[Characteristics of Microorganisms and Antibiotic Resistance Genes of the Riparian Soil in the Lanzhou Section of the Yellow River].

Riparian soil is a critical area of watersheds. The characteristics of biological contaminants in riparian soil affect the pollution control of the watershed water environment. Thus, the microbial community structure, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) in the riparian soil of the Lanzhou section of the Yellow River were investigated by analyzing the characteristics of soil samples collected from farmland, mountains, and industrial land. The results showed that the Proteobacteria, Bacteroidetes, and Actinobacteria were the dominant phyla in the riparian soil of Lanzhou section of the Yellow River. The microbial structure in the riparian soil was significantly correlated with the land use type (P < 0.05). The α diversity index of bacterial communities in land types was in the order of farmland > mountain > industry. Sulfonamide-typed ARGs were the most dominant genes in the soil of the Lanzhou section of the Yellow River Basin, among which the sul1 gene had the highest abundance, 20-36 000 times that of other detected ARGs. Moreover, the total absolute abundance of ARGs in industrial soil was the highest. Principal coordinate analysis (PCoA) displayed that the ARGs characteristics had a significant correlation with land types (P < 0.05), and intl1 and tnpA-04 drove the diffuseness of sulfonamide and tetracycline ARGs, respectively. Redundancy analysis (RDA) demonstrated that the content of inorganic salt ions and total phosphorus in the soil of the riparian zone of the Yellow River Lanzhou section were the main environmental factors, modifying the distribution of the microbial structure. Halobacterota and Acidobacteriota were the main microflora that drove the structural change in ARGs.

Phages in sludge from the A/O wastewater treatment process play an important role in the transmission of ARGs.

Phages can influence the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs) through transduction, but their profiles and effects on the transmission of ARGs are unclear, especially in complex swine sludge. In this study, we investigated the characterization of phage and ARG profiles in sludge generated from anoxic/oxic (A/O) wastewater treatment processes on swine farms using metagenomes and viromes. The results demonstrated that 205-221 subtypes of ARGs could be identified in swine sludge, among which sul1, tet(M), and floR were the dominant ARGs, indicating that sludge is an important reservoir of ARGs, especially in sludge (S) tanks. The greater abundance of mobile genetic elements (MGEs) in the S tank could significantly contribute to the greater abundance of ARGs there compared to the anoxic (A) and oxic (O) tanks (P < 0.05). However, when we compared the abundances of ARGs and MGEs in the A and O tanks, we observed opposite significant differences (P < 0.05), suggesting that MGEs are not the only factor influencing the abundance of ARGs. The high proportion of lysogenic phages in sludge from the S tank can also have a major impact on the ARG profile. Siphoviridae, Myoviridae, and Podoviridae were the dominant phage families in sludge, and a network diagram of bacteria-ARG-phages revealed that dominant phages and bacteria acted simultaneously as potential hosts for ARGs, which may have led to phage-mediated HGT of ARGs. Therefore, the risk of phage-mediated HGT of ARGs cannot be overlooked.

Mobile genetic elements mediate the cross-media transmission of antibiotic resistance genes from pig farms and their risks.

Manure composting in traditional small-scale pig farms leads to the migration and diffusion of antibiotics and antibiotics resistance genes (ARGs) along the chain of transmission to the surrounding environment, increasing the risk of environmental resistance. Understanding the transmission patterns, driving factors, and health risks of ARGs on small-scale pig farms is important for effective control of ARGs transmission. This study was conducted on a small pig farm and its surrounding environment. The cross-media transmission of ARGs and their risks in the farming habitat were investigated using Metagenomic annotation and qPCR quantitative detection. The results indicate that ARGs in farms spread with manure pile-soil-channel sediment-mudflat sediment. Pig farm manure contributed 22.49 % of the mudflat sediment ARGs. Mobile genetic elements mediate the spread of ARGs across different media. Among them, tnpA and IS26 have the highest degree. Transmission of high-risk ARGs sul1 and tetM resulted in a 50 % and 116 % increase in host risk for sediment, respectively. This study provides a basis for farm manure management and control of the ARGs spread.

The proliferation of antibiotic resistance genes (ARGs) and microbial communities in industrial wastewater treatment plant treating N,N-dimethylformamide (DMF) by AAO process.

The excessive use of antibiotics has resulted in the contamination of the environment with antibiotic resistance genes (ARGs), posing a significant threat to public health. Wastewater treatment plants (WWTPs) are known to be reservoirs of ARGs and considered to be hotspots for horizontal gene transfer (HGT) between bacterial communities. However, most studies focused on the distribution and dissemination of ARGs in hospital and urban WWTPs, and little is known about their fate in industrial WWTPs. In this study, collected the 15 wastewater samples containing N,N-dimethylformamide (DMF) from five stages of the anaerobic anoxic aerobic (AAO) process in an industrial WWTPs. The findings revealed a stepwise decrease in DMF and chemical oxygen demand (COD) content with the progression of treatment. However, the number and abundances of ARGs increase in the effluents of biological treatments. Furthermore, the residues of DMF and the treatment process altered the structure of the bacterial community. The correlation analysis indicated that the shift in bacterial community structures might be the main driver for the dynamics change of ARGs. Interestingly, observed that the AAO process may acted as a microbial source and increased the total abundance of ARGs instead of attenuating it. Additionally, found that non-pathogenic bacteria had higher ARGs abundance than pathogenic bacteria in effluents. The study provides insights into the microbial community structure and the mechanisms that drive the variation in ARGs abundance in industrial WWTPs.

Machine learning reveals the selection pressure exerted by nonantibiotic pharmaceuticals at environmentally relevant concentrations on antibiotic resistance genotypes.

The emergence and increasing prevalence of antibiotic resistance pose a global public risk for human health, and nonantimicrobial pharmaceuticals play an important role in this process. Herein, five nonantimicrobial pharmaceuticals, including acetaminophen (ACT), clofibric acid (CA), carbamazepine (CBZ), caffeine (CF) and nicotine (NCT), tetracycline-resistant strains, five ARGs (sul1, sul2, tetG, tetM and tetW) and one integrase gene (intI1), were detected in 101 wastewater samples during two typical sewage treatment processes including anaerobic-oxic (A/O) and biological aerated filter (BAF) in Harbin, China. The impact of nonantibiotic pharmaceuticals at environmentally relevant concentrations on both the resistance genotypes and resistance phenotypes were explored. The results showed that a significant impact of nonantibiotic pharmaceuticals at environmentally relevant concentrations on tetracycline resistance genes encoding ribosomal protection proteins (RPPs) was found, while no changes in antibiotic phenotypes, such as minimal inhibitory concentrations (MICs), were observed. Machine learning was applied to further sort out the contribution of nonantibiotic pharmaceuticals at environmentally relevant concentrations to different ARG subtypes. The highest contribution and correlation were found at concentrations of 1400-1800 ng/L for NCT, 900-1500 ng/L for ACT and 7000-10,000 ng/L for CF for tetracycline resistance genes encoding RPPs, while no significant correlation was found between the target compounds and ARGs when their concentrations were lower than 500 ng/L for NCT, 100 ng/L for ACT and 1000 ng/L for CF, which were higher than the concentrations detected in effluent samples. Therefore, the removal of nonantibiotic pharmaceuticals in WWTPs can reduce their selection pressure for resistance genes in wastewater.

Causal-ARG: a causality-guided framework for annotating properties of antibiotic resistance genes.

MOTIVATION: The crisis of antibiotic resistance, which causes antibiotics used to treat bacterial infections to become less effective, has emerged as one of the foremost challenges to public health. Identifying the properties of antibiotic resistance genes (ARGs) is an essential way to mitigate this issue. Although numerous methods have been proposed for this task, most of these approaches concentrate solely on predicting antibiotic class, disregarding other important properties of ARGs. In addition, existing methods for simultaneously predicting multiple properties of ARGs fail to account for the causal relationships among these properties, limiting the predictive performance. RESULTS: In this study, we propose a causality-guided framework for annotating properties of ARGs, in which causal inference is utilized for representation learning. More specifically, the hidden biological patterns determining the properties of ARGs are described by a Gaussian Mixture Model, and procedure of causal representation learning is used to derive the hidden features. In addition, a causal graph among different properties is constructed to capture the causal relationships among properties of ARGs, which is integrated into the task of annotating properties of ARGs. The experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework on the task of annotating properties of ARGs. AVAILABILITY AND IMPLEMENTATION: The data and source codes are available in GitHub at https://github.com/David-WZhao/CausalARG.

Occurrence and distribution of antibiotics and antibiotic resistance genes from the land to ocean in Daliao River-Liaodong Bay, China.

In this study, the pollution status of antibiotics and ARGs in sediments from the land-sea intersection of Liaodong Bay was analyzed. The results showed that the level of antibiotic pollution ranged from ND to 433.27 ng/kg, with quinolones and tetracycline as the dominant antibiotics. The relative abundance of ARGs ranged from 3.62 × 10-3 to 1.32 × 10-1 copies/16SrRNA copies, with aminoglycoside and MLSB resistance genes being dominant. Regarding spatial distribution, the land and estuary areas showed higher antibiotic pollution levels than the offshore areas. Similarly, the land and estuary areas exhibited higher antibiotic diversity than the offshore areas. The ARGs were widely distributed on land, and their abundance gradually decreased to the downstream estuary area. Land and coastal areas exhibited higher ARG diversity than estuary areas. Analysis of environmental factors revealed a significant correlation between ARGs and non-corresponding antibiotics, and some ARGs were affected by heavy metals Cu and Pb.

Temporal Dynamics and Contribution of Phage Community to the Prevalence of Antibiotic Resistance Genes in a Full-Scale Sludge Anaerobic Digestion Plant.

Anaerobic digestion (AD) is an important biological resource recovery process, where microorganisms play key roles for material transformation. There has been some knowledge about the prokaryotic community and antibiotic resistance genes (ARGs) in AD, but there has been very limited knowledge of phages. In this study, samples from a full-scale AD plant were collected over 13 months, sequenced, and analyzed for viral and prokaryotic metagenomes. Totally, 3015 viral operational taxonomic units (vOTUs) were detected, mostly assigned to Caudoviricetes. The phage community had faster temporal variation than the prokaryotic community. Warm seasons harbored a higher abundance of both temperate phages and broad host-range phages. Seven ARGs of 6 subtypes were carried by 20 vOTUs, a representative ermT gene was synthesized and expressed, and the resistance activity in the host was examined, confirming the real activity of virus-carried ARGs in the AD process. Some of the ARGs were horizontally transferred between the phage and prokaryotic genomes. However, phage infection was not found to contribute to ARG transfer. This study provided an insight into the ecological patterns of the phage community, confirmed the antibiotic resistance activity of virus-carried ARGs, evaluated the contribution of phages on the ARG prevalence, and laid the foundation for the control strategies of the community and antibiotic resistance in the AD process.

Comparison of qPCR and metagenomic sequencing methods for quantifying antibiotic resistance genes in wastewater.

Surveillance methods of circulating antibiotic resistance genes (ARGs) are of utmost importance in order to tackle what has been described as one of the greatest threats to humanity in the 21st century. In order to be effective, these methods have to be accurate, quickly deployable, and scalable. In this study, we compare metagenomic shotgun sequencing (TruSeq DNA sequencing) of wastewater samples with a state-of-the-art PCR-based method (Resistomap HT-qPCR) on four wastewater samples that were taken from hospital, industrial, urban and rural areas. ARGs that confer resistance to 11 antibiotic classes have been identified in these wastewater samples using both methods, with the most abundant observed classes of ARGs conferring resistance to aminoglycoside, multidrug-resistance (MDR), macrolide-lincosamide-streptogramin B (MLSB), tetracycline and beta-lactams. In comparing the methods, we observed a strong correlation of relative abundance of ARGs obtained by the two tested methods for the majority of antibiotic classes. Finally, we investigated the source of discrepancies in the results obtained by the two methods. This analysis revealed that false negatives were more likely to occur in qPCR due to mutated primer target sites, whereas ARGs with incomplete or low coverage were not detected by the sequencing method due to the parameters set in the bioinformatics pipeline. Indeed, despite the good correlation between the methods, each has its advantages and disadvantages which are also discussed here. By using both methods together, a more robust ARG surveillance program can be established. Overall, the work described here can aid wastewater treatment plants that plan on implementing an ARG surveillance program.

Mathematical modelling of antibiotic interaction on evolution of antibiotic resistance: an analytical approach.

Background: The emergence and spread of antibiotic-resistant pathogens have led to the exploration of antibiotic combinations to enhance clinical effectiveness and counter resistance development. Synergistic and antagonistic interactions between antibiotics can intensify or diminish the combined therapy's impact. Moreover, these interactions can evolve as bacteria transition from wildtype to mutant (resistant) strains. Experimental studies have shown that the antagonistically interacting antibiotics against wildtype bacteria slow down the evolution of resistance. Interestingly, other studies have shown that antibiotics that interact antagonistically against mutants accelerate resistance. However, it is unclear if the beneficial effect of antagonism in the wildtype bacteria is more critical than the detrimental effect of antagonism in the mutants. This study aims to illuminate the importance of antibiotic interactions against wildtype bacteria and mutants on the deacceleration of antimicrobial resistance. Methods: To address this, we developed and analyzed a mathematical model that explores the population dynamics of wildtype and mutant bacteria under the influence of interacting antibiotics. The model investigates the relationship between synergistic and antagonistic antibiotic interactions with respect to the growth rate of mutant bacteria acquiring resistance. Stability analysis was conducted for equilibrium points representing bacteria-free conditions, all-mutant scenarios, and coexistence of both types. Numerical simulations corroborated the analytical findings, illustrating the temporal dynamics of wildtype and mutant bacteria under different combination therapies. Results: Our analysis provides analytical clarification and numerical validation that antibiotic interactions against wildtype bacteria exert a more significant effect on reducing the rate of resistance development than interactions against mutants. Specifically, our findings highlight the crucial role of antagonistic antibiotic interactions against wildtype bacteria in slowing the growth rate of resistant mutants. In contrast, antagonistic interactions against mutants only marginally affect resistance evolution and may even accelerate it. Conclusion: Our results emphasize the importance of considering the nature of antibiotic interactions against wildtype bacteria rather than mutants when aiming to slow down the acquisition of antibiotic resistance.

Integrating metagenomic and isolation strategies revealed high contamination of pathogenies and resistome in market shrimps.

This study employs a comprehensive approach combining metagenomic analysis and bacterial isolation to elucidate the microbial composition, antibiotic resistance genes (ARGs), and virulence factors (VFGs) present in shrimps from market and supermarket. Metagenomic analysis of shrimps revealed a dominance of Proteobacteria and Bacteroidetes with Firmicutes notably enriched in some samples. On the other hand, the dominant bacteria isolated included Citrobacter portucalensis, Escherichia coli, Salmonella enterica, Vibrio species and Klebsiella pneumonaie. Metagenomic analysis unveiled a diverse spectrum of 23 main types and 380 subtypes of ARGs in shrimp samples including many clinical significant ARGs such as blaKPC, blaNDM, mcr, tet(X4) etc. Genomic analysis of isolated bacterial strains identified 14 ARG types with 109 subtype genes, which complemented the metagenomic data. Genomic analysis also allowed us to identify a rich amount of MDR plasmids, which provided further insights into the dissemination of resistance genes in different species of bacteria in the same samples. Examination of VFGs and mobile genetic elements (MGEs) in both metagenomic and bacterial genomes revealed a complex landscape of factors contributing to bacterial virulence and genetic mobility. Potential co-occurrence patterns of ARGs and VFGs within human pathogenic bacteria underlined the intricate interplay between antibiotic resistance and virulence. In conclusion, this integrated analysis for the first time provides a comprehensive view and sheds new light on the potential hazards associated with shrimp products in the markets. The findings underscore the necessity of ongoing surveillance and intervention strategies to mitigate risks posed by antibiotic-resistant bacteria in the food supply chain using the novel comprehensive approaches.

Chemical attributes, bacterial community, and antibiotic resistance genes are affected by intensive use of soil in agro-ecosystems of the Atlantic Forest, Southeastern Brazil.

Soil is one of the largest reservoirs of microbial diversity in nature. Although soil management is vital for agricultural purposes, intensive practices can have a significant impact on fertility, microbial community, and resistome. Thus, the aim of this study was to evaluate the effects of an intensive soil management system on the chemical attributes, composition and structure of prevalent bacterial communities, and presence and abundance of antimicrobial resistance genes (ARGs). The chemical characterization, bacterial diversity and relative abundance of ARGs were evaluated in soils from areas of intensive vegetable cultivation and forests. Results indicate that levels of nutrients and heavy metals were higher in soil samples from cultivated areas. Similarly, greater enrichment and diversity of bacterial genera was detected in agricultural areas. Of the 18 target ARGs evaluated, seven were detected in studied soils. The oprD gene exhibited the highest abundance among the studied genes and was the only one that showed a significantly different prevalence between areas. The oprD gene was identified only from soil of the cultivated areas. The blaSFO, erm(36), oprD and van genes, in addition to the pH, showed greater correlation with in soil of cultivated areas, which in turn exhibited higher contents of nutrients. Thus, in addition to changes in chemical attributes and in the microbial community of the soil, intensive agricultural cultivation systems cause a modification of its resistome, reinforcing the importance of the study of antimicrobial resistance in a One Health approach.

Leveraging machine learning for prediction of antibiotic resistance genes post thermal hydrolysis-anaerobic digestion in dairy waste.

Anaerobic digestion holds promise as a method for removing antibiotic resistance genes (ARGs) from dairy waste. However, accurately predicting the efficiency of ARG removal remains a challenge. This study introduces a novel appproach utilizing machine learning to forecast changes in ARG abundances following thermal hydrolysis-anaerobic digestion (TH-AD) treatment. Through network analysis and redundancy analyses, key determinants of affect ARG fluctuations were identified, facilitating the development of machine learning models capable of accurately predicting ARG changes during TH-AD processes. The decision tree model demonstrated impressive predictive power, achieving an impessive R2 value of 87% against validation data. Feature analysis revealed that the genes intI2 and intI1 had a critical impact on the absolute abundance of ARGs. The predictive model developed in this study offers valuable insights for improving operational and managerial practices in dairy waste treatment facilities, with the ultimate goal of mitigating the spread of antibiotic resistance.

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Antibiotic resistance genes (ARGs) have attracted widespread attention as a new global pollutant, mainly due to the abuse of antibiotics. To investigate the diversity of ARGs in three rodent species, we used metagenomic sequencing analysis to analyze the diversity of antibiotic resistance genes of 17 individuals of Apodemus peninsulae and 17 individuals of Myodes rufocanus collected from Mudanfeng, and nine individuals of Apodemus agrarius collected from Sandaoguan. A total of 19 types and 248 subclasses of ARGs were detected in the three rodent species. Seven ARGs showed significant difference and five ARGs showed extremely significant difference between M. rufocanus and A. agrarius. Seven ARGs showed significant difference and four ARGs showed extremely significant difference between A. peninsulae and A. agrarius. Four ARGs showed significant difference and five ARGs showed extremely significant difference between M. rufocanus and A. peninsulae. ARGs showing high abundance in three rodents were macrolides, lincoamides, tetracyclines, and ß-lactams. ARGs were widely distributed in the three rodent species. The significant differences in ARGs among different species might be due to the different distribution areas and their diet differentiation. The study could provide a basis for further studies of ARGs in mice and improve the understanding of the harm of ARGs transmission.

Regulation of ARGs abundance by biofilm colonization on microplastics under selective pressure of antibiotics in river water environment.

Interactions of microplastics (MPs) biofilm with antibiotic resistance genes (ARGs) and antibiotics in aquatic environments have made microplastic biofilm an issue of keen scholarly interest. The process of biofilm formation and the degree of ARGs enrichment in the presence of antibiotic-selective pressure and the impact on the microbial community need to be further investigated. In this paper, the selective pressure of ciprofloxacin (CIP) and illumination conditions were investigated to affect the physicochemical properties, biomass, and extracellular polymer secretion of polyvinyl chloride (PVC) microplastic biofilm. In addition, relative copy numbers of nine ARGs were analyzed by real-time quantitative polymerase chain reaction (qPCR). In the presence of CIP, microorganisms in the water and microplastic biofilm were more inclined to carry associated ARGs (2-3 times higher), which had a contributing effect on ARGs enrichment. The process of pre-microplastic biofilm formation might have an inhibitory effect on ARGs (total relative abundance up to 0.151) transfer and proliferation compared to the surrounding water (total relative abundance up to 0.488). However, in the presence of CIP stress, microplastic biofilm maintained the abundance of ARGs (from 0.151 to 0.149) better compared to the surrounding water (from 0.488 to 0.386). Therefore, microplastic biofilm act as abundance buffer island of ARGs stabilizing the concentration of ARGs. In addition, high-throughput analyses showed the presence of antibiotic-resistant (Pseudomonas) and pathogenic (Vibrio) microorganisms in biofilm under different conditions. The above research deepens our understanding of ARGs enrichment in biofilm and provides important insights into the ecological risks of interactions between ARGs, antibiotics, and microplastic biofilm.

Urbanization influences the indoor transfer of airborne antibiotic resistance genes, which has a seasonally dependent pattern.

Over the last few years, the cumulative use of antibiotics in healthcare institutions, as well as the rearing of livestock and poultry, has resulted in the accumulation of antibiotic resistance genes (ARGs). This presents a substantial danger to human health worldwide. The characteristics of airborne ARGs, especially those transferred from outdoors to indoors, remains largely unexplored in neighborhoods, even though a majority of human population spends most of their time there. We investigated airborne ARGs and mobile genetic element (MGE, IntI1), plant communities, and airborne microbiota transferred indoors, as well as respiratory disease (RD) prevalence using a combination of metabarcode sequencing, real-time quantitative PCR and questionnaires in 72 neighborhoods in Shanghai. We hypothesized that (i) urbanization regulates ARGs abundance, (ii) the urbanization effect on ARGs varies seasonally, and (iii) land use types are associated with ARGs abundance. Supporting these hypotheses, during the warm season, the abundance of ARGs in peri-urban areas was higher than in urban areas. The abundance of ARGs was also affected by the surrounding land use and plant communities: an increase in the proportion of gray infrastructure (e.g., residential area) around neighborhoods can lead to an increase in some ARGs (mecA, qnrA, ermB and mexD). Additionally, there were variations observed in the relationship between ARGs and bacterial genera in different seasons. Specifically, Stenotrophomonas and Campylobacter were positively correlated with vanA during warm seasons, whereas Pseudomonas, Bacteroides, Treponema and Stenotrophomonas positively correlated with tetX in the cold season. Interstingly, a noteworthy positive correlation was observed between the abundance of vanA and the occurrence of both rhinitis and rhinoconjunctivitis. Taken together, our study underlines the importance of urbanization and season in controlling the indoor transfer of airborne ARGs. Furthermore, we also highlight the augmentation of green-blue infrastructure in urban environments has the potential to mitigate an excess of ARGs.

Plasmid-mediated phenotypic noise leads to transient antibiotic resistance in bacteria.

The rise of antibiotic resistance is a critical public health concern, requiring an understanding of mechanisms that enable bacteria to tolerate antimicrobial agents. Bacteria use diverse strategies, including the amplification of drug-resistance genes. In this paper, we showed that multicopy plasmids, often carrying antibiotic resistance genes in clinical bacteria, can rapidly amplify genes, leading to plasmid-mediated phenotypic noise and transient antibiotic resistance. By combining stochastic simulations of a computational model with high-throughput single-cell measurements of blaTEM-1 expression in Escherichia coli MG1655, we showed that plasmid copy number variability stably maintains populations composed of cells with both low and high plasmid copy numbers. This diversity in plasmid copy number enhances the probability of bacterial survival in the presence of antibiotics, while also rapidly reducing the burden of carrying multiple plasmids in drug-free environments. Our results further support the tenet that multicopy plasmids not only act as vehicles for the horizontal transfer of genetic information between cells but also as drivers of bacterial adaptation, enabling rapid modulation of gene copy numbers. Understanding the role of multicopy plasmids in antibiotic resistance is critical, and our study provides insights into how bacteria can transiently survive lethal concentrations of antibiotics.

Spatiotemporal distribution, interactions and toxic effect of microorganisms and ARGs/MGEs from the bioreaction tank in hospital sewage treatment facility.

Antibiotic resistance genes (ARGs) can be emitted from wastewater to ambient air and impose unignorable inhalable hazards, which could be exacerbated in antibiotic-concentrated hospital sewage. However, whether the ARG-carrying pathogens are more likely to infect cells remains largely unknown. Here, this study investigated and analyzed the spatiotemporal distribution, interaction, and toxicity of airborne microorganisms and their hosting ARGs in a hospital sewage treatment facility. The average concentration of ARGs/MGEs in sewage of bioreaction tank (BRT-W) was 2.27 × 104 gene copies/L. In the air of bioreaction tank (BRT-A), the average concentration of ARGs/MGEs was 15.86 gene copies/m3. In the four seasons, the ARGs concentration of sewage gradually decreased over time; The concentration of ARGs in the air first decreased and then increased. In spring, the concentration of ARGs/MGEs (qacedelta1-01) in BRT-W was highest (1.05 × 105 gene copies/L); The concentration of ARGs/MGEs (strB) in BRT-A in winter was higher than other seasons (26.18 gene copies/m3). Different from the past, this study also paid attention to the pathogenic potential of ARGs/MGEs in the air. The results of cell experiments showed that the cytotoxicity of drug-resistant Escherichia coli could reach Grade V. This suggested that the longer the drug-resistant E. coli were exposed to cells, the greater the cytotoxicity. Moreover, the cytotoxicity of bacteria increased with the increase in exposure time. In spring, the toxic effect of ARGs/MGEs in sewage of BRT-W was highest. Traceability analysis proved that BRT-W was an essential source of microorganisms and ARGs/MGEs in BRT-A. Furthermore, the combined risk of people exposed to the air of BRT in spring was higher than that in other seasons.

Genome mining of Escherichia coli WG5D from drinking water source: unraveling antibiotic resistance genes, virulence factors, and pathogenicity.

BACKGROUND: Escherichia coli, a ubiquitous inhabitant of the gut microbiota, has been recognized as an indicator of fecal contamination and a potential reservoir for antibiotic resistance genes. Its prevalence in drinking water sources raises concerns about the potential dissemination of antibiotic resistance within aquatic ecosystems and the subsequent impact on public health. The ability of E. coli to acquire and transfer resistance genes, coupled with the constant exposure to low levels of antibiotics in the environment, underscores the need for comprehensive surveillance and rigorous antimicrobial stewardship strategies to safeguard the quality and safety of drinking water supplies, ultimately mitigating the escalation of antibiotic resistance and its implications for human well-being. METHODS: WG5D strain, isolated from a drinking water distribution source in North-West Province, South Africa, underwent genomic analysis following isolation on nutrient agar, anaerobic cultivation, and DNA extraction. Paired-end Illumina sequencing with a Nextera XT Library Preparation kit was performed. The assembly, annotation, and subsequent genomic analyses, including phylogenetic analysis using TYGS, pairwise comparisons, and determination of genes related to antimicrobial resistance and virulence, were carried out following standard protocols and tools, ensuring comprehensive insights into the strain's genomic features. RESULTS: This study explores the notable characteristics of E. coli strain WG5D. This strain stands out because it possesses multiple antibiotic resistance genes, encompassing tetracycline, cephalosporin, vancomycin, and aminoglycoside resistances. Additionally, virulence-associated genes indicate potential heightened pathogenicity, complemented by the identification of mobile genetic elements that underscore its adaptability. The intriguing possibility of bacteriophage involvement and factors contributing to pathogenicity further enriches our understanding. We identified E. coli WG5D as a potential human pathogen associated with a drinking water source in South Africa. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. It further identified WG5D as a potential human pathogen. The occurrence of E. coli WG5D raised the awareness of the potential pathogens and the carrying of antibiotic resistance in drinking water. CONCLUSIONS: The findings of this study have highlighted the advantages of the genomic approach in identifying the bacterial species and antibiotic resistance genes of E. coli and its potential as a human pathogen.

[Contamination Characteristics，Detection Methods，and Control Methods of Antibiotic Resistance in Pharmaceutical Wastewater].

Pharmaceutical industry wastewater contains a large number of emerging pollutants such as antibiotics， antibiotic resistant bacteria （ARBs）， and antibiotic resistance genes （ARGs）. The present biological water treatment processes cannot effectively remove these pollutants. Eventually， they are discharged into various water bodies or penetrate into soil with the effluent， causing environmental pollution and affecting human health. Therefore， exploring the pollution characteristics of antibiotics， ARBs， and ARGs in pharmaceutical wastewater and knowing the methods to detect and control antibiotic resistance pollution in wastewater are crucial for reducing the contamination of antibiotics and ARGs and assessing the ecological risks of antibiotic resistance. Aiming at the problem of antibiotic resistance pollution in a pharmaceutical wastewater treatment plant （PWWTPs）， the pollution status of antibiotics， ARBs， and ARGs in pharmaceutical wastewater was discussed. Different assessment methods of antibiotic resistance in pharmaceutical wastewater were summarized. Finally， the wastewater treatment technologies commonly used to remove antibiotics and ARGs in PWWTPs were summarized in order to provide a theoretical basis for the ecological risk assessment and scientific control of antibiotics and ARGs in the environment.