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.

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.

探索微生物群落时空分布和构建机制一直是环境微生物生态学研究的目标和挑战。近年来，微生物生态学规律和理论逐渐在工程系统中得到应用，分类群-面积关系、分类群-时间关系和距离-衰减效应等规律已在污水处理系统的微生物群落分布中得到验证。随着研究的发展，微生物时空分布研究已从群落分布规律的发现和描述，拓展到驱动群落分布的因素，即群落构建机制的探索。介绍了污水处理系统微生物群落时空分布规律和构建机制的研究进展，并对未来的方向进行了展望，强调了将生态理论和工程实践相结合的重要性。未来应在污水处理系统核心微生物研究、微生物群落的生物多样性、构建机制与污水处理性能的关联、多组学技术在微生物时空分布和构建机制研究中的应用等方面有所突破。

In bioaugmented wastewater treatment systems, it is essential for recalcitrant pollutant-degrading bacteria to form biofilms. Inducing biofilm formation in these bacteria, however, is challenging as it involves multiple inter-related regulating pathways and environmental factors. Herein, we report the remarkable promoting effect of Ca2+ on biofilm formation of two novel pyridine-degrading bacteria with poor innate biofilm-forming capabilities, Pseudomonas sp. ZX01 and Arthrobacter sp. ZX07. The roles of Ca2+ in different biofilm development stages were investigated. Our data showed strong influences of Ca2+ on the initial attachment of the two strains onto positively charged glass surfaces by altering cell surface charge as well as the cation bridging effect. Contrary to many other biofilm promoting mechanisms, Ca2+ downregulated the extracellular polymeric substances (EPS) production per cell in both Pseudomonas sp. ZX01 and Arthrobacter sp. ZX07, while increasing biofilm biomass. This is attributed to the strong cationic bridging between Ca2+ and EPS which can elevate the efficiency of the extracellular products in binding bacterial cells. Furthermore, Ca2+ increased the protein-to-polysaccharide (PN/PS) ratio in biofilm EPS of both strains, which favored cell aggregation, and biofilm establishment by increasing the hydrophobicity of cell surfaces. More intriguingly, the intracellular c-di-GMP, which can drive the switch of bacterial lifestyle from planktonic state to biofilm state, was also elevated markedly by exogenous Ca2+. Taken together, these results would be of guidance for applying the two strains into bioaugmented biofilm reactors where Ca2+ supplement strategy can be employed to facilitate their biofilm formation on the surfaces of engineering carriers.

Nutrient scarcity is pervasive for natural microbial communities, affecting species reproduction and co-existence. However, it remains unclear whether there are general rules of how microbial species abundances are shaped by biotic and abiotic factors. Here we show that the ribosomal RNA gene operon (rrn) copy number, a genomic trait related to bacterial growth rate and nutrient demand, decreases from the abundant to the rare biosphere in the nutrient-rich coastal sediment but exhibits the opposite pattern in the nutrient-scarce pelagic zone of the global ocean. Both patterns are underlain by positive correlations between community-level rrn copy number and nutrients. Furthermore, inter-species co-exclusion inferred by negative network associations is observed more in coastal sediment than in ocean water samples. Nutrient manipulation experiments yield effects of nutrient availability on rrn copy numbers and network associations that are consistent with our field observations. Based on these results, we propose a “hunger games” hypothesis to define microbial species abundance rules using the rrn copy number, ecological interaction, and nutrient availability.

Microplastics have become global emerging issue and received widespread attention in recent years. Due to their chemical persistence, plastic particles can be broken into smaller items but accumulated for long time in the environment like sediment. However, limited by current detection technologies, the distribution and characteristics of small-sized microplastics in coastal sediment remain uncertain. In this study, we established a new method based on micro-Raman spectroscopy for detecting small-sized microplastics, namely multipoint confocal micro-Raman spectrum scanning (MCmRSS). The MCmRSS was first applied in detecting microplastics in the sediment samples collected from three bays of the East China Sea. The minimum size of microplastics was 4 μm and average microplastics concentration was 91 ± 55 items /g dry weight sediment, with fragment and polyethylene as the most common shape and polymer type, respectively. The spatial variation of microplastics was in accordance with the strength of coastal human activities and marine dynamics. In all the microplastic items, the small-sized ones (<10 μm) accounted for 67%; and the relationship between microplastic concentration and its size followed a power-exponential equation. Compared with previous studies, the number of microplastics in coastal sediments detected by the MCmRSS increased by 2 orders of magnitude, which was benefited from the advantages of multipoint scanning in the fixed identification areas and high resolution of micro-Raman spectrum. Our findings would summon the re-evaluation of the potential risks of small-sized microplastics in the coastal environment.

难降解工业废水高效处理是制约我国经济发展与环境保护的重大问题,近年来我国及其他国家在该领域取得了技术和理论上的巨大进步。首先总结了工业废水预处理-生物处理-深度处理三级处理体系的技术全貌,对各级处理单元具有代表性的技术及其适用性、发展趋势进行了讨论;其次重点论述了在污染物降解途径识别、微生物群落结构和功能解析、高风险污染物生态和健康风险评价等方面的理论探索。在我国大力推进生态文明建设、实施绿色低碳发展战略的背景下,日益多元化和系统化的废水治理技术与理论体系将深刻影响未来工业发展的布局和路径。

Background Mangrove ecosystems are vulnerable due to the exotic Spartina alterniflora (S. alterniflora) invasion in China. However, little is known about mangrove sediment microbial community assembly processes and interactions under S. alterniflora invasion. Here, we investigated the assembly processes and co-occurrence networks of the archaeal and bacterial communities under S. alterniflora invasion along the coastlines of Fujian province, southeast China. Results Assembly of overall archaeal and bacterial communities was driven predominantly by stochastic processes, and the relative role of stochasticity was stronger for bacteria than archaea. Co-occurrence network analyses showed that the network structure of bacteria was more complex than that of the archaea. The keystone taxa often had low relative abundances (conditionally rare taxa), suggesting low abundance taxa may significantly contribute to network stability. Moreover, S. alterniflora invasion increased bacterial and archaeal drift process (part of stochastic processes), and improved archaeal network complexity and stability, but decreased the network complexity and stability of bacteria. This could be attributed to S. alterniflora invasion influenced microbial communities diversity and dispersal ability, as well as soil environmental conditions. Conclusions This study fills a gap in the community assembly and co-occurrence patterns of both archaea and bacteria in mangrove ecosystem under S. alterniflora invasion. Thereby provides new insights of the plant invasion on mangrove microbial biogeographic distribution and co-occurrence network patterns.