Comparing the fate of antibiotic resistance genes in two full-scale thermophilic anaerobic digestion plants treating food wastewater

A "Turn-on" fluorescence sensing strategy based on DNA-templated silver nanoclusters for the detection of antibiotic resistance genes

BACKGROUND

Antibiotic resistance genes (ARGs) are emerging environmental contaminants that pose serious threats to human health and ecological security due to their rapid migration and transformation in the environment. Thus, developing a sensitive and rapid method to detect ARGs is significant.

RESULTS

In this study, the neighborhood-dependent fluorescent sensor was established with DNA templated silver nanoclusters (AgNCs) and multi-branched linear structure to detect the typical macrolide resistance gene ermB. A DNA fluorescent probe with a specific recognition fragment for AgNCs and a tuning enhancement sequence were designed. The probe and the target resistance genes were complementary hybridized to form a linear multi-branch DNA structure of bright yellow silver nanocluster beacon that realized fluorescence signal amplification and transduction.

SIGNIFICANCE

This method has the advantages of being enzyme-free, label-free and amplification-free for being applied to the rapid detection of specific ARGs and successfully detected macrolide resistance gene ermB with the LOD as low as 0.37 nM in environmental samples with complex composition.

Different combinations of operating temperature and solids retention time during two-phase anaerobic digestion impacts removal of antibiotic resistance genes

Two-phase anaerobic digestion (AD) performance is significantly influenced by operating parameters such as temperature and solids retention time (SRT), while their impact on antibiotic resistance genes (ARGs) during the acidogenic (AP) and methanogenic (MP) phases remains unclear. This study assessed the abundance of eight ARGs in full-scale two-phase AD, then operated lab-scale two-phase AD systems to evaluate temperature combinations (thermophilic-thermophilic, thermophilic-mesophilic, mesophilic-thermophilic, and mesophilic-mesophilic) at a constant SRT (AP = 2/MP = 13d) and to further assess different SRTs (AP = 2/MP = 13d and AP = 4/MP = 11d). qPCR results revealed that full-scale two-phase AD reduced total ARGs abundance by 87.70 ± 0.50 %. In lab-scale tests, the thermophilic-thermophilic configuration achieved nearly complete ARGs removal (97.61 ± 0.21 %), while the combination of AP = 4/MP = 11d had the highest removal efficiency (83.39 ± 1.17 %). Network analysis indicated that Firmicutes, Bacteroidota, and Proteobacteria were the primary ARG hosts, with Firmicutes dominant. These findings highlight the optimal operating parameters in two-phase AD for maximizing ARGs removal.

Insights into kinetic and regression models developed to estimate the abundance of antibiotic-resistant genes during biological digestion of wastewater sludge

Wastewater treatment plants are hubs of antibiotic-resistant genes (ARGs). During wastewater treatment, ARGs accumulate in wastewater sludge and some survive biological digestion. After land application of digested sludge, ARGs are transported to soil, water, and air, and may encounter humans and animals. ARGs are typically quantified by quantitative polymerase chain reaction (qPCR) on isolated DNA. Nevertheless, DNA isolation and qPCR are time-consuming, expensive, and prone to contamination. Therefore, there is a need to estimate ARGs quantities via methods that can be readily employed. Such estimation would help to protect public health via modifying biological digestion to maximize the removal of ARGs. Two approaches that make such estimation are kinetic and regression modeling. The kinetic models have been mainly of the first order. This review examines the application of the kinetic models to estimate the abundance of ARGs during biological sludge digestion. It also discusses how biological sludge digesters can be designed using kinetic models. The literature provides single and multiple regression models, from which an ARGs -Solids -Nutrients nexus, a focal point of this review, is inferred. This review demonstrates that regression models are mathematical expressions of that nexus. Also, existing challenges are highlighted and suggestions for future are provided.

Fate of intracellular and extracellular antibiotic resistance genes in sewage sludge by full-scale anaerobic digestion

Storage tank (ST) is a promising strategy for solid-liquid separation following anaerobic digestion (AD). However, little is known regarding the effects of ST on antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and microbial communities. Therefore, this study first investigated eight typical ARGs (sul1, sul2, tetW, tetA, tetO, tetX, ermF, and ermB) and three MGEs (int1, int2, and tnpA) during full-scale AD of sludge and the liquid and biosolids phases of ST. Following that, intracellular ARGs (iARGs), extracellular polymeric substances (EPS)-associated ARGs, and cell-free ARGs removal were quantified in AD process, which is largely unknown for full-scale AD of sludge. The qPCR results showed that both AD and ST significantly removed ARGs, with ST biosolids showing the highest removal efficiency for the total measured relative (82.27 ± 2.09 %) and absolute (92.38 ± 0.89 %) abundance of ARGs compared to the raw sludge. Proteobacteria, Bacteroidota, Firmicutes and Campilobacterota were the main potential ARGs hosts in the sludge. Moreover, the results of different ARGs fractions showed that the total relative and absolute abundance of iARGs decreased by 90.12 ± 0.83 % and 79.89 ± 1.41 %, respectively, following AD. The same trend was observed for the abundance of EPS-associated ARGs, while those of cell-free ARGs increased after AD. These results underscore the risk of extracellular ARGs and provided new insights on extracellular ARGs dissemination evaluation.

An overview of the occurrence, impact of process parameters, and the fate of antibiotic resistance genes during anaerobic digestion processes

Antibiotic resistance genes (ARGs) have emerged as a significant global health threat, contributing to fatalities worldwide. Wastewater treatment plants (WWTPs) and livestock farms serve as primary reservoirs for these genes due to the limited efficacy of existing treatment methods and microbial adaptation to environmental stressors. Anaerobic digestion (AD) stands as a prevalent biological treatment for managing sewage sludge and manure in these settings. Given the agricultural utility of AD digestate as biofertilizers, understanding ARGs' fate within AD processes is essential to devise effective mitigation strategies. However, understanding the impact of various factors on ARGs occurrence, dissemination, and fate remains limited. This review article explores various AD treatment parameters and correlates to various resistance mechanisms and hotspots of ARGs in the environment. It further evaluates the dissemination and occurrence of ARGs in AD feedstocks and provides a comprehensive understanding of the fate of ARGs in AD systems. This review explores the influence of key AD parameters such as feedstock properties, pretreatments, additives, and operational strategies on ARGs. Results show that properties such as high solid content and optimum co-digestion ratios can enhance ARG removal, while the presence of heavy metals, microplastics, and antibiotics could elevate ARG abundance. Also, operational enhancements, such as employing two-stage digestion, have shown promise in improving ARG removal. However, certain pretreatment methods, like thermal hydrolysis, may exhibit a rebounding effect on ARG levels. Overall, this review systematically addresses current challenges and offers future perspectives associated with the fate of ARGs in AD systems.

Promising bioprocesses for the efficient removal of antibiotics and antibiotic-resistance genes from urban and hospital wastewaters: Potentialities of aerobic granular systems

The use, overuse, and improper use of antibiotics have resulted in higher levels of antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs), which have profoundly disturbed the equilibrium of the environment. Furthermore, once antibiotic agents are excreted in urine and feces, these substances often can reach wastewater treatment plants (WWTPs), in which improper treatments have been highlighted as the main reason for stronger dissemination of antibiotics, ARB, and ARGs to the receiving bodies. Hence, achieving better antibiotic removal capacities in WWTPs is proposed as an adequate approach to limit the spread of antibiotics, ARB, and ARGs into the environment. In this review, we highlight hospital wastewater (WW) as a critical hotspot for the dissemination of antibiotic resistance due to its high level of antibiotics and pathogens. Hence, monitoring the composition and structure of the bacterial communities related to hospital WW is a key factor in controlling the spread of ARGs. In addition, we discuss the advantages and drawbacks of the current biological WW treatments regarding the antibiotic-resistance phenomenon. Widely used conventional activated sludge technology has proved to be ineffective in mitigating the dissemination of ARB and ARGs to the environment. However, aerobic granular sludge (AGS) technology is a promising technology-with broad adaptability and excellent performance-that could successfully reduce antibiotics, ARB, and ARGs in the generated effluents. We also outline the main operational parameters involved in mitigating antibiotics, ARB, and ARGs in WWTPs. In this regard, WW operation under long hydraulic and solid retention times allows better removal of antibiotics, ARB, and ARGs independently of the WW technology employed. Finally, we address the current knowledge of the adsorption and degradation of antibiotics and their importance in removing ARB and ARGs. Notably, AGS can enhance the removal of antibiotics, ARB, and ARGs due to the complex microbial metabolism within the granular biomass.

Removal behavior and key drivers of antibiotic resistance genes in two full-scale leachate treatment plants

Leachate is a critical reservoir of antibiotic resistance genes (ARGs) and its proper treatment is closely related to human health and ecosystem safety. Here, we used high-throughput qPCR to explore the removal behavior of ARGs in two full-scale leachate treatment plants (LTPs) where biological treatment and membrane filtration processes were integrated. A total of 286 ARGs and 55 mobile genetic elements (MGEs) were detected, with aminoglycoside, multidrug and MLSB resistance genes being the most prevalent and abundant. Anaerobic digestion was found to be an important pretreatment process for leachate, while anoxic/aerobic tanks in membrane bioreactor (MBR) acted as incubators for ARGs due to their significant proliferation effect on ARGs. Integrated membrane filtration (UF-NF-RO) excelled in ARGs removal with absolute abundances reduced by 3 to 6 orders of magnitude, from about 10⁹ copies/mL in raw leachate to 10³-10⁵ copies/mL in effluents. Our results also showed that leachate treatment processes significantly altered the composition of ARGs and bacterial communities. Procrustes analysis and network analysis revealed strong associations between microbes and ARGs, with several hub genes and bacterial genera identified. Structural equation models (SEMs) indicated that bacterial composition, MGEs and basic water properties were the key drivers shaping ARGs dynamics in the raw leachate, biological system and filtration system, respectively. Notably, several pathogens (e.g., Klebsiella, Vibrio, Aeromonas) were closely correlated with ARGs in raw leachate and may amplify the dissemination risks of ARGs. Moreover, insertion sequences in biological systems would accelerate the horizontal gene transfer of ARGs. In short, this study provides new insights into the mechanisms of ARGs removal and dissemination behavior in industrial-scale LTPs.

Exploration of machine learning algorithms for predicting the changes in abundance of antibiotic resistance genes in anaerobic digestion

The land application of digestate from anaerobic digestion (AD) is considered a significant route for transmitting antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) to ecosystems. To date, efforts towards understanding complex non-linear interactions between AD operating parameters with ARG/MGE abundances rely on experimental investigations due to a lack of mechanistic models. Herein, three different machine learning (ML) algorithms, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN), were compared for their predictive capacities in simulating ARG/MGE abundance changes during AD. The models were trained and cross-validated using experimental data collected from 33 published literature. The comparison of model performance using coefficients of determination (R²) and root mean squared errors (RMSE) indicated that ANN was more reliable than RF and XGBoost. The mode of operation (batch/semi-continuous), co-digestion of food waste and sewage sludge, and residence time were identified as the three most critical features in predicting ARG/MGE abundance changes. Moreover, the trained ANN model could simulate non-linear interactions between operational parameters and ARG/MGE abundance changes that could be interpreted intuitively based on existing knowledge. Overall, this study demonstrates that machine learning can enable a reliable predictive model that can provide a holistic optimization tool for mitigating the ARG/MGE transmission potential of AD.

How heavy metal stress promotes dissemination of antibiotic resistance genes in the activated sludge process

Heavy metals have been recently revealed as promoters to antibiotic resistance gene (ARG) dissemination in water environment, but their influence on ARG transfer in the activated sludge process has not been clear. In this study, a set of sequencing batch reactors (SBRs) and micro-scale microfluidic chips were established to quantify the impacts of heavy metals (0.5 mM of Pb, 0.1 mM of As, and 0.005 mM of Hg) on the ARG spreading in the activated sludge consortium. Under heavy metal stress, transfer frequencies were 1.7-3.6 folds increase compared to the control. Gram-negative bacteria increased significantly after heavy metal added, which were more prone to receiving resistant plasmid from donors. Meanwhile, the relative expression of genes related to conjugation changed in activated sludge, especially the expression of outer membrane protein and oxidative stress regulatory genes increased by 2.9-7.4 folds and 7.8-13.1 folds, respectively. Furthermore, using microfluidic chips, the dynamics of ARG transfer was observed at single cell level under heavy metal pressure. Heavy metals firstly promoted conjugation and then vertical gene transfer played an important part for ARG spreading. The results provided in-depth understanding of the influence of heavy metals on ARG behavior in the environment.

A critical review of process parameters influencing the fate of antibiotic resistance genes in the anaerobic digestion of organic waste

The overuse and inappropriate disposal of antibiotics raised severe public health risks worldwide. Specifically, the incomplete antibiotics metabolism in human and animal bodies contributes to the significant release of antibiotics into the natural ecosystems and the proliferation of antibiotic-resistant bacteria carrying antibiotic-resistant genes. Moreover, the organic feedstocks used for anaerobic digestion are often highly-rich in residual antibiotics and antibiotic-resistant genes. Hence, understanding their fate during anaerobic digestion has become a significant research focus recently. Previous studies demonstrated that various process parameters could considerably influence the propagation of the antibiotic-resistant genes during anaerobic digestion and their transmission via land application of digestate. This review article scrutinizes the influences of process parameters on antibiotic-resistant genes propagation in anaerobic digestion and the inherent fundamentals behind their effects. Based on the literature review, critical research gaps and challenges are summarized to guide the prospects for future studies.

Identification of factors affecting removal of antibiotic resistance genes in full-scale anaerobic digesters treating organic solid wastes

Efficiencies of removing antibiotic resistance genes (ARGs) and intI1 were explored using eight full-scale anaerobic digesters. The digesters demonstrated different characteristics on the basis of substrate types (food waste, manure or sludge); configuration (single or two-stage); temperature (psychrophilic, mesophilic or thermophilic); hydraulic retention time (HRT) (9.7-44 days); and operation mode (continuous stirred tank reactor or plug flow reactor). Digesters' configuration or operating parameters showed a greater effect on abundance of ARGs than the type of input substrate. Redundancy analysis (RDA) accounted for 85.2% of the total variances and digesters with the same configuration and operational conditions showed similar performance for removal of ARGs. The highest efficiencies of removing ARGs (99.99%) were observed in two-stage thermophilic digesters with relatively long HRTs (32 days). The lowest removal efficiency (97.93%) was observed in single-stage mesophilic with relatively short HRTs (9.7 days), likely due to vertical and horizontal gene transfer.

Comparison of the elimination effectiveness of tetracycline and AmpC β-lactamase resistance genes in a municipal wastewater treatment plant using four parallel processes

Municipal wastewater treatment plants (mWWTPs), considered reservoirs of antibiotic resistance genes (ARGs), are selected to compare the contributions of technology and process to ARG removal. Fifteen ARGs (tetA, tetB, tetC, tetE, tetG, tetL, tetM, tetO, tetQ, tetS, tetX, MOX, CIT, EBC, and FOX) and two integron genes (intI1, intI2) were tracked and detected in wastewater samples from a large-scale mWWTP with four parallel processes, including three biological technologies of AAO (anaerobic-anoxic-oxic), AB (adsorption-biodegradation), and UNITANK, two different disinfection technologies, and two primary sedimentation steps. The results showed that ARGs were widely detected, among which tetA and tetM had the highest detection rate at 100%. AAO was the most effective process in removing ARGs, followed by the AB and UNITANK processes, where the separation step was critical: 37.5% AmpC β-lactamase genes were reduced by the secondary clarifier. UV disinfection was more efficient than chlorination disinfection by 47.0% in ARG removal. Both disinfection and primary sedimentation processes could effectively remove integrons, and the swirling flow grit chamber was a more effective primary settling facility in total ARG removal than the aerated grit chamber. The tet genes and AmpC β-lactamase genes were significantly correlated with the water quality indexes of BOD5, CODCr, SS, TP, TOC, pH and NH4+-N (p < 0.05). In addition, the correlation between efflux pump genes and AmpC β-lactamase genes was strongly significant (r2 = 0.717, p < 0.01). This study provides a more powerful guide for selecting and designing treatment processes in mWWTPs with additional consideration of ARG removal.

The variation of antibiotic resistance genes and their links with microbial communities during full-scale food waste leachate biotreatment processes

The prevalence of antibiotic resistance genes (ARGs) has been widely reported in various environments. However, little is known of them in food waste (FW) leachate with high organic content and how their distribution is influenced by biotreatment processes. Here, twelve ARGs, two integrase genes and bacterial communities were investigated during two full-scale FW biotreatment processes. High ARGs abundances (absolute: 1.03 × 10⁷-2.82 × 10⁹copies/mL; relative: 0.076-2.778copies/16S rRNA) were observed across all samples. Although biotreatment effectively reduced absolute abundance of ARGs, additional bacteria acquiring ARGs caused an increase in their relative abundance, which further increased the transmission risk of ARGs. mexF, blaCTX-M, sul1 played crucial roles and sul1 might be considered as an indicator for the prediction of total ARGs. It is worrying that the discharge (effluent and sludge) included highly abundant ARGs (5.09 × 10¹⁴-4.83 × 10¹⁵copies/d), integrons (1.11 × 10¹⁴-6.04 × 10¹⁴copies/d) and potential pathogens (such as Pseudomonas and Streptococcus), which should be given more attentions. blaCTX-M and tetQ possessed most potential hosts, Proteobacteria-L and Firmicutes-W were predominant contributors of ARGs-hosts at genus level. This study suggested FW leachate biotreatment systems could be reservoirs of ARGs and facilitated the proliferation of them. The exploration of effective removal methods and formulation of emission standard are necessary for future ARGs mitigation.

Characteristics of bacterial community and ARGs profile in engineered goldfish tanks with stresses of sulfanilamide and copper

Abuse of antibiotics in aquaculture have been alarming and might aggravate spread of resistance genes in the environment. Holistic ARGs proliferation checks require deeper analyses of coupled absolute abundances in 16S rRNA bacteria communities at the phylum level to detect biomarkers. Sulfanilamide (sul) and copper II sulfate (CuSO₄ II) were, therefore, designed and added as separate or combined treatments in 9 replicate engineered goldfish tanks comprising 3 individual sul, 3 CuSO₄ II, 3 (sul + CuSO₄ II) combinations, and 3 controls within 180 days. The DNA from water and fish guts was sequenced under qPCR to determine 16S rRNA bacteria biomarkers co-occurring with the correspondent ARGs. Combined chemical addition at 0.8-1.5 mg sul + 0.5-1.0 mg CuSO₄ II/3 L of tank waters reduced sequenced 16S rRNA bacteria absolute abundances in fish gut and water samples while portraying the biomarkers. Absolute abundances of the entire 16S rRNA bacteria was higher in fish guts (3.4 × 10¹⁴-4.9 × 10⁸ copies/g) than water samples (1.5 × 10⁹-2.6 × 10¹⁵ copies/L), respectively. Much as sul 1(log) were dominant over intl 1(log) genes, and their fundamental profiles were also higher in the fish guts than water samples; the Spearman's correlation analyses revealed positive relationship (p < 0.01 and r = 0.873) among the biomarkers of both ARG pairs at the phylum level and the physicochemical parameters. In the fish gut and water samples ratios, Bacteroidetes (10-85:12-85%) > Proteobacteria (10-50:15-65%) > Planktomycetes (10-52:8-25%) featured prominently based on LEfSe use as the hot-spotted biomarkers, hence justifying its higher prospects towards innovative environmental microbiological and biotechnological studies.

Does lipid stress affect performance, fate of antibiotic resistance genes and microbial dynamics during anaerobic digestion of food waste?

The dissemination of antibiotic resistance genes (ARGs) in food waste (FW) disposal can pose severe threats to public health. Lipid is a primary composition in FW, while whether lipid stress can affect ARGs dynamics during anaerobic digestion (AD) process of FW is uncertain. This study focused on the impacts of lipid stress on methane production, fate of ARGs and its microbial mechanisms during AD of FW. Results showed that high lipid content increased methane yield but prolonged hydrolysis and lag time of methane production compared to AD of FW without oil. Moreover, variations of ARGs were more susceptible to lipid stress. Lipid stress could facilitate the reduction of total ARGs abundances compared to the group without oil, particularly restraining the proliferation of sul1, aadA1 and mefA in AD systems (P < 0.05). Mantel test suggested that integrons (intl1 and intl2) were significantly correlated with all detected ARGs (r: 0.33, P < 0.05), indicating that horizontal gene transfer mediated by integrons could be the driving force on ARGs dissemination. Network analysis suggested that Firmicutes, Bacteroidetes, Synergistetes and Proteobacteria were the main potential hosts of ARGs. In addition, under the lipid stress, the reduction of host bacteria was responsible for the elimination of several specific ARGs, thereby affecting ARGs profiles. These findings firstly deciphered ARGs dynamics and their driving factors responding to lipid stress during anaerobic biological treatment of FW.