Variations in antibiotic resistance genes and microbial community in sludges passing through biological nutrient removal and anaerobic digestion processes in municipal wastewater treatment plants.

Antimicrobial resistance (AMR) represents a relentless, silent pandemic. Contributing to this are wastewater treatment plants (WWTPs), a potential source of antibiotic resistance genes' (ARGs) transmission to the environment, threatening public health. The presence of ARGs in pathogenic bacteria and their release into the environment by WWTPs threatens the public health. The current study investigated changes in ARGs' abundance in biological nutrient removal (BNR) processes and anaerobic digestion (AD) reactors of two WWTPs. Also, microbial community structure, which is known to shape the distribution and abundance of ARGs, was also analyzed. The relative abundance of eight ARGs (tetX, tetA, tetM, TEM, sul1, sul2, ermB and qnrD) was quantified as ARGs' copies/16 S rRNA gene copies using quantitative polymerase chain reaction (qPCR). Microbial community composition was assessed by 16 S rRNA microbiome sequencing analysis. TetX was prevalent among the eight ARGs, followed by TEM and sul1. However, its abundance was decreased in the AD sludges compared to BNR sludges. Proteobacteria was the major bacterial phylum found in all the sludge samples, while Arcobacter, 12up and Acidovorax were the predominant genera. Acinetobacter and Flavobacterium were significantly more abundant in the BNR sludges, while 12up and Aeromonas were predominant in AD sludges. Principal component analysis (PCA) revealed a clear difference in dominant ARGs and bacteria between the sludges in the processes of BNR and AD of the two WWTPs. Clinically relevant bacterial genera, Klebsiella and Enterococcus, found in both the BNR and AD sludges, were significantly correlated with the tetX gene. Throughout this study, the relationship between microbial communities and specific ARGs was revealed, illustrating that the composition of the microbial community could play a vital role in the abundance of ARGs. These results will better inform future studies aimed at controlling the spread of ARGs and their potential hosts from WWTPs.

Spatial and temporal effects of fish feed on antibiotic resistance in coastal aquaculture farms.

For the first time, both spatial and temporal effects of fish feed on changes in abundance of antibiotic resistance genes (ARGs) were investigated in South Korea via quantifying ARGs and analyzing physicochemical parameters in the influent (IN) and effluent before (BF) and 30 min after (AF) the fish feeding time of sixteen flow-through fish farms. The absolute abundance of ARGs in AF samples was 5 times higher than in BF and 12 times higher than in IN samples. Values of physicochemical parameters such as ammonia, total nitrogen, suspended solids and turbidity in the effluent significantly increased by 21.6, 4.2, 2.6 and 1.65 times, respectively, after fish feeding. Spatially, the fish farms on Jeju Island exhibited higher relative abundance (3.02 × 10-4 - 6.1 × 10-2) of ARGs compared to the farms in nearby Jeollanam-do (3.4 × 10-5 - 8.3 × 10-3). Seasonally, samples in summer and autumn showed a higher abundance of ARGs than in winter and spring. To assess risk to the food chain as well as public health, further studies are warranted to explore the pathogenic potential of these ARGs.

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.

Abundance and diversity of antibiotic resistance genes and bacterial communities in the western Pacific and Southern Oceans.

This study investigated the abundance and diversity of antibiotic resistance genes (ARGs) and the composition of bacterial communities along a transect covering the western Pacific Ocean (36°N) to the Southern Ocean (74°S) using the Korean icebreaker R/V Araon (total cruise distance: 14,942 km). The relative abundances of ARGs and bacteria were assessed with quantitative PCR and next generation sequencing, respectively. The absolute abundance of ARGs was 3.0 × 106 ± 1.6 × 106 copies/mL in the western Pacific Ocean, with the highest value (7.8 × 106 copies/mL) recorded at a station in the Tasman Sea (37°S). The absolute abundance of ARGs in the Southern Ocean was 1.8-fold lower than that in the western Pacific Ocean, and slightly increased (0.7-fold) toward Terra Nova Bay in Antarctica, possibly resulting from natural terrestrial sources or human activity. ß-Lactam and tetracycline resistance genes were dominant in all samples (88-99%), indicating that they are likely the key ARGs in the ocean. Correlation and network analysis showed that Bdellovibrionota, Bacteroidetes, Cyanobacteria, Margulisbacteria, and Proteobacteria were positively correlated with ARGs, suggesting that these bacteria are the most likely ARG carriers. This study highlights the latitudinal profile of ARG distribution in the open ocean system and provides insights that will help in monitoring emerging pollutants on a global scale.

Reduction of antibiotic resistome in influent of a wastewater treatment plant (WWTP) via a chemically enhanced primary treatment (CEPT) process.

Chemically enhanced primary treatment (CEPT) has been considered for maximizing wastewater energy recovery by enhancing the carbon captured through the primary treatment. However, evaluating the potential of CEPT as a primary treatment process for removing antibiotic resistance genes (ARGs) in the influent from a wastewater treatment plant (WWTP) has seldom been investigated. In this study, CEPT was conducted to assess simultaneous reduction of 13 major targeted ARGs and common pollutants in wastewater compared with primary sedimentation alone (non-CEPT). CEPT processes using three types of coagulants (PACl, FeCl3 and alum) effectively reduced absolute abundance of ARGs and intI1 in the influent from municipal WWTP. Average log-removal of absolute abundance of ARGs was achieved up to 1.77 ± 0.41 along with 90% turbidity reduction compared to non-CEPT. Through the simultaneous reduction of ARGs and intI1 genes during a CEPT process, ARGs proliferation may be limited directly through reduction of antibiotic resistant bacteria or indirectly through decreasing the possibility of horizontal gene transfer by intI1 removal. Reduction of ARGs and intI1 was improved by increasing coagulants' doses: abundances of residual ARGs under optimal dose conditions were similar, regardless of the different characteristics of coagulant types. The strongly positive correlation between reduction of turbidity/total phosphorus (T-P) and ARGs was explored, identifying that turbidity or T-P might be suitable indicators linked with variations in the abundance of ARGs during CEPT. As a result, CEPT may prove promising in efforts to control ARGs flowing into a WWTP.

Effect of type of coagulants on removal efficiency and removal mechanisms of antibiotic resistance genes in anaerobic digestion of primary sludge produced via a chemically enhanced primary treatment process.

The potential impact of the trivalent coagulant cations on the removal mechanisms, removal efficiencies and removal patterns of antibiotic resistance genes (ARGs) during anaerobic digestion (AD) of chemically enhanced primary treatment sludge (CEPTS) was investigated using polyaluminium chloride (PACl), ferric chloride (FeCl3) and mixed FeCl3-PACl. The removal efficiency of 23 ARGs and intI1 improved to 72.1% in AD of primary sludge with 100 mg/L FeCl3 and was lowest (only 54.4 %) in AD of primary sludge with 25 mg/L PACl. The removal of ARGs in AD of CEPTS with addition of single or mixed types of Al-based coagulant began to increase rapidly at the onset of batch operation. On the other hand, both the rapid increase in the removal efficiency of ARGs in AD with FeCl3 and the maximum removal efficiency were attained later than in the other ADs.

Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models.

Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model for biogas prediction is developed using deep learning (DL). We propose a hybrid DL architecture, i.e., DA-LSTM-VSN, wherein a dual-stage-attention (DA)-based long short-term memory (LSTM) network is integrated with variable selection networks (VSNs). To enhance the model predictability, we perform hyperparameter optimization. The model accuracy is validated using long-term AcoD monitoring data measured over two years of municipal wastewater treatment plant operation and then compared with those of two other DL-based models (i.e., DA-LSTM and the standard LSTM). In addition, the feature importance (FI) is analyzed to investigate the relative contribution of input variables to biogas production prediction. Finally, we demonstrate the successful application of the validated DL model to the AcoD process optimization. Results show that the model accuracy improved significantly by incorporating DA into LSTM, i.e., the coefficient of determination (R2) increased from 0.38 to 0.68; however, the R2 can be further increased to 0.76 by combining DA-LSTM with a VSN. For the biogas prediction of the AcoD model, the VSN contributes significantly by employing the discontinuous time series of measurement data on biodegradable organic-associated variables during AcoD. In addition, the VSN allows the AcoD model to be interpretable via FI analysis using its weighted input features. The FI results show that the relative importance is vital to variables associated with food waste leachate, whereas it is marginal for those associated with the primary and chemically assisted sedimentation sludges. In conclusion, the AcoD model proposed herein can be utilized in practical applications as a robust tool because it can provide the optimal sludge conditions to improve biogas production. This is because it facilitates the time-series biogas prediction at the full scale using unprocessed datasets with either missing value imputation or outlier removal.

Temporal triggers of N2O emissions during cyclical and seasonal variations of a full-scale sequencing batch reactor treating municipal wastewater.

To investigate the major triggers of nitrous oxide (N2O) production in a full-scale wastewater treatment plant, N2O emissions and wastewater characteristics (ammonia, nitrite, nitrate, total nitrogen, dissolved inorganic carbon, dissolved organic carbon, pH, temperature, dissolved oxygen and specific oxygen uptake rate), the results of variations in the cycling of a sequential batch reactor (SBR, where only full nitrification was performed), were monitored seasonally for 16 months. Major triggers of N2O production were investigated based on a seasonal measured database using a random forest (RF) model and sensitivity analysis, which was applied to identify important input variables. As the result of seasonal monitoring in the full-scale SBR, the N2O emission factor relative to daily total nitrogen removal ranged from 0.05 to 2.68%, corresponding to a range of N2O production rate from 0.02 to 0.70 kg-N/day. Results from the RF model and sensitivity analysis revealed that emissions during nitrification were directly or indirectly related to nitrite accumulation, temperature, ammonia loading rate and the specific oxygen uptake rate ratio between ammonia oxidizing bacteria and nitrite oxidizing bacteria (sOUR-ratio). However, changes in the microbial community did not significantly impact N2O emissions. Based on these results, the sOUR-ratio could represent the major trigger for N2O emission in a full-scale BNR system: a higher sOUR-ratio value with an average of 3.13 ± 0.23 was linked to a higher N2O production rate with an average value of 1.27 ± 0.12 kg-N/day (corresponding to 3.96 ± 1.20% of N2O emission factor relative to daily TN removal), while a lower sOUR-ratio with an average value of 2.39 ± 0.27 was correlated with a lower N2O production average rate of 0.17 ± 0.11 kg-N/day (corresponding to 0.74 ± 0.69% of N2O emission factor) (p-value = 0.00001, Mann-Whitney test).

Effects of biological pretreatments of microalgae on hydrolysis, biomethane potential and microbial community.

Parameters of temperature-phased anaerobic digestion (TPAD) were varied to study their effects on hydrolysis, biomethane potential (BMP), and microbial diversity of microalgae biodegradation. Anaerobic pretreatments at 85 °C demonstrated the release of soluble carbohydrate and protein molecules under low microbial metabolic activity. However, at 55 °C, anaerobic pretreatments showed superior performance in methane yield, nutrient release, and volatile fatty acids (VFAs) production due to dominant Clostridium. Furthermore, the highest destruction of volatile solids (VS) was observed during aerobic pretreatments at 55 °C under the influence of various quantities of these genera - Luteimonas, Symbiobacterium, Soehngenia, Thermobacillus, and Ureibacillus. Statistical analysis revealed that hydrolysis and BMP were not correlated. However, soluble nitrogen and phosphorous showed strong correlation with methane (r = 0.623 and 0.948, respectively) under thermo-anaerobic pretreatment, while VS removal and concentrations of acetic and butyric acids and lipids were positively correlated with each other under thermo-aerobic pretreatment.

Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models.

Antibiotic resistance genes (ARGs) have been reported to threaten the public health of beachgoers worldwide. Although ARG monitoring and beach guidelines are necessary, substantial efforts are required for ARG sampling and analysis. Accordingly, in this study, we predicted ARGs occurrence that are primarily found on the coast after rainfall using a conventional long short-term memory (LSTM), LSTM-convolutional neural network (CNN) hybrid model, and input attention (IA)-LSTM. To develop the models, 10 categories of environmental data collected at 30-min intervals and concentration data of 4 types of major ARGs (i.e., aac(6'-Ib-cr), blaTEM, sul1, and tetX) obtained at the Gwangalli Beach in South Korea, between 2018 and 2019 were used. When individually predicting ARGs occurrence, the conventional LSTM and IA-LSTM exhibited poor R2 values during training and testing. In contrast, the LSTM-CNN exhibited a 2-6-times improvement in accuracy over those of the conventional LSTM and IA-LSTM. However, when predicting all ARGs occurrence simultaneously, the IA-LSTM model exhibited a superior performance overall compared to that of LSTM-CNN. Additionally, the influence of environmental variables on prediction was investigated using the IA-LSTM model, and the ranges of input variables that affect each ARG were identified. Consequently, this study demonstrated the possibility of predicting the occurrence and distribution of major ARGs at the beach based on various environmental variables, and the results are expected to contribute to management of ARG occurrence at a recreational beach.

Hydrometeorological Influence on Antibiotic-Resistance Genes (ARGs) and Bacterial Community at a Recreational Beach in Korea.

We investigated the occurrence and distribution of antibiotic-resistance genes (ARGs) and the composition of a bacterial community under conditions of rainfall on a recreational beach in Korea. Seawater samples, collected every 1‒5 hours in June 2018 and May 2019, were analyzed using quantitative real-time polymerase chain reaction and next-generation sequencing. We found a substantial influence of rainfall and tidal levels on the relative abundance of total ARGs and bacterial operational taxonomic units (OTUs), which showed 1.9 × 103 and 1.1 × 101 fold increases, respectively. In particular, the elevated levels of ARGs were maintained for up to 32 hours after rainfall. An increased abundance of sewage-related ARGs and bacterial OTUs suggested that combined sewer overflow (CSO) may be the major factor contributing to the increase in the number and diversity of ARGs and related bacterial communities. Network analysis of ARGs and OTUs indicated that, at the genus level, Acinetobacter, Pseudomonas, and Prevotella were the main potential pathogens carrying the observed ARGs in the recreational seawater. Overall, these findings highlight the potential threat to public health on beaches, and indicate the requirement for more adequate monitoring, with greater efforts to mitigate the propagation of ARGs arising from CSOs.

Designing a marine outfall to reduce microbial risk on a recreational beach: Field experiment and modeling.

A marine outfall can be a wastewater management system that discharges sewage and stormwater into the sea; hence, it is a source of microbial pollution on recreational beaches, including antibiotic resistant genes (ARGs), which lead to an increase in untreatable diseases. In this regard, a marine outfall must be efficiently located to mitigate these risks. This study aimed to 1) investigate the spatiotemporal variability of Escherichia coli (E. coli) and ARGs on a recreational beach and 2) design marine outfalls to reduce microbial risks. For this purpose, E. coli and ARGs with influential environmental variables were intensively monitored on Gwangalli beach, South Korea in this study. Environmental fluid dynamic code (EFDC) was used and calibrated using the monitoring data, and 12 outfall extension scenarios were explored (6 locations at 2 depths). The results revealed that repositioning the marine outfall can significantly reduce the concentrations of E. coli and ARGs on the beach by 46-99%. Offshore extended outfalls at the bottom of the sea reduced concentrations of E. coli and ARGs on the beach more effectively than onshore outfalls at the sea surface. These findings could be helpful in establishing microbial pollution management plans at recreational beaches in the future.

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

This study focus on the fate of ARGs in the full-scale AD of food wastewater (FWW). Residue was collected from two different full-scale thermophilic AD treating FWW. Ten selected ARGs, including tetracycline resistance genes (tetM, tetX, tetQ, tetH and tetG), sulfonamide resistance genes (sul1 and sul2), quinolone resistance genes (qnrD) and macrolide resistance genes (ermB and ermC), were amplified using quantitative polymerase chain reaction (qPCR). Furthermore, the class 1 integron-integrase gene (intI1) was selected as a representative mobile gene element. Remarkable reduction in the ARGs and intI1 was observed in two-stage (acidogenic-methanogenic) AD, particularly, tetG, tetH, tetM, tetQ, tetX and intI1 not detected. Additionally, significant positive correlation (p < 0.01) between ARGs and intI1 suggested a strong likelihood of horizontal gene transfer (HGT). Furthermore, stepwise multiple linear regression analysis revealed significant factors related to the fate of individual ARGs and intI1 during AD.

Determining the composition of bacterial community and relative abundance of specific antibiotics resistance genes via thermophilic anaerobic digestion of sewage sludge.

In this study, the effects of different temperature transitions on the dynamics of antibiotic resistance genes (ARGs) and bacterial community were investigated during start-up of thermophilic anaerobic digestion (AD) of sewage sludge. Although two thermophilic reactors showed dissimilar removal efficiencies of ARGs in batch mode, both the removal efficiency and reduction patterns of ARGs were similar in continuous stirred tank reactor (CSTR) mode, resulting in significant reduction of the total sum of the relative abundance of ARGs. Using network analysis to explore the correlation between bacterial community and some specific ARGs revealed that composition of the bacterial community played a vital role in the fluctuations in the relative abundance of the antibiotic resistome, demonstrating that shaping the development of ARGs was facilitated by vertical gene transfer. To facilitate eliminating ARGs, minimizing their hosts which persist even under long-term operations is vital in thermophilic AD.

Reducing food waste in residential complexes using a pilot-scale on-site system.

A pilot-scale on-site system combining biological treatment and a drying stage was applied to achieve mass reduction of food waste (FW) at an urban residential complex. The effectiveness of biodegrading the organic portion of FW via microorganisms existing in FW improved by 38.80% by controlling rates of FW loading and air-flow. In one stage of the on-site biological treatment, the major bacterial community was identified to be mesophilic and facultative; Lactobacillus was the most dominant genus, accounting for 78.1% of bacterial community. Total mass reduction of FW approached 90.15% by increasing removal of both moisture and the organic portion of FW. In addition, the solids and liquids of the final by-products have the potential to be recycled into resources such as fertilizer, a bio-solid refuse fuel or external carbon sources for wastewater treatment plants. The proposed decentralized system offers practical and environmental approaches for FW management in residential complexes.

Thermophilic anaerobic digestion: Effect of start-up strategies on performance and microbial community.

Effects of two different start-up methods were compared during conversion from mesophilic to thermophilic anaerobic digestion of sewage sludge. During the batch operation, a transient increase in both total bacterial concentration and relative abundance of thermophilic bacteria in R1 (a one-step increase method) resulted in 34% higher volatile solids (VS) removal efficiency by R1 compared to R2 (a step-wise increase method). Meanwhile, higher total archaeal concentration and increased relative abundance of thermophilic archaea in R2 were attributed to 65% higher methane production by R2 compared to R1. The same trends for VS removal and methane production were observed during the subsequent continuous mode, although the microbial composition of the two reactors became similar. These findings may prove helpful for determining the preferred start-up method for thermophilic anaerobic digestion: a one-step method can be proposed for higher VS removal efficiency, or a step-wise method can be selected for enhanced methane production.

Additional reduction of antibiotic resistance genes and human bacterial pathogens via thermophilic aerobic digestion of anaerobically digested sludge.

Thermophilic aerobic digestion (TAD) was applied to further reduce ARGs and heavy metal resistance genes (HMRGs) as well as class 1 integrons (intI1) in sludge from anaerobic digestion (AnD). Unlike after AnD, there was no enrichment of ARGs, HMRGs and intI1 after TAD. Residual gene fractions of intI1 and total ARGs (sum of targeted ARGs) were 0.03 and 0.08, respectively. Two kinetic models (Collins-Selleck and first-order) described the decay patterns of targeted genes, revealing rapid removal of intI1 during TAD. After TAD, the relative abundance of human bacterial pathogens (HBPs) and the numbers of HBPs species decreased to approximately 68% and 64% compared to anaerobically digested sludge, respectively. Thus, TAD, subsequent to AnD, may possess high potential for reducing biological risks resulting from ARGs, HMRGs, intI1 and HBPs in sewage sludge.

Response of antibiotic and heavy metal resistance genes to two different temperature sequences in anaerobic digestion of waste activated sludge.

Response of antibiotic resistance genes (ARGs) and heavy metal resistance genes (HMRGs) to two different temperature sequences (i.e., mesophilic-thermophilic and thermophilic-mesophilic) were investigated. Higher removal of total ARGs (twenty-one targeted subtypes) and HMRGs (three targeted subtypes) was achieved by the mesophilic-thermophilic sequence than by the thermophilic-mesophilic sequence. The sequence of mesophilic-thermophilic showed the highest removal of total ARGs, but the sequence of thermophilic-mesophilic proved more suitable for removal of class 1 integrons (intI1). Correlation analysis indicated that intI1 correlated significantly with tetG, tetQ, tetX, sul2, aac(6')-lb-cr, blaTEM, ermB and floR. High-throughput sequencing revealed that the mesophilic-thermophilic sequence TPAD removed more human bacterial pathogens (HBPs) than did the thermophilic-mesophilic sequence. Also, significantly positive correlation was observed between ARGs and HBPs. For instance, Mycoplasma pneumonia showed significantly positive correlation with several ARGs including tetE, tetQ, tetX, tetZ, sul1, sul2, aac(6')-lb-cr and floR.

Fate of antibiotic resistance genes and metal resistance genes during thermophilic aerobic digestion of sewage sludge.

This study examines the fate of twenty-three representative antibiotic resistance genes (ARGs) encoding tetracyclines, sulfonamides, quinolones, ß-lactam antibiotics, macrolides, florfenicol and multidrug resistance during thermophilic aerobic digestion (TAD) of sewage sludge. The bacterial community, class 1 integrons (intI1) and four metal resistance genes (MRGs) were also quantified to determine the key drivers of changes in ARGs during TAD. At the end of digestion, significant decreases in the quantities of ARGs, MRGs and intI1 as well as 16S rRNA genes were observed. Partial redundancy analysis (RDA) showed that shifts in temperature were the key factors affecting a decrease in ARGs. Shifts in temperature led to decreased amounts of ARGs by reducing resistome and bacterial diversity, rather than by lowering horizontal transfer potential via intI1 or co-resistance via MRGs.