment. Furthermore, the antibiotic resistome in the effluent-receiving area (ERA) showed significant difference from that in HZB. For the first time, we identified that industrial WWTP effluent boosted antibiotic resistome risk in coastal sediment. The crucial evidences included: 1) the proportion of ARGs derived from WWTP activated sludge (WA) was higher (14.3 %) and two high-risky polymyxin resistance genes (mcr-4 and mcr-5) were enriched in the industrial effluent receiving area; 2) the HGT potential was higher between resistant microbiome of the industrial effluent and its ERA sediment; and 3) the highest resistome risk was determined in the industrial effluent, and some biocide resistance genes located on high-risky contigs were related to long-term stress of industrial chemicals. These findings highlight the important effects of industrial activities on the development of environmental antimicrobial resistance.