Changes in microbial community structure during pig manure composting and its relationship to the fate of antibiotics and antibiotic resistance genes

Journal Pre-proof Changes in microbial community structure during pig manure composting and its relationship to the fates of antibiotics and antibiotic resistance genes Yuanwang Liu (Conceptualization) (Methodology) (Writing - original draft), Dengmiao Cheng (Data curation) (Methodology), Jianming Xue (Supervision) (Writing - review and editing), Louise Weaver (Writing - review and editing), Steve A. Wakelin (Writing - review and editing), Yao Feng (Software) (Investigation), Zhaojun Li (Conceptualization) (Funding acquisition) (Project administration) (Resources) (Supervision)

PII:

S0304-3894(20)30068-6

DOI:

https://doi.org/10.1016/j.jhazmat.2020.122082

Reference:

HAZMAT 122082

To appear in:

Journal of Hazardous Materials

Received Date:

3 September 2019

Revised Date:

30 December 2019

Accepted Date:

12 January 2020

Please cite this article as: Liu Y, Cheng D, Xue J, Weaver L, Wakelin SA, Feng Y, Li Z, Changes in microbial community structure during pig manure composting and its relationship to the fates of antibiotics and antibiotic resistance genes, Journal of Hazardous Materials (2020), doi: https://doi.org/10.1016/j.jhazmat.2020.122082

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Title Page

Title: Changes in microbial community structure during pig manure composting and its relationship to the fates of antibiotics and antibiotic resistance genes Authors:

Yuanwang Liua,b, Dengmiao Chengc, Jianming Xued,e, Louise Weaverb, Steve A. Wakeline, Yao Fenga,

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Zhaojun Lia,*

Affiliations

Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, China-New Zealand Joint

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a

Laboratory for soil Molecular Ecology, Institute of Agricultural Resources and Regional Planning,

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Chinese Academy of Agricultural Sciences, Beijing 100081, China b

Institute of Environmental Science and Research Ltd, Christchurch 8041, New Zealand

Research Center for Eco-Environmental Engineering, Dongguan University of Technology, Dongguan

523808, China d

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c

College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China

Scion, Private Bag 29237, Christchurch, New Zealand

Corresponding author. Tel: +86 82108657. Fax: +86 10 8210 9640. E-mail: [email protected].

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e

Graphical abstract

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Antibiotic types affected the microbial composition during composting Temperature and pH accounted for higher explanations for bacterial composition Thermophilic stage played a key role in the reduction of ARGs, especially TARGs The potential hosts of QARGs and SARGs were more affected by mixture of antibiotics

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   

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Highlights

Abstract

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Animal manure containing veterinary antibiotics is a significant source of microbial antibiotic resistance genes (ARGs). Composting of animal manure with wheat straw and sawdust was explored as

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a means to reduce ARGs load in the final material. The effects of ciprofloxacin, oxytetracycline, sulfamerazine on the bacterial community composition, and how this then affected the removal of seven tetracycline resistance genes (TARGs), four sulfonamide resistance genes (SARGs), and two

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fluoroquinolone resistance genes (QARGs) were investigated. Treatments receiving either ciprofloxacin or the three mixed antibiotics had reduced bacterial alpha-diversity and displayed shifts in the abundance of Proteobacteria and Firmicutes. This demonstrated that different antibiotics played an important role in bacterial community composition. Furthermore, variation in the physicochemical

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properties of compost, particularly pH and temperature, was also strongly linked to shifts in bacterial composition over time. Based on network analysis, the reduction of TARGs were associated with loss of Pseudomonas, Pseudoxanthomonas, Pusillimonas, Aquamicrobium, Ureibacillus, Lysinibacillus, Bacillus and Brachybacterium during the thermophilic stage. However, QARGs and SARGs were more strongly affected by the presence of multiple antibiotics. Our results have important implications for reducing the spread of certain ARGs by controlling the composting temperature, pH or the antibiotics species used in husbandry.

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Key words: antibiotic; pig manure; antibiotic resistance gene; microbial community structure; network analysis

Abbreviations ARGs: Antibiotic Resistance Genes TARGs: Tetracycline Resistance Genes SARGs: Sulfonamide Resistance Genes

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QARGs: Fluoroquinolone Resistance Genes WHO: World Health Organization TOC: Total Organic Carbon TN: Total Nitrogen

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OTUs: Operational Taxonomic Units PCA: Principal Component Analysis

1. Introduction

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RDA: Redundancy Discriminant Analysis

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PERMANOVA: Permutational Multivariate Analysis of Variance

The emergence and spread of antibiotic resistance genes (ARGs) in the environment, especially

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among bacterial pathogens, is a serious global issue affecting public health [1, 2]. In 2018, surveillance data from the World Health Organization (WHO) revealed high incidence of antibiotic resistant bacteria in both developed and developing countries [3]. The movement of these antibiotic resistant taxa, or the key genetic elements conferring resistance, into human-associated microorganisms represents a serious

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challenge for the clinic effectiveness of antibiotics in the future [4]. The presence of ARGs has been reported in samples of 30,000-year-old permafrost, long before

human use and industrial production [5]. However, selection pressure resulting from high rates of antibiotic use has dramatically increased the emergence and spread of ARGs in the environment [6], thus impacting effectiveness of antibiotics in disease treatment [7]. In China alone, it has been reported that more than 100,000 tons of antibiotics are consumed by livestock industry every year [8]. However, many antibiotics are poorly absorbed or metabolized by animals and, as such, 30%-90% of those used

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enter the environment (faecal deposition) as the in the parent compound form [9]. As such, livestock manure is a significant source of antibiotics as a reservoir of resistant microbial taxa and their resistance genes [10]. The land-based application of animal manure (fertilizer source) is, therefore, a key point of entry of ARGs into the soil and water environment, and represents a pathway for ARGs into the food chain and, ultimately, societies [1, 11, 12, 13, 14, 15]. Composting is an environmentally and economically sound practice for the processing of solid organic wastes [16, 17]. While some studies have reported that composting can effectively reduce ARGs in manure [18], compositing has been found to have little effect elsewhere [19, 20]. This

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variation may be associated with compositing feed material and conditions. Qian et al. [10] reported that the trajectory of ARGs during composting followed different fates among manure types. For

example, pig manure was more likely to have higher initial abundance of ARGs than other manure types [10]. However, the starting concentration may have only a limited impact on final (post

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composting) concentrations, with factors such as the mixture of different ARG’s present, through to

abundance and composition of key microbial consortia during composting, also affecting composting

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outcomes [10, 21].

Until now, few studies have comparatively evaluated the effects of individual and mixed

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antibiotics on the fate of ARGs alongside the abundance and composition of microorganisms during composting. We hypothesize that different antibiotics have different impacts on microbial community composition during composting, thus affecting the fate of ARG removal. To test this, the antibiotics,

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ciprofloxacin, sulfamerazine and oxytetracycline (commonly used fluoroquinolones, sulfonamides and tetracyclines, respectively), were chosen to investigate the effects of antibiotic types on microbial community structures and evaluate the correlations between ARGs, antibiotics, microbial community

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composition.

2. Materials and Methods 2.1 Composting process and sampling Details of the substrates used for this composting have been described previously [22]. Briefly, 12

pigs were fed without antibiotics for two weeks in a livestock farm in Beijing. Fresh manure was collected and delivered to a nearby organic fertilizer factory. The manure was air dried to a moisture content between 20-30%, then crushing and sieving through a 5-mm mesh. The manure had a total

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organic carbon (TOC) content of 29.62%, total nitrogen (TN) of 2.50%, and pH of 7.57. The concentrations of ciprofloxacin, sulfamerazine and oxytetracycline, were below the detection limits mentioned in our previous study [23]. The wheat straw and sawdust collected from neighboring farms had TOC contents of 44.63% and 49.27%, and TN contents of 1.13% and 0.09%, respectively. The manure, wheat straw, and sawdust were used to make five composting treatments: (1) pig manure + wheat straw + sawdust (Control); (2) pig manure + wheat straw + sawdust + 10 mg kg−1 ciprofloxacin (CIP); (3) pig manure + wheat straw + sawdust + 10 mg kg−1 sulfamerazine (SML); (4) pig manure + wheat straw + sawdust + 200 mg kg−1 oxytetracycline (OTC); (5) pig manure + wheat

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straw + sawdust + three antibiotics (CIP, SML and OTC) at concentrations used in treatments 2-4 (MIX). Each composting treatment was prepared in triplicate. To ensure samples were homogenized, the target antibiotics were dissolved in aqueous solution (approximately 2 L) and sprayed over the

swine manures, stirring constantly. The Control compost mixture (1) was prepared using water without

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added antibiotics. Then, the manure mixes with specifically assigned antibiotics, were mixed

thoroughly with wheat straw and sawdust at the ratios, by weight, of 15 (compost mixture): 8.76 (wheat

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straw): 3.75 (sawdust) to give a final C:N ratio of approximately 25:1 [24]. Distilled water was added to the mixed composts to obtain a final moisture content of 55% by weight for all treatments [6].

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The mixed materials (55 kg samples) were transferred into bubble boxes of approximately 137 l (800 mm × 490 mm × 350 mm) with temperature sensors embedded in the middle of the piles. The boxes were covered and the laboratory-scale composting conducted over 42 days. During the

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composting period, the moisture levels were not re-adjusted. The piles were turned every day in the first week and every two days after the first week to maintain the bio-oxidation process. Samples (approximate 0.3 kg) were collected by mixing subsamples taken from the bottom, middle and top layers of each pile on days 3, 21 and 42, representing thermophilic, cooling, and mature stages,

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respectively. One sub-sample was stored at -80°C for DNA extraction at a later date. The rest was used for the determination of antibiotics and physicochemical properties. The results of the antibiotics and physicochemical properties have been shown in our previous publication [22].

2.2 DNA extraction, sequencing and real-time (RT) qPCR The total DNA was extracted from 0.2 g composting sample using the PowerSoil DNA isolation kit following the manufacturer’s instructions (Omega Bio-tek, Norcross, GA, U.S.). DNA integrity and

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concentration were measured using agarose gel electrophoresis and Qubit fluorescence, respectively. To assess the bacterial community composition, V3-V4 variable region of 16S rRNA gene was amplified using 341F (5’-CCTAYGGGRBGCASCAG- 3’) and 806R (5’-GGACTACNNGGGTATCTAAT-3’) primers [20]. The PCR reaction system consisted of 10 ng of template DNA, 0.8 μl of both forward and reverse primers (5 μM each), 4 μl of 5×FastPfu Buffer, 2 μl of 2.5 mM dNTPs and 0.4 μl of FastPfu Taq polymerase. The PCR conditions were as follows: Initial denaturation for 5 min at 95°C, followed by 27 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 45 s. Thermocycling ended with a final elongation step for 10 min at 72°C [20]. The amplified 16S rRNA products were purified using DNA

Total Genomics Solution (TGS) Institute (Shenzhen, China).

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Extraction Kit (Tiangen DNA extraction Kit, China) and sequenced on a Illumina HiSeq 2500 platform

The abundances of seven tetracycline resistance genes (tetM, tetO, tetQ, tetW, tetG, tetK, tetX),

four sulfonamide resistance genes (dfrA1, dfrA7, sul1 and sul2), two fluoroquinolone resistance genes

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(qepA and qnrB), and 16S rRNA gene were measured using Real-Time qPCR on ABI VIIA™ 7

Real-Time PCR system (Applied Biosystems, Life Technologies, Foster City, CA, USA) in Wcgene

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Biotech (Shanghai, China). Details and main results of the amplifications are shown in our previous

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study [22].

2.3 Bioinformatics and statistical analyses

The raw paired-end sequence reads were assembled after quality filtering using Quantitative

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Insights into Microbial Ecology software package (QIIME, V1.9.0, http://qiime.org/index.html) [25]. The obtained effective tags were clustered into operational taxonomic units (OTUs) at 97% sequence identity using Uparse (http://drive5.com/uparse/) [26]. Shannon’s and the Chao1 indices were calculated within QIIME to assess alpha-diversity [25]. To evaluate the differences of bacterial

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community beta-diversity (composition) between treatments, principal components analysis (PCA) was performed, at genus level classification, in Canoco 5.0, and permutation-based multivariate analysis of variance (PERMANOVA) used to test for significance of treatment effects in R version 3.6.1 [27]. Network analysis was performed based on the Spearman correlation coefficient using Cytoscape 3.6.0 to analyze interrelationships among different ARGs and the relationships between specific ARGs and the main genera (above 1%), by which the potential hosts of specific ARGs were assessed [28]. Redundancy discriminant analysis (RDA; Canoco 5.0) was further used to explore relationships

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between different ARGs and microbial genera (present at >1%), as well as the associations between with physicochemical properties, for the five treatments. Analysis of variance (ANOVA) and multiple comparison tests (Duncan’s multiple range test) were conducted using SPSS V.19 (IBM, USA) and visualized using Excel 2007 (Microsoft, USA) and OriginPro 8.5 (OriginLab, USA).

3. Results and discussion 3.1 Bacterial diversity After the raw paired-end reads were quality filtered and assembled, 1,558,833 sequences were

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obtained. The number of effective sequences per sample ranged from 30,163 to 44,982 and these were clustered into 26,900 OTUs (Operational Taxonomy Units) using 97% sequence identity (Table S1). Shannon’s index and Chao1 index were used to evaluate microbial alpha diversity during

composting; the data are given in Table S1. Shannon’s index balances microbial richness and evenness,

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while Chao1 index is used to estimate microbial taxa abundance. Both the CIP and MIX treatments, at cooling stage (i.e. day 21), showed significantly lower Shannon’s indices than other treatments. This

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indicates a selective effect of ciprofloxacin against bacterial taxa at composting stage. CIP and MIX treatments also had lower Chao1 indices, suggesting an effect of ciprofloxacin on bacterial richness.

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Separation of treatments based on community structure (beta-diversity) are given in the PCA ordination plot (Fig. 1). Axis PC1 and PC2 explained 76.40% and 11.04%, respectively, of the genera level variation in community composition. Samples at the thermophilic stage (3 d) were completely

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separate from the other treatment stages (cooling maturation). This was likely due to differences in temperature or pH among the composting stages, as explained in our previous study [22]. Treatments at days 21 and 42 were grouped along PC1 but separated across the second (PC2) axis. This separation could not be linked with temperature and, therefore, variables such as organic matter and

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concentrations of ciprofloxacin may have driven the differences [22].

3.2 Bacterial community composition at phyla level A total of twenty-four bacterial phyla were found across all the compost samples. Sixteen,

twenty-four, and twenty-two phyla were present in thermophilic stage (3 d), cooling stage (21d) and mature stage (42 d), respectively; the nine with a total relative abundance >1% are shown in Fig. 2A. Similar to a previous study [24, 29], Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes were

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the predominant phyla during the composting, accounting for 48.58%, 15.77%, 15.34% and 9.83%, of the phyla respectively. In most aerobic composting studies, Proteobacteria are typically the most (or second most) dominant phyla [20, 24, 30]. In the present study, Proteobacteria, accounting for approximately 44.70%, 54.42% and 46.62% at thermophilic, cooling and mature stages respectively, and had the highest abundance in all samples except the Control on day 3 (Firmicutes dominant sample). This may be attributed to the significant inhibition of the three antibiotics on Firmicutes at the thermophilic stage. Actinobacteria were the second most abundant phylum (Fig. 2A). These taxa have been found at

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relatively high abundance in other co-composting studies that have used manure accompanied by substrates rich in cellulose and lignose (e.g. rice straw/chaff, hay, hardwood, wheat straw, sawdust) [24, 30, 31, 32, 33]. This indicates a link between Actinobacteria and the degradation of cellulose and

lignose. The widespread use of Actinobacteria as a source of antibiotics may partly explain its high

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abundance during this composting period; i.e. antibiotic tolerance [6].

Firmicutes often exhibit a relative high enrichment throughout composting due to temperature

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tolerance [20]. Thus, it was not surprising to find distinctly higher abundances of Firmicutes at the thermophilic stage (23.01%) than the other two stages (3.41% and 5.52%) in the present study (Fig.

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2A). Our results, at least partially, supported the previous studies that Firmicutes abundance is linked with decomposition of organic matter at the thermophilic stage, while Actinobacteria having a stronger association with this process during lower-temperature stages [20, 32]. Firmicutes were less abundant

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in CIP and MIX (with ciprofloxacin added) treatments indicating sensitivity to ciprofloxacin rather than oxytetracycline or sulfamerazine.

Bacteroidetes was the fourth abundant phylum during the composting period (Fig. 2A). These taxa were in distinctly higher abundance at the cooling compared with thermophilic stage, indicating lack of

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thermophilic tolerance characteristics. This is supported by observations from other research groups [31, 34].

There was an effect of antibiotic administration at phyla level, compared with the control compost,

at the thermophilic stage (Fig 2A). The largest effect was seen in the Firmicutes, which reduced in the presence of antibiotics, especially CIP and MIX. An opposite effect was observed, compared to the control for Actinobacteria, where and increase in relative abundance was seen, especially with CIP and MIX treatments. During the cooling stage most effect of antibiotics was seen again within CIP and

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MIX treatments. An increase in Proteobacteria and a decrease in Bacteroidetes was observed for CIP and MIX, compared with control (Fig 2A). These indicate that ciprofloxacin displays more effects on bacterial community composition during composting. Less differences in relative abundance were observed in the maturation stage and across the control and all treatments the relative abundances seen were similar, which may result from the less antibiotics detected at this stage. 3.3 Bacterial community composition at genus level Genus level bacterial taxa across all treatments with relative abundance >1% are shown in Fig. 2B. The number of major genera (i.e. > 1%) detected at thermophilic stage (17 genera) was more than that

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at cooling (10 genera) and mature stages (13 genera) across all treatments. Comparing the treatments with the Control compost, increases in specific genera were observed, especially for CIP and MIX

treatments. In thermophilic stage, an increase in Luteimonas genera was observed across all antibiotic treatments compared with the Control. An effect on the relative abundance of Pseudomonas was seen

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for CIP and MIX treatments only. This demonstrated the variation and specific effects of different

antibiotics on bacterial communities. In the cooling stage there was a big impact of antibiotics on the

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bacterial composition, compared to the Control and overall there was a reduction in genera observed and a large increase in dominance of specific genera present. The biggest effect was on the relative

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abundance of Halomonas, which increased, especially with CIP and MIX treatments. Less differences were seen in the maturation stage of composting across the control and all treatments had no significant increase or decrease in the dominant genera observed.

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Halomonas (Proteobacteria) was the most abundant genus throughout composting. This is a genus of halophilic microorganisms that can grow in alkaline and salty environments [35]. The abundance of Halomonas increased from 8.91% at the thermophilic stage to 25.06% at the cooling stage, and growth was coupled with an increase in pH from 6.53 to 8.30; this association has been noted previously [22].

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On day 21, Halomonas had high abundance in the CIP and MIX treatments, and this was also coincided with relatively high pH (8.63 and 8.40, respectively). These results indicate that pH plays a key role in selection for Halomonas during composting [36]. We also infer that Halomonas is more sensitive to oxytetracycline and sulfamerazine than ciprofloxacin, and also ciprofloxacin could reduce the effects of oxytetracycline and sulfamerazine on Halomonas (MIX treatment). The ability of Halomonas to degrade recalcitrant biomass [37] may further explain its persistence at the later stages of composting; refractory organic matter is often microbially decomposed after the thermophilic stage is complete [37,

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38]. Pseudomonas (Proteobacteria genus) are often isolated from different environments including animal guts [38, 39]. The abundance of Pseudomonas has previously been correlated with enriched ARGs, especially those related to tetracyclines, sulfonamides and aminoglycosides antibiotics during composting [40, 41, 42]. In the present study, Pseudomonas had distinctly lower abundance values in the CIP and MIX treatments. This further indicates tolerance of Pseudomonas to oxytetracycline and sulfamerazine compared with than ciprofloxacin. Ureibacillus, Bacillus and Lysinibacillus (Firmicutes), are thermotolerant genera typically found

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in compost particularly during the thermophilic stage of aerobic composting [43, 44]. Compared to other treatments, MIX harbored the most Ureibacillus; this coincided with the highest temperature

(61.2oC) and lower content of TOC on day 3, as the data shown in our previous publication [22]. This suggested the coupling of Ureibacillus abundance with heat release and rapid organic matter

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decomposition. Bacillus are the most frequently detected Firmicutes found during the composting period, especially at the thermophilic stage [43]. As suggested in previous studies, Bacillus often

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showed resistance to various antibiotics and their presence is linked with degradation of antibiotics, organic matter, and nitrification [6, 20, 45]. This may explain the insignificant differences in the

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abundance of Bacillus among the five treatments. Lysinibacillus accounted for 6.27%, 0.22% and 0.43% of taxa in the thermophilic, cooling, and mature composting stages. This group had significantly lower

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abundance in the MIX treatment compared with any of the individual antibiotics.

3.4 Associations between bacterial community composition and physicochemical properties Non-parametric correlations between the dominant bacteria and physicochemical properties of composting piles are given in Fig. 3. Based on the different composting stages, the enriched genera

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included three groups: (A) bacteria enriched on the 3rd day; (B) bacteria dominated on the 21st day; and (C), bacteria enriched on the 42nd day. These groups clustered separately and showed distinctly different correlation patterns with the physicochemical properties of the compost (Fig 3). The genera in the A-cluster, thermotolerant bacteria mainly present at the thermophilic phase, were positively related (P<0.05) to total nitrogen (TN), moisture, temperature and total organic carbon (TOC). It is interesting to note that most bacteria increases observed were in the antibiotic administered composts. In previous studies, Bacillus and Oceanobacillus have been found to have relatively high abundances at the end of

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composting chicken manure and antibiotic fermentation residues [16, 20, 46]. This may be attributed to the materials used and their specific physicochemical properties. The abundances of Halomonas and Flavobacterium (group B cluster), were not significantly associated with any of the physicochemical properties assessed in this study, except for an association between Halomonas and pH (p<0.05). At the mature composting stage, the dominant genera were in cluster C. The enrichment of these taxa occurred alongside an increase in pH, and decline of TN, moisture, temperature, and TOC. This was supported by the RDA conducted between the dominant genera (>1%) and physicochemical

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properties (Fig. S1). According to the results, variation in physicochemical properties explained 64.43% of total variance in bacterial community composition, with pH and temperature accounting for a large component of this (27.2% and 26.1%, respectively).

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3.5 The relationships among ARGs and the main bacterial drivers for dynamics of ARGs

Investigation of the co-occurrence of different ARGs makes it convenient to predicate abundance

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of total or specific ARGs in the environment [10, 47]. In this study, network analysis was employed to explore the interrelationships among different ARGs (Fig. 4A and Table S2). Co-association was

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common between tetracyclines resistance genes (TARGs) and quinolone (QARGs) or sulfonamides resistance genes (SARGs). Furthermore, many TARGs were associated with other TARG’s. These results agreed with previous findings [10, 48, 49] and is likely underpinned by co-occurrence of ARGs

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in the same host (bacterium), or even in the same DNA fragments. This enables spread in the environment via propagation of bacteria and/or DNA fragments (i.e. horizontal gene transfer, HGT). However, bacterial community composition is often found to have a dominant role in the spread of ARGs [33, 42]. This was supported by RDA analysis, where community composition explained most of

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the variance in ARG occurrence in the different composting treatments (Fig. 5). Given this, we focused analysis of establishing relationships between the main bacteria taxa present and occurrence of ARGs. Despite Halomonas having the highest abundance during the composting period (Table S3), the

presence of this genus was not significantly related to the fate of ARGs. Furthermore, the genera Luteimonas, Truepera, Anseongella, Altererythrobacter, and Steroidobacter each only had negative correlations with TARGs. As these genera are mostly associated with cooling and mature stages of composting, these findings indicate that microbial processes occurring during the thermophilic phase

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were primarily associated with ARG decline. Relationships among the other nine genera (>1%), all of which showed significant correlations with different ARGs, were assessed using network analysis (Fig. 4B). Proteobacteria (Pseudomonas, Pseudoxanthomonas, Pusillimonas, and Aquamicrobium), Firmicutes (Ureibacillus, Lysinibacillus and Bacillus), Actinobacteria (Brachybacterium) and Bacteroidetes (Flavobacterium) were all assocatied with the fate of ARGs (TARGs, QARGs and SARGs). In the previous study [48], these four phyla were also found to be associated with the fate of TARGs, SARGs, and macrolide resistance genes during composting of swine manure and wheat straw. In the present study, the four TARGs encoding

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ribosomal protection proteins including tetM, tetO, tetQ and tetW, and one TARG encoding efflux pump (tetK) were linked with the same eight taxa. These bacteria were all thermophilic genera and

became inactive at the later composting stages where TARGs were absent. This supports the potential to decrease the transfer of ARGs through altering composting processes, especially achieving

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sufficiently high temperatures [49].

It has been reported previously that tetX is significantly associated with the presence

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Lysinibacillus, Pseudomonas, Psychrobacter, Solibacillus and Acinetobacter [24, 39, 48], however we only found an association with Lysinibacillus . Similar to our study, Qian et al. [49] also reported that

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tetC decreased significantly after the thermophilic phase. On the contrary, others pointed out that tetC increased along with the enrichment of its other potential mesophilic bacterial hosts [6, 50]. This demonstrates the importance of microbial composition on the fate of ARGs during composting.

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For QARGs, qepA was not correlated with any of main bacterial taxa found in this study. Previously, however, removal of qnrB has been accompanied with the decrease of Lysinibacillus and Brachybacterium [10]. Network analysis also showed that qnrB and qnrS potentially shared the same host, Brachybacterium. In addition, qnrS was also linked to Lysinibacillus, whereas qnrB also had other

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potential hosts, Ureibacillus and Pseudoxanthomonas (Fig. 4B). SARGs, exhibiting much higher abundance than QARGs [22], and were significantly associated

with the four most abundant bacterial phyla bacteria classified throughout the composting. These include Proteobacteria (Pseudomonas, Pseudoxanthomonas, Pusillimonas, and Aquamicrobium), Firmicutes (Bacillus), Actinobacteria (Brachybacterium), and Bacteriodetes (Flavobacterium) (Fig. 4B). Qian et al. [10] reported that dfrA1 is abundant in chicken, pig and cow manure composting, however no associations with bacteria involved were made. In this study, the potential hosts of dfrA1 were

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Pseudoxanthomonas, Pusillimonas, Aquamicrobium and Bacillus. Similarly, Sul1 and sul2 had six and five potential thermophilic hosts, respectively (Fig. 4B). Within the SARGs, Proteobacteria were the dominant phylum, and Flavobacterium was the only mesophilic bacteria associated with SARGs [49]. The results of network analysis are supported by RDA analysis, which showed the differences in the composition of ARGs among different compositing treatments, and links with the bacteria present (Fig. 5). Across all three composting stages (3d, 21d, and 42d), the CIP treatment consistently separated from Control and MIX along the primary axis (RDA 1), which explained the majority (74.86%) of the variance (Fig. 5A). This indicated that a strong association between ciprofloxacin and QARGs

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dynamics. The close distance between Control and MIX indicates that the mixture of the three antibiotics could reduce the selective pressure of ciprofloxacin, maybe by limiting the reproduction of

the bacteria that were resistant to ciprofloxacin, such as Lysinibacillus and Brachybacterium (negative correlations with Control and MIX along RDA axis 1).

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According to Fig. 5B (TARGs plot), the Control, OTC and MIX treatments on day 3 were

separated along axis 1 (RDA1; 59.18% of the variance). Separation in TARGs was most closely related

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to the abundance of thermophilic bacteria, a finding supported by the network analysis (see previous results and discussion; Fig. 4). This further demonstrates the importance of composting temperature as

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a key factor mediating the fate of TARGs during the composting process. For all composting stages, the samples from the MIX treatment was separated from others along RDA axis 2 (27.13%). This demonstrates that the antibiotic mixtures also affected the distribution of TARGs present.

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Separation in SARGs across treatments are shown in Fig. 5C. The Control and SML treatments had similar SARG composition at each timepoint, while those in the MIX treatment were distinct (especially on days 3 and 21). These results suggesting that ciprofloxacin and oxytetracycline could enhance the effects of sulfamerazine on SARGs.

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By analyzing the correlations between ARGs and main bacterial genera using RDA and network analysis, the potential bacterial hosts for specific ARGs including QARGs, TARGs and SARGs were speculated. However, it is not so sufficient to state which taxa are hosts of certain ARGs. Therefore, in the future, the combination of correlation analysis, culture-dependent method and metagenomics should be performed for further confirmation of the relationships between hosts, especially pathogenic and ARGs.

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4. Conclusion During the co-composting of pig manure with wheat straw and sawdust, the community of bacterial present was significantly (p<0.05) affected by both the presence of different antibiotics and also the physicochemical properties of the compost (particularly temperature and pH). We propose that bacteria in the phylum Firmicutes have higher sensitivity to ciprofloxacin than to oxytetracycline and sulfamerazine, and were responsible for the decomposition of organic matter at thermophilic stage. In contrast, Actinobacteria and Bacteroidetes are more abundant during low-temperature phases of composting. The reduction in ARGs, and especially TARGs, was linked with Pseudomonas,

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Pseudoxanthomonas, Pusillimonas, Aquamicrobium, Ureibacillus, Lysinibacillus Bacillus and Brachybacterium during the thermophilic composting stage. In contrast, the potential hosts of QARGs

and SARGs were more affected by the mixture of antibiotics present. The spread of ARGs from animal manure can, therefore, be reduced through microbial processes occurring in composting. Close

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monitoring and management of key parameters, such as pH and temperature, may present an

opportunity for ensuring effective ARG removal. In addition, the use of mixed antibiotics and CIP

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appears to have the most effect on the community composition and showed a significant shift in community composition compared to the control. Careful consideration on the administration of mixed

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antibiotics needs to be made as the results demonstrate an increased potential for antibiotic and ARG transmission to the environment. It does appear that a maturation stage of composting affords the bacterial community to adjust to a wider diversity closer to that of a compost without antibiotic

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presence. This could indicate that careful composting including adequate maturation stage could allow for the bacterial community to recover, thus reducing the effect on the environment.

Credit Author Statement

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Yuanwang Liu ： Conceptualization, Methodology, Writing- Original draft preparation Dengmiao Cheng: Data curation, Methodology Jianming Xue: Supervision, Writing - review & editing Louise Weaver: Writing - review & editing Steve A Wakelin: Writing - review & editing Yao Feng: Software, Investigation. Zhaojun Li: Conceptualization, Funding acquisition, Project administration, Resources, Supervision Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Acknowledgements This study was financially supported by the National Key R&D Program of China (No.

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2018YFD0500206) and the National Natural Science Foundation of China (No. 31972946).

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Figure legends

Fig. 1. PCA ordination for bacterial community similarity of different antibiotic treatments (mean, n=3) on day 3, day 21, and day 42 at OTU level. Diamond symbols represent the Control treatment, circle symbols represent CIP treatment, and square symbols the OTC treatment. The upward pointing triangle symbols represent the SML treatment and the downward triangle symbols represent the MIX treatment. The red symbols are treatments at day 3 (thermophilic stage), and the blue symbols are treatments at day 21 (cooling stage). The green symbols are treatments at day 42 (maturation stage).

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Fig. 2. Bacterial community composition at phylum (A) and genus (B) levels associated with different antibiotic treatments on days 3, 21 and 42 of composting. Only classified bacteria with abundance of >1% during the composting stage are shown. Bars display the standard error.

Fig. 3. Correlations between main genera (>1% in any individual composting stage) plotted on the Y-axis and physicochemical properties plotted on the X-axis based on Spearman’s rank analysis. “+” and “*” represent the significant correlations at the 0.05 and 0.01 levels, respectively. The genera

right corner). TN, total nitrogen; TOC, total organic carbon.

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labeled with different colors are the most dominant in the specific treatments if the same colors (see top

Fig. 4. Network analyses showing the co-occurrence of ARGs (A), and the co-occurrence of ARGs and

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their potential bacterial hosts (B). Nodes in different colors correspond to specific ARGs or bacterial

phyla, and edges represent significantly positive correlations between specific nodes (p<0.05). QARG,

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quinolone resistance genes; SARG, sulfonamides resistance genes; TARG, tetracycline resistance

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genes.

Fig. 5. RDA triplots showing the relationships between main bacterial genera (>1%) occurred in different antibiotic treatments (mean, n=3) and QARGs (A), TARGs (B), and SARGs (C). Diamond

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symbols represent the Control treatment and circle symbols represent MIX treatment. The upward pointing triangle symbols in A, B and C represent CIP, OTC and SML treatment, respectively. The red symbols are treatments at day 3 (thermophilic stage), and the purple symbols are treatments at day 21

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(cooling stage). The brown symbols are treatments at day 42 (maturation stage).

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Fig. 5.

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