Unraveling the effect of reductive soil disinfestation on oxytetracycline and antibiotic resistance genes in soil

Unraveling the effect of reductive soil disinfestation on oxytetracycline and antibiotic resistance genes in soil | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 8 February 2025 V1 Latest version Share on Unraveling the effect of reductive soil disinfestation on oxytetracycline and antibiotic resistance genes in soil Authors : Chenpan Gong , Ranran Zhang [email protected] , Yuze Gao , Yushui Chen , Yifei Zhang , Yufei Zhao , Jinjie Zhang , Haifeng Zhuang , Xun Qian , Shengdao Shan , and Yong Sik Ok 0000-0003-3401-0912 Authors Info & Affiliations https://doi.org/10.22541/au.173900721.11938829/v1 213 views 147 downloads Contents Abstract 1. Introduction 2. Materials and methods 3. Results and discussion Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Reductive soil disinfestation (RSD) is a soil remediation technology that effectively inhibits the transfer and spread of antibiotic resistance genes (ARGs) in soil. However, in soil contaminated with varying concentrations of oxytetracycline (OTC), the effect of RSD technology on OTC and ARGs remains unknown. In the laboratory, we established three soil treatments: OS (original soil samples); Soil Cultivation (control soils with five different residual concentrations of OTC (0, 5, 20, 50, 100 mg/kg)); RSD (treated soils with five different residual concentrations of OTC incubated at a constant temperature of 37 °C for 30 days). Results indicated that RSD can effectively degrade the concentration of OTC in soil, with degradation rates ranging from 22.91% to 82.83%. Additionally, RSD significantly reduced the relative abundance of ARGs, mobile genetic elements (MGEs) (P < 0.05), with reduction rates ranging from 24.39% to 86.56%. Network analysis indicated that Microbispora and Clostridium are the main potential hosts of ARGs. Redundancy analysis suggested that MGEs (42.7%) and microbial communities (19.5%) are the primary factors contributing to changes in ARGs. Therefore, the inhibition of MGEs abundance and reduction of host bacteria abundance by RSD are the primary mechanisms for reducing ARGs. In summary, RSD shows the potential for removing OTC and inhibiting the spread of ARGs in soil. This study provides a theoretical basis for using RSD in remediation of agricultural soils contaminated with antibiotics. Title Page Unraveling the effect of reductive soil disinfestation on oxytetracycline and antibiotic resistance genes in soil Authors: Chenpan Gong a , Ranran Zhang a,* , Yuze Gao a , Yushui Chen a , Yifei Zhang a , Yufei Zhao b , Jinjie Zhang a , Haifeng Zhuang a , Xun Qian c , Shengdao Shan a , Yong Sik Ok d,* Affiliations and addresses: a Key Laboratory of Recycling and Eco-Treatment of Waste Biomass of Zhejiang Province, School of Environmental and Natural Resource, Zhejiang University of Science and Technology, Zhejiang, Hangzhou, 310023, China b School of Environment and Energy, Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, 510006, China c Interdisciplinary Research Center for Soil Microbial Ecology and Land Sustainable Productivity in Dry Areas, Northwest A&F University, Yangling, 712100, Shaanxi, China d Korea Biochar Research Center, APRU Sustainable Waste Management Program, Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea Corresponding Author: Ranran Zhang, Yong Sik Ok Correspondence to: Key Laboratory of Recycling and Eco-Treatment of Waste Biomass of Zhejiang Province, School of Environmental and Natural Resource, Zhejiang University of Science and Technology, Zhejiang, Hangzhou, 310023, China; Korea Biochar Research Center, APRU Sustainable Waste Management Program, Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea Email addresses: [email protected] ; [email protected] Abstract Reductive soil disinfestation (RSD) is a soil remediation technology that effectively inhibits the transfer and spread of antibiotic resistance genes (ARGs) in soil. However, in soil contaminated with varying concentrations of oxytetracycline (OTC), the effect of RSD technology on OTC and ARGs remains unknown. In the laboratory, we established three soil treatments: OS (original soil samples); Soil Cultivation (control soils with five different residual concentrations of OTC (0, 5, 20, 50, 100 mg/kg)); RSD (treated soils with five different residual concentrations of OTC incubated at a constant temperature of 37 °C for 30 days). Results indicated that RSD can effectively degrade the concentration of OTC in soil, with degradation rates ranging from 22.91% to 82.83%. Additionally, RSD significantly reduced the relative abundance of ARGs, mobile genetic elements (MGEs) (P < 0.05), with reduction rates ranging from 24.39% to 86.56%. Network analysis indicated that Microbispora and Clostridium are the main potential hosts of ARGs. Redundancy analysis suggested that MGEs (42.7%) and microbial communities (19.5%) are the primary factors contributing to changes in ARGs. Therefore, the inhibition of MGEs abundance and reduction of host bacteria abundance by RSD are the primary mechanisms for reducing ARGs. In summary, RSD shows the potential for removing OTC and inhibiting the spread of ARGs in soil. This study provides a theoretical basis for using RSD in remediation of agricultural soils contaminated with antibiotics. Keywords : Antibiotic resistance risk; Antibiotic pollution; Virulence factor gene; Potential host bacteria; Redundancy analysis 1. Introduction Widespread use of antibiotics in agriculture and the use of manure fertilizers are the main reasons for the accumulation of antibiotic residues and antibiotic resistance genes (ARGs) enrichment in soil (Chung et al., 2017). ARGs can spread and transfer among soil and rhizosphere microorganisms through horizontal gene transfer (HGT), facilitated by mobile genetic elements (MGEs) (Wang et al., 2023). Therefore, they could enter the food chain, threaten ecosystems, and pose a risk to human health (Zhu et al., 2013). According to statistical predictions, by 2050, approximately 10 million deaths globally will be closely associated with bacterial antibiotic resistance (Zhang et al., 2021). Therefore, it is crucial to investigate methods for removing residual antibiotics and controlling ARGs contamination in soil. Reducing soil disinfection (RSD) is a soil remediation method used before crop planting. The method involves the addition of large amounts of readily decomposable organic matter, then flooding soil and covering with plastic mulch, creating a rapid and strong reducing soil condition in the short term (Huang et al., 2016). This method has been proven to effectively enhance soil fertility and inhibit the proliferation of soil-borne pathogens (Zhao et al., 2018; Zhao et al., 2024). However, with the increasing problem of antibiotic resistance pollution in agricultural facility soils, studies on the effect of RSD on soil ARGs is gradually increasing. For example, Chen et al. (2021) conducted a preliminary investigation on the effect of RSD on soil ARGs and found that RSD can effectively suppress the enrichment of ARGs abundance and controlled the diversity of ARGs in soil, with reduction efficiencies of 10.8% and 18.6%, respectively. Duan et al. (2024) conducted laboratory simulations to investigate the effects of adding multiple types of organic materials (such as distillers’ grains, peanut shells, etc.) on ARGs during the RSD process, they finding that various organic materials had removal effects on ARGs (10.7% to 30.6%). Overall, RSD is a method that can effectively prevent and control ARGs in soil. However, the primary source driving the spread and diffusion of ARGs is the overuse of antibiotics. This phenomenon of antibiotic residues in soil is widespread. Therefore, it is worthwhile to further investigate the effect of RSD on antibiotics and ARGs in soil with residual antibiotics. In the livestock industry, the widespread use of oxytetracycline (OTC) has led to high concentrations of OTC residues in animal manure (Cheng et al., 2019; Wang et al., 2017). Li et al. (2011) measured residual concentrations of OTC in soil can reaching up to 144 mg/kg through agricultural use of fertilizers. In response to the pollution of OTC in soil, most of the previous studies focused on the adsorption and degradation of OTC. For example, Wallace et al. (2018) found in an anaerobic fermentation system, the removal rate of OTC reached 29%. This is mainly due to the ability of anaerobic microorganisms to degrade OTC during anaerobic fermentation (Chen et al., 2022). The flooding in the RSD process creates an anaerobic environment in the soil, which may promote the proliferation of anaerobic microorganisms, thereby enhancing the degradation of OTC. In addition, the physicochemical properties of soil also play a key role in the desorption of OTC. Xiao et al. (2020) found that the soil pH affects the adsorption of oxytetracycline, with OTC primarily existing in cationic form and its adsorption being promoted by electrostatic attraction at pH values less than or equal to 7. Zhang et al. (2019) found that increased organic matter content in the soil enhances microbial metabolic activity and degradation capability, thereby accelerating the degradation rate of antibiotics. RSD requires the addition of rich organic materials. Under microbial activity, these organic materials produce organic acids, creating an acidic environment in the soil. Additionally, the addition of organic materials increases the organic matter content, both of which provide favorable conditions for the degradation of OTC. Therefore, we hypothesize that RSD can effectively degrade OTC, thereby reducing the induction risk of OTC on ARGs and further controlling the spread of ARGs. Numerous studies have found that in various environmental media, the distribution of MGEs and the succession of microbial communities are key mechanisms controlling the transfer and spread of ARGs in different environmental medias (Fang et al., 2022; Han et al., 2023). Wang et al. (2023) found that soil solarization can effectively reduce the abundance of MGEs, thus controlling the transfer of ARGs. Microorganisms are hosts of ARGs, RSD systems transition from a facultative anaerobic to an aerobic environment, leading to significant changes in soil microbial succession, which greatly affect the distribution and composition of ARGs in the soil. Therefore, it is essential to explore the effect of RSD on microbial community succession and MGEs on ARGs in soil with varying residual concentrations of OTC. In this study, we focus on comprehensively understanding the effect of RSD on ARGs, MGEs, OTC, and soil microbes in soil with varying residual concentrations of OTC. This study aimed to were (1) to observe the changes in soil properties and OTC concentration in soil with different residual concentrations after RSD, (2) to analyze the diversity and abundance of ARGs and MGEs, (3) to explore the impact mechanisms of RSD on ARGs in soils with different residual concentrations of OTC by examining MGEs and the succession of microbial communities. This study will provide a theoretical basis for the application of RSD and addressing the ecological pollution of antibiotics and ARGs in soil ecosystems. 2. Materials and methods 2.1 Soil sampling and treatments Soil samples (0–20 cm) were taken from a greenhouse farm in Lin’an, Hangzhou, China (30 °18 ’N, 119 °30 ’E). The soil samples were air-dried, and then sieved through a 2 mm mesh to determine its properties. Three treatment groups were designed for this experiment. The experimental treatments were as follows: OS (Original soil samples), CK (Control soil incubated for 30 days after the addition of antibiotics at five gradient concentrations), and RSD (treated soil with RSD following the addition of antibiotics at five gradient concentrations, with destructive sampling on days 7, 14, and 30). The experiment included three treatment groups, with a total of 21 samples, each sample with three replicates. Based on existing literature research (Duan et al 2017; Li et al., 2011), we selected an OTC concentration range of 0-100 mg/kg for our study, we prepare a stock solution of OTC (100 mg/mL). Then thoroughly mix the diluted OTC solution with the soil. The soil was spiked with of OTC on a dry weight (DW) basis. CK groups specific operational as follows: Cylindrical plastic bottles (85 mm diameter, 110 mm height) were each filled with mixing 300g of soil, add five different concentrations of OTC（0, 5, 20, 50, or 100 mg/kg）maintaining soil moisture at 60%. The samples were incubated in a dark environment at 37 °C in a constant temperature incubator for 30 days. (Treatment group names corresponding to OTC concentrations: CK_0, CK_5, CK_20, CK_50, CK_100). RSD treatments specific operational as follows: Cylindrical plastic bottles (85 mm diameter, 110 mm height) were each filled with mixing 300g of soil containing 2% dry weight of maize straw. The maize straw was procured from a farm in Hangzhou and crushed into particles of 3-5 mm. It had a nitrogen content of 7.98 g/kg and a carbon content of 402.85 g/kg. The soil was flooded with sterile water and then sealed with a plastic mulch (3 replicates of each treatment). All plastic bottles were incubated for 30 days at 37 °C in a constant temperature incubator. On the 7th day, soil samples were collected via destructively sampling from the containers (Treatment group names corresponding to OTC concentrations on the 7th day: R_0_7d, R_5_7d, R_20_7d, R_50_7d, R_100_7d). On the 21st day, the plastic mulch was removed, and soil samples were immediately collected (Treatment group names corresponding to OTC concentrations on the 21th day: R_0_21d, R_5_21d, R_20_21d, R_50_21d, R_100_21d). On the 30th day, the final soil samples were collected (Treatment group names corresponding to OTC concentrations on the 30th day: R_0_30d, R_5_30d, R_20_30d, R_50_30d, R_100_30d). Each set of soil samples we sample is divided into two subsamples. One subsample was air-dried, sieved, and processed for the determination of soil physicochemical properties (pH, EC, SOM, TN, NH 4 + -N, NO 3 \sout - -N); The other subsample was freeze-dried for the measurement of oxytetracycline concentrations and stored at -80°C for DNA extraction. 2.2 Sample chemistry and determination of OTC concentrations The pH, electrical conductivity (EC), soil organic matter (SOM), available ammonium (NH 4 + -N), available nitrate (NO 3 \sout - -N), total nitrogen (TN) and the concentration of OTC of the samples were measured. The OTC concentration was determined by high-performance liquid chromatography. For the specific OTC determinations we referred to a previous study that utilized high-performance liquid chromatography (AGLIENT1290, USA) to determine the OTC concentration (Chitescu et al., 2013). The detailed methods for measuring soil physicochemical properties and OTC concentrations were described in (Supplementary Information). 2.3 DNA extraction and ARGs quantification Freeze-dried samples weighing 0.5000g were used to extract DNA using the Soil Rapid DNA Kit (MP Biomedicals, USA). The detailed operating procedures followed the instructions provided with the kit. Subsequently, DNA concentration and purity by spectrophotometer (Biotek Elx808, USA). ARGs, MGEs, and virulence factor genes (VFGs) detection were performed using the high-throughput quantitative polymerase chain reaction system (WaferGen SmartChip, Yuanzai Biotechnology Co., China). We referred to previous studies for detailed thermal cycling conditions and the steps of the PCR reaction system (Wang et al., 2023; Zhu et al., 2018). This system is capable of running 5184-nanowell qPCR reactions in parallel each time. The PCR reaction mixture was first added to the microwell chip using the nanoliter-scale multiple sample dispensing (MSND) system in a 36 (samples) ×144 (assays) configuration, a total of 130 ARGs, 13 MGEs, and 16S rRNA gene were quantified, which had been detected in previous studies (Zhu et al., 2018). PCR primer information is provided in the supplementary materials (Table S1). Subsequently, the primers underwent qPCR reactions on a cycler, each sample undergoes three technical replicates. Ct values obtained from the PCR system, with a threshold cycle (Ct) of 31 set as the detection limit (Zhou et al., 2021). Ct > 31 were interpreted as indicating no amplification. The relative quantity of each gene in each sample was determined using the formula: relative gene copy number = 10 ^ (31 - CT)/ (10/3). We used ARGs copies/16S rRNA gene as the relative abundance of ARGs (Li et al., 2022). 2.4 16S rRNA gene sequencing This study utilized the Illumina MiSeq platform (Meiji Biological Medicine Co., Ltd., Shanghai, China) to sequence bacterial community structure and composition. The V3-V4 region of 16S rRNA was amplified with primer pairs (343F: 5-TACGGRAGGCAGCAG-3; 798R: 5-AGGGTATCTAATCCT-3) (Liu et al., 2016). Where the PCR products were purified, quantified, and normalized to construct libraries, followed by quality inspection on LabChip, with constructing small-fragment libraries and paired-end sequencing analysis to classify the obtained biological information into operation taxonomy units (OTUs) (Zheng et al., 2017). Based on the OTUs information, Bioinformatic analysis of the soil bacterial by using the Majorbio Cloud platform at https://cloud.majorbio.com. 2.5 Statistical analysis The diagrams were produced using Origin 2021. GraphPad Prism 9 was used to create heatmaps depicting the genes’ changes in different samples. For the variations in soil physicochemical properties, gene abundance, and bacterial community structure, we used Spearman’s correlation coefficients by using SPSS 19.0 (IBM, USA) and performed variance analysis (ANOVA, P < 0.05). Gephi 0.10.1 software was to identify potential host bacteria, based on correlation coefficients (P 0.8) between ARGs, MGEs, VFGs, and bacterial communities. Redundancy analysis (RDA) by using CANOCO 5.0 software. Variance Partitioning Analysis (VPA) illustrates the contributions of MGEs, OTC, and SOM to ARGs, depicted through a Venn diagram. Mantel analyzed was performed using the OmicStudio tools at https://www.omicstudio.cn/tool. 3. Results and discussion 3.1 Effects of RSD on soil properties and oxytetracycline concentration The soil properties (pH, SOM, TN, NH 4 + -N, NO 3 \sout - -N) of each treatment exhibited significant changes after undergoing RSD treatment (Fig. S1, p < 0.05). For example, after RSD treatment, the soil pH increased from 4.6 to 6.8, approaching neutrality. Additionally, the original soil samples contained 30.72 g/kg of organic matter. After RSD, the organic matter content in RSD samples significantly increased, ranging from 43.31 to 55.87 g/kg. In summary, RSD treatment can enhance soil fertility, our results are consistent with those of previous studies (Chen et al., 2021; Li et al., 2021). It is noteworthy that there is no significant difference in the increase of soil organic matter (SOM) and total nitrogen (TN) after RSD treatment among soils with different residual antibiotic concentrations (Fig. S1). This indicates that antibiotic residues do not affect the contribution of organic material fermentation during RSD treatment to soil fertility. Compared to the CK groups, the RSD treatments showed an increase in OTC degradation rates by 15% to 89%, with degradation rates reaching 72.19%, 22.91%, 65.28%, 82.83%, and 66.64%, respectively (Fig.1). The degradation dynamics of OTC by RSD treatment exhibited a consistent trend, with OTC concentrations gradually decreasing over time. The relationship between OTC concentration and time was fitted using a first-order kinetic equation (Fig.S2), with coefficients of determination (R²) ranging from 0.81 to 0.98. This indicates that soil treated with RSD follows a first-order reaction kinetics in OTC degradation process. Previous studies have found that soil properties can affect the degradation efficiency of OTC. For example, Li et al. (2008) discovered the degradation efficiency of OTC increases with the elevation of pH, while Fernandes et al. (2015) found that an increase in soil organic matter content increased the adsorption capacity of soil for OTC. In this study, soils with different residual concentrations of OTC showed significant increases in pH and organic matter content after undergoing RSD treatment, thereby enhancing the degradation efficiency of OTC. 3.2 Diversity and abundance of ARGs, MGEs, and VFGs To investigate the effect of RSD on ARGs in soils with different residual concentrations of OTC, we employed high-throughput qPCR to sequence a total of 130 types of ARGs and 13 types of MGEs. Ultimately, 62 subtypes of ARGs and 8 subtypes of MGEs were detected. In original soil sample, 35 gene subtypes were detected. After soil cultivation, there was a significant increase in the number of ARGs and MGEs subtypes, with the CK_5 soil showing the highest diversity of ARGs and MGEs, reaching 56 species (Fig. 2a). However, compared to the CK groups, the number of ARGs and MGEs subtypes decreased by 8.1% to 53.5% after RSD (Fig. 2b). The diagrams showed the total relative abundance changes of ARGs and MGEs in each treatment group (Fig.2 c, d). The detected ARGs in all samples were mainly categorized into nine major classes based on their antibiotic resistance mechanisms, including sulfonamide, tetracycline, aminoglycoside, MLSB, beta-lactamase, vancomycin, chloramphenicol, multidrug resistance. Among them, the relative abundance of sulfonamide resistance genes is the highest, accounting for 59.8% of the total ARGs. In farmland where livestock manure is applied, these ARGs maintain high abundance and detection rates (Qian et al., 2018; Zhang et al., 2024). In original soil sample, the total relative abundance of ARGs and MGEs reached 0.07 copies/g. In CK groups, soils with different concentrations of residual oxytetracycline showed varying degrees of enrichment in ARGs. Among them, the enrichment effect of ARGs was most significant in the CK_100, with a relative abundance reaching 0.117 copies/g. However, after RSD, there was a significant reduction in the relative abundance of ARGs, with reduction rates ranging from 24.39% to 86.56%. Chen et al. (2021) found that after treating the soil with RSD, both the abundance and diversity of ARGs were reduced, which is consistent with our research findings. In addition, previous studies have found that the agricultural application of manure not only introduces high abundances of ARGs and residual antibiotics (Rietra et al., 2024; Zhang et al., 2024) but also enriches virulence factor genes (VFGs) in soil (Xie et al., 2023). Therefore, we also focused on the impact of RSD on VFGs in the soil. In this study, the changes in the relative abundance of VFGs in soil samples from different treatment groups showed a similar trend to the changes observed in ARGs (Fig.S3). After soil cultivation, the abundance of VFGs increased. The enrichment effect of CK_5 was the most significant, with the abundance of the stx2 virulence factor increasing by 61.1% compared to the CK_0. The stx2 gene, as a high-risk virulence factor, can lead to a series of clinical diseases (Lodato, 2021). Fortunately, after RSD, the relative abundance of VFGs was significantly inhibited, with reduction rates ranging from 34.35% to 96.13%. Overall, soil with residual OTC undergoes enrichment of ARGs and VFGs after soil cultivation. However, even in soil with high concentrations of residua OTC, effective removal of ARGs and VFGs is achieved through RSD treatment. 3.3 Effects of RSD on soil ARGs composition profiles Different subtypes of ARGs exhibited distinct distribution patterns during the experimental treatments (Fig.3). In both OS and CK treatments, various subtypes of ARGs maintained relatively high abundances. However, after RSD treatment, the abundance of ARGs was reduced to varying degrees. i : Sulfonamide resistance genes The distribution pattern of sulfonamide ARGs (Fig.2c, d), which represent the most abundant subtype in terms of relative abundance, underwent significant changes during the RSD treatment process. After RSD, both drfa1 , drfa12, and sul1 ARGs exhibited significant reductions, with reduction rates ranging from 38.26% to 93.7%. sul1 is one of the most abundant and frequently detected ARGs in the environment, and it is also one of the most critical ARGs in terms of dissemination risk (Dungan et al., 2018; Wu et al., 2023; Xu et al., 2021). Therefore, it is essential to pay attention to the distribution characteristics of the sul1 gene. Among them, soil with a residual concentration of 100 mg/kg OTC, RSD treatment showed the best reduction effect on ARGs, with a degradation rate of sul1 reaching 53.37%. This indicates that even in soil with relatively high antibiotic residues, RSD treatment can still achieve significant removal of ARGs. ii: Tetracycline resistance genes Tetracycline ARGs, being the most prominent in terms of detection rate and abundance in livestock manure and soil (Qiao et al., 2018). Sui et al. (2019) conducted long-term monitoring of soils treated with organic fertilizers and found that genes like tetG and tetM can persist in the soil, posing a more profound threat to soil crops and ecosystems. In this study, the relative abundance of tetracycline ARGs in soils with different concentrations of residual tetracycline was significantly reduced after RSD treatment, with reduction rates ranging from 56.19% to 98.7%. It is worth noting that the abundance of the tetM-01 gene was relatively high in the RSD_50 and RSD_100 groups, possibly attributed to the higher residual concentration of OTC, thereby exerting selective pressure on soil microbiota, consequently promoting the dissemination of ARGs (Bao et al., 2024). iii: MLSB , Aminoglycoside , Vancomycin resistance genes After RSD, the reduction rates of MLSB, Aminoglycoside, and Vancomycin ARGs in the soil were 72.14% to 94.57%, 51.25% to 70.46%, and 56.32% to 91.86%, respectively. Similar to sulfonamide resistance genes, soil with a residual concentration of 100 mg/kg OTC exhibited the most effective reduction in ARGs after RSD. Duan et al. (2024) found that after RSD treatment using distillers’ grain as organic materials, the abundance of ErmB , lnuB , and aadA in the soil was significantly reduced, which is consistent with the results of this experiment. Vancomycin is a crucial antibiotic in clinical medicine. In clinical medicine, infections caused by Vancomycin-resistant Enterococci (VRE) leave little options for treatment (Fremin et al., 2017). Fortunately, in this study, after RSD, VanA was effectively removed. iv: Mobile Genetic Element (MGEs) Li et al. (2024) found that residual OTC in soil induces the expression of MGEs. Surprisingly, in soil treated with 100 mg/kg OTC, the relative abundance of MGEs increased by 2.19 times. However, soil with residual concentrations of 0, 20, 50, and 100 mg/kg of OTC showed significant reductions in the relative abundance of MGEs after RSD, with the Intl1 gene showing the most pronounced reduction. Previous studies have found a significant positive correlation between the abundance of sul1 and Intl1 in soils treated with organic fertilizers. The Intl1 gene plays a crucial role in mediating the horizontal transfer of ARGs (Ma et al., 2017; Wang et al., 2015; Zhu et al., 2017). In this study, RSD treatment significantly reduced the relative abundance of MGEs. We speculate that this may decrease the horizontal gene transfer ability of ARGs among microorganisms, thereby exerting a control effect on the dissemination of ARGs. Overall, after RSD treatment, soil with different concentrations of residual OTC showed significant reductions in the relative abundance of both ARGs and MGEs. Among them, soil with a residual concentration of 100 mg/kg OTC exhibited the most effective reduction after RSD treatment, indicating that high concentrations of antibiotic residues do not interfere with the effectiveness of RSD in reducing ARGs and MGEs in soil. However, the mechanism underlying the effect of RSD on ARGs still requires further investigation. 3.4 Effects of RSD on Soil Microbial Communities In this study, a total of 1,357,951 high-quality sequences were obtained from soil samples. These sequences were utilized to analyze the bacterial community distribution in soil samples (Fig.S4). The variation in microbial phylum-level composition after RSD treatment of soils with different concentrations of residual OTC is shown in Fig. 4a. Firmicutes (10.86%~90.96%), Acidobacteriota (2.03%~30.40%), Proteobacteria (0.2%~48.50%) and Chloroflexi (2.44%~6.46%) were the main bacterial phyla. On the 7th and 21st days of RSD treatment, the relative abundance of Firmicutes reached 88.12% to 95.44%. On the 30th day, significant changes occurred again in the microbial composition of the soil. The activity of aerobic bacteria gradually increased, with Proteobacteria and Actinobacteria becoming the dominant phylum. This is consistent with previous research findings (Duan et al., 2024). These results indicate that RSD treatment can alter the structure and abundance of the microbial community. After RSD, the microbial communities exhibited significant changes at the genus level (Fig. 4b). On the 7th and 21st days of RSD, dominant genera mainly belonged to Firmicutes, including Hydrogenispora , Ruminiclostridium , and Fonticella . On the 30th day, the predominant genera in the soil were primarily represented by Actinobacteriota, including Streptomyces , Actinomadura , and Microbispora , as well as Proteobacteria genera like Azospirillum and Microvirga . The bacterial community in the soil mainly clustered based on the duration of RSD and the concentration of OTC. In this study, on the 7th and 21st days of RSD treatment, the soil was in a flooded anaerobic environment; While on the 30th day, the plastic film was removed, restoring an aerobic environment. Therefore, the drastic changes in the soil environment led to alterations in the distribution characteristics of microbial communities. 3.5 Relationship among bacterial communities, ARGs, MGEs, and VFGs Correlation analysis was conducted using bacteria (top 30 genera selected), ARGs, MGEs, and VFGs, focusing on coefficients exceeding 0.80 for inclusion. The network contained 46 nodes and 214 edges, which it included 34 ARGs, 2 MGEs, 3 VFGs, and 10 bacterial genera (Fig.5). ARGs, MGEs, VFGs, and bacterial genera exhibit close correlations, it is possible to share potential bacterial hosts (Li et al., 2015). For example, Clostridium_sensu_stricto_8 exhibits significant correlations with blaTEM , sul2 , Intl1 , and tetT (P < 0.05). Unclassified_f__Lachnospiraceae shows significant correlations with sul1 , aadE , and Intl1 (P < 0.05). Microbispora demonstrates significant correlations with blaTEM , sul1 , tetX , Intl1 , IS26 , aadE , and stx2 (P < 0.05), the abundance of Microbispora was somewhat inhibited after RSD treatment, which may contribute to the suppression of VFGs such as stx2 . The Clostridium genus is closely associated with ermC , tetG-01 , and several other genus. Leclercq et al. (2016) found that the Clostridium genus, as a species associated with clinical intestinal diseases, could serve as a potential host for ARGs. In this study, the abundance of Clostridium in the soil after RSD treatment was significantly suppressed, potentially reducing the risk of ARGs transmission. 3.6 Driving factors of reducing ARGs To further explore the key driving factors behind the reduction of ARGs by RSD, we utilized Redundancy Analysis (RDA) to study the contributions of environmental factors (SOM, TN, EC, NH 4 + -N, NO 3 − -N, pH), OTC concentration, bacterial communities (considering the top five most abundant phylum), and MGEs to the abundance of 8 classes of ARGs and VFGs. RDA analysis revealed that the associated variables explained 66.22% of the total variance in ARGs and VFGs. Among them, RDA1 and RDA2 accounted for 51.11% and 16.13% of the variance, respectively (Fig.6a). By utilizing VPA, we visually illustrate the explanatory power of four variables on ARGs and VFGs (Fig. 6b). The results indicate that among the considered factors, MGEs had the greatest influence on the variation in ARGs, explaining 42.7% of the total variance. Previous studies have focused on the significant effect of MGEs on ARGs. For example, Zhu et al. (2023) observed a decrease in the relative abundance of MGEs during high-temperature composting, which was identified as a major factor weakening the horizontal transfer capability of ARGs. Additionally, Wang et al. (2023) investigated changes in ARGs in soil during fallow periods using flooding, mulching, and sunlight exposure methods. They found that Intl1 accounted for up to 45.8% of the variability in ARGs, with a significant correlation between the changes in the abundance of MGEs and ARGs. To investigate this, we performed linear fitting of the relative abundances of MGEs and ARGs to observe their correlation. We found a positive correlation between the changes in MGEs and ARGs (R² = 0.66) (Fig. S5), further confirming the high explanatory power of MGEs on ARGs. This also indicates that RSD can reduce the horizontal gene transfer mediated by MGEs, thereby suppressing the dissemination of ARGs. Secondly, Microbial communities contributed 19.5% of the explanatory power. Soil microbial, as hosts of ARGs, exhibit a close correlation between their community composition, structure, diversity characteristics, and the abundance of ARGs (Xiang et al., 2019). By observing the abundance of potential host bacteria in the network, we found that RSD treatment effectively suppressed the potential host bacteria ( Microbispor and Clostridium ) associated with ARGs and VFGs, thereby reducing the abundance of ARGs and VFGs. Eventually, OTC concentration contributed 6.4%. In this study, RSD significantly increased the degradation efficiency of OTC, which likely further reduced the selective pressure of OTC on soil microorganisms, thereby inhibiting the induction and formation of ARGs (Zhang et al., 2021). Among all the soil properties, NO 3 − -N had the highest explanatory power, reaching 4.9%. Mantel test revealed significant correlations between the composition of ARGs, MGEs, and VFGs in the soil and various environmental variables (Fig.6c). Previous studies have found that changes in soil properties significantly influence the succession of soil microbial communities, the potential hosts of most ARGs may be primarily influenced by NO 3 − -N (Chen et al., 2017; Xu et al., 2019). The dynamic changes in inorganic nitrogen can also affect the abundance of bacteria hosting ARGs, thereby altering the abundance of ARGs (Sun et al., 2020). The soil pollution status is complex. In addition to causing high concentrations of antibiotic residues, the use of manure in agriculture also introduces residual heavy metals from the manure into the soil. Previous studies have found that residual heavy metals in the soil exert co-selective pressure, promoting the evolution of ARGs host bacteria, thereby increasing the risk of ARGs dissemination (Qi et al., 2021; Zhang et al., 2023). In this study, 19.2% of the variables remained unexplained, possibly including the aforementioned influencing factors. Therefore, these factors warrant further investigation in future studies. not-yet-known not-yet-known not-yet-known unknown 4. Conclusion This study is the first to comprehensively investigate the mechanisms by which RSD removes OTC and affects ARGs in soil with different residual concentrations of OTC. The results indicated that MGEs and microbial community succession are the primary factors driving changes in ARGs. RSD significantly reduces the abundance of MGEs in soil, therefore decreasing the ability for ARGs horizontal gene transfer. Microbispor and Clostridium are potential host bacteria for ARGs, and RSD treatment effectively suppresses their abundance, consequently reducing ARGs abundance. We found that antibiotics only explain 6.4% of the variation in ARGs. However, RSD significantly enhances the degradation efficiency of OTC, indicating that it has the potential to reduce the selective pressure of antibiotics on soil microorganisms and thus control ARGs formation. Overall, RSD demonstrates effectiveness in degrading OTC in soil and reducing antibiotic resistance. Given its environmentally friendly attributes and ease of use, it merits widespread application in remediating polluted farmland. not-yet-known not-yet-known not-yet-known unknown CRediT authorship contribution statement Chenpan Gong: Designed the research, lead the lab work, performed data analysis, Writing – original draft, Visualization. Ranran Zhang: Designed the research, performed data analysis, Writing – original draft, Writing – review & editing. Yuze Gao: Writing – review & editing. Yushui Chen: Writing – review & editing. Yufei Zhao: Writing – review & editing. Jinjie Zhang: Writing – review & editing. Haifeng Zhuang: Writing – review & editing. Xun Qian: Writing – review & editing. Shengdao Shan: Writing – review & editing. Yong Sik Ok: Designed the research, performed data analysis, Writing – review & editing. not-yet-known not-yet-known not-yet-known unknown Data availability Data will be made available on request. Declaration of Competing Interest No part of this paper has been published or submitted elsewhere. All authors declare no conflicts of interest. not-yet-known not-yet-known not-yet-known unknown Acknowledgments This study was funded by National Natural Science Foundation of China (42107029), Key Technologies of Carbonization and Sustainable Utilization of Urban Perishable Waste Driven by Data and Knowledge (2022YFE0196000), Zhejiang University of Science and Technology youth Science Fund project (2023QN044), and Zhejiang University of Science and Technology research start-up funds (F701119M01). Prof. Yong Sik Ok’s research was carried out with the support of the Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01475801) from Rural Development Administration and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1A6A1A10045235) in Korea. This work was partly supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2022M3J4A1091450). We thank Prof. Yong Sik Ok for editing and improving the manuscript. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version. not-yet-known not-yet-known not-yet-known unknown References Bao, H., Chen, Z., Wen, Q., Wu, Y., Fu, Q., 2024. Effects of oxytetracycline on variation in intracellular and extracellular antibiotic resistance genes during swine manure composting. Bioresource Technology, 393, 130127. Chen, Z.Y., Zhang, W., Wang, G., Zhang, Y., Gao, Y., Boyd, S. A., Teppen, B. J., Tiedje, J. M., Zhu, D., Li, H., 2017. Bioavailability of soil-sorbed tetracycline to Escherichia coli under unsaturated conditions. Environmental science technology, 51(11), 6165-6173. Chen, Y., Yang, K., Ye, Y., Zhang, Y., Mi, H., Li, C., Li, Z., Pei, Z., Chen, F., Yan, J., Wang, X., Wang, Y., 2021. 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Figure legends Fig. 1 Oxytetracycline concentrations in soil under different treatments. Fig. 2 Numbers of ARGs and MGEs under OS, CK groups (A) and RSD groups (B). The relative abundances of different classes of ARGs and MGEs under OS, CK groups (C), and RSD groups (D). Fig. 3 Heatmap showing the relative abundances of ARGs, MGEs, and VFGs under different treatments. Fig. 4 Relative abundances of dominant bacterial phyla in RSD groups (A). Heatmap showing the relative abundances of the top 45 genera in RSD groups (B). Fig. 5 Network analysis based on the co-occurrence of ARGs, MGEs, VFGs, and bacteria genera in RSD groups to investigate potential host bacteria for ARGs. Node sizes represent the total abundances of ARGs, MGEs, or bacteria. (Spearman’s correlation coefficient r>0.80) and significant (P<0.05) correlation. Nodes were colored based on the classification of bacteria and ARGs, MGEs, and VFGs. The size of nodes was proportional to the abundance of genera and ARGs, MGEs, and VFGs subtypes. The edges are colored green to indicate positive correlations and brown to indicate negative correlations. Fig. 6 Redundancy analysis (RDA) was used to study environmental factors (OTC concentration, pH, EC, SOM, TN, NH 4 + -N, NO 3 - -N), main bacterial phyla, and MGEs contribution to ARGs and VFGs (A). Variation partitioning analysis determined the proportions of the different effects of MGEs, microbial communities, OTC concentration, and Soil properties on the variations within the ARGs profile, depicted through a Venn diagram (B). Mantel tests revealed correlations of environmental factors, OTC concentration, and Phylum-level bacteria with ARGs, MGEs, and VFGs in RSD groups (C). 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Keywords antibiotic pollution antibiotic resistance risk potential host bacteria redundancy analysis virulence factor gene Authors Affiliations Chenpan Gong Zhejiang University of Science and Technology View all articles by this author Ranran Zhang [email protected] Zhejiang University of Science and Technology View all articles by this author Yuze Gao Zhejiang University of Science and Technology View all articles by this author Yushui Chen Zhejiang University of Science and Technology View all articles by this author Yifei Zhang Zhejiang University of Science and Technology View all articles by this author Yufei Zhao South China University of Technology View all articles by this author Jinjie Zhang Zhejiang University of Science and Technology View all articles by this author Haifeng Zhuang Zhejiang University of Science and Technology View all articles by this author Xun Qian Northwest A&F University View all articles by this author Shengdao Shan Zhejiang University of Science and Technology View all articles by this author Yong Sik Ok 0000-0003-3401-0912 Korea University View all articles by this author Metrics & Citations Metrics Article Usage 213 views 147 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Chenpan Gong, Ranran Zhang, Yuze Gao, et al. Unraveling the effect of reductive soil disinfestation on oxytetracycline and antibiotic resistance genes in soil. Authorea . 08 February 2025. DOI: https://doi.org/10.22541/au.173900721.11938829/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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