Prevalence of Antibiotic Resistance Genes and Bacterial Pathogens in

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Prevalence of antibiotic resistance genes and bacterial pathogens in longterm manured greenhouse soils as revealed by metagenomic survey Hua Fang, Huifang Wang, Lin Cai, and Yunlong Yu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es504157v • Publication Date (Web): 16 Dec 2014 Downloaded from http://pubs.acs.org on December 24, 2014

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Environmental Science & Technology

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Prevalence of antibiotic resistance genes and bacterial pathogens in long-term manured

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greenhouse soils as revealed by metagenomic survey

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Hua Fang,† Huifang Wang,† Lin Cai,‡ and YunlongYu*,†

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†

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Institute of Pesticide and Environmental Toxicology, College of Agriculture & Biotechnology, Zhejiang University, Hangzhou 310058, China

‡

Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China

*Correspondence author, Tel/Fax: +86-571-88982433, Email: [email protected]

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ABSTRACT: Antibiotic resistance genes (ARGs), human pathogenic bacteria (HPB), and

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HPB carrying ARGs pose a high risk to soil ecology and public health. Here, we used

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metagenomic approach to investigate their diversity and abundance in chicken manures and

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greenhouse soils collected from Guli, Pulangke, and Hushu vegetable bases with different

41

greenhouse planting years in Nanjing, Eastern China. There was a positive correlation

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between the levels of antibiotics, ARGs, HPB, and HPB carrying ARGs in manures and

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greenhouse soils. In total, 156.2-5001.4 µg/kg of antibiotic residues, 22 classes of ARGs, 32

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HPB species, and 46 species of HPB carrying ARGs were found. The highest relative

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abundance was tetracycline resistance genes (manures) and multidrug resistance genes

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(greenhouse soils). The dominant HPB and HPB carrying ARGs in the manures were Bacillus

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anthracis and Bordetella pertussis, and B. anthracis (sulfonamide resistance gene, sul1),

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respectively. The corresponding findings in greenhouse soils were Mycobacterium

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tuberculosis and M. ulcerans, M. tuberculosis (macrolide-lincosamide-streptogramin

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resistance protein, MLSRP), and B. anthracis (sul1), respectively. Our findings confirmed

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high levels of antibiotics, ARGs, HPB, and HPB carrying ARGs in the manured greenhouse

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soils compared with those in the field soils, and their relative abundance increased with the

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extension of greenhouse planting years.

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INTRODUCTION

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Antibiotics have been widely used in China since the early 1990s as food additives at

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sub-therapeutic doses in livestock and poultry breeding to prevent diseases in animals and

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improve production performance.1 Approximately 30-90% of the antibiotics fed to animals

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can be excreted by feces or urine as parent compounds or metabolites. Subsequently, these

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residual antibiotics can enter the soil environment following the land application of animal

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wastes at the level of 15,000-150,000 kg/ha per year in the cultivation of greenhouse

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vegetables in China, which accounts for 85% of global total greenhouse cultivation area.2-5

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Antibiotic residues in greenhouse soils are usually low (i.e., µg/kg to mg/kg) because of their

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adsorption, biodegradation, photolysis, and transport.6 However, repeated applications of

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manure can still result in their "persistent" pollution.3

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Manure carries antibiotic resistance genes (ARGs) and incorporates antibiotic residues

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into soils, and these residues even at low concentraions exerts a selective pressure on the

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microbial community and induces the emergence of diverse ARGs or multidrug resistance

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(MDR) genes.4,7 The occurrence of E. coli carrying aadA and tetB was significantly more

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frequent in the manued soil samples compared with swine manure.8 The abundance of

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sulfonamide

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sulfonamide-contaminated pig manure in arable soils.9 In addition, Zhu et al.10 reported that

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the abundance of the top 63 ARGs subtypes of the detected 149 ARGs increased 192-28,000

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folds in swine manures compared with antibiotic-free swine manures and control soils.

ARGs

clearly

increased

due

to

repeated

applications

of

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ARGs are readily captured by human pathogenic bacteria (HPB) to form Superbugs such

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as Salmonella, Bacteroidales, Campylobacter, Shigella, and E. coli O157:H7.11-13 Micallef et 4


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al.14 found that eight Enterococcus species with resistance to ciprofloxacin, rifampicin, and

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levofloxacin were the prevalent opportunistic pathogens in tomato farm soil from the

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Mid-Atlantic United States. Yang et al.15 reported that the Bacteroidales bacteria Myroides

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ordoratimimus (antibiotic resistant bacteria) and Sphingobacterium spp. (MDR bacteria) were

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related to human clinical opportunistic pathogens in chicken manure. These HPB confer

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antibiotic resistance and pathogenicity and easily infect humans by contact or via the

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consumption of raw vegetables (e.g., radishes, tomatoes, strawberries, raspberries, lettuce),16

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which in turn poses a serious threat to public health.17 Although the diversity and abundance

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of ARGs in manures and farm soils have been investigated in several studies,10,18 little is

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known about the diversity and abundance of ARGs, HPB, and especially HPB carrying ARGs

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in greenhouse soils following long-term applications of manure.

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The present study examines the diversity and abundance of ARGs, HPB, and HPB

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carrying ARGs in manure-amended greenhouse soils from different planting years by

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metagenomic analysis using an Illumina high-throughput shotgun sequencing technique. The

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objectives of this study were: 1) to determine the residual amounts of different classes of

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antibiotics; 2) to detect the diversity and abundance of ARGs, HPB, and HPB carrying ARGs;

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3) to reveal the correlations between antibiotic residues, ARGs, HPB, HPB carrying ARGs,

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and greenhouse planting years. These findings will contribute to a more comprehensive and

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accurate evaluation of the ecological risks associated with manure application in greenhouse

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soil environment.

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MATERIALS AND METHODS

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Chemicals

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Technical grade antibiotics were purchased form Dr. Ehrenstorfer (Augsburg, Germany)

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and included: tetracycline (97.0%, TC), oxytetracycline (96.5%, OTC), chloroteracycline

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(92.5%, CTC), sulfadiazine (99.0%, SDZ), sulfadimidine (99.0%, SDD), sulfamethoxazole

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(99.0%, SMX), lincomycin (98.0%, LCC), norfloxacin (99.5%, NOR), ciprofloxacin (95.0%,

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CIP), enrofloxacin (98.5%, ENR), and chloramphenicol (98.5%, CPC). These antibiotics are

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divided into five classes: tetracyclines (TC, OTC, and CTC), sulfonamides (SDZ, SDD, and

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SMX), fluoroquinolones (NFC, OTC, and CTC), lincosamides (LCC), and chloramphenicols

112

(CPC). Analytical grade and chromatographic grade methanol and acetonitrile were purchased

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from Merck (Darmstadt, Germany).

114 115

Manure and Soil Sampling

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Chicken manure samples and corresponding manure-amended greenhouse soil samples

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(0-15 cm) were collected from three representative vegetable cultivation bases in the Guli

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(GL), Pulangke (PLK), and Hushu (HS), located in Nanjing suburbs in Eastern China. The

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three chicken manures originated mainly from three local chicken farms in the surrounding

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counties and were used as organic fertilizer. Field soil samples (0-15 cm) were collected from

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a vegetable field adjacent to the greenhouse and used as the controls (no history of manure

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application). Soil collected from five sampling sites within each vegetable greenhouse and

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was thoroughly mixed to obtain a composite sample. Detailed information on the three

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representative vegetable cultivation bases and three chicken manures is summarized in Table 6


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S1 and S2. Leaf vegetables (Chinese cabbage, pakchoi, bokchoi, spinach, and lettuce) and

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fruit vegetables (cucumber and tomato) were cultivated in these bases for 4-12 years. Three

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chicken manure samples and seven soil samples were designated as follows: GL chicken

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manure (GL-M), PLK chicken manure (PLK-M), and HS chicken manure (HS-M), GL

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greenhouse soil for 4 years (GL-G4), GL field soil for 4 years (GL-F4), PLK greenhouse soil

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for 12 years (PLK-G12), PLK greenhouse for 6 years followed by an uncovered shed for 6

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years (PLK-G6/F6), HS greenhouse soil for 4 years (HS-G4), and HS field soil for 4 years

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(HS-F4). The physicochemical properties of the manures and soils are summarized in Table

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S3. All samples were individually transferred into a plastic bag and transported immediately

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to the laboratory within 2 h. Subsequently, each sample was sieved (2 mm) to remove stones

135

and debris and was stored at -20 oC until further analysis. Each treatment was replicated three

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times for the determination of antibiotic residues.

137 138

Extraction and Determination of Antibiotics

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The residues of the 11 antibiotics in the manures and soils were extracted from the

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chicken manure and soil samples following the method described by Fang et al.19 and

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quantified according to the method described by Ho et al.20 using an ultra performance liquid

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chromatography-tandem mass spectrometry (UPLC-MS/MS, Waters, USA). The analytical

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conditions, limit of detection (LOD) and limit of quantitation (LOQ) of the 11 antibiotics are

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summarized in Table S4. To evaluate the effectiveness of the antibiotic extraction method, a

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recovery experiment was conducted. Three replicated standard concentrations (0.1, 1, and 10

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mg/kg) of the 11 antibiotics were mixed together with 2 g (dry weight equivalent) of either 7



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manure or soil samples and processed as described above.

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DNA Extraction and Sequencing

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Total DNA was extracted from 1.0 g of each manure or soil sample using a FastDNA

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SPIN Kit for Soil (MP Biomedicals, CA, USA) according to the manufacturer's instructions.

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The DNA extracted from three technical replicates of each sample was pooled into one DNA

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sample to minimize any potential DNA extraction bias. The concentration and quality of the

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extracted DNA were determined using spectrophotometry (NanoDrop ND-1000, Wilmington,

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DE). Prepared DNA samples were sent to Novegene (Beijing, China), and approximately 5 μg

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of the each DNA samples was used for shotgun library construction. Subsequently, Illumina

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high-throughput sequencing was performed with the HiSeq 2000 platform using a

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PE101+8+101 cycle (Paired-end sequencing, 101-bp reads and 8-bp index sequence)

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sequencing strategy. Approximately 5 Gb of metagenomic data were generated for each DNA

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sample. Each manure and soil sample was sequenced for three technical replicates.

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Quality Filtering

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The metagenomic datasets were filtered using a self-written script to remove the reads

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containing three or more ambiguous nucleotides and those with a length less than 100 bp.

165

Next, the 100 bp paired-end raw reads were paired-merged using a self-written script to

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screen for 10-50 bp overlap paired-end reads and to assemble them into 150-190 bp iTags

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(Illumina tags). Finally, the number of iTags was normalized to 10,000,000 in each

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metagenomic dataset using a self-written script for downstream bioinformatic analysis. The 8


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obtained clean iTag datasets for all samples were uploaded to the MG-RAST server

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(http://metagenomics.anl.gov/, MG-RAST IDs are summarized in Table S5).

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Bioinformatic Analysis A detailed flowchart for data analysis is shown in Figure 1. Four bioinformatic analyses were conducted in this study: (i) ARGs

A widely accepted ARGs database was downloaded from the Antibiotic

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Resistance Database (ARDB, http://ardb.cbcb.umd.edu/).21 The redundant sequences from the

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downloaded database were removed using a self-written script. The resulting database

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retained 2998 non-redundant sequences of 7797 original sequences from the ARDB. A total of

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22 sub-databases were established for the ARG subtypes (Table S6). The metagenomic iTags

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from each sample were searched against the non-redundant ARDB using BLASTX with an

181

E-value < 1e-5. An iTag sequence was annotated as an ARG-like sequence if its best hit in the

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non-redundant ARDB had ≥90% amino acid identity and an alignment length ≥ 25 amino

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acids (75 bp).

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(ii) 16S rRNA gene (16S)

The Greengenes 16S database (version 2013) was

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downloaded directly from the Greengenes website (http://greengenes.lbl.gov/).22 The

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metagenomic iTags from each sample were searched against the Greengenes 16S database

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using BLASTN with an E-value < 1e-20. The Greengenes 16S hit iTags were extracted from

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the metagenomic iTags datasets.

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(iii) HPB An HPB 16S database was constructed based on the taxonomic list derived

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from the HPB virulence factor database (http://www.mgc.ac.cn/VFs/)23 and other 9



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references.24,25 All of the selected HPB 16S are publicly available from the NCBI GenBank

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(http://www.ncbi.nlm.nih.gov/) because their complete genomes have already been sequenced.

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As shown in Table S7, a total of 708 16S sequences were retrieved and assigned to 61 human

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pathogenic bacterial species. The 16S iTags from each sample were searched against the HPB

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16S database using BLASTN with an E-value < 1e-20. The BLAST hit outputs were further

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filtered to annotate the HPB using the strict criteria of amino acid identity ≥ 99%, alignment

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length ≥ 150 bp, and mismatch ≤ 1 bp.

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(iv) HPB carrying ARGs

To reveal the diversity and abundance of HPB carrying ARGs,

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the genome sequences of the BLAST hit HPB were directly downloaded from the NCBI

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GenBank, and then searched against the above ARG-like sequences for each sample. The

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BLAST hit outputs were further filtered to annotate the HPB carrying ARGs using strict

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criteria with amino acid identity ≥ 90% and alignment length ≥ 25 amino acids.

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Statistical Analysis

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Univariate analysis of covariance was conducted between antibiotic residues, ARGs, HPB,

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and HPB carrying ARGs in manures and soils using SPSS 19.0 (SPSS Inc., Chicago, IL,

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USA). The averages and standard deviations of all data were processed using Microsoft Excel

208

2007 (Microsoft Corporation, Redmond, WA, USA). To distinguish the differences in

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diversity and abundance of ARG subtypes, a heat map of each dominant ARG class was

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visualized using Matlab 7.0 (The MathWorks, Natick, MA, USA).

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RESULTS

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Residual Levels of Antibiotics in the Manures and Soils

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The recoveries of the 11 antibiotics at three concentrations of 0.1, 1.0, and 10.0 mg/kg

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were 60.1-83.5% with relative standard deviations (RSDs) < 4.3% in the chicken manures,

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and 62.3-91.1% with RSDs < 3.5% in the soils. The LOD and LOQ of the 11 antibiotics in all

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samples were 0.1-5.0 µg/kg and 0.5-15.0 µg/kg, respectively (Table S4). These results indicate

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that our extraction method was suitable for antibiotic residues analysis. As shown in Figure 2

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and Table S8, the residual concentrations of the antibiotics, expressed as the sum of

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tetracyclines, sulfonamides, fluoroquinolones, LCC, and CPC, were 2526.0, 5001.4, 4722.1

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μg/kg in PLK-M, GL-M, HS-M, respectively, and 631.7, 156.2, 395.7, 384.1 μg/kg in

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PLK-G12, PLK-G6/F6, GL-G4, HS-G4, respectively. However, antibiotic residues were

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under the LOD in PLK-F12, GL-F4, and HS-F4. These results show that several classes of

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antibiotic residues were present in the chicken manures and greenhouse soils. The residual

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levels of antibiotics in the chicken manures were considerably higher than those found in the

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greenhouse soils. Furthermore, the residual levels of tetracyclines and fluoroquinolones were

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higher than those of other antibiotics in both the chicken manures and soils. In addition, the

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individual antibiotic level in PLK-G6/F6 (cultivation in the greenhouse for 6 years and then

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cultivation in an uncovered shed for 6 years) decreased to 11.6-64.5% of the antibiotic level in

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PLK-G12 (cultivation in the greenhouse for 12 years), indicating that the uncovered shed

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significantly decreased antibiotic residues in soils.

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As shown Table S9, significant (P ≤ 0.01) positive correlations were observed in the

234

levels of antibiotics between the chicken manures and the greenhouse soils using univariate 11



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analysis of covariance, e.g., PLK-M and PLK-G12 (R = 0.785), GL-M and GL-G4 (R =

236

0.771), and HS-M and HS-G4 (R = 0.794). A gradual accumulation of antibiotic residues in

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the greenhouse soils was significantly and positively correlated (R = 0.680, P ≤ 0.05) with an

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extension of the greenhouse planting years (Figure S1 and Table S12).

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Diversity and Abundance of ARGs in the Manures and Soils

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The relative abundance (i.e., the ARGs hit number divided by metagenomic iTags number

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in each sample) of ARGs in each chicken manure and soil sample is shown in Figure 3a. The

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relative abundance of ARGs varied from 0.01% to 0.23% in the chicken manures, 0.007% to

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0.015% in the greenhouse soils, and 0.0009% to 0.0015% in the field soils. These results

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show that the ARGs abundance in the chicken manures and greenhouse soils was 9.9-220.1

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and 5.5-8.9 times higher, respectively, than those in the field soils.

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In total, 22 types of ARGs were found in all samples (Figure 3b). Tetracycline resistance

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(TCR) genes were the most abundant ARGs in the chicken manures, followed by those

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encoding resistance to CPC, sulfonamide, aminoglycoside, and purine. However, the most

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abundant ARGs in the greenhouse soils were those encoding MDR, followed by ARGs

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encoding resistance to macrolide-lincosamide-streptogramin (MLS), acridine, tetracycline,

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and fosmidomycin. A higher abundance of MDR genes and a lower abundance of other ARG

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classes were observed in the greenhouse soils compared with the chicken manures (Figure 3b).

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The abundance of MDR genes in the greenhouse soils was 4.7-12.5 times greater than that in

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the field soils, and no significant (P ≤ 0.05) difference was found among the GL-F4, PLK-F12,

256

and HS-F4. Additionally, the abundance of MDR genes in PLK-G6/F6 was only 67.6% of that 12


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in PLK-G12, which suggests that uncovering a shed noticeably decreased the abundance of

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MDR genes.

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A comparison of the diversity and abundance of the 8 dominant ARG classes in the

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manures and soils is shown in Figure 4. These dominant ARGs included MDR (20 subtypes),

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TCR (25 subtypes), beta-lactam resistance (10 subtypes), CPC resistance (11 subtypes),

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fosfomycin resistance (3 subtypes), aminoglycoside resistance (16 subtypes), acridine

263

resistance (5 subtypes), and MLS resistance (8 subtypes) genes. The dominant subtypes of

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ARGs in the greenhouse soils were mexF and bpeF (MDR), which had a higher relative

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abundance than those in the chicken manure and field soils (Figure 4). Simultaneously, the

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abundant subtypes of ARGs in the chicken manures were tetA(G), tetX2, tetA, tetX, tetA(33)

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(TCR), followed by aminoglycoside acetyltransferase (AAT), aadA, aphD (aminoglycoside

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ARGs), and cmx (CPC ARGs).

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Significant (P ≤ 0.05) positive correlations were found in the ARGs between the chicken

270

manure and greenhouse soil using univariate analysis of covariance, e. g., GL-M and GL-4 (R

271

= 0.809), PLK-M and PLK-G12 (R = 0.996), PLK-M and PLK-G6/F6 (R = 0.985), and HS-M

272

and HS-G4 (R = 0.993) (Table S9). Interestingly, significant (P ≤ 0.05) positive correlations

273

were observed between the residual levels of tetracyclines, sulfonamides, lincosamides,

274

fluoroquinolones, and CPC and their corresponding relative abundance of ARGs class with

275

high correlation coefficients of 0.809, 0.815, 0.752, 0.890, 0.734, and 0.853, respectively

276

(Table S10). The abundance of ARGs in the greenhouse soils gradually increased with the

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extension of greenhouse planting years with a highly positive correlation coefficient (R =

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0.786, P ≤ 0.05) (Figure S1 and Table S12). 13



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Diversity and Abundance of HPB in the Manures and Soils

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The diversity and relative abundance (i.e., the HPB 16S hit number divided by the

281

Greengenes 16S hit number in each sample, and Greengenes 16S hit number in each

282

metagenomic iTags dataset is shown in Figure S2) of HPB in the chicken manures and soils is

283

shown in Figure 5. A total of 32 pathogenic bacteria were found. Mycobacterium tuberculosis

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and M. ulcerans were the dominant HPB species in the soils, followed by Bordetella pertussis,

285

Bacillus anthracis, Brucella melitensis, Corynebacterium diphtheria, Bartonella quintana,

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and M. leprae. The abundance of M. tuberculosis and M. ulcerans in the greenhouse soils was

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1.7-14.0 and 1.6-2.4 times higher, respectively, compared with the field soils. The relative

288

abundance of these two HPB in PLK-G6/F6 was 45.9% and 34.7% of the PLK-G12,

289

respectively. The dominant HPB in the chicken manures were B. anthracis and B. pertussis

290

were the dominant HPB species in the chicken manures, followed by Staphylococcus aureus,

291

C. diphtheria, Enterococcus faecalis, B. melitensis, M. tuberculosis, C. jeikeium, and M.

292

ulcerans (Figure 5). The mean relative abundance of HPB in the chicken manures was

293

considerably higher than that in the greenhouse and field soils, and the highest relative

294

abundant HPB was B. pertussis in GL-M, E. faecalis in PLK-M, and B. anthracis in HS-M.

295

Significant (P ≤ 0.01) positive correlations were found in the HPB between the chicken

296

manure and greenhouse soil, e.g., GL-M and GL-G4 (R = 0.691), PLK-M and PLK-G12 (R =

297

0.970), PLK-M and PLK-G6/F6 (R = 0.899), and HS-M and HS-G4 (R = 0.964) (Table S9).

298

Similarly, a significant positive correlation (R = 0.693, P ≤ 0.01) was also found between

299

HPB abundance in the greenhouse soils and greenhouse planting years (Figure S1 and Table

300

S12). 14


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HPB Carrying ARGs in the Manures and Soils

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Figure 6 shows the diversity and relative abundance (i.e., the HPB carrying ARGs hit

303

number divided by the Greengenes 16S hit number in each sample) of HPB carrying ARGs in

304

the chicken manures and soils. As shown in Figure 6 and Table S13, a total of 46 HPB

305

carrying ARGs were found, and the ARGs harbored in the HPB contained 25 subtypes, such

306

as sul1, cmx, tetT, adeB, OXA-53, vanRG, aac, msrA, tetM etc. The most dominant HPB

307

carrying ARGs in the chicken manures was B. anthracis harboring sulfonamide sul1 followed

308

by M. tuberculosis (MLSRP), C. diphtheriae (sulfonamide dihydropteroate synthase), C.

309

jeikeium (CPC cmx), S. aureus (aminoglycoside phosphotransferase), E. faecalis

310

(aminoglycoside phosphotransferase), and S. aureus (glycopeptide resistance protein). The

311

mean relative abundance of HPB carrying ARGs in the chicken manures was 1.9 and 23.4

312

times higher, respectively, than that in the greenhouse and field soils. As shown in Figure 6,

313

both M. tuberculosis (MLSRP) and B. anthracis (sul1) were the most dominant HPB carrying

314

ARGs in the soils, with a higher abundance inside the greenhouses compared with the fields.

315

The relative abundance of these HPB carrying ARGs in PLK-G6/F6 decreased significantly to

316

57.3% and 47.8%, respectively, of the abundance in PLK-G12. In this study, the MLSRP

317

subtype was found in M. tuberculosis, S. flexneri, S. dysenteriae, and S. agalactiae. The MDR

318

gene can be harbored by some pathogenic bacteria such as Acinetobacter baumannii,

319

Salmonella enteric, Yersinia enterocolitica, Pseudomonas aeruginosa, Shigella boydii, and S.

320

dysenteriae. Additionally, E. faecalis can carry diverse ARGs such as aminoglycoside

321

phosphotransferase,

322

nucleotidyltransferase, tetT, and vanRG.

sulfonamide

dihydropteroate

15


synthase,

lincosamide


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Significant (P ≤ 0.01) positive correlations were found in the HPB carrying ARGs

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between all chicken manures and all greenhouse soils, such as PLK-M and PLK-G12 (R =

325

0.751), PLK-M and PLK-G6/F6 (R = 0.849), HS-M and HS-G4 (R = 0.626), and GL-M and

326

GL-G4 (R = 751) (Table S9). There were significant (P ≤ 0.01) positive correlations between

327

all HPB carrying ARGs and all ARGs (R = 0.901) and between all HPB carrying ARGs and

328

all HPB (R = 0.870) in all samples (Table S11). Additionally, the relative abundance of HPB

329

carrying ARGs in the greenhouse soils gradually increased with an extension of the

330

greenhouse planting years, and a significant positive correlation (R = 0.756, P ≤ 0.05) is

331

presented in Figure S1 and Table S12.

332 333 334

DISCUSSION

335

Antibiotic residues in soil have been shown to be correlated with manure type, manure

336

application rate, soil type, vegetable species, cultivation method, and environmental

337

conditions.26 In this study, several classes of antibiotics were found in chicken manures and

338

greenhouse soils, which may have resulted from the long-term fertilization of

339

antibiotic-contaminated chicken manure in the greenhouse soils.27 Similarly, the residual

340

concentrations of tetracyclines, sulfonamides, and CPC were 4.5-24.7, 5.9-33.4, and 3.3-17.9

341

mg/kg, respectively, in manures (swine, bird, and cattle) and soils collected from Shanghai,

342

Eastern China.28 In addition, Huang et al.29 reported that the residual levels of TC, OTC, CTC,

343

ENR, CIP, and ofloxacin ranged from 189.8 μg/kg to 2668.9 μg/kg in farmland soils from

344

four coastal cities in Fujian, Eastern China. In the current study, the observed lower 16


Page 17 of 33


345

concentrations of antibiotics in the greenhouse soils compared with the chicken manures may

346

be due to the adsorption, biodegradation, photolysis, and infiltration of antibiotics in the

347

soil.19 Nevertheless, the long-term repeated application of chicken manure can still lead to the

348

persistent contamination of greenhouse soils with antibiotics. Meanwhile, it is noteworthy that

349

higher residual levels of antibiotics were observed in PLK-G12 (organic vegetable cultivation)

350

compared with GL-G4 and HS-G4 (traditional vegetable cultivation) (Figure 2), which may

351

be attributed to the high application of chicken manure in the organic vegetable base (Table

352

S1). Similarly, the absence of antibiotic residues in the field soils may be attributed to the fact

353

that chicken manure was not applied to these soils.

354

In this study, the long-term application of chicken manure led to a noticeable increase in

355

ARGs diversity and abundance in the greenhouse soils. Other studies have reported that

356

different types of manure resulted in a marked increase in ARGs abundance in soil,9,30 such as

357

ermF, sul1, and sul2.18 Cook et al.31 reported that the abundance of sulfonamides,

358

streptomycins, and tetracyclines ARGs increased up to 3 orders of magnitude in soil after

359

poultry litter application. Several pathways have been identified as potential contributors to

360

the diversity and abundance of ARGs in greenhouse soils: (i) Inherent ARGs in the natural

361

environment; (ii) ARGs carried by chicken manure; (iii) ARGs induced by antibiotic residues;

362

(iv) Horizontal gene transfer (HGT) of ARGs among soil bacteria. Pruden et al.32

363

demonstrated that ARGs can be transferred between non-pathogens, pathogens, and even

364

distantly related organisms (Gram-positive and Gram-negative bacteria) by mobile genetic

365

elements such as class 1 integrons (intl1), plasmids, insertion sequences, transposons, and

366

phages. In this study, an integron database was constructed based on 411 intl1 sequences 17



Page 18 of 33

367

(Table S14). The relative abundance of intl1 was considerably higher in the chicken manures

368

than that in the greenhouse soils, and no intl1 sequence was observed in the field soils (Figure

369

S3 and Table S15). The results show that chicken manures contained a large number of intl1

370

sequences, and furthermore, these sequences may be transported into greenhouse soils

371

following land application.

372

Following the long-term application of chicken manures, the accumulation of MDR genes

373

was observed in the greenhouse soils compared with the field soils, which may be due to the

374

presences of different classes of antibiotics. A similar finding was reported by Heuer et al.,9

375

who found an accumulation of sulfonamide ARGs in arable soils due to repeated applications

376

of pig manure containing SDZ residues. In the current study, the dominant MDR subtypes,

377

such as mexF, bpeF, and mexD, encode an efflux pump that export intracellular antibiotics out

378

of cells, which is an important mechanism of resistance in MDR genes.33 Meanwhile, the

379

most abundant gene found in chicken manures was the TCR gene, which is in agreement with

380

those findings reported for piggery manure,34 swine manure,35 and cow manure.36

381

The findings of this study revealed that the levels of antibiotic residues, ARGs, HPB, and

382

HPB carrying ARGs varied greatly with sample type and sampling location, and their

383

abundance in the greenhouse soils was highly positively correlated with greenhouse planting

384

years. The most dominant ARG classes in the chicken manure and greenhouse soils were the

385

TCR and MDR genes, respectively. The most dominant HPB were B. anthracis and B.

386

pertussis in the chicken manures and M. tuberculosis and M. ulcerans in the greenhouse soils.

387

The most highly abundant HPB carrying ARGs were B. anthracis (sul1) in the chicken

388

manures and M. tuberculosis (MLSRP) and B. anthracis (sul1) in the greenhouse soils. A 18


Page 19 of 33


389

good positive correlation was found in antibiotic residues, ARGs, HPB, and HPB carrying

390

ARGs between chicken manures and greenhouse soils, and their abundance in the greenhouse

391

soils

392

metatranscriptomic analyses are required to reveal the expression levels of ARGs (particularly

393

ARGs harbored in the HPB) in soil microbial communities.

increased

with

an

extension

of

the

greenhouse

planting

years.

Further

394 395

ASSOCIATED CONTENT

396

Supporting Information

397

Increased abundance of antibiotic residues, ARGs, HPB, and HPB carrying ARGs with the

398

extension of greenhouse planting years (Figure S1); relative abundance of the Greengenes

399

16S hit number in metagenomic iTag datasets (Figure S2); relative abundance of class 1

400

integrons in chicken manures and soils (Figure S3); information on three vegetable bases

401

(Table S1); information on three manure samples (Table S2); physicochemical properties of

402

all samples (Table S3); optimal analysis conditions of antibiotics (Table S4); metagenome

403

MG-RAST IDs and sample sizes (Table S5); composition of the ARDB database (Table S6);

404

composition of the HPB database (Table S7); antibiotic residues in all samples (Table S8);

405

analysis of covariance on antibiotic residues, ARGs, HPB, and HPB carrying ARGs between

406

chicken manures and greenhouse soils (Table S9); analysis of covariance between antibiotic

407

residues and ARGs in all samples (Table S10); analysis of covariance between ARGs, HPB,

408

and HPB carrying ARGs in all samples (Table S11); analysis of covariance between

409

environmental pollutants (antibiotic residues, ARGs, HPB, and HPB carrying ARGs) in the

410

greenhouse soils and greenhouse planting years (Table S12); diversity and abundance of HPB 19



Page 20 of 33

411

carrying ARGs in chicken manures and soils (Table S13); list of class 1 integrons (Table S14);

412

and abundance and diversity of class 1 integrons in chicken manures and soils (Table S15).

413

This material is available free of charge via the Internet at http://pubs.acs.org.

414 415

AUTHOR INFORMATION

416

Corresponding Author

417

*Tel./Fax: +86-571-88982433. E-mail: [email protected].

418

Notes

419

The authors declare no competing financial interest.

420 421

ACKNOWLEDGMENTS

422

This work was supported by the National Nature Science Foundation of China (Nos.

423

21377112, 41271489, 20907040) and the National High Technology R&D Program of China

424

(No. 2012AA06A204).

425 426

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E.; Angly, F.; Dinsdale, E. A.; Edwards, R. A. Comparative metagenomics reveals host

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specific metavirulomes and horizontalGene transfer elements in the chicken cecum

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microbiome. PLoS One 2008, 3 (8), e2945.

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E.; Wise, M. G.; Siragusa, G. R.; Hiett, K. L.; Seal, B. S. The poultry-associated microbiome:

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network analysis and farm-to-fork characterizations. PLoS One 2013, 8 (2), e57190.

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(26) Li, Y. W.; Mo, C. H.; Zhao, N.; Tai, Y. P.; Bao, Y. P.; Wang, J. Y.; Li, M. Y.; Liang, W. M.

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Investigation of sulfonamides and tetracyclines antibiotics in soils from various vegetable

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fields. Environ. Sci. 2009, 30 (6), 1762-1766.

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perturbation of soil and groundwater microbial communities due to pig production activities.

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resistance gene abundances associated with antibiotics and heavy metals in animal manures

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and agricultural soils adjacent to feedlots in Shanghai, China. J. Hazard. Mater. 2012, 235,

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around swine feedlots in Fujian Province, China. Environ. Sci. Pollut. Res. 2013, 20 (12),

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antibiotic resistance in soil over at least two months. Environ. Microbiol. 2007, 9 (3),

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657-666.

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(31)Cook, K. L.; Netthisinghe, A. M. P.; Gilfillen, R. A. Detection of pathogens, indicators,

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and antibiotic resistance genes after land application of poultry litter. J. Environ. Qual. 2014,

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(32)Pruden, A.; Pei, R. T.; Storteboom, H.; Carlson, K. H. Antibiotic resistance genes as

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(33) Martinez-Garcia, E.; de Lorenzo, V. Engineering multiple genomic deletions in

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538

(35) Wu, N.; Qiao, M.; Zhang, B.; Cheng, W. D.; Zhu, Y. G. Abundance and diversity of

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540

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541

(36) Munir, M.; Xagoraraki, I. Levels of antibiotic resistance genes in manure, biosolids, and

542

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543

Page 26 of 33

FIGURE CAPTIONS

544 545

Figure 1 Flowchart of the metagenomic analysis for antibiotic resistance genes (ARGs),

546

human pathogenic bacteria (HPB), and HPB carrying ARGs in chicken manures and soils.

547 548

Figure 2 Residual levels of antibiotics in chicken manures and soils. Each value is the mean

549

of three replicates.

550 551

Figure 3 Relative abundance of total antibiotic resistance genes (ARGs) in chicken manures

552

and soils (a). The diversity and abundance of different classes of ARGs in both manures and

553

soils (b). All ARGs were categorized according to the classes of antibiotics. The number of

554

iTags in each sample was normalized to the same size (20,000,000). The relative abundance

555

of ARGs was defined as the ARGs hit number divided by metagenomic iTags number in each

556

sample. "1/10000" indicates one ARG-like iTag in ten thousand Illumina iTags. Error bars

557

represent one standard deviation of the mean. Each ARG class was classified into different

558

subtypes

559

macrolide-lincosamide-streptogramin.

according

to

different

resistance

mechanisms.

MLS:

560 561

Figure 4 Heat maps of the dominant ARG subtypes in chicken manures and soils. (a):

562

multidrug resistance genes (MDR); (b): tetracycline resistance genes; (c): aminoglycoside

563

(AG) resistance genes, acridine resistance genes, and macrolide-lincosamide-streptogramin

564

(MLS) resistance genes; (d): beta-lactam resistance genes, chloramphenicol (CPC) resistance 26


Page 27 of 33


565

genes, and the fosfomycin resistance genes. The color intensity in each panel shows the

566

common logarithm value of the ARG subtypes hit number in each normalized metagenomic

567

iTags dataset (10,000,000), referring to the color bar below. AAT: AG acetyltransferase;

568

ARPA: AG resistance protein B; KNT: kanamycin nucleotidyltransferase; FAT: fused AG

569

3'-adenyltransferase-AG 6'-acetyltransferase; HARK: hydroxyurea antibiotic resistant kinase;

570

3-PT: AG 3'-phosphotransferase; APT: AG phosphotransferase; ARPB: AG resistance protein

571

B; GAT: gentamicin acetyltransferase; GRP: gentamicin resistance protein; ARPB: acridine

572

resistance protein B; AFRPB: acriflavin resistance protein B; AEP: acridine efflux pump;

573

ARPA: acridine resistance protein A; AFRPA: acriflavin resistance protein B; MLSRP: MLS

574

resistance protein; CAT: CPC acetyltransferase; CFE: CPC and florfenicol (FFC) exporter;

575

CFRP: CPC and FFC resistance protein; CRD: CPC resistance determinant; CT: CPC

576

transporter; FRPB: fosfomycin resistance protein B.

577 578

Figure 5 Diversity and relative abundance of human pathogenic bacteria (HPB) in chicken

579

manures and soils. The relative abundance of HPB is defined as the HPB 16S rRNA gene hit

580

number divided by Greengenes 16S rRNA gene hit number.

581 582

Figure 6 Diversity and relative abundance of human pathogenic bacteria (HPB) carrying

583

antibiotic resistance genes (ARGs) in chicken manures and soils. The relative abundance of

584

HPB carrying ARGs is defined as the HPB carrying ARGs hit number divided by Greengenes

585

16S rRNA gene hit number in each sample). MLSRP: macrolide-lincosamide-streptogramin

586

resistance protein. 27



Figure 1

Guli (GL)、 Pulangke (PLK)、Hushu (HS) vegetable planting bases Sampling

Greenhouse soil (G)、field soil (F)、chicken manure (M) Sample IDs

PLK-G12 PLK-G6/F6 PLK-F12 PLK-M

GL-G4 GL-F4 GL-M

Pair-end reads merging

High-throughput shotgun sequencing

Sample preparation

587

Page 28 of 33

HS-G4 HS-F4 HS-M

DNA preparation Illumina HiSeq sequencing

Raw reads datasets Clean pair-end reads

Pair-end read 1 (100 bp)

5' 5' 5'

Overlap region 3' 3' 3' 3' 3' 3'

Pair-end read 2 (100 bp)

Merging Merged read (150 bp) 5'

3'

Overlap region

5' 5'

3'

10-50 bp

3'

Merged read (190 bp)

Antibiotic resistance genes database (ARDB)

BLASTX

Illumina iTags (150-190 bp)

BLASTN

Script Identity ≥ 90%

Alignment ≥ 75 bp

Alignment ≥ 75 bp

BLAST results of antibiotic resistance genes (ARGs)

Greengene 16S rRNA gene database Filtration by cutoff

Filtration by cutoff


Bioinformatic analysis

5' 5' 5'

Extracting 16S rRNA gene iTags

Script

BLAST results of 16S rRNA gene

BLASTN Script

Extracting ARGs-like iTags

Human pathogenic bacteria (HPB) 16S rRNA gene database

Script Filtration by cutoff Identity ≥ 99% Alignment ≥ 150 bp Mismatch ≤ 1 bp

BLASTN Filtration by cutoff


Alignment ≥ 75 bp

HPB carrying ARGs

588 28


BLAST results of HPB HPB genome from NCBI

Page 29 of 33

589


Figure 2

590 Tetracycline (TC)

GL-M

Oxytetracycline (OTC)

GL-G4

Chloroteracycline (CTC)

GL-F4

Sulfadiazine (SDZ)

PLK-M

Sulfadimidine (SDD)

PLK-G12

Sulfamethoxazole (SMX)

PLK-G6/F6

Lincomycin (LCC)

PLK-F12

Norfloxacin (NFC) HS-M

Ciprofloxacin (CPF)

HS-G4

Enrofloxacin (ENR)

HS-F4

Chloramphenicol (CPC) 0

591

1000

2000

3000

4000

5000

6000

Antibiotic residues in manure and soil samples (μg/kg)

592 593 594 595 596 597 598 599 600 601 602 603 604 29



605

Figure 3 (a)

GL-M GL-G4 GL-F4 PLK-M PLK-G12 PLK-G6/F6 PLK-F12 HS-M HS-G4 HS-F4 0.0 0.5 1.0 1.5 2.0 2.5 18

20

22

24

26

Relative abundance of total ARGs in each sample (1/10000) (b) GL-M GL-G4 GL-G4

GL-F4 PLK-M PLK-G12

GL-F4 PLK-G12

enlarge

PLK-G6/F6 PLK-F12 HS-G4

PLK-G6/F6 PLK-F12

HS-F4

0

0.4

0.8

1.2

1.6

HS-M HS-G4 HS-F4

606

0 4 8 12 16 20 24 28 Relative abundance of each ARG class in each sample (1/10000)

607 608 609 610 611 612 613 30


acridine aminoglycosides beta-lactams bicyclomycins chloramphenicol fluoroquinolones fosmidomycins glycopeptides glycylcyclines lincosamides macrolides MLS multidrug penicillins peptides purines quinolones streptomycins sulfonamides tetracenomycins tetracyclines others

Page 30 of 33

Page 31 of 33

mdtF AmrB acrA mexA mexE adeB mdfA mdtO mexG adeA oprN mdtH

Acridine ARGs

Aminoglycoside ARGs

mdtL mexB AAT aadA aphD ARPA KNT FAT HARK 3-PT APT ARPB aac6 aadB GAT GRP aac strA ARPB AFRPB AEP ARPA AFRPA MLSRP ermX ermGM ermFS ermT mef msrA ermG

(d)

(c) 0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

616 31


1.8

2

Tetracycline ARGs

Multidrug resistance genes (MDR)

Rpos

Beta-lactam ARGs

sdeY acrB

Fosfomycin ARGs Chloramphenicol ARGs

bpeF mexD

MLS ARGs

(b) tetA(G) tetA(31) tetX2 tetA tetX tetA(33) tetM tetL tetT tetQ tetG tetW tetY tet32 tetS tetA(39) tetA(P) tetB tetV tetO tetA(D) tetA(41) tetA(B) tetA(M) tetH OXA CARB mecA Sed1 PSE-1 TEM-21 VIM-18 ACT-1 L1 ampc catB2 catB3 ceoB cmlA cmx CAT CFE CFRP floR CRD CT FRP fosB rosA

mexF

615

HS-F4

HS-G4

HS-M

PLK-F12

PLK-G6/F6

PLK-G12

PLK-M

GL-F4

GL-G4

GL-M

HS-F4

HS-G4

HS-M

PLK-F12

PLK-G6/F6

PLK-G12

PLK-M

GL-F4

(a)

GL-G4

Figure 4

GL-M

614



617

Page 32 of 33

Figure 5

618 Acinetobacter baumannii Acinetobacter calcoaceticus Bacillus anthracis Bacillus cereus Bartonella henselae Bartonella quintana Bordetella pertussis Brucella melitensis Burkholderia cenocepacia Clostridium botulinum Clostridium difficile Clostridium novyi Clostridium perfringens Corynebacterium diphtheriae Corynebacterium jeikeium Enterococcus faecalis Legionella pneumophila Listeria ivanovii Mycobacterium leprae Mycobacterium tuberculosis Mycobacterium ulcerans Neisseria meningitidis Pseudomonas aeruginosa Salmonella enterica Shigella boydii Shigella dysenteriae Shigella flexneri Staphylococcus aureus Streptococcus agalactiae Streptococcus pyogenes Yersinia enterocolitica Yersinia pestis

GL-M GL-G4 GL-F4 PLK-M PLK-G12 PLK-G6/F6 PLK-F12 HS-M HS-G4 HS-F4 0

619

10

20

30

40

50

Relative abundance of human pathogenic bacteria (‰)

620 621 622 623 624 625 626 627 628 32


Page 33 of 33

629


Figure 6

630 Acinetobacter baumannii (aminoglycoside aac) Acinetobacter baumannii (aminoglycoside kinase) Acinetobacter baumannii (chloramphenicol acetyltransferase) Acinetobacter baumannii (multidrug adeB) Acinetobacter baumannii (sulfonamide dihydropteroate synthase) Bacillus anthracis (sulfonamide sulI) Bacillus cereus (others) Clostridium botulinum (aminoglycoside acetyltransferase) Clostridium difficile (tetracycline tetM) Corynebacterium diphtheriae (sulfonamide dihydropteroate synthase) Corynebacterium jeikeium (chloramphenicol cmx) Corynebacterium jeikeium (others) Clostridium perfringens (tetracycline tetT) Enterococcus faecalis (aminoglycoside phosphotransferase) Enterococcus faecalis (sulfonamide dihydropteroate synthase) Enterococcus faecalis (lincosamide nucleotidyltransferase) Enterococcus faecalis (others) Enterococcus faecalis (tetracycline tetT) Enterococcus faecalis (glycopeptide vanRG) Mycobacterium tuberculosis (MLSRP) Mycobacterium tuberculosis (others) Pseudomonas aeruginosa (multidrug resistance protein) Pseudomonas aeruginosa (tetracycline tetM) Staphylococcus aureus (purine N-6-methyltransferase) Staphylococcus aureus (aminoglycoside phosphotransferase) Staphylococcus aureus (beta-lactamase) Staphylococcus aureus (chloramphenicol acetyltransferase) Staphylococcus aureus (glycopeptide resistance protein) Staphylococcus aureus (MLS msrA) Staphylococcus aureus (others) Staphylococcus aureus (penicillin binding protein pbp2a) Streptococcus agalactiae (MLSRP) Shigella boydii (multidrug efflux system protein mdtO) Shigella dysenteriae (acridine resistance protein) Shigella dysenteriae (MLSRP) Shigella dysenteriae (multidrug resistance protein) Salmonella enterica (beta-lactam OXA-53) Salmonella enterica (chloramphenicol exporter) Salmonella enterica (sulfonamide dihydropteroate synthase) Salmonella enterica (multidrug resistance protein) Salmonella enterica (penicillin binding protein pbp2a) Shigella flexneri (acridine resistance protein) Shigella flexneri (MLSRP) Streptococcus pyogenes (tetracycline tetT) Yersinia enterocolitica (multidrug resistance protein) Yersinia pestis (aminoglycoside acetyltransferase)

GL-M

GL-G4

GL-F4

PLK-M

PLK-G12

PLK-G6/F6

PLK-F12

HS-M

HS-G4

HS-F4 0

631

10

20

30

40

Relative abundance of HPB carrying ARGs (‰)

33


Prevalence of Antibiotic Resistance Genes and Bacterial Pathogens in

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