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

Livestock and poultry breeding farms as a fixed and underestimated source of antibiotic resistance genes

The excessive use of antibiotics, disinfectants, and drugs in livestock and poultry breeding has resulted in a rise in the presence of antibiotic resistance genes (ARGs). Antibiotic-resistant bacteria (ARB) and ARGs have been widely found in animal feces, farm wastewater, and farm air. ARGs can not only spread across media through adsorption and migration, but also transfer resistance across bacterial genera through horizontal gene transfer. Livestock breeding has become a fixed and unavoidable source of ARGs in the environment. Existing technologies for controlling ARGs, such as composting, disinfection, and sewage treatment, are not efficient in removing ARB and ARGs from waste. Furthermore, the remaining ARGs still possess a strong capacity for dissemination. At present, antibiotics used in animal husbandry are difficult to replace in a short period of time. The growth and potential risks of resistance genes in livestock and poultry breeding sources in the receiving environment are not yet clear. In this paper, we summarize the current situation of ARGs in the livestock and poultry breeding environment. We also explain the key environmental processes, main influencing factors, and corresponding ecological risks associated with ARGs in this environment. The advantages and disadvantages of current technologies for the removal of ARGs are primarily discussed. There is a particular emphasis on clarifying the spatiotemporal evolution patterns and environmental process mechanisms of ARGs, as well as highlighting the importance and urgency of developing efficient pollution control technologies.

Dynamics of antibiotic resistance genes in the sediments of a water-diversion lake and its human exposure risk behaviour

The dynamics and exposure risk behaviours of antibiotic resistance genes (ARGs) in the sediments of water-diversion lakes remain poorly understood. In this study, spatiotemporal investigations of ARG profiles in sediments targeting non-water (NWDP) and water diversion periods (WDP) were conducted in Luoma Lake, a typical water-diversion lake, and an innovative dynamics-based risk assessment framework was constructed to evaluate ARG exposure risks to local residents. ARGs in sediments were significantly more abundant in the WDP than in the NWDP, but there was no significant variation in their spatial distribution in either period. Moreover, the pattern of ARG dissemination in sediments was unchanged between the WDP and NWDP, with horizontal gene transfer (HGT) and vertical gene transfer (VGT) contributing to ARG dissemination in both periods. However, water diversion altered the pattern in lake water, with HGT and VGT in the NWDP but only HGT in the WDP, which were critical pathways for the dissemination of ARGs. The significantly lower ARG sediment-water partition coefficient in the WDP indicated that water diversion could shift the fate of ARGs and facilitate their aqueous partitioning. Risk assessment showed that all age groups faced a higher human exposure risk of ARGs (HERA) in the WDP than in the NWDP, with the 45-59 age group having the highest risk. Furthermore, HERA increased overall with the bacterial carrying capacity in the local environment and peaked when the carrying capacity reached three (NWDP) or four (WDP) orders of magnitude higher than the observed bacterial population. HGT and VGT promoted, whereas ODF covering gene mutation and loss mainly reduced HERA in the lake. As the carrying capacity increased, the relative contribution of ODF to HERA remained relatively stable, whereas the dominant mechanism of HERA development shifted from HGT to VGT.

Variations in antibiotic resistomes associated with archaeal, bacterial, and viral communities affected by integrated rice-fish farming in the paddy field ecosystem

Antibiotic resistance genes (ARGs) serving as a newly recognized pollutant that poses potential risks to global human health, which in the paddy soil can be potentially altered by different agricultural production patterns. To elucidate the impacts and mechanisms of the widely used and sustainable agricultural production pattern, namely integrated rice-fish farming, on the antibiotic resistomes, we applied metagenomic sequencing to assess ARGs, mobile genetic elements (MGEs), bacteria, archaea, and viruses in paddy soil. There were 20 types and 359 subtypes of ARGs identified in paddy soil. The integrated rice-fish farming reduced the ARG and MGE diversities and the abundances of dominant ARGs and MGEs. Significantly decreased ARGs were mainly antibiotic deactivation and regulator types and primarily ranked level IV based on their potential threat to human health. The integrated rice-fish farming decreased the alpha diversities and altered microbial community compositions. MGEs, bacteria, archaea, and virus exhibited significant correlations with ARGs, while integrated rice-fish farming effectively changed their interrelationships. Viruses, bacteria, and MGEs played crucial roles in affecting the ARGs by the integrated rice-fish farming. The most crucial pathway by which integrated rice-fish farming affected ARGs was through the modulation of viral communities, thereby directly or indirectly influencing ARG abundance. Our research contributed to the control and restoration of ARGs pollution from a new perspective and providing theoretical support for the development of clean and sustainable agricultural production.

Metagenomic evidence for antibiotic-associated actinomycetes in the Karamay Gobi region

Due to the misuse of antibiotics, there is an increasing emergence and spread of multidrug-resistant (MDR) bacteria, leading to a human health crisis. To address clinical antibiotic resistance and prevent/control pathogenic microorganisms, the development of novel antibiotics is essential. This also offers a new approach to discovering valuable actinobacterial flora capable of producing natural bioactive products. In this study, we employed bioinformatics and macro-genome sequencing to collect 15 soil samples from three different locations in the Karamay Gobi region. First, we assessed the diversity of microorganisms in soil samples from different locations, analyzing the content of bacteria, archaea, actinomycetes, and fungi. The biodiversity of soil samples from outside the Gobi was found to be higher than that of soil samples from within and in the center of the Gobi. Second, through microbial interaction network analysis, we identified actinomycetes as the dominant group in the system. We have identified the top four antibiotic genes, such as Ecol_fabG_TRC, Efac_liaR_DAP, tetA (58), and macB, by CARD. These genes are associated with peptide antibiotics, disinfecting agents and antiseptics, tetracycline antibiotics, and macrolide antibiotics. In addition, we also obtained 40 other antibiotic-related genes through CARD alignment. Through in-depth analysis of desert soil samples, we identified several unstudied microbial species belonging to different families, including Erythrobacteriaceae, Solirubrobacterales, Thermoleophilaceae, Gaiellaceae, Nocardioidaceae, Actinomycetia, Egibacteraceae, and Acidimicrobiales. These species have the capability to produce peptide antibiotics, macrolide antibiotics, and tetracycline antibiotics, as well as disinfectants and preservatives. This study provides valuable theoretical support for future in-depth research.

Effects of the coexistence of antibiotics and heavy metals on the fate of antibiotic resistance genes in chicken manure and surrounding soils

Both heavy metals and antibiotics exert selection pressure on bacterial resistance, and as they are commonly co-contaminated in the environment, they may play a larger role in bacterial resistance. This study examined how breeding cycles affect antibiotic resistance genes (ARGs) in chicken manure and the surrounding topsoils at 20, 50, 100, 200, and 300 m from twelve typical laying hen farms in the Ningxia Hui Autonomous Region of northwest China. Six antibiotics, seven heavy metals, ten mobile genetic elements (MGEs), and microbial community affected the ARGs profile in chicken dung and soil samples. Tetracycline antibiotic residues were prevalent in chicken manure, as were relatively high content of aureomycin during each culture period. Zinc (Zn) content was highest among the seven heavy metals in chicken feces. Chicken dung also enriched aminoglycosides, MLSB, and tetracycline ARGs, notably during brooding and high production. The farm had a minimal influence on antibiotics in the surrounding soil, but its effect on ARGs and MGEs closer to the farm (50 m) was stronger, and several ARGs and MGEs increased with distance. Manure microbial composition differed dramatically throughout breeding cycles and sampling distances. ARGs were more strongly related with antibiotics and heavy metals in manure than soil, whereas MGEs were the reverse. Antibiotics, heavy metals, MGEs, and bacteria in manure accounted 12.28%, 22.25%, 0.74%, and 0.19% of ARGs composition variance, respectively, according to RDA and VPA. Bacteria (2.89%) and MGEs (2.82%) only affected soil ARGs composition. These findings showed that heavy metals and antibiotics are the main factors affecting faecal ARGs and bacteria and MGEs soil ARGs. This paper includes antibiotic resistance data for large-scale laying hen husbandry in northwest China and a theoretical framework for decreasing antibiotic resistance.

Antimicrobial resistome and mobilome in the urban river affected by combined sewer overflows and wastewater treatment effluent

The dissemination of antimicrobial resistance in the environment is an emerging global health problem. Wastewater treatment effluent and combined sewer overflows (CSOs) are major sources of antimicrobial resistance in urban rivers. This study aimed to clarify the effect of municipal wastewater treatment effluent and CSO on antimicrobial resistance genes (ARGs), mobile gene elements, and the microbial community in an urban river. The ARG abundance per 16S-based microbial population in the target river was 0.37-0.54 and 0.030-0.097 during the CSO event and dry weather, respectively. During the CSO event, the antimicrobial resistome in the river shifted toward a higher abundance of ARGs to clinically important drug classes, including macrolide, fluoroquinolone, and β-lactam, whereas ARGs to sulfonamide and multidrug by efflux pump were relatively abundant in dry weather. The abundance of intI1 and tnpA genes were highly associated with the total ARG abundance, suggesting their potential application as an indicator for estimating resistome contamination. Increase of prophage during the CSO event suggested that impact of CSO has a greater potential for horizontal gene transfer (HGT) via transduction. Consequently, CSO not only increases the abundance of ARGs to clinically important antimicrobials but also possibly enhances potential of HGT in urban rivers.

Response of prokaryotic, eukaryotic and algal communities to heavy rainfall in a reservoir supplied with reclaimed water

The global climate change made the heavy rainfall happen more frequently, and the non-point source pollution caused by it would exacerbate the risk to the water ecological environment. In this study, we took a reservoir (Shahe reservoir, Beijing, China) supplied with reclaimed water as an exapmle to investigate how spatiotemporal changes in the quantity and diversity of prokaryotic, eukaryotic, and algal communities respond to heavy rainfall. Results showed that heavy rainfall could directly impact the composition of the prokaryotic community by introducing amounts of runoff closely associated bacterium especially for the human potential pathogens such as Aliarcobacter, Aeromonas and Pseudomonas in the Shahe reservoir area. While the eukaryotic community was rather stable, and the development and changes in algal communities occurred in the last few days after heavy rainfall. The microbial source tracking through FEAST indicated that Nansha river (S) was the major contributor to the development of all the three concerned communities in the reservoir. The co-occurrence analysis showed that the modules with the highest cumulative abundance in each community were all strongly and positively connected with Chl-a, pH, turbidity, COD and TOC, but negatively correlated with NO₃-N (p < 0.01). The network analysis showed that the eukaryotes played a key role in the interaction network among the three communities, and were more likely to interact with algae and prokaryotes. It was suggested that the controlling of human potential pathogens associated with prokaryotic community should be emphasized at the beginning of the heavy rainfall, but the prevention of the eutrophication bloom should be another focus after the heavy rainfall. This study provided valuable information concerning the role of heavy rainfall on the water ecological environment from the perspective of microbial community.

Metagenomic analysis reveals patterns and hosts of antibiotic resistance in different pig farms

In actual production environments, antibiotic-resistant genes (ARGs) are abundant in pig manure, which can form transmission chains through animals, the environment, and humans, thereby threatening human health. Therefore, based on metagenomic analysis methods, ARGs and mobile genetic elements (MGEs) were annotated in pig manure samples from 6 pig farms in 3 regions of Shanxi Province, and the potential hosts of ARGs were analyzed. The results showed that a total of 14 ARG types were detected, including 182 ARG subtypes, among which tetracycline, phenol, aminoglycoside, and macrolide resistance genes were the main ones. ARG profiles, MGE composition, and microbial communities were significantly different in different regions as well as between different pig farms. In addition, Anaerobutyricum, Butyrivibrio, and Turicibacter were significantly associated with multiple ARGs, and bacteria such as Prevotella, Bacteroides, and the family Oscillospiraceae carried multiple ARGs, suggesting that these bacteria are potential ARG hosts in pig manure. Procrustes analysis showed that bacterial communities and MGEs were significantly correlated with ARG profiles. Variation partitioning analysis results indicated that the combined effect of MGEs and bacterial communities accounted for 64.08% of resistance variation and played an important role in ARG profiles. These findings contribute to our understanding of the dissemination and persistence of ARGs in actual production settings, and offer some guidance for the prevention and control of ARGs contamination.

Characteristics of antibiotic resistance gene distribution in rainfall runoff and combined sewer overflow

Rainfall runoff and combined sewer overflow (CSO) converge with organic waste, nutrients, and microbes from the ground and wastewater. These pollutants promote the spread and transformation of antibiotic resistance genes (ARGs). In this study, four rainfall runoff and one CSO outfall were chosen, and samples were collected to explore the occurrence and distribution of ARGs. The ARGs were extracted from suspended solids and analyzed using metagenomic sequencing. A total of 888 ARG subtypes, belonging to 17 ARG types, were detected in all samples. Eleven ARG types were shared by all the samples. Multidrug resistance genes had the highest relative abundance. Their total relative abundance reached 1.07 ratio (ARG copy number/16S rRNA gene copy number) and comprised 46.6% of all the ARGs. In all samples, the CSO outfall had the highest total relative abundance (8.25 × 10^-1 ratio) of ARGs, with a ratio ranging ND (not detected)-3.78 × 10^-1 ratio. Furthermore, the relationship between ARG types and environmental factors was determined using redundancy analysis. The results showed that chemical organic demand (COD) and bacterial abundance were positively correlated with most ARG types, including multidrug, bacitracin, aminoglycoside, β-lactam, tetracycline, and sulfonamide. NH₃-N, TN, and TP were positively correlated with rifamycin, fosmidomycin, and vancomycin resistance genes. The relationship among the ARG subtypes was investigated using network analyses. The multidrug resistance gene subtypes had the highest frequency of co-occurrence. This study provides insights into the occurrence and distribution of ARGs under non-point source pollution and may contribute to the control of ARGs.

Molluscs-A ticking microbial bomb

Bivalve shellfish consumption (ark shells, clams, cockles, and oysters) has increased over the last decades. Following this trend, infectious disease outbreaks associated with their consumption have been reported more frequently. Molluscs are a diverse group of organisms found wild and farmed. They are common on our tables, but unfortunately, despite their great taste, they can also pose a threat as a potential vector for numerous species of pathogenic microorganisms. Clams, in particular, might be filled with pathogens because of their filter-feeding diet. This specific way of feeding favors the accumulation of excessive amounts of pathogenic microorganisms like Vibrio spp., including Vibrio cholerae and V. parahaemolyticus, Pseudomonas aeruginosa, Escherichia coli, Arcobacter spp., and fecal coliforms, and intestinal enterococci. The problems of pathogen dissemination and disease outbreaks caused by exogenous bacteria in many geographical regions quickly became an unwanted effect of globalized food supply chains, global climate change, and natural pathogen transmission dynamics. Moreover, some pathogens like Shewanella spp., with high zoonotic potential, are spreading worldwide along with food transport. These bacteria, contained in food, are also responsible for the potential transmission of antibiotic-resistance genes to species belonging to the human microbiota. Finally, they end up in wastewater, thus colonizing new areas, which enables them to introduce new antibiotic-resistance genes (ARG) into the environment and extend the existing spectrum of ARGs already present in local biomes. Foodborne pathogens require modern methods of detection. Similarly, detecting ARGs is necessary to prevent resistance dissemination in new environments, thus preventing future outbreaks, which could threaten associated consumers and workers in the food processing industry.

Class 1 integron and related antimicrobial resistance gene dynamics along a complex freshwater system affected by different anthropogenic pressures

The risk for human health posed by polluted aquatic environments, and especially those carrying antibiotic resistance genes (ARGs) of clinical interest, is still debated. This is because of our limited knowledge of the dynamics of antimicrobial resistance in the environment, the selection mechanisms underlying the spread of ARGs, and the ecological factors potentially favoring their return to humans. The Class 1 integron is one of the most effective platforms for the dissemination of ARGs. In this study we investigated a freshwater system consisting of a lake-river-lake continuum, determining the abundance of class 1 integrons and their associated ARGs by a modulated metagenomic approach. Bacterial abundance and community composition were used to identify the potential carriers of class 1 integrons and their associated ARGs over a period of six months. Class 1 integrons and their ARG cargoes were significantly more abundant in riverine sampling sites receiving treated wastewater. Further, class 1 integrons carried ARGs ranked at the highest risk for human health (e.g., catB genes), in particular, genes encoding resistance to aminoglycosides. Genera of potential pathogens, such as Pseudomonas and Escherichia-Shigella, were correlated with class 1 integrons. The lake-river-lake system demonstrated a clear relationship between the integrase gene of class 1 integrons (intI1) and anthropogenic impact, but also a strong environmental filtering that favored the elimination of intI1 once the human derived stressors were reduced. Overall, the results of this study underline the role class 1 integrons as proxy of anthropogenic pollution and suggest this genetic platform as an important driver of aminoglycoside resistance genes, including high risk ARGs, of potential concern for human health.

The source, fate and prospect of antibiotic resistance genes in soil: A review

Antibiotic resistance genes (ARGs), environmental pollutants of emerging concern, have posed a potential threat to the public health. Soil is one of the huge reservoirs and propagation hotspot of ARGs. To alleviate the potential risk of ARGs, it is necessary to figure out the source and fate of ARGs in the soil. This paper mainly reviewed recent studies on the association of ARGs with the microbiome and the transmission mechanism of ARGs in soil. The compositions and abundance of ARGs can be changed by modulating microbiome, soil physicochemical properties, such as pH and moisture. The relationships of ARGs with antibiotics, heavy metals, polycyclic aromatic hydrocarbons and pesticides were discussed in this review. Among the various factors mentioned above, microbial community structure, mobile genetic elements, pH and heavy metals have a relatively more important impact on ARGs profiles. Moreover, human health could be impacted by soil ARGs through plants and animals. Understanding the dynamic changes of ARGs with influencing factors promotes us to develop strategies for mitigating the occurrence and dissemination of ARGs to reduce health risks.

Metagenomic insights into the antibiotic resistome in freshwater and seawater from an Antarctic ice-free area

The comprehensive profiles of antibiotic resistance genes (ARGs) in the Antarctic water environments and their potential health risks are not well understood. The present study characterized the bacterial community compositions and ARG profiles of freshwater (11 samples) and seawater (28 samples) around the Fildes Region (an ice-free area in Antarctica) using a shotgun metagenomic sequencing approach for the first time. There were significant differences in the compositions of the bacterial community and ARG profiles between freshwater and seawater. In the 39 water samples, 114 ARG subtypes belonging to 15 ARG types were detectable. In freshwater, the dominant ARGs were related to multidrug and rifamycin resistance. In seawater, the dominant ARGs were related to peptide, multidrug, and beta-lactam resistance. Both the bacterial community compositions and ARG profiles were significantly related to certain physicochemical properties (e.g., pH, salinity, NO₃^-). Procrustes analysis revealed a significant correlation between the bacterial community compositions and ARG profiles of freshwater and seawater samples. A total of 31 metagenome-assembled genomes (MAGs) carrying 35 ARG subtypes were obtained and identified. The results will contribute to a better evaluation of the ARG contamination in relation to human health in the Antarctic aquatic environments.

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. β-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.

Metagenomics insights into the profiles of antibiotic resistome in combined sewage overflows from reads to metagenome assembly genomes

Combined sewage overflows (CSOs) have become an important source of antibiotic resistance genes (ARGs) in the environment, while the distribution and dynamics of antibiotic resistome in the CSOs events have not been well understood. This study deciphered the profiles of antibiotic resitome in the CSOs based on metagenomics analysis from reads to metagenome assembly genomes (MAGs), and the dynamical changes of ARGs were clarified through continuous monitoring of the CSO event. Results showed that antibiotic inactivation was the dominant resistance mechanism, and sulfonamide, aminoglycoside along with multidrug resistance were the dominant antibiotic resistance types. It was speculated that the antibiotic resistome were generally determined by sewer sediment flushed out along with the CSOs not domestic sewage in the pipes. The host range and mobility of the antibiotic resistome were determined at contigs level, and the hosts mainly belonged to the Proteobacteria with the genus of Pseudomonas, Escherichia, Enterobacter and Aeromonas being dominant. The transposase (tnpA), IS91 and integrons were mobile genetic elements (MGEs) located together with ARGs, and a MAG carrying 32 ARGs and 140 VFGs was assembled. Although microbial community contributed most to the changes of antibiotic resistome in the CSOs directly, the risks caused by the MGEs should be paid more attention.

Analysis of micropollutants in a marine outfall using network analysis and decision tree

The presence of micropollutants (MPs), including pharmaceutical, industrial, and pesticidal compounds, threatens both human health and the aquatic ecosystem. The development and extensive use of new chemicals have also inevitably led to the accumulation of MPs in aquatic environments. Recreational beaches are especially vulnerable to contamination, affecting humans and aquatic animals via the absorption of MPs in water during marine activities (e.g., swimming, sailing, and windsurfing). Additionally, marine outfalls in an urbanized coastal city can cause serious chemical and microbial pollution on recreational beaches, leading to an increase in adverse effects on public health and the ecological system. Therefore, the aim of this study was to, with the use of network and decision tree analyses, identify the features and factors that influence the change in MP concentrations in a marine outfall. These analyses were conducted to inspect the relationship between each MP and its hierarchical structure as well as hydrometeorological variables. Additionally, a risk analysis was conducted in this study in which the MPs were prioritized based on their optimized risk quotient values. During our monitoring of MP concentrations over time at the marine outfall, high concentrations of pharmaceutical and industrial compounds were detected when the tide level was low after rainfall. Furthermore, results of the risk analysis and the prioritization revealed that a total of 18 substances identified in our study posed a risk to the ecosystem; these include major ecotoxicologically hazardous substances such as telmisartan, mevinphos, and methiocarb. Results of the network analysis demonstrated distinct trends for pharmaceutical and industrial substances, whilst those for pesticide compounds were irregular. Additionally, the hierarchical structures for most MPs consisted of rainfall, tide level, and antecedent dry hours; this implies that these factors influence MP dynamics. These findings will be helpful for establishing chemical contamination management plans for recreational beaches in the future.

Tropical cyclone effects on water and sediment chemistry and the microbial community in estuarine ecosystems

Frequent and intense storm disturbances can have widespread and strong effects on the nitrogen and iron cycles and their associated microbial communities in estuary systems. A three-year investigation was conducted in the Pearl River and Zhanjiang estuaries in Guangdong Province, China through repeated sampling at three timepoints, defined as pre-storm (<1 month before storm), post-storm (<1 month after storm), and non-storm (6-8 months after storm). Increased nutrient concentrations (total organic carbon, nitrate, nitrite, ammonium, and sulfate) in both the sediment and water column were observed immediately after storm. The microbial community experienced extensive and immediate changes determined by an observed composition shift in the nitrogen and iron-cycling microbiomes. Analysis of sediment samples displayed a shift from nitrogen-to sulfur-cycling microorganisms and an increase in microbial interactions that were not observed in the water column. The chemical profile and microbial community components both returned to baseline conditions 6-8 months following storm disturbance. Finally, significant correlations were found between chemical and microbial data, suggesting that niche-sharing microbes may respond similarly to stimuli that impact their ecosystem. Increases in nutrient availability can favor the abundance of specific taxa, as demonstrated by an increase in Acidimicrobium that affect both nitrogen and iron cycling.

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), bla_TEM, 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.