The proliferation of antibiotic resistance genes (ARGs) in environmental microbiomes represents a major and growing threat to public health, creating a critical demand for precise and efficient tools to monitor resistance risk. Current approaches often depend on contig-based quantification or lack comprehensive risk indices, which compromises their accuracy and utility. To address this, we developed MetaRanker (https://github.com/SteamedFish6/MetaRanker), a computational pipeline that assesses resistome risk by integrating the abundance of ARGs, mobile genetic elements (MGEs), and virulence factors (VFs)-calculated directly from sequencing reads-with their genetic co-occurrence on contigs into a unified risk index (RI). This index reflects the potential for horizontal transfer and pathogen emergence. Evaluated using in silico and diverse real-world metagenomes (n = 353), MetaRanker demonstrated superior accuracy and stronger discriminatory power than existing methods. Its optimized compact database (29.6 MB) and alignment strategy reduced runtime by over 50% in comparison to MetaCompare 2.0 under identical hardware configurations (32 CPU cores, 128 GB RAM). Practical applications confirmed that MetaRanker effectively discriminates risk levels across environments (e.g., hospital wastewater versus natural soil) and quantifies risk mitigation through wastewater treatment. As a robust, lightweight, and sequencing-platform-agnostic tool, MetaRanker offers a powerful solution for comprehensive environmental resistome surveillance and evidence-based risk management.IMPORTANCEThe environmental reservoir of antibiotic resistance is a key contributor to the global health crisis of antimicrobial resistance. Effective surveillance and risk assessment of complex microbial communities are essential for prioritizing interventions and safeguarding public health. However, existing methods often provide fragmented or computationally demanding analyses, limiting their practical application for large-scale environmental monitoring. The significance of our work lies in developing MetaRanker, which overcomes these barriers by delivering a fast, accurate, and integrated metric of resistome risk. By simultaneously accounting for the abundance, mobility potential, and pathogenicity linkage of resistance determinants, MetaRanker enables a more realistic threat assessment. This tool empowers researchers and public health officials to track resistance hotspots, evaluate the impact of human activities such as waste disposal, and monitor the effectiveness of mitigation strategies, ultimately supporting data-driven decisions to curb the environmental spread of resistance.

The lack of a predictive, first-principles model has confined the development of isothermal exponential amplification (IEA) to empirical optimization for decades, hindering its quantitative potential. Here, we resolve this by establishing a universal kinetic framework that defines amplification efficiency through three fundamental physical parameters: the polymerase extension rate (Se), the amplicon size (Sa), and the primer-template binding efficiency (ξ). The model reveals the apparent doubling time as $T = \frac{{{{S}_a}}}{{\xi \cdot {{S}_e}}}$, providing a unified physical explanation for IEA efficiency across diverse mechanisms, including loop-mediated isothermal amplification (LAMP), strand displacement amplification (SDA), recombinase polymerase amplification (RPA), and helicase-dependent amplification (HDA). Crucially, we mathematically demonstrate that the complex kinetics of LAMP, a case study with extreme product heterogeneity, are structurally isomorphic to simple exponential growth. A Taylor expansion proves that LAMP product heterogeneity emerges as a Poisson process, a prediction we confirm experimentally. This framework accurately predicts quantification outcomes under varying conditions (enzyme, temperature, and inhibitors) and enables robust viral quantification in wastewater. By bridging fundamental enzymology with point-of-care applications, our work provides a general blueprint for optimizing IEA by engineering polymerase speed (Se), minimizing amplicon size (Sa), and fine-tuning primer-binding efficiency (ξ).

Reverse transcription quantitative PCR (RT-qPCR) is widely used in wastewater-based epidemiology (WBE) but is frequently compromised by matrix-associated inhibition. While mitigation strategies abound, a systematic framework for diagnosing RT-qPCR inhibition in wastewater remains lacking. Here, a mechanistic classification framework for RT-qPCR inhibitors in wastewater is established based on two orthogonal dimensions: kinetic effect (linear vs. exponential inhibition) and molecular target (nucleic acid sequestrators vs. enzyme activity inhibitors). This framework enables diagnosis of the dominant inhibitor types in a given sample and predicts the efficacy of mitigation strategies. Guided by this framework, the following findings are demonstrated: (1) sample dilution effectively relieves enzyme activity inhibition but fails to address nucleic acid sequestrators; (2) two-step RT-qPCR—by decoupling reverse transcription and PCR amplification—effectively circumvents RT-qPCR inhibition under the tested conditions. Notably, supplementation with T4 gene 32 protein (gp32), a single-stranded DNA-binding protein predicted by the framework to selectively relieve RNA sequestrators, did not produce consistent improvement across wastewater samples—a result that, within the diagnostic logic of the framework, implicates enzyme inhibitors as the predominant inhibitory species in our sample set. The deinhibition rate, introduced here as a quantitative metric, varied predictably with wastewater characteristics, extraction method, and target RNA concentration, with high-abundance RNA viruses showing disproportionately stronger effects. These findings provide a theoretical foundation and practical guidance for improving the accuracy and reliability of RT-qPCR-based wastewater surveillance.

Wastewater-based epidemiology (WBE) enables community-level pathogen surveillance, yet incomplete understanding of viral partitioning behavior complicates strategy optimization and data interpretation. We demonstrated that pH and surfactants critically govern viral distribution between wastewater phases. Despite high solid-liquid partition coefficients, viruses predominantly reside in the liquid phase due to wastewater's low solid content (102-103 mg/L). Leveraging these insights, we conducted one-year RT-qPCR surveillance across Sichuan University and Chengdu, capturing two SARS-CoV-2 waves and an influenza A outbreak. To address lineage demixing challenges from suboptimal sequencing, we developed NextVpower, a deconvolution tool resolving co-circulating lineages while tracking critical mutations for clinical early-warning. Notably, NextVpower achieved the first demixing of both HA- and NA-lineages for H3N2 influenza A virus in wastewater. This advances WBE's capacity to link wastewater-derived mutations to epidemiological trends, enhancing real-time outbreak preparedness through optimized viral recovery and lineage-resolved analytics.

The rapid development of industry has led to the discharge of large quantities of organic pollutants into water bodies, posing a significant threat to aquatic safety. It is imperative to develop efficient and environmentally friendly methods for the elimination of organic pollutants. The integration of hydrogel membranes with advanced oxidation processes (AOPs) for water purification has attracted considerable interest due to their high efficiency. However, conventional wet membrane materials stored in aqueous environments are more prone to swelling and leakage of loaded metal species. This limits its application in the degradation of organic pollutants. This study employs a vacuum drying strategy for wet hydrogels, incorporating molybdenum disulfide as a cocatalyst and Co2+ cross-linking within the alginate matrix, resulting in a dried MoS2–cobalt alginate hydrogel membrane (D-MoS2-CoAlg). The drying process of the D-MoS2-CoAlg membrane not only significantly enhanced its mechanical strength and anti-swelling capacity but also effectively mitigated the leaching of Co2+. Throughout five consecutive cycles, the concentration of leached Co2+ remained below 0.032 mg/L. This enables the membrane to achieve a balance between reusability and environmental compatibility. Under the conditions of a drying time of 60 min, a peroxymonosulfate (PMS) dosage of 0.2 mmol/L, and an initial methylisothiazolinone (MIT) concentration of 20 mg/L, the D-MoS2-CoAlg membrane exhibited exceptional catalytic performance, achieving a degradation rate of MIT as high as 92.14% within 5 min. The D-MoS2-CoAlg membrane demonstrates high catalytic activity and good stability, showing promising potential for application in the field of organic wastewater treatment.

The extensive prescription of fluoroquinolone antibiotics has resulted in their ubiquitous presence in the environment, fueling the ongoing development of antibiotic resistance. Besides antibiotics, fluoroquinolone production intermediates, an overlooked category of pollutants that oftentimes possess the intact fluoroquinolone core structure, may also contribute to this public health crisis. To assess their relative potency and collectively examine the structural effects of fluoroquinolones on resistance development, wild-type Escherichia coli K12 was exposed to ten fluoroquinolone antibiotics and five intermediates at their environmentally relevant concentrations for 30 days. Phenotypic resistance alterations revealed that the absence of the C7 ring system in fluoroquinolones significantly impaired their capacity to induce resistance in E. coli, potentially due to diminished oxidative DNA damage and gyrase-mediated dsDNA breaks. Genetic and transcriptional analyses indicated that a uniform resistance mechanism emerged under both antibiotic and intermediate stress. Quantitative structure-activity relationship (QSAR) analysis further emphasized the positive impact of both basic nitrogenous heterocyclic rings at C7 (particularly the hydrogen-bond-donor pharmacophores) and aromatic rings at N1 in promoting resistance development, while highlighting the adverse effects of hydrophobic and hydrogen-bond-donor groups at N1. A robust QSAR model was developed and applied to assess the relative risks of other 105 fluoroquinolones. This study underscored the direct role of fluoroquinolone production intermediates in promoting environmental antibiotic resistance and illustrated how different structural features of fluoroquinolone pollutants will influence this process, offering theoretical insights for future antibiotic design and environmental regulation efforts.

Sewage sludge, a ubiquitous by-product of wastewater treatment, accumulates globally. Land application, a prominent waste valorization strategy, inadvertently disseminates the sludge antibiotic resistome into ecosystems, threatening ecological security and public health. Risk assessment of antibiotic resistance (AR) during sludge land application is urgently needed. Herein, we conducted a field study by planting three crops in sludge-amended soil, and monitoring the dynamic evolution of AR risk throughout their growth cycles. Metagenomic sequencing assessed antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), virulence factors (VFs), and their co-occurrence. Sludge amendment exerted persistent, yet largely recoverable, impacts on soil microbial community and the resistome. The resulting AR risk evolution was nonlinear and fluctuating, dominated by soil microbial community reconstruction. Given the differences in crop edible parts, growth periods of crops, complex AR risk dynamics, and external factors like weather, we propose a time-sensitive control strategy targeting critical risk windows. This strategy aims to mitigate AR risk under the "One Health" paradigm for sustainable sludge land application.

During the COVID-19, wastewater-based epidemiology (WBE) has become a powerful epidemic surveillance tool widely used worldwide. However, the development and application of this technology in Chinese Mainland are relatively lagging. Herein, we for the first time monitored the community circulation of SARS-CoV-2 lineages using WBE methods in Chinese Mainland. During the peak period of infection outbreak at the end of 2022, six precious sewage samples were collected from the manhole in the student dormitory area on Wangjiang Campus of Sichuan University. RT-qPCR revealed that the six sewage samples were all positive for SARS-CoV-2 RNA. Multiplex PCR amplicon sequencing of the sewage samples reflected the local transmission of SARS-CoV-2 variants. The results of two deconvolution methods indicate that the main virus lineages have clear evolutionary genetic correlations. Furthermore, the sampling time is consistent with the timeline of concern for these virus lineages, as well as the timeline of uploading the nucleic acid sequences from the corresponding lineages in Sichuan to the database. These results demonstrate the reliability of the sewage sequencing results. Multiplex PCR amplicon sequencing is by far the most powerful analytical tool of WBE, enabling quantitative detection of virus lineages transmission and evolution at the community level.

Lanthanide-organic frameworks (LnOFs) are a class of promising catalysts on a large number of organic reactions because of the higher coordination number of Ln ions, inspired by which exploratory preparation of cluster-based LnOFs was carried out by us. Herein, the exquisite combination of spindly [Ln(μ-OH)(CO)(HO)] clusters (abbreviated as {Ln}) and fluorine-functionalized tetratopic ligand of 2',3'-difluoro-[-terphenyl]-3,3″,5,5″-tetracarboxylic acid (F-HPTTA) engendered two highly robust isomorphic nanoporous frameworks of {[Ln(FPTTA)(μ-OH)(HO)](NO)} (, = and ). compounds are rarely reported {Ln}-based 3D frameworks with nano-caged voids (19 Å × 17 Å), which are shaped by twelve [Ln(μ-OH)(COO)] clusters and eight completely deprotonated F-PTTA ligands. Activated compounds are characterized by plentiful coexisted Lewis acid-base sites of open Ln sites, capped μ-OH, and -F. Judged by the ideal adsorbed solution theory (IAST), activated had a high CO/CH adsorptive selectivity with the value of 12.7 (CO/CH = 50/50) and 9.1 (CO/CH = 5/95) at 298 K, which could lead to high-purity CH (≥99.9996%). Furthermore, catalytic experiments exhibited that , as a representative, could efficiently catalyze the cycloaddition reactions of CO with epoxides as well as the Knoevenagel condensation reactions of aldehydes and malononitrile. This work proves that the {Ln}-based skeletons of with chemical stability, heterogeneity, and recyclability are an excellent acid-base bifunctional catalyst for some organic reactions.

Antibiotic resistance has become a comprehensive and complicated environmental problem. It is of great importance to effectively determine the abundance of various antibiotic resistance genes (ARGs) in the environment. Here, we attempted to find a practical method for monitoring environmental antibiotic resistance. The results of culture-based analysis of antibiotic resistance and metagenomic sequencing indicate that egrets inhabiting along the urban river (Jinjiang River) can be used as the sentinel of environmental antibiotic resistance. The antibiotic resistance in the environment fluctuated with time, while that in the wild bird was relatively stable. The network analysis based on metagenomic sequencing data gave the co-occurrence pattern of ARGs. The overall situation of the antibiotic resistance in the river was determined by quantifying several module hub genes of the co-occurrence network in river sediments. The temporal and spatial distribution of ARGs in Jinjiang River is highly correlated with that of human gut-specific bacteriophage (crAssphage), which indicates that one main source of the antibiotic resistance in the river is likely to be municipal sewage. The mobility potential of ARGs varying among different niches suggests the transmission direction of antibiotic resistance in the environment.

During the pandemic of COVID-19, wastewater-based epidemiology has become a powerful epidemic surveillance tool widely used around the world. However, the development and application of this technology in Chinese Mainland are relatively lagging. Herein, we report the first case of community circulation of SARS-CoV-2 lineages monitored by WBE in Chinese Mainland during the infection outbreak at the end of 2022 after the comprehensive relaxation of epidemic prevention policies. During the peak period of infection, six precious sewage samples were collected from the manhole in the student dormitory area of Wangjiang Campus of Sichuan University. According to the results RT-qPCR, the six sewage samples were all positive for SARS-CoV-2 RNA. Based on multiplex PCR amplicon sequencing, the local transmission of SARS-CoV-2 variants at that time was analyzed. The results show that the main virus lineages in sewage have clear evolutionary genetic correlations. Furthermore, the sampling time is very consistent with the timeline of concern for these virus lineages and consistent with the timeline for uploading the nucleic acid sequences of the corresponding lineages in Sichuan to the database. These results demonstrate the reliability of the sequencing results of SARS-CoV-2 nucleic acid in wastewater. Multiplex PCR amplicon sequencing is by far the most powerful analytical tool of WBE, enabling quantitative monitoring of virus lineage prevalence at the community level.Highlights 1. Six sewage samples were collected on Wangjiang Campus of Sichuan university at the end of 2022.2. SARS-CoV-2 nucleic acid was detected in all six sewage samples via qPCR.3. Multiplex PCR amplicon sequencing reveals the local transmission of SARS-CoV-2 lineages.4. Multiplex PCR amplicon sequencing is to date the most powerful WBE tool.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementThis study was funded by the National Natural Science Foundation of China (No. 22176133, No. 21677104).### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesAll data produced in the present study are available upon reasonable request to the authors* A : Barcode matrix containing lineage-defining mutations for known SARS-CoV-2 lineages a i,j : the mutation of virus lineage i at site j R a - : relative abundance of SARS-CoV-2 gene in sewage (against crAssphage CPQ_056) R a,SARS-CoV-2/GAPDH : relative abundance of SARS-CoV-2 genome in sewage (against GAPDH) C SARS-CoV-2 : concentration of SARS-CoV-2 genome in sewage nucleic acid extracts C T : cycle threshold c 0 : initial copy number of the target gene during qPCR amplification (GC/reaction) P : vectors recording the probability of each mutation site p j : the overall probability of mutation site j t : hydraulic retention time (HRT) of virus/biomarker in sewage (h) t 1/2 : half-life of virus in the sewage (h) X : the vector indicating relative abundance of virus lineages X* : the optimized relative abundance vector x i the relative abundance of virus lineage i

Wastewater-based epidemiology has become a powerful surveillance tool for monitoring the pandemic of COVID-19. Although it is promising to quantitatively correlate the SARS-CoV-2 RNA concentration in wastewater with the incidence of community infection, there is still no consensus on whether the viral nucleic acid concentration in sewage should be normalized against the abundance of endogenous biomarkers and which biomarker should be used as a reference for the normalization. Here, several candidate endogenous reference biomarkers for normalization of SARS-CoV-2 signal in municipal sewage were evaluated. The human fecal indicator virus (crAssphage) is a promising candidate of endogenous reference biomarker for data normalization of both DNA and RNA viruses for its intrinsic viral nature and high and stable content in sewage. Without constructing standard curves, the relative quantification of sewage viral nucleic acid against the abundance of the reference biomarker can be used to correlate with community COVID-19 incidence, which was proved via mimic experiments by spiking pseudovirus of different concentrations in sewage samples. Dilution of pseudovirus-seeded wastewater did not affect the relative abundance of viral nucleic acid, demonstrating that relative quantification can overcome the sewage dilution effects caused by the greywater input, precipitation and/or groundwater infiltration. The process of concentration, recovery and detection of the endogenous biomarker was consistent with that of SARS-CoV-2 RNA. Thus, it is necessary to co-quantify the endogenous biomarker because it can be not only an internal reference for data normalization, but also a process control.

Antibiotic resistance has become a complicated environmental problem. Controlling the emission of antibiotics, antibiotic-resistant bacteria (ARB), and their antibiotic-resistance genes (ARGs) at hotspots is important for reducing environmental antibiotic resistance. Here, a Fe3O4-polydopamine (PDA)-Ag nanocomposite was successfully fabricated via hydrothermal synthesis, polydopaminc coating, and in situ Ag reduction. The nanocomposite exhibited a core-shell structure with a nanosized magnetic Fe3O4 core (similar to 200 nm) coated with one layer of nanosilver Ag nanoparticles (Ag NPs) decorated polydopamine. Its application potential as a bifunctional material for the removal of multidrug-resistant (MDR) bacteria, ARGs, and antibiotics was investigated. The Fe3O4-PDA-Ag showed a good performance on inhibiting the MDR bacteria and effectively reduced the abundance of ARGs. The removal of ciprofloxacin (CIP) via catalytic reduction with this composite was evaluated. The optimized results showed that nearly 82.3% of CIP (C-0 = 10 mg/L) was removed within 30 min with the amount of Fe3O4-PDA-Ag of 0.5 g/L and the concentration of NaBH4 of 10 mM. Furthermore, the catalytic activity of the composite did not decrease even after five cycles, indicating its good reusability as the catalyst. This study provided a preliminary two birds with one stone strategy for solving the environmental problem of antibiotic-resistance pollution. (C) 2022 American Society of Civil Engineers.

Wastewater-based epidemiology (WBE) is expected to become a powerful tool to monitor the dissemination of SARS-CoV-2 at the community level, which has attracted the attention of scholars all over the world. However, there is not yet a standard protocol to guide its implementation. In this paper, we proposed a comprehensive technical and theoretical framework of relative quantification via qPCR for determining the virus abundance in wastewater and estimating the infection ratio in corresponding communities, which is expected to achieve horizontal and vertical comparability of the data using a human-specific biomarker as the internal reference. Critical factors affecting the virus detectability and the estimation of infection ratio include virus concentration methods, lag-period, per capita virus shedding amount, sewage generation rate, temperature-related decay kinetics of virus/biomarker in wastewater, and hydraulic retention time (HRT), etc. Theoretical simulation shows that the main factors affecting the detectability of virus in sewage are per capita virus shedding amount and sewage generation rate. While the decay of SARS-CoV-2 RNA in sewage is a relatively slow process, which may have limited impact on its detection. Under the ideal condition of high per capita virus shedding amount and low sewage generation rate, it is expected to detect a single infected person within 400,000 people.

The reversibility of antibiotic resistance is theoretically attractive due to the prospect of restoring the clinical potency of antibiotics. It is important to find out the factors that affect the reversibility of antibiotic resistance. Here, an mcr-1-positive multidrug-resistant (MDR) environmental Escherichia coli isolate was successively passaged under four antibiotic-free culture conditions. The relative abundances of multiple antibiotic resistance genes (ARGs) kept decreasing during the successive passages. The linear correlations between abundances of ARGs on the same MDR plasmid reflected that the decay of antibiotic resistance during the passage was mainly due to the elimination of the MDR plasmid (pMCR_W5-6). Colistin-susceptible strains were isolated at the end of the passage. The whole-genome sequencing of two susceptible isolates detected the elimination of the MDR plasmid and deletion of the mcr-1 gene. Deletions of DNA fragments from chromosome and plasmid were closely related to a variety of insertion sequences (ISs). The results of coculture of resistant and susceptible strains at different antibiotic concentrations indicated that the high fitness cost led to the poor stability of mobile ARGs. Strict control of the use of antibiotics can at least reverse the severe antibiotic resistance caused by mobile ARGs of high fitness cost. IMPORTANCE The dissemination of bacterial antibiotic resistance is a serious threat to human health. The development of new antibiotics faces both economic and technological challenges. The reversibility of antibiotic resistance has become an important issue causing wide concern due to the prospect of restoring the clinical potency of antibiotics. Our study suggests that the high mobility of ARGs of high fitness cost may just reflect their poor stability. Therefore, strict control of the use of antibiotics can at least reverse the severe antibiotic resistance caused by mobile ARGs of high fitness cost. This study brings hope for the possibility of curbing the dissemination of antibiotic resistance.

In this work, a CuZnFe(2)O(4-)loaded activated carbon composite (CZF-AC) was synthesized by a simple one-pot hydrothermal method. The obtained material was characterized by X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), and vibrating sample magnetometer (VSM), which proved that it possessed good magnetic response and retained the physical and chemical properties of the original activated carbon. Cationic dyes such as methylene blue, malachite green, and rhodamine B were removed from aqueous solutions using the obtained magnetic activated carbon as the adsorbent. The adsorption behavior of these cationic dyes onto the CZF-AC was systematically studied via dynamic and equilibrium adsorption experiments. Good adsorption capacity (100 to 970 mg dye/g CZF-AC), fast adsorption kinetics (reaching equilibrium within 20 min), and excellent reusability (no adsorption performance loss even after 4 adsorption-desorption round were observed for the synthesized CZF-AC. This work not only provides a facile method for the construction of magnetic carbon adsorbents but also gives a potential green magnetization strategy for other functional materials.

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