Class 1 integrons facilitate horizontal gene transfer, significantly influencing antibiotic resistance gene (ARG) dissemination within microbial communities. Wastewater treatment plants (WWTPs) are critical reservoirs of ARGs and integrons, yet the integron-mediated dynamics of ARG transfer across different WWTP types remain poorly understood. Here we show distinct ARG profiles associated with class 1 integrons in municipal and industrial WWTPs using a novel approach combining nested-like high-throughput qPCR and PacBio sequencing. Although industrial WWTPs contained higher absolute integron abundances, their relative ARG content was lower (1.27 × 107–9.59 × 107 copies/ng integron) compared to municipal WWTPs (3.72 × 107–1.98 × 108 copies/ng integron). Of the 132,084 coding sequences detected from integrons, 56.8 % encoded antibiotic resistance, with industrial plants showing lower ARG proportions, reduced ARG array diversity, and greater incorporation of non-ARG sequences. These findings suggest industrial WWTP integrons integrate a broader array of exogenous genes, reflecting adaptation to complex wastewater compositions. This work enhances our understanding of integron-driven ARG dynamics in wastewater and offers a robust strategy for environmental integron analysis.

Quorum quenching (QQ)-based strategies are efficient for biofouling control. However, the feasibility of using QQ bacteria in antibiotic-stressed membrane bioreactors (MBRs) remains unknown. In this study, we isolated three novel QQ strains (Bacillus sp. QX01 and QX03, Delftia sp. QX14) from the activated sludge of an actual MBR. They can degrade 11 N-acyl-homoserine lactones (AHLs) with high efficiencies and rates through intracellular QQ pathways involving putative acylases and lactonases. Running two lab-scale MBRs, we found that introducing antibiotics (sulfamethoxazole, azithromycin, and ciprofloxacin, each at 100 μg/L) shortened the fouling cycle by 71.4 %. However, the immobilized inoculation of QX01 into one MBR extended the fouling cycle by 1.5-2.0 times. Quantitative detection revealed that QX01 significantly reduced the concentrations of two AHLs (C4-HSL and C8-HSL), which were positively correlated with the contents of extracellular polymeric substances (EPS) (Pearson's r = 0.62-0.83, P < 0.01). This suggests that QX01 could perform its QQ activity robustly under antibiotic stress, thereby inhibiting EPS production (proteins especially) and biofilm formation. Moreover, QX01 notably altered the succession patterns of both sludge and fouling communities, with more pronounced effects on abundant taxa. Genera associated with AHL synthesis and EPS production, such as Terrimonas and Rhodobacter, were significantly depleted, contributing to the mitigated biofouling. Additionally, QX01 increased the bacterial community diversity (evenness especially), which was inhibited by antibiotics. Overall, we demonstrate that the novel QQ bacteria could be effective for biofouling control in antibiotic-stressed MBRs, though future work is needed to develop practical approaches for prolonging QQ activity.

Coastal sediment cores provide important records of land-based antibiotics' deposition. This study examined sediment cores from the Hangzhou Bay, East China Sea, dating back to 1980–2020 using 210Pbex. The 40-year analysis revealed a mismatch between sediment depth and age. Wastewater treatment facilities have significantly reduced antibiotics discharge into the sea. We identified 27 antibiotics, with enrofloxacin (ERFX) and nadifloxacin (NDFX) exhibiting the highest average concentrations of 84.9 and 83.4 ng/g, respectively. Quinolones (QNs) were prominent, displaying strong co-occurrence and similar distribution patterns shaped by comparable soil-water distribution coefficient (Kd). QNs correlated positively with total antibiotic concentration, serving as indicators. We proposed a multi-dimensional risk assessment of antibiotics, encompassing ecological and antimicrobial resistance (AMR) risks, complementing each other. The assessment revealed antibiotics with distinct risks: sulfacetamide (SCM) and clindamycin (CLIN) exhibited high ecological risks, while ERFX, ciprofloxacin (CFX), norfloxacin (NFX), gatifloxacin (GTFX), moxifloxacin (MXFX), and marbofloxacin (MBFX) presented high AMR risks.

Effective risk assessment and control of environmental antibiotic resistance depend on comprehensive information about antibiotic resistance genes (ARGs) and their microbial hosts. Advances in sequencing technologies and bioinformatics have enabled the identification of ARG hosts using metagenome-assembled contigs and genomes. However, these approaches often suffer from information loss and require extensive computational resources. Here we introduce a bioinformatic strategy that identifies ARG hosts by prescreening ARG-like reads (ALRs) directly from total metagenomic datasets. This ALR-based method offers several advantages: (1) it enables the detection of low-abundance ARG hosts with higher accuracy in complex environments; (2) it establishes a direct relationship between the abundance of ARGs and their hosts; and (3) it reduces computation time by approximately 44–96% compared to strategies relying on assembled contigs and genomes. We applied our ALR-based strategy alongside two traditional methods to investigate a typical human-impacted environment. The results were consistent across all methods, revealing that ARGs are predominantly carried by Gammaproteobacteria and Bacilli, and their distribution patterns may indicate the impact of wastewater discharge on coastal resistome. Our strategy provides rapid and accurate identification of antibiotic-resistant bacteria, offering valuable insights for the high-throughput surveillance of environmental antibiotic resistance. This study further expands our knowledge of ARG-related risk management in future.

The ecological impact of microplastics (MPs) in coastal environments has been widely studied. However, the influence of small microplastics in the actual environment is often overlooked due to measurement challenges. In this study, Hangzhou Bay (HZB), China, was selected as our study area. High-throughput metagenomic sequencing and micro-Raman spectrometry were employed to analyze the microbial communities and microplastics of coastal sediment samples, respectively. We aimed to explore the ecological impact of MPs with small sizes (≤ 100 μm) in real coastal sediment environments. Our results revealed that as microplastic size decreased, the environmental behavior of MPs underwent alterations. In the coastal sediments, no significant correlations were observed between the detected MPs and the whole microbial communities, but small MPs posed potential hazards to eukaryotic communities. Moreover, these small MPs were more prone to microbial degradation and significantly affected carbon metabolism in the habitat. This study is the first to reveal the comprehensive impact of small MPs on microbial communities in a real coastal sediment environment.

污水处理厂(WWTPs)是连接物质的社会循环和自然循环的枢纽。现代WWTPs能够去除污水中的大量污染物，但是残留污染物及菌体仍随排水进入自然环境，对受纳水域造成很大干扰。微生物驱动着物质的生物地球化学循环，受纳水域的微生物群落是响应排水干扰的先锋生物。从群落结构、响应策略、致病菌与抗生素抗性传播3个方面总结了WWTPs尾水排放对受纳水域微生物群落的影响。尾水排放显著改变了受纳水域的微生物群落结构；微生物群落通过改变营养利用策略与种间关系以响应排放干扰，使污染物代谢功能在微生物群落中富集。尾水是向水环境输入致病菌与耐药菌的重要点源，也在一定程度上促进了致病菌与抗生素抗性在微生物群落中的传播。充分理解WWTPs排水对受纳水体微生物群落的影响，是开展WWTPs排水管理和健康风险控制的科学基础。

以污染形势严峻的东海杭州湾(HB)为研究对象,采用超高效液相色谱质谱联用仪,探究6类77种抗生素在污水处理厂、近岸纳污区和近海地区的组成和分布规律。检测结果显示,污水处理厂对抗生素的去除率介于31.1%～88.8%,其中对喹诺酮类抗生素去除率最高,平均为80.3%。污水厂出水排入相应的近岸纳污区,嘉兴(JX)纳污区检出53种抗生素,平均浓度为48180.7 ng/L,上虞(SY)纳污区检出63种抗生素,平均浓度为341.2 ng/L。主成分分析结果表明,污水处理厂是SY纳污区抗生素污染的重要来源,而JX纳污区抗生素受污水处理厂排水的影响小,明显受到含有兽用抗生素的其他污染源影响。近岸纳污区汇集了含抗生素废水后,成为近海抗生素污染的“源”。近海检出51种抗生素,平均浓度达189.5 ng/L。抗生素浓度从近岸向近海扩散存在明显的“距离衰减”趋势,尤其以喹诺酮类抗生素的衰减幅度最大。

Fecal waste is a significant source of antimicrobial resistance (AMR) pollution and provides valuable insights into the AMR development in animal and human populations within the “One health” framework. Various genetic elements, including antibiotic resistance genes (ARGs), biocide and metal resistance genes (BMGs), mobile genetic elements (MGEs), and virulence factor genes (VFGs), are crucial AMR risk determinants (ARDs). However, few studies focused on compositional characteristics of ARDs in different feces. Here, we analyzed 753 public metagenomes from human, pig, chicken, and cattle feces, revealing significant differences in ARD richness and abundance across fecal types, notably lowest in cattle samples. Tetracycline, multi-metal, and -biocide resistance genes were dominant resistome. A few core genes contributed to 25.6%–91.1% of gene abundance, and their correlations were stronger in cattle samples. Procrustes analysis showed that microbial composition had higher correlations with ARGs (M2 = 0.579) and BMGs (M2 = 0.519). Gammaproteobacteria was identified as major ARD-hosts especially in human and pig feces, and they mainly carried multi-resistance genes. MGEs exhibited direct positive effects on ARGs and BMGs, indirectly impacting VFGs. Utilizing random forest methods, we identified 42 indicator genes for tracking AMR pollution originating from fecal sources in the environments. This study offers new insights into understanding and controlling the AMR pollution of fecal waste from human and food animals.

Bacterial community is strongly associated with activated sludge performance, but there still remains a knowledge gap regarding the rare bacterial community assembly and their influence on the system performance in industrial wastewater treatment plants (IWWTPs). Here, we investigated bacterial communities in 11 full-scale IWWTPs with similar process designs, aiming to uncover ecological processes and functional traits regulating abundant and rare communities. Our findings indicated that abundant bacterial community assembly was governed by stochastic processes; thereby, abundant taxa are generally present in wastewater treatment compartments across different industrial types. On the contrary, rare bacterial taxa were primarily driven by deterministic processes (homogeneous selection 61.9%-79.7%), thus they only exited in specific IWWTPs compartments and wastewater types. The co-occurrence networks analysis showed that the majority of keystone taxa were rare bacterial taxa, with rare taxa contributing more to network stability. Furthermore, rare bacteria rather than abundant bacteria in the oxic compartment contributed more to the degradation of xenobiotics compounds, and they were main potential drivers of pollutant removal. This study demonstrated the irreplaceable roles of rare bacterial taxa in maintaining system performance of IWWTPs, and called for environmental engineers and microbial ecologists to increase their attention on rare biosphere.

Quorum sensing (QS)-based manipulations emerge as a promising solution for biofilm reactors to overcome challenges from inefficient biofilm formation and lengthy start-ups. However, the ecological mechanisms underlying how QS regulates microbial behaviors and community assembly remain elusive. Herein, by introducing different levels of N-acyl-homoserine lactones, we manipulated the strength of QS during the start-up of moving bed biofilm reactors and compared the dynamics of bacterial communities. We found that enhanced QS elevated the fitness of fast-growing bacteria with high ribosomal RNA operon (rrn) copy numbers in their genomes in both the sludge and biofilm communities. This led to notably increased extracellular substance production, as evidenced by strong positive correlations between community-level rrn copy numbers and extracellular proteins and polysaccharides (Pearson's r = 0.529−0.830, P < 0.001). Network analyses demonstrated that enhanced QS significantly promoted the ecological interactions among taxa, particularly cooperative interactions. Bacterial taxa with higher network degrees were more strongly correlated with extracellular substances, suggesting their crucial roles as public goods in regulating bacterial interactions and shaping network structures. However, the assembly of more cooperative communities in QS-enhanced reactors came at the cost of decreased network stability and modularity. Null model and dissimilarity-overlap curve analysis revealed that enhanced QS strengthened stochastic processes in community assembly and rendered the universal population dynamics more convergent. Additionally, these shaping effects were consistent for both the sludge and biofilm communities, underpinning the planktonic-to-biofilm transition. This work highlights that QS manipulations efficiently drive community assembly and confer specialized functional traits to communities by recruiting taxa with specific life strategies and regulating interspecific interactions. These ecological insights deepen our understanding of the rules governing microbial societies and provide guidance for managing engineering ecosystems.

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.

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。

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.