Viability-based quantification of antibiotic resistance genes and human fecal markers in wastewater effluent and receiving waters

Antibiotic resistance genes in aquatic systems: Sources, transmission, and risks

The widespread use of antibiotics has significantly contributed to the spread of antibiotic resistance genes (ARGs), which have become a major challenge to global ecological and public health. Antibiotic resistance not only proliferates in clinical settings but also persists in aquatic systems, where its residues and cross-domain spread pose a dual threat to both ecosystems and human health. ARGs spread rapidly within microbial communities through horizontal gene transfer (HGT) and vertical gene transfer (VGT). Aquatic systems are the key transmission medium. This review summarizes recent studies on the Source-Transport-Sink dynamics of ARGs in aquatic environments, along with their environmental and health risk assessments, with a particular focus on the potential ecotoxicity of ARGs transmission. It also examines the distribution characteristics of ARGs across different regions and the ecological risk assessment methods employed, highlighting the limitations of existing models when addressing the complex behaviors of ARGs. By analyzing the potential hazards of ARGs to aquatic ecosystems and public health, this article aims to provide a scientific foundation for future research and the development of public policies.

First Report and Pathogenicity Analysis of Photobacterium damselae subsp. piscicida in Cage-Cultured Black Rockfish (Sebastes schlegelii) Associated with Skin Ulcers

Photobacterium damselae subsp. Piscicida (PDP), a marine bacterium, has been reported to infect a variety of economically important marine species worldwide. Understanding the occurrence and pathogenicity of PDP is crucial for effective disease control and ensuring the success of aquaculture operations. In late August 2023, an epidemic outbreak of P. damselae subsp. piscicida DQ-SS1, accompanied by significant mortality, was recorded in cage-cultured black rockfish (Sebastes schlegelii) located on Daqin Island for the first time. Genomic analysis revealed that DQ-SS1 possesses 2 chromosomes, with a total size of 4,510,445 bp and 3923 predicted CDSs. Pathogenic genes analysis identified 573 and 314 genes related to pathogen-host interactions and virulence, respectively. Additionally, DQ-SS1 displayed susceptibility to 15 antimicrobials, was resistant to 11 antimicrobials, and was intermediately sensitive to four antibiotics. Meanwhile, the in vitro assay revealed that the extracellular products (ECP) of DQ-SS1 were lethal to macrophages and exhibited hemolysin, lipase, and amylase activities. Moreover, DQ-SS1 also demonstrated the ability to survive in fish serum and resist complement-mediated killing. The in vivo assay showed that the infected fish exhibited severe histopathological alterations, such as the infiltration of inflammatory cells, cellular degeneration and necrosis, and loose cell aggregation. Lastly, the in vivo infection assays revealed the LD50 of DQ-SS1 was 1.7 × 103 CFU/g. This is the first study to elucidate the pathogenicity and genomic characteristics of multidrug-resistant PDP in cage-cultured S. schlegelii, which contributes to the advancement of diagnostic and preventative strategies for this disease in marine-cultured fishes and provides information for an in-depth study of the pathogenic mechanism of PDP.

The influence of urbanization and water reclamation plants on fecal indicator bacteria and antibiotic resistance in the Los Angeles River watershed: A case study with complementary monitoring methods

Urban land use and water reclamation plants (WRPs) can impact fecal indicator bacteria (FIB) and antimicrobial resistance (AMR) in coastal watersheds. However, there is a lack of studies exploring these effects on the US West Coast. Additionally, there is limited research using a complementary approach across culture-, qPCR-, and metagenomics-based techniques for characterizing environmental AMR. In this study, sixteen locations were sampled in the Los Angeles River, encompassing both upstream and downstream of three WRPs discharging into the river. Culture-dependent methods quantified Enterococcus, total coliforms, E. coli, and extended spectrum beta-lactamase-producing E. coli as a low-cost screening tool for AMR, while qPCR measured selected antibiotic resistance genes (ARGs): sul1, ermF, tetW, blaSHV, along with intI1 and 16S rRNA genes. Bacteroides HF183 and crAssphage markers were quantified via ddPCR. All samples underwent shotgun sequencing to investigate gene abundance and mobility and an overall risk score for AMR. Results reveal downstream sites contain ARGs at least two orders of magnitude greater than upstream locations. Developed areas had the highest ARG sequence abundances and the most ARG classes as indicated by metagenomic analysis. WRP effluent exhibited elevated ARGs and co-location of ARGs, mobile genetic elements, and pathogens. A culture-based assessment of AR in E. coli and Pseudomonas aeruginosa revealed increased resistance ratios for most antibiotics from upstream to downstream a WRP discharge point. This study highlights the impacts of land use and WRPs on ARGs and FIB, offering a multi-pronged analysis of AMR.

Antibiotic resistant bacteria and antibiotic resistance genes as contaminants of emerging concern: Occurrences, impacts, mitigations and future guidelines

Antibiotic resistance, driven by the proliferation of antibiotic resistance genes (ARGs) and antibiotic resistance bacteria (ARBs), has emerged as a pressing global health concern. Antimicrobial resistance is exacerbated by the widespread use of antibiotics in agriculture, aquaculture, and human medicine, leading to their accumulation in various environmental compartments such as soil, water, and sediments. The presence of ARGs in the environment, particularly in municipal water, animal husbandry, and hospital environments, poses significant risks to human health, as they can be transferred to potential human pathogens. Current remediation strategies, including the use of pyroligneous acid, coagulants, advanced oxidation, and bioelectrochemical systems, have shown promising results in reducing ARGs and ARBs from soil and water. However, these methods come with their own set of challenges, such as the need for elevated base levels in UV-activated persulfate and the long residence period required for photocatalysts. The future of combating antibiotic resistance lies in the development of standardized monitoring techniques, global collaboration, and the exploration of innovative remediation methods. Emphasis on combination therapies, advanced oxidation processes, and monitoring horizontal gene transfer can pave the way for a comprehensive approach to mitigate the spread of antibiotic resistance in the environment.

Revealing the Viable Microbial Community of Biofilm in a Sewage Treatment System Using Propidium Monoazide Combined with Real-Time PCR and Metagenomics

Microbial community composition, function, and viability are important for biofilm-based sewage treatment technologies. Most studies of microbial communities mainly rely on the total deoxyribonucleic acid (DNA) extracted from the biofilm. However, nucleotide materials released from dead microorganisms may interfere with the analysis of viable microorganisms and their metabolic potential. In this study, we developed a protocol to assess viability as well as viable community composition and function in biofilm in a sewage treatment system using propidium monoazide (PMA) coupled with real-time quantitative polymerase chain reaction (qPCR) and metagenomic technology. The optimal removal of PMA from non-viable cells was achieved by a PMA concentration of 4 μM, incubation in darkness for 5 min, and exposure for 5 min. Simultaneously, the detection limit can reach a viable bacteria proportion of 1%, within the detection concentration range of 102-108 CFU/mL (colony forming unit/mL), showing its effectiveness in removing interference from dead cells. Under the optimal conditions, the result of PMA-metagenomic sequencing revealed that 6.72% to 8.18% of non-viable microorganisms were influenced and the composition and relative abundance of the dominant genera were changed. Overall, this study established a fast, sensitive, and highly specific biofilm viability detection method, which could provide technical support for accurately deciphering the structural composition and function of viable microbial communities in sewage treatment biofilms.

Distribution, source apportionment, and ecological risk assessment of soil antibiotic resistance genes in urban green spaces

Urban green spaces play a crucial role in cities by providing near-natural environments that greatly impacts the health of residents. However, these green spaces have recently been scrutinized as potential reservoirs of antibiotic resistance genes (ARGs), posing significant ecological risks. Despite this concern, our understanding of the distribution, sources, and ecological risks associated with ARGs remains limited. In this study, we investigated the spatial distribution of soil ARGs using spatial interpolation and auto-correlation analysis. To apportion the source of soil ARGs in urban green spaces of Tianjin, Geo-detector method (GDM) was employed. Furthermore, we evaluated the ecological risk posed by ARGs employing risk quotients (RQ). The results of our study showed a significantly higher abundance of Quinolone resistance genes in the soil of urban green spaces in Tianjin. These genes were mainly found in the northwest, central, and eastern regions of the city. Our investigation identified three main factors contributing to the presence of soil ARGs: antibiotic production, precipitation, livestock breeding, and hospital. The results of ecological risk in RQ value showed a high risk associated with Quinolone resistance genes, followed by Aminoglycoside, Tetracycline, Multidrug, MLSB, Beta Lactam, Sulfonamide, and Chloramphenicol. Mantel-test and correlation analysis revealed that the ecological risk of ARGs was greatly influenced by soil properties and heavy metals. This study provides a new perspective on source apportionment and the ecological risk assessment of soil ARGs in urban green spaces.

Design and Validation of Primer Sets for the Detection and Quantification of Antibiotic Resistance Genes in Environmental Samples by Quantitative PCR

The high prevalence of antibiotic resistant bacteria (ARB) in several environments is a great concern threatening human health. Particularly, wastewater treatment plants (WWTP) become important contributors to the dissemination of ARB to receiving water bodies, due to the inefficient management or treatment of highly antibiotic-concentrated wastewaters. Hence, it is vital to develop molecular tools that allow proper monitoring of the genes encoding resistances to these important therapeutic compounds (antibiotic resistant genes, ARGs). For an accurate quantification of ARGs, there is a need for sensitive and robust qPCR assays supported by a good design of primers and validated protocols. In this study, eleven relevant ARGs were selected as targets, including aadA and aadB (conferring resistance to aminoglycosides); ampC, blaTEM, blaSHV, and mecA (resistance to beta-lactams); dfrA1 (resistance to trimethoprim); ermB (resistance to macrolides); fosA (resistance to fosfomycin); qnrS (resistance to quinolones); and tetA(A) (resistance to tetracyclines). The in silico design of the new primer sets was performed based on the alignment of all the sequences of the target ARGs (orthology grade > 70%) deposited in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, allowing higher coverages of the ARGs' biodiversity than those of several primers described to date. The adequate design and performance of the new molecular tools were validated in six samples, retrieved from both natural and engineered environments related to wastewater treatment. The hallmarks of the optimized qPCR assays were high amplification efficiency (> 90%), good linearity of the standard curve (R2 > 0.980), repeatability and reproducibility across experiments, and a wide linear dynamic range. The new primer sets and methodology described here are valuable tools to upgrade the monitorization of the abundance and emergence of the targeted ARGs by qPCR in WWTPs and related environments.

Unlocking the molecular realm: advanced approaches for identifying clinically and environmentally relevant bacteria

Rapid, effective, and specific identification of clinical and environmental bacterial pathogens is of major importance for their control. Traditionally, bacteria have been identified by phenotypic methods based on morphological, biochemical, and metabolic properties. While these methods are very useful in clinical practice, they have limitations including a poor ability to differentiate within and between species and time-consuming workflows. Newly developed molecular methods can greatly improve the accuracy of taxonomic characterization, identifying specific strains of medical or environmental importance. However, due to high costs and the need for trained professionals, these methods are not yet routine in diagnostic laboratories. Thus, disseminating knowledge on advances in molecular identification techniques is pivotal to make these methodologies accessible. The objective of this work was to review and discuss current molecular techniques for bacteria identification aiming to track and monitor microbial agents in clinical and environmental samples.

Hospital and urban wastewaters shape the matrix and active resistome of environmental biofilms

Understanding the dynamics of antibiotic resistance gene (ARG) transfer and dissemination in natural environments remains challenging. Biofilms play a crucial role in bacterial survival and antimicrobial resistance (AMR) dissemination in natural environments, particularly in aquatic systems. This study focused on hospital and urban wastewater (WW) biofilms to investigate the potential for ARG dissemination through mobile genetic elements (MGEs). The analysis included assessing the biofilm extracellular polymeric substances (EPS), microbiota composition as well as metatranscriptomic profiling of the resistome and mobilome. We produced both in vitro and in situ biofilms and performed phenotypic and genomic analyses. In the in vitro setup, untreated urban and hospital WW was used to establish biofilm reactors, with ciprofloxacin added as a selective agent at minimal selective concentration. In the in situ setup, biofilms were developed directly in hospital and urban WW pipes. We first showed that a) the composition of EPS differed depending on the growth environment (in situ and in vitro) and the sampling origin (hospital vs urban WW) and that b) ciprofloxacin impacted the composition of the EPS. The metatranscriptomic approach showed that a) expression of several ARGs and MGEs increased upon adding ciprofloxacin for biofilms from hospital WW only and b) that the abundance and type of plasmids that carried individual or multiple ARGs varied depending on the WW origins of the biofilms. When the same plasmids were present in both, urban and hospital WW biofilms, they carried different ARGs.  We showed that hospital and urban wastewaters shaped the structure and active resistome of environmental biofilms, and we confirmed that hospital WW is an important hot spot for the dissemination and selection of antimicrobial resistance. Our study provides a comprehensive assessment of WW biofilms as crucial hotspots for ARG transfer. Hospital WW biofilms exhibited distinct characteristics, including higher eDNA abundance and expression levels of ARGs and MGEs, highlighting their role in antimicrobial resistance dissemination. These findings emphasize the importance of understanding the structural, ecological, functional, and genetic organization of biofilms in anthropized environments and their contribution to antibiotic resistance dynamics.

Addressing antibiotic resistance: computational answers to a biological problem?

The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformatics and artificial intelligence (AI) methods applied to metagenomic sequencing data offer the capacity to detect known and infer yet-unknown resistance mechanisms, and predict future outbreaks of antibiotic-resistant infections. Machine learning methods, in particular, could revive the waning antibiotic discovery pipeline by helping to predict the molecular structure and function of antibiotic resistance compounds, and optimising their interactions with target proteins. Consequently, AI has the capacity to play a central role in guiding antibiotic stewardship and future clinical decision-making around antibiotic resistance.

Strategy to Evaluate Changes in Bacterial Community Profiles and Bacterial Pathogen Load Reduction After Sewage Disinfection

Sewage effluent discharge is a major source of pathogenic contamination to the environment. The disinfection process is critical for the elimination of pathogens in sewage. In this study, we examined the impact of chlorine disinfection on the total, viable, and culturable populations of indicator bacteria, pathogens, and bacterial communities in two contrasting types of effluents (primarily treated saline and secondarily treated freshwater). Effluents collected bimonthly over 1 year were examined using cultivation, quantitative PCR (qPCR), and 16S rRNA gene amplicon sequencing coupled with or without propidium monoazide (PMA) treatment. The results showed that each type of effluent was characterized by a specific set of representative genera before disinfection. Salinity appeared to be the major abiotic factor associated with the differences in bacterial community compositions. The pathogen analysis pipeline revealed over 20 viable clinically important pathogenic species in the effluents. Although the bacterial communities differed markedly between the two types of effluents before disinfection, the species of pathogens persisting after disinfection were similar, many of them were members of Enterobacter and Vibrio. The relative abundances of all pathogens identified in the amplicon sequences were multiplied by the 16S rRNA gene copy numbers of total bacteria detected by PMA-qPCR to estimate their concentrations. Pathogens remained viable after disinfection reached 8 log₁₀ 16S rRNA copies ml⁻¹ effluent. Meanwhile, around 80 % of the populations of three indicator bacteria including Escherichia coli, Enterococcus, and Bacteroidales were viable after disinfection, but over 99 % of the viable E. coli and Enterococcus were in the non-culturable state. We estimated the total pathogen load by adding the concentrations of all viable pathogens and examined their correlations with indicator bacteria of different types, physiological states, and effluents. The results showed that the PMA-qPCR measurement of E. coli is a reliable proxy of bacterial pathogen loads in both types of effluents. The utility of viable indicator bacteria as a biological index to assess the overall bacteriological hazards in effluents is discussed.

Abundance, diversity, and host assignment of total, intracellular, and extracellular antibiotic resistance genes in riverbed sediments

Human health risk assessment for environmental antibiotic resistant microbes requires not only quantifying the abundance of antibiotic resistance genes (ARGs) in environmental matrices, but also understanding their hosts and genetic context. Further, differentiating ARGs in intracellular and extracellular DNA (iDNA and eDNA) fractions may help refine our understanding of ARG transferability. The objectives of this study were to understand the (O1) abundance and diversity of extracellular, intracellular, and total ARGs along a land use gradient and (O2) impact of bioinformatics pipeline on the assignment of putative hosts for the ARGs observed in the different DNA fractions. Sediment samples were collected along a land use gradient in the Raritan River, New Jersey, USA. DNA was extracted to separate eDNA and iDNA and qPCR was performed for select ARGs and the 16S rRNA gene. Shotgun metagenomic sequencing was performed on DNA extracts for the different DNA fractions. ARG hosts were assigned via two different bioinformatic pipelines: network analysis of raw reads versus assembly. Results of the two pipelines were compared to evaluate their performance in terms of number and diversity of linkages and accuracy of in silico matrix spike host assignments. No differences were observed in the 16S rRNA gene normalized sul1 concentrations between the DNA fractions. The overall microbial community structure was more similar for iDNA and total DNA compared to eDNA and generally clustered by sampling site. ARGs associated with mobile genetic elements increased in iDNA for the downstream sites. Regarding host assignment, the raw reads pipeline via network analysis identified 247 ARG hosts as compared to 53 hosts identified by assembly pipeline. Other comparisons between the pipelines were made including ARG assignment to taxa containing waterborne pathogens and practical considerations regarding processing time.

Metabolically Active Prokaryotes and Actively Transcribed Antibiotic Resistance Genes in Sewer Systems: Implications for Public Health and Microbially Induced Corrosion

Sewer systems are reservoirs of pathogens and bacteria carrying antibiotic resistance genes (ARGs). However, most recent high-throughput studies rely on DNA-based techniques that cannot provide information on the physiological state of the cells nor expression of ARGs. In this study, wastewater and sewer sediment samples were collected from combined and separate sanitary sewer systems. The metabolically active prokaryote community was evaluated using 16S rRNA amplicon sequencing and actively transcribed ARG abundance was measured using mRNA RT-qPCR. Three (sul1, bla_TEM, tet(G)) of the eight tested ARGs were quantifiable in select samples. Sewer sediment samples had greater abundance of actively transcribed ARGs compared to wastewater. Microbiome analysis showed the presence of metabolically active family taxa that contain clinically relevant pathogens (Pseudomonadaceae, Enterobacteraceae, Streptococcaceae, Arcobacteraceae, and Clostridiaceae) and corrosion-causing prokaryotes (Desulfobulbaceae and Desulfovibrionaceae) in both matrices. Spirochaetaceae and methanogens were more common in the sediment matrix while Mycobacteraceae were more common in wastewater. The microbiome obtained from 16S rRNA sequencing had a significantly different structure from the 16S rRNA gene microbiome. Overall, this study demonstrates active transcription of ARGs in sewer systems and provides insight into the abundance and physiological state of taxa of interest in the different sewer matrices and sewer types relevant for wastewater-based epidemiology, corrosion, and understanding the hazard posed by different matrices during sewer overflows.

Monitoring antibiotic resistance genes in wastewater treatment: Current strategies and future challenges

Antimicrobial resistance (AMR) is a growing threat to human and animal health. Progress in molecular biology has revealed new and significant challenges for AMR mitigation given the immense diversity of antibiotic resistance genes (ARGs), the complexity of ARG transfer, and the broad range of omnipresent factors contributing to AMR. Municipal, hospital and abattoir wastewater are collected and treated in wastewater treatment plants (WWTPs), where the presence of diverse selection pressures together with a highly concentrated consortium of pathogenic/commensal microbes create favourable conditions for the transfer of ARGs and proliferation of antibiotic resistant bacteria (ARB). The rapid emergence of antibiotic resistant pathogens of clinical and veterinary significance over the past 80 years has re-defined the role of WWTPs as a focal point in the fight against AMR. By reviewing the occurrence of ARGs in wastewater and sludge and the current technologies used to quantify ARGs and identify ARB, this paper provides a research roadmap to address existing challenges in AMR control via wastewater treatment. Wastewater treatment is a double-edged sword that can act as either a pathway for AMR spread or as a barrier to reduce the environmental release of anthropogenic AMR. State of the art ARB identification technologies, such as metagenomic sequencing and fluorescence-activated cell sorting, have enriched ARG/ARB databases, unveiled keystone species in AMR networks, and improved the resolution of AMR dissemination models. Data and information provided in this review highlight significant knowledge gaps. These include inconsistencies in ARG reporting units, lack of ARG/ARB monitoring surrogates, lack of a standardised protocol for determining ARG removal via wastewater treatments, and the inability to support appropriate risk assessment. This is due to a lack of standard monitoring targets and agreed threshold values, and paucity of information on the ARG-pathogen host relationship and risk management. These research gaps need to be addressed and research findings need to be transformed into practical guidance for WWTP operators to enable effective progress towards mitigating the evolution and spread of AMR.

High-valent iron-oxo species on pyridine-containing MWCNTs generated in a solar-induced H2O2 activation system for the removal of antimicrobials

The overuse of antimicrobials has resulted in serious damage to the ecosystem and human health. Therefore, the development of an efficient, stable, and reusable catalyst to eliminate antimicrobials under mild conditions is highly desired. Drawing inspiration from the metabolism of drugs by the enzymes in the human body, such as heme catalase, we developed a simulated enzyme catalyst, perchloride iron phthalocyanine (FePcCl₁₆), immobilized on pyridine-modified multiwalled carbon nanotubes (FePcCl₁₆-Py-MWCNTs). In the catalyst, FePcCl₁₆ worked as the active site, and the axial fifth ligand, 4-aminopyridine, was introduced to cleave H₂O₂ heterolytically. Inspired by the reaction mechanism of heme catalase and H₂O₂, the catalytic system was designed based on FePcCl₁₆-Py-MWCNTs for oxidizing 4-chloro-3,5-dimethylphenol (PCMX) by H₂O₂ activation. The results showed that the catalytic activity of the system was significantly increased under simulated solar light irradiation, which can promote electron transfer for heterolytic cleavage of H₂O₂. The enzyme-like catalyst achieved much higher catalytic activity than the Fenton reaction when the pH was close to neutral. It turned out that the main active species was high-valent iron-oxo (Fe(Ⅳ) = O) rather than hydroxyl radial (•OH) or superoxide radical (•O₂^-), different from most mechanisms. Ultraperformance liquid chromatography-high-definition mass spectrometry showed that the substrate was degraded to small molecule acids by Fe(Ⅳ) = O active species and further mineralization indicated by total organic carbon. The catalytic system exhibited highly efficient, stable, recyclable catalytic performance under mild conditions and did not cause secondary pollution to the environment. This study of a simulated enzyme catalytic system offers important insight into sewage treatment.

Seasonal influences on the use of genetic markers as performance indicators for small wastewater treatment plants

The development of microbial source tracking methods has resulted in an array of genetic faecal markers for assessing human health risks posed from surface water pollution. However, their use as performance metrics at wastewater treatment plants (WWTPs) has not been explored extensively. Here we compared three Bacteroides (HF183, HumM2, AllBac) and two E. coli (H8, RodA) genetic markers for summer and winter performance monitoring at twelve small rural (<250 PE) and three larger WWTPs in NE England. Small WWTPs are of interest because they are poorly understood and their impact on surface water quality may be underestimated. Overall, genetic marker data showed significant differences in treatment performance at smaller versus larger WWTPs. For example, effluent abundances of HF183 and HumM2 were significantly higher in smaller systems (p = 0.003 for HumM2; p = 0.02 for HF183). Genetic markers also showed significant differences in performance between seasons (p < 0.01, n = 120), with human-specific markers (i.e., HF183, HumM2, H8) being generally better for summer WWTP monitoring. In contrast, Bacteroides markers were much more suitable for winter monitoring, possibly because the E. coli markers are less sensitive to differences in temperature and sunlight conditions. Overall, Bacteroides markers best described WWTP treatment performance across all samples, although seasonal differences suggest caution is needed when markers are used for performance monitoring. Genetic markers definitely provide rapid and new information about WWTP performance, but more spatially diverse studies are needed to refine their use for routine WWTP monitoring.

Tagging the vanA gene in wastewater microbial communities for cell sorting and taxonomy of vanA carrying cells

Failure to understand the microbial ecology driving the proliferation of antibiotic resistance in the environment prevents us from developing strategies to limit the spread of antibiotic resistant infectious disease. In this study, we developed for the first time a tyramide signal amplification-fluorescence in situ hybridization-fluorescence-activated cell sorting protocol (TSA-FISH-FACS) for the characterization of all vanA carrying bacteria in wastewater samples. Firstly, we validated the TSA-FISH protocol through microscopy in pure cultures and wastewater influent. Then, samples were sorted and quantified by FACS and qPCR. Significantly higher percentage tagging of cells was detected in vanA carrying pure cultures and wastewater samples spiked with vanA carrying cells as compared to vanA negative Gram positive strains and non-spiked wastewater samples respectively. qPCR analysis targeting vanZ, a regulating gene in the vanA cluster, showed its relative abundance was significantly greater in Enterococcus faecium ATCC 700221-spiked and positively sorted samples compared to the E. faecium spiked and negatively sorted samples. Phylogenetic analysis was then performed. Although further efforts are needed to overcome technical problems, we have, for the first time, demonstrated sorting bacterial-cells carrying antibiotic resistance genes from wastewater samples through a TSA-FISH-FACS protocol and provided insight into the microbial ecology of vancomycin resistant bacteria. Future potential applications using this approach will include the separation of members of an environmental microbial community (cultured and hard-to-culture) to allow for metagenomics on single cells or, in the case of clumping, targeting a smaller portion of the community with a priori knowledge that the target gene is present.

Sewer biofilm microbiome and antibiotic resistance genes as function of pipe material, source of microbes, and disinfection: field and laboratory studies

Wastewater systems are recognized pathways for the spread of antibiotic resistant bacteria, but relatively little is known about the microbial ecology of the sewer environment. Sewer biofilm colonization by antibiotic resistance gene (ARG) carrying bacteria may impact interpretations of sewage epidemiology data, water quality during sewer overflows, and hazard to utility workers. The objectives of this research were to evaluate the (1) microbiome of real and simulated sewer biofilms and their potential to accumulate ARGs and (2) susceptibility of simulated sewer biofilms to bleach disinfection. First, biofilm samples were collected from sewer municipal systems. Next, an annular biofilm reactor was used to simulate the sewer environment while controlling the pipe material (concrete vs. PVC). The reactor was operated either as fed semi-batch with sewer sediment and synthetic wastewater (Sed-SB) or fed with a continuous flow of raw sewage (WW-CF). The abundance of ARGs, human fecal marker HF183, and 16S rRNA gene copies in these biofilm samples was measured with qPCR. Amplicon sequencing was performed to compare the prokaryotic diversity between samples. Finally, the susceptibility of reactor biofilm to a 4.6% bleach disnfection protocol was evaluated using viability qPCR and amplicon sequencing. Field and WW-CF biofilms contained the most ARG copies and the microbial community compositions varied between the different biofilm samples (field, Sed-SB, and WW-CF). Pipe material did not affect the abundance of ARGs in the reactor samples. However, log removal following bleach treatment suggested that the biofilm grown on PVC surface was primarily dislodged from the surface by the bleach treatment whereas more bacteria were lysed within the biofilm that remained on the concrete surface. Viable bacteria carrying ARGs were observed following 10 minutes of treatment. This study showed that sewer biofilms can accumulate bacteria carrying ARGs and that while bleach can reduce sewer biofilm density, the protocol tested here will not completely remove the biofilms.

Fate of antibiotics, antibiotic-resistant bacteria, and cell-free antibiotic-resistant genes in full-scale membrane bioreactor wastewater treatment plants

The removal of antibiotics, antibiotic-resistant bacteria (ARB), and cell-free antibiotic-resistant genes (ARGs) and the microbial community of ARB were investigated in detail to understand their fate and provide valuable information on the feasibility of full-scale membrane bioreactor (MBR). The potential risks of cell-free ARGs to the receiving environment were discovered. High influent antibiotic concentration could inhibit the microbial activity of MBR sludge, whereas good antibiotic removal could be maintained because of relatively long solid retention time and high biomass retention. Approximately 61.8%-77.5% of the total antibiotics were degraded, and 22.5%-38.2% of the total antibiotics were adsorbed by MBR sludge on average. The individual antibiotic removal presented intense discrepancy because of the chemical construction and distribution coefficient of antibiotics. Aeromonas exhibited specific antibiotic resistance to ampicillin and erythromycin, Escherichia became the predominant genera in kanamycin-ARB and tetracycline-ARB, and Klebsiella and Bacteroides were the particular genera that exhibited distinct antibiotic resistance to ciprofloxacin. A significant correlation was found between cell-free ARG abundance and ARB content, and relatively high effluent cell-free ARG abundance facilitated the proliferation and transmission of ARB. The impacts of the receiving environment to eliminate the ecological risks and severe threats to human health should be investigated because of the low decay ratio and long-term persistence of cell-free ARGs.

Occurrence of Bacterial Markers and Antibiotic Resistance Genes in Sub-Saharan Rivers Receiving Animal Farm Wastewaters

Antibiotic resistant bacteria and genes which confer resistance to antibiotics from human/animal sources are currently considered a serious environmental and a public health concern. This problem is still little investigated in aquatic environment of developing countries according to the different climatic conditions. In this research, the total bacterial load, the abundance of relevant bacteria (Escherichia coli (E. coli), Enterococcus (Ent), and Pseudomonas), and antibiotic resistance genes (ARGs: blaOXA-48, blaCTX-M, sul1, sul2, sul3, and tet(B)) were quantified using Quantitative Polymerase Chain Reaction (qPCR) in sediments from two rivers receiving animal farming wastewaters under tropical conditions in Kinshasa, capital city of the Democratic Republic of the Congo. Human and pig host-specific markers were exploited to examine the sources of contamination. The total bacterial load correlated with relevant bacteria and genes blaOXA-48, sul3, and tet(B) (P value < 0.01). E. coli strongly correlated with 16s rDNA, Enterococcus, Pseudomonas spp., blaOXA-48, sul3, and tet(B) (P value < 0.01) and with blaCTX-M, sul1, and sul2 at a lower magnitude (P value < 0.05). The most abundant and most commonly detected ARGs were sul1, and sul2. Our findings confirmed at least two sources of contamination originating from pigs and anthropogenic activities and that animal farm wastewaters didn't exclusively contribute to antibiotic resistance profile. Moreover, our analysis sheds the light on developing countries where less than adequate infrastructure or lack of it adds to the complexity of antibiotic resistance proliferation with potential risks to the human exposure and aquatic living organisms. This research presents useful tools for the evaluation of emerging microbial contaminants in aquatic ecosystems which can be applied in the similar environment.