Metagenomic analysis of effects of oxytetracycline and copper on antibiotic resistance genes and associated pathogenic hosts in swine manure compost

Honghong Guo Northwest Agriculture and Forestry University jie gu (  gujie205@sina.com ) Northwest Agriculture and Forestry University https://orcid.org/0000-0001-7592-5751 Xiaojuan Wang Northwest Agriculture and Forestry University Zilin Song Northwest Agriculture and Forestry University Xun Qian Northwest Agriculture and Forestry University Wei Sun Northwest Agriculture and Forestry University Jing Yu Northwest Agriculture and Forestry University Liusheng Lei Northwest Agriculture and Forestry University


Background
Since the beginning of the last century, large-scale intensive farming systems have become increasingly popular, and they rely on antibiotics to prevent and treat animal diseases and improve growth performance [1]. However, veterinary antibiotics are not metabolized well by animals and up to 90% of the applied antibiotics can be excreted in urine or feces as the parent compounds or metabolites [2]. These residual antibiotics exert selective pressures on the microbial community even at low concentrations, thereby inducing the enrichment and dissemination of antibiotic resistance genes (ARGs) [3]. ARGs are readily acquired by human pathogenic bacteria (HPB) to generate superbacteria. ARGs are carried in agricultural products due to the agricultural application of manure, which can eventually eliminate the e cacy of antibiotics used in the treatment and prevention of human bacterial infections [4][5][6][7]. It has been suggested that if appropriate measures are not taken to address the important health issues associated with antimicrobial resistance, then the number of deaths due to antibiotic-resistant infections will exceed 10 million by 2050 [8,9]. At present, organic agriculture is being promoted, and thus the use of compost that connects human health and agricultural waste resources is being investigated intensively to assess the risks associated with the presence of antibiotics and the spread of antibiotic resistance [10,11]. In particular, oxytetracycline (OTC) is one of the most common antimicrobial agents used for the prevention and treatment of animal diseases. In the US swine industry, OTC is commonly used to treat a variety of swine bacterial diseases, including respiratory diseases caused by pathogens such as Glässerella, Pasteurella, and Mycoplasma [12]. Therefore, it is necessary to conduct in-depth analyses to determine the effects of OTC residues in animal feces on the distribution and diversity of ARGs as well as identifying their pathogenic hosts during composting.
Human pathogens employ similar mechanisms to those used by pathogens to resist antibiotics in the natural environment [13]. ARGs encoding defense mechanisms are readily transferred between pathogenic microorganisms through horizontal gene transfer (HGT) mediated by mobile genetic elements (MGEs), and integrons are considered to be the main contributors to the acquisition and spread of ARGs [14,15]. Shterzer and Mizrahi [16] have reported HGT occur in the gastrointestinal tracts of livestock, and it is enhanced in the presence of antibiotics [17,18]. In addition, both ARGs and heavy metal resistance genes (MRG) have similarly ancient origins [19]. Luo et al. [20] analyzed 5,436 complete bacterial genomes and showed that MRGs and ARGs coexist extensively in clinical and environmental bacteria.
Plasmids containing both ARGs and MRGs are more likely to be conjugated and transferred between different bacterial groups [21]. It is considered that the co-selection of MRG and ARG genes is due to the selective pressure imposed by heavy metals on ARGs through cross or co-resistance [22]. Heavy metals can also be applied in animal feeds as animal growth promoters, where Cu is detected at high concentrations in livestock and poultry manure, and it is considered to have the greatest capacity for promoting the transfer of conjugated ARGs [23,24]. Thus, it is necessary to explore the relationships between ARGs, MRGs, and MGEs in order to understand the selection, transfer, and persistence of ARGs in composting environments.
Metagenomics methods and structured gene databases have become powerful new tools for accurately and comprehensively identifying and quantifying ARGs, MRGs, and MGE in different environments [25][26][27]. In addition, pathogenic bacteria affect the risk of resistance transferring to the human microbiome.
Metagenomic sequencing can allow the classi cation of most unculturable and rare pathogenic bacteria, as well as the speci c ARGs that they carry [3,28], thereby providing a theoretical basis for further optimizing the treatment regimen to avoid the spread of antibiotic resistance.
The present study aimed to determine: (i) how the diversity and richness of ARGs, MRGs, and MGEs are affected by OTC and Cu during the composting process; (ii) the speci c ARGs carried by pathogenic bacteria and their potential human health risks; and (iii) the contributions of different factors to the fates of ARGs

Results And Discussion
Antibiotic resistome determined for microbes during composting Metagenomic analysis based on the structured SARG database was conducted to determine the antibiotic resistome for microbes during composting. The results showed that ARGs were diverse and abundant in swine feces, even when OTC or Cu was not administered in the CK treatment (Fig. 1). Aerobic composting effectively reduced the abundances and diversity of ARGs. These results are consistent with previous demonstrations [32,36]. In total, 289 ARG subtypes and 19 ARG types were detected throughout the composting process. On day 0 of the composting process, 235 ARGs were detected but the amount decreased to 135-160 on day 10 and 106-120 on day 42. Sixty ARGs were prevalent throughout the composting process (Figs. 1a and 1b). The total abundances of ARGs were 9.39 ⋅ 10 − 1 copies/16S rRNA on day 0, 1.44-2.41 ⋅ 10 − 1 copies/16S rRNA on day 10, and 1.08-1.36 ⋅ 10 − 1 copies/16S rRNA on day 42. The application of OTC or Cu increased the abundance of ARGs compared with CK, where the total abundances were 43.57%, 39.76%, and 67.17% higher in O, Cu, and OCu on day 10, respectively, and 4.66%, 8.93%, and 26.17% higher on day 42.
The detected ARGs were characterized by three major resistance mechanisms: antibiotic inactivation (37.02%), e ux pump (34.26%), and cell protection (21.45%), which are consistent with the results obtained by Zhu et al. [37] and Qian et al. [32]. The ARG subtypes with antibiotic inactivation mechanisms were the most common with up to 85, but the number decreased to 25-30 in the different treatments at the end of composting. The application of OTC and Cu inhibited the decreases in the abundance of ARGs with the three mechanisms on day 10, and strongly inhibited the removal of ARGs characterized by antibiotic inactivation mechanisms in the compost product. In particular, the abundance of ARGs with antibiotic inactivation mechanisms was 2.10 times that of CK in OCu (Fig. 1c).
The ARGs detected in compost can facilitate resistance to the major antibiotics used in humans and animals, thereby resulting in a high public health risk when employed in agriculture. The ARGs detected in this study mainly conferred resistance to three major classes of antibiotics comprising tetracycline (1.17 ⋅ 10 − 2 to 3.12 ⋅ 10 − 1 copies/16S rRNA), aminoglycoside (1.73 ⋅ 10 − 2 to 2.01 ⋅ 10 − 1 copies/16S rRNA) and MLS (1.23 ⋅ 10 − 2 to 2.20 ⋅ 10 − 1 copies/16S rRNA) resistance genes. The relative abundances of the general ARG types comprising tetracyclines, macrolide-lincosamide-streptogramin (MLS), and aminoglycosides in pig manure compost have been previously reported, and they have also been found in other speci c niches [17,32,37]. Composting was highly effective at removing these three types of ARGs as well as chloramphenicol and trimethoprim resistance genes, with removal rates above 90.47% (except the removal rate for aminoglycoside resistance genes was 80.47% in OCu) (Fig. 1d). However, multidrug, rifamycin, fosfomycin, and fosmidomycin genes were enriched. Compared with CK, the addition of OTC and Cu increased the abundances of tetracycline resistance genes in the compost product by 16.55% and 41.66%, respectively, and the combined addition of OTC and Cu increased the abundance of aminoglycoside resistance genes by 1.28 times.
PCA showed that during the composting process, the samples were signi cantly separated at the ARG subtype level, especially in the compost treated with both OTC and Cu (Fig. 2a), possibly because they had the maximum effect on ARGs with different resistance mechanisms. Figure 2b shows the pro les for the 40 ARG subtypes during the composting process with average abundances > 1.0 ⋅ 10 − 3 copies/16S rRNA. These ARGs mainly encoded resistance to tetracycline (tetL and tetW), MLS (ermB and ermC), aminoglycosides (aadA, aadE, and aph(3′′)-I), multidrug (multidrug_transporter), sulfonamide (sul1), and chloramphenicol (chloramphenicol exporter). The genes encoding multidrug (multidrug_transporter, multidrug_ABC_transporter, acrB, mexF, and ykkC), MLS (macB and mphA), and rifamycin (rifampin monooxygenase) resistance were enriched in the compost product, whereas the abundances of other genes decreased as the composting process continued compared with day 0. The removal rates of 17 ARGs exceeded 90%, i.e., seven tetracycline, ve MLS, four aminoglycoside, and one chloramphenicol resistance gene. TetL is a tetracycline e ux protein found in Gram-negative and Gram-positive bacteria and it was the most abundant ARG subtype in the compost on day 0. At the end of composting, the removal rate for tetL reached 98.44-98.79%. On day 10, the addition of either OTC or Cu alone and both together increased the abundances of all aminoglycoside and tetracycline resistance genes (except for tet44 and tetX in O and OCu) compared with CK. The ARG subtypes in the compost products varied among the different treatments. For example, compared with CK, the abundances of tetracycline resistance genes comprising tetL, tetP, tetX, and tetracycline_resistance_protein tended to increase in the treatments with added OTC and Cu, and their abundances were highest when treated with OTC and Cu combined. However, compared with CK, the abundances of most MLS resistance genes (except for lnuB) decreased in the compost product under the combined treatment, where the ermB, ermA, ermC, ermF, ermX, and ermG genes mainly encode resistance to antibiotics via cell protection.
Four universal primers for two tetracycline ARGs (tetW and tetX) and two sulfonamide ARGs (sul1 and sul2) were developed in previous studies, and their prevalence was veri ed by qPCR. Compared with CK, the abundances of tetracycline ARGs (tetW and tetX) and sulfonamide ARGs (sul1 and sul2) tended to increase in O, Cu, and OCu in a similar manner to the results obtained using metagenomic methods. However, the relative abundances of the genes quanti ed by qPCR were relatively small, probably due to the great sequence diversity covered by the macrogenes, which could only amplify speci c sequences or regions of the target gene [28].

Heavy metal resistome of microbes during composting
The enrichment of ARG in various environments can be caused by co-selective pressure exerted by heavy metals. In water, soil, and fertilizer environments, signi cant positive correlations between the concentrations of heavy metals and the abundances of ARGs have been widely reported [38][39][40]. In total, 41 CRGs were detected in the compost samples (Fig. 3) and the total abundance ranged from 4.95 ⋅ 10 − 2 to 1.29 ⋅ 10 − 1 copies/16S rRNA. Aerobic composting effectively reduced the abundances and diversity of CRGs. In total, 41 CRGs were detected on day 0 and the number decreased to 18-24 in the composting products obtained under different treatments. The total abundance of CRGs before composting was 8.02 ⋅ 10 − 2 copies/16S rRNA and it decreased to 4.95-6.27 ⋅ 10 − 2 copies/16S rRNA after 42 days. Since these CRGs are often associated with ARGs, it is not surprising that their abundance is reduced [41,42]. During the composting process, the total abundances of CRGs were always higher in Cu and OCu than CK and O, and the abundance was highest in OCu. Compared with CK, the Cu treatment increased the total abundance of CRGs by 3.41% and 3.08% on day 10 and day 42, respectively, and OCu increased the total abundance of CRGs by 15.05% and 20.82% on day 10 and day 42. These results indicate that the combined effect of OTC and Cu was far greater than that of each single treatment.
In this study, copA was the most abundant CRG in the composting process. CopA encodes the ATPase in the Cu ion e ux pump system, which can excrete copper ions from the cytoplasm into the periplasmic space [43]. The abundance of copA was reduced by 27.74-40.19% in the nal compost product compared with day 0. In other CRGs, the periplasmic pco system exists only on plasmids and it provides high resistance to Cu [44]. Composting was effective at removing pco genes, and the removal rates for pco genes reached 100% at the end of composting.

Occurrence and abundances of MGEs
The study also identi ed the presence of MGEs, including three important integrons and one transposon [45,46] (Fig. 3), which play important roles in the transfer and acquisition of ARGs in various microorganisms via HGT. Integrons can capture exogenous ARG cassettes and then integrate them into their own gene cassettes through targeted recombination [47]. However, integron genes are defective due to their inability to move, but they are usually linked to transposons, which can serve as a vector for the transmission of genetic material [48,49]. Aerobic composting reduced the total MGE abundances in the different treatments by 95.11-96.63%. The integrase gene intI1 was the most abundant, where its abundance ranged from 1.38 ⋅ 10 − 3 to 4.09 ⋅ 10 − 2 copies/16S rRNA during the composting process.
Following the tnpA transposon, the abundance range ranged from 3.11 ⋅ 10 − 4 to 1.25 ⋅ 10 − 2 copies/16S rRNA. The application of OTC and Cu increased the abundances of intI1 and tnpA on day 10. Compared with CK, the abundance of intI1 was 97.38%, 31.99%, and 133.42% higher in O, Cu, and OCu, respectively, and that of tnpA was 56.93%, 43.55%, and 107.33% higher. However, O did not increase the abundances of intI1 and tnpA in the composting products, whereas Cu and OCu increased the abundance of tnpA by 19.07% and 25.90%, respectively. These results indicate that the presence of Cu in pig manure had a more profound impact on ARGs and it was more conducive to increasing the risk of ARGs spreading after the agricultural application of compost.

ARGs carried by HPB during composting
Composting effectively reduced the abundances of HPB in pig manure. Compared with day 0, 58.16-65.43% and 77.61-83.71% of the total HPB in compost were removed on day 10 and day 42, respectively, under different treatments. The ARGs carried by HPB comprised 37 subtypes and the variations in three ARG types mainly affected the resistance pro les of HPB during the whole composting process. Tetracycline and multidrug resistance genes were the most common ARG subtypes with 11 and 12 genes, respectively. Only seven subtypes of MLS resistance genes were detected in HPB but they were present in 9 HPB species, where macB was carried by nine HPB (Fig. 4).
ARGs were harbored by 20 different pathogenic hosts. These pathogenic hosts were dominated by bacteria such as Escherichia coli, Clostridium botulinum, Enterococcus faecium, and Corynebacterium jeikeium, which belong to Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, and Chlamydiae.
These ndings are consistent with previous studies of cow feces, which found that the ARGs originated from Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria [50]. Among the HPB that carried ARGs, Escherichia coli was the main host bacteria and it harbored the highest diversity ARGs, including genes encoding resistance to tetracycline, MLS, multidrug, fosmidomycin, quinolone, bacitracin, and chloramphenicol. A previous survey of surface water in aquaculture areas found that the frequency of resistant Escherichia coli isolates increased as the distance decreased from farms [51]. Corynebacterium is an opportunistic pathogen that settles on human skin and it has recently been implicated as the cause of various infections [52]. Corynebacterium infections are resistant to multiple antibiotics [53]. However, in the present study, adding OTC and/or Cu increased the abundance of Corynebacterium jeikeium by 11.17%, 61.78%, and 17.90% in the composting products obtained with O, Cu, and OCu, respectively, compared with CK. Enterococcus faecalis and Enterococcus faecium are increasingly important hospital pathogens worldwide, and they are mainly related to speci c multi-drug resistance clone lineages in hospital environments [54]. However, other studies found that tcrB was located on a conjugating plasmid in Enterococcus faecium. The addition of the heavy metal Cu and copper tolerance may help to select for or maintain multi-drug resistant Enterococcus [55]. Enterococcus exhibited multidrug, MLS, and bacitracin resistance in the present study, and the abundances of Enterococcus faecalis and Enterococcus faecium in the compost products were 21.99% and 38.76% higher, respectively, in Cu treatment compared with CK. In addition, Pseudomonas aeruginosa is recognized as a well-known di cult to treat HPB and its e ux mechanism responsible for antibiotic resistance represents a great challenge for the treatment of human diseases [56]. In the present study, the addition of OTC and Cu increased the abundance of Pseudomonas aeruginosa in the compost products by 8.82%, 32.28%, and 2.98% in O, Cu, and OCu, respectively, and it was mainly resistant to tetracycline (tetB and tet32) and bacitracin (bcra).

Factors that affected ARG pro les during composting
The ranges of ARGs carried by the microorganisms were determined in this study. Various factors affected the abundances of ARG but the key factors related to the responses of the dominant ARGs to composting should be emphasized. RDA and SEMs were used to separate and order the factors related to changes in ARGs [57,58]. The rst two axes for HPB and CRGs were extracted by PCA before RDA because the number of environmental variables (related factors) cannot exceed the number of species variables (ARGs). The results showed that the factors considered in this study could explain 96.8% of the fate of ARGs (Fig. 5), where HPB_1, MRG_1, tnpA, intI1, and intI2 were the main factors that in uenced the variations in ARGs, where they explained 19.10%, 19.03%, 18.89%, 18.09%, and 17.54% of the variations in the ARG pro les, respectively. Microorganisms are carriers of genes so the reductions in the abundances of HPB during composting contributed to the reductions in the abundances of ARGs. However, the increases in the abundances of potential pathogens after composting were concerning, such as Pseudomonas aeruginosa, Mycobacterium tuberculosis, and Bordetella bronchiseptica. In this study, the ARGs in these HPB encoded tetracycline, bacitracin, and multidrug resistance.
SEMs were used to assess the direct and indirect effects of the ve main drivers (HPB_1, MRG_1, tnpA, intI1, and intI2) on three major antibiotic resistance pro les (Fig. 6). HPB was the most important positive factor for shaping the ARG pro les. HPB can impose an indirect effect on ARGs by strongly affecting the abundance of MGEs and MRGs in the composting process. MGEs had strong and direct impacts on the abundances of ARGs in the composting process. HPB_1 had the highest standardized total effect on the ARG pro les (0.98-0.99), followed by intI1 (0.78-0.85). In addition, the co-selective effect of MRGs on ARGs cannot be ignored. In particular, MRGs signi cantly increased the abundance of ARGs by positively affecting intI1. Similar results were obtained in previous studies, where Rosewarne et al. [59] and Wright et al. [60] found intI1 abundance was signi cantly increased due to the presence of heavy metals.

Conclusion
The changes in the antibiotic resistome during composting were analyzed in this study, thereby providing new insights into the effects of universal additives (OTC and Cu) in feed on the risks for human health and the potential for spreading antibiotic resistance diffusion. The effects of OTC and Cu on enhancing the antibiotic resistome during composting depended on speci c ARG subtypes rather than the overall ARGs at the community level. In total, 289 ARG subtypes belonging to 19 ARG types were detected with abundances ranging from 1.08 ⋅ 10 − 1 to 9.39 ⋅ 10 − 1 copies/16S rRNA. These ARGs were mainly tetracycline, aminoglycoside, and MLS resistance genes. The combined treatment with OTC and Cu had a much greater effect on ARGs than each separate treatment. The ARGs were harbored by 20 different HPB hosts. Three ARG types comprising tetracycline, multidrug, and MLS resistance genes signi cantly affected resistance by HPB throughout the composting process. In addition, HPB and intI1 had the most important positive effects on the ARG pro les during composting, and the co-selective pressure imposed by heavy metals was favorable for ARG enrichment.

Materials And Methods
Experimental materials OTC and Cu were added to swine manure compost, and the effects of OTC and Cu alone and in combination on ARGs and their pathogenic hosts were compared to determine their potential environmental risks. The amounts added were determined based on the average concentrations in swine manure [29][30][31]. The swine manure used in this study was collected from a medium-sized farm in Yangling, Shaanxi Province, China. Feeds containing antibiotics or heavy metals were stopped for 2 weeks before sampling. Fresh feces were transported immediately back to the laboratory and stored in a refrigerator at 4°C for future use. Wheat straw was collected from an experimental eld at Northwest A&F University, China. The straw was chopped to about 1-2 cm after air drying. The moisture content and C/N ratio of the initial compost were adjusted to 60% and 30, respectively. OTC (purity > 98%, Sigma) and CuCl 2 (purity ≥ 99%, China) were prepared as 10 mg/mL and 50 mg/mL stock solutions, respectively.
Before the experiment, the OTC and CuCl 2 stock solutions were diluted to suitable concentrations with sterile water and mixed with pig manure. The supplementary materials shows the basic properties of the raw composting materials.

Experimental setup and sample collection
The effective capacity of the pilot-scale compost reactor was 70 L. Each reactor was lled with 25 kg of compost mixture. Four compost mixtures were tested in triplicate, where 10 mg/kg OTC (O), 500 mg/kg Cu (Cu), and 10 mg/kg OTC + 500 mg/kg Cu (OCu) were added based on the dry weight of the swine manure, and a control group (CK) was prepared without any added OTC or Cu. The entire composting process lasted 42 days and the compost was turned over every 7 days from day 3 in order to fully mix the composting matrix and reduce edge effects. At the beginning of the composting process, the mixed and balanced raw composting materials were collected as samples on day 0, and compost samples were then collected subsequently on days 10 and 42. Finally, each sample weighing 100 g was freeze dried immediately in a freeze dryer (Beijing Songyuan, China) and pulverized to 1 mm with an ultracentrifugal mill (Retsch Z200, Germany), before storing at − 80°C for DNA extraction.

Determination of OTC and diethylenetriaminepentaacetic acid (DTPA)-extractable heavy metal concentrations
The total Cu and DTPA-extractable Cu contents of compost samples were determined as described previously [32]. OTC residues were determined as described Duan et al. [33] and the full details are provided in the supplementary information.
DNA extraction, library construction, and sequencing The 0.1000 g composting sample was weighed and the total genomic DNA was extracted in triplicate using FastDNA kit (MP Biomedicals, France). DNA from each experimental treatment group was combined and mixed well. After genomic DNA extraction, the concentration was detected with a TBS-380 system, while the purity was con rmed using a NanoDrop200 system and the integrity was detected by 1% agarose gel electrophoresis. DNA was fragmented using a Covaris M220 ultrasonicator (Gene Corporation, China) and a paired-end fragment library (approximately 300 bp) was constructed using a TruSeq™ DNA Sample Prep Kit (Illumina, San Diego, CA, USA).
Paired-end metagenomic sequencing was performed on the Illumina HiSeq4000 platform (Illumina Inc., San Diego, CA, USA) using a HiSeq 3000/4000 SBS kit and HiSeq 3000/4000 PE Cluster kit according to the manufacturer's instructions. Quality ltering of the data was conducted before subsequent biological analyses by using Seqprep (https://github.com/jstjohn/SeqPrep) to remove the adapter sequences at the 3′ and 5′ ends, and low-quality reads (length < 50 bp or with a quality value < 20 or having N bases) were removed using Sickle (https://github.com/najoshi/sickle). After quality control, metagenomics data were assembled using MEGAHIT (https://github.com/voutcn/megahit). Contigs ≥ 300 bp were selected as the nal assembly results and the contigs were then used for further gene prediction and annotation.

Identi cation of ARGs, MRGs, and MGEs
The metagenomic sequencing data obtained for each sample were compared with the structured ARG database SARG v2.0 (which integrates the sequences in the ARDB and CARD databases, as well as the latest protein sequences from the NCBI-NR database) to determine the corresponding functional annotations for ARGs [26]. MRGs were annotated by searching the BacMet database for proven MRGs (http://bacmet.biomedicine.gu.se/index.html). This study focused on copper resistance genes (CRGs) because Cu was applied in the experimental treatments. In addition, annotation information for MGEs was obtained from the Fungene database (http://fungene.cme.msu.edu/). If the best hit shared similarity with the reference sequence of not less than 80% and an alignment length of not less than 75%, then it was considered to be an like sequence. BLAST searches were conducted with a cutoff E-value < 10 − 7 . In order to further compare the distributions of the target gene in the microbial community, the abundance of the target gene was normalized and expressed as the target gene copy number per 16S rRNA (copy/16S rRNA).

Identi cation of pathogenic hosts of target genes
To further identify the hosts of the target genes, BLASTX searches were conducted for contigs with an Evalue < 10 − 10 to predict open reading frames (ORFs). An ORF sequence was identi ed as an ARG-like ORF when the optimal BLASTX hit alignment with the target gene sequence satis ed 80% similarity and 70% coverage. Hu et al. [34] suggested that this recognition method obtains high accuracy (accuracy = 99.1%).
BLASTP was used to annotate the contigs carrying the target genes against the NCBI NR database for taxonomic annotation. If E-value < 10 − 5 , the taxonomy was determined based on a minimum similarity of 95% and a read length greater than 95%. In addition, annotation of virulence factors was conducted using BLASTP search (Version 2.2.28+) against the VFDB database (http://www.mgc.ac.cn/VFs/) with an Evalue cutoff of 10 − 5 . Further comparisons were performed based on the HPB virulence factor database and previously published pathogen genome sequences [3,35] to identify HPB in compost.
Real-time quantitative polymerase chain reaction(qPCR) The partial ARG abundance of all samples was further quanti ed using qPCR. By normalizing the 16S rRNA genes, the units of ARG were converted into relative abundances as ARG copies of each 16S rRNA gene. The supplementary materials listed the ampli cation information of ARGs and 16S rRNA genes. Availability of data and materials

Statistical analysis and visualization of biological data
The data and result supporting the ndings of the study are available in this article and its supplementary information les.
Ethics approval and consent to participate Not applicable.

Consent for publication
Not applicable.  Dynamic changes in pathogenic hosts of ARGs during composting. ARGs in brackets indicate that they were carried by HPB. CK: with no added OTC or Cu; O: 10 mg/kg OTC; Cu: 500 mg/kg Cu; OCu: 10 mg/kg OTC + 500 mg/kg Cu.

Supplementary Files
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