Carrying Plasmid in Chicken-Waste-Impacted Farm Soil - Applied and ...

Detection of a Common and Persistent tet(L)-Carrying Plasmid in Chicken-Waste-Impacted Farm Soil Yaqi You,a Markus Hilpert,a and Mandy J. Wardb Department of Geography and Environmental Engineering, Johns Hopkins University, Baltimore, Maryland, USA,a and Department of Earth Sciences, University of Southern California, Los Angeles, California, USAb

The connection between farm-generated animal waste and the dissemination of antibiotic resistance in soil microbial communities, via mobile genetic elements, remains obscure. In this study, electromagnetic induction (EMI) surveying of a broiler chicken farm assisted soil sampling from a chicken-waste-impacted site and a marginally affected site. Consistent with the EMI survey, a disparity existed between the two sites with regard to soil pH, tetracycline resistance (Tcr) levels among culturable soil bacteria, and the incidence and prevalence of several tet and erm genes in the soils. No significant difference was observed in these aspects between the marginally affected site and several sites in a relatively pristine regional forest. When the farm was in operation, tet(L), tet(M), tet(O), erm(A), erm(B), and erm(C) genes were detected in the waste-affected soil. Two years after all waste was removed from the farm, tet(L), tet(M), tet(O), and erm(C) genes were still detected. The abundances of tet(L), tet(O), and erm(B) were measured using quantitative PCR, and the copy numbers of each were normalized to eubacterial 16S rRNA gene copy numbers. tet(L) was the most prevalent gene, whereas tet(O) was the most persistent, although all declined over the 2-year period. A mobilizable plasmid carrying tet(L) was identified in seven of 14 Tcr soil isolates. The plasmid’s hosts were identified as species of Bhargavaea, Sporosarcina, and Bacillus. The plasmid’s mobilization (mob) gene was quantified to estimate its prevalence in the soil, and the ratio of tet(L) to mob was shown to have changed from 34:1 to 1:1 over the 2-year sampling period.

T

he widespread use of antibiotics in concentrated animal feeding operations (CAFOs) has sparked debate on whether this practice might constitute an environmental and public health concern (52, 62). Globally, at least 50% of all antimicrobials are used in agricultural animals (22, 58, 62), but until recently little evidence clearly connected the agricultural use of antibiotics with drug-resistant infections in the human community (22). However, in Sweden, Denmark, and other European Union countries, both voluntary and regulatory actions caused a drop in the use of antibiotics as growth promoters. Following these changes, a decline in antibiotic-resistant bacteria (ARB) on farms and in meat (2), and in carriage of ARB by humans (59, 60), was observed. Nonetheless, the routine nontherapeutic use of antibiotics in CAFOs continues in many countries (52). Consequently, more research is required to identify the effects of CAFOs on the dissemination of antibiotic resistance. One major impact of CAFOs on the environment is through animal waste (14, 30, 41). This is because this waste is rich in antibiotic residues (63), antibiotic-resistant bacteria, and antibiotic resistance genes (ARGs) (10, 17, 23, 29), which can enter the environment through disposal practices (14). Growing evidence further shows that animal waste, including poultry litter, contains various mobile genetic elements (MGEs) harboring ARGs (8, 10, 11, 40), which facilitate the spread of ARGs to soil microbial communities when animal waste is applied onto agricultural soils (30). While an increasing number of studies have reported ARG occurrence in poultry-litter-affected soils, the ecological effects on soil bacterial communities of exposure to poultry litter have not been elucidated (14). A recent review on the dissemination of manurederived ARGs highlighted the important ecological role of MGEs in resistance spread (30). That review suggested that ARGs residing on MGEs would be enriched in manure from animals exposed to antibiotics and that these ARGs might horizontally transfer to indigenous soil bacteria and thus persist in the soil microbial com-

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munity. Consequently, more research is required to identify the influence of poultry litter deposition on soil microbes (14), such as the prevalence of specific MGEs in animal waste and in soils with and without exposure to animal waste, as well as the fate of MGEassociated ARGs in the environment (30). Tetracyclines (Tcs) and the MLSB group of antibiotics (macrolides, lincosamides, and streptogramin B antibiotics that include erythromycin, lincomycin, and tylosin) are inexpensive and broadly effective and have been used at both therapeutic and nontherapeutic levels in chickens for decades (13, 52). Resistance to these antibiotics has frequently been observed in bacterial isolates from poultry litter (10, 17, 23, 29). Furthermore, some MGEs simultaneously carry genes encoding tetracycline resistance (Tcr; tet) and MLSB resistance (erm) (13, 49) and facilitate the dissemination of resistance to these antibiotics among environmental, commensal, and clinical bacteria (48). In this case study, we used geophysical exploration to identify potential chicken-waste-affected soils on a broiler chicken farm. While geophysical approaches have been successfully used to infer the relative concentrations, extents, and movements of contaminants from animal waste-holding facilities (6, 18, 19, 28, 37), this may be the first application of such an approach in a microbiological study of antibiotic resistance. Farm soil samples were taken both during poultry production, when chicken waste was routinely stored on-site in an open house, and 2 years after production was terminated, when all the chickens and their waste had

Received 2 December 2011 Accepted 17 February 2012 Published ahead of print 2 March 2012 Address correspondence to Y. You, [email protected]. Copyright © 2012, American Society for Microbiology. All Rights Reserved. doi:10.1128/AEM.07763-11

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been removed from the site. These samples offered an unusual opportunity for studying the impact of chicken waste on ARG occurrence and prevalence in soil microbial communities and the potential for the reversibility of this impact. The occurrence of tetracycline and MLSB resistance in the farm soils was investigated using both culture-dependent and -independent methods and compared to results from soils taken from a regional state forest that had not been used for agricultural purposes for decades. Realtime quantitative PCR (qPCR) was used to evaluate the relative abundances of several ARGs in the waste-impacted soil during farm operation and after closing down of the farm. Plasmids were identified in soil bacterial isolates of different genera in order to gain a preliminary understanding of one possible mechanism for the prevalence and persistence of tet genes. Relatively few studies have targeted the fate of MGE-associated ARGs in litter-impacted soils. Therefore, the results from this study may contribute to our understanding of ARG spread in the environment via MGEs. MATERIALS AND METHODS Geophysical exploration and sample collection. The conventional broiler chicken farm (housing over 50,000 birds) involved in this study was located on the delmarva (Delaware-Maryland-Virginia) peninsula. The farmers used chicken feed supplied by the integrator and were unaware of the presence and/or type of antimicrobials in the feed. In one field trip, soil taxonomic classification was performed for the area surrounding a waste storage shed and two chicken houses. Electromagnetic measurements were taken in this area using a Geonics DAS70 data acquisition system, which consists of an EM38 meter (Geonics Ltd., Mississauga, Ontario, Canada), an Allegro CX field computer (Juniper System, North Logan, UT), and a Garmin GPS Map 76 receiver (Garmin International Inc., Olathe, KS). The EM38 meter (with a 1-m intercoil spacing and a frequency of 14,600 Hz) was operated in the deeper-sensing (0 to 1.5 m), vertical dipole orientation and continuous mode, with measurements recorded at 1-s intervals. The NAV38 and Trackmaker38 software programs (Geomar Software Inc., Mississauga, Ontario, Canada) were used to record, store, and process apparent electrical conductivity (ECa) and global positioning system (GPS) data. SURFER v8.0 software (Golden Software, Inc., Golden, CO) was used to construct a simulation of the ECa data, while a grid was created using kriging methods with an octant search. All ECa data were temperature corrected to 25°C. Based on the results of the geophysical exploration, samples of topsoil (the upper 1 to 10 cm) and aquifer material (⬎60 cm below the ground surface) were collected using a soil auger from two sites at the chicken farm (in April 2008 and in November 2010). In addition, more-pristine soils were collected (in November 2010) from three sites in the Pocomoke State Forest, which is located in the same agricultural region but has not been affected by farm-generated poultry waste for decades. To ensure that the collected forest soils were of the same type as the collected farm soils, the Web Soil Survey site (http://websoilsurvey.nrcs.usda.gov/app /HomePage.htm) of the U.S. Department of Agriculture (USDA) was consulted to generate soil maps and identify potential sampling sites. Randomly picked sampling spots were approached as closely as possible using a GPS (Garmin Oregon 300) device during a field trip. All samples were stored in clean plastic bags on ice in the field, returned to the laboratory within 4 h, and then stored at 4°C in the dark to protect against antibiotic photodegradation. Prior to analysis, soil samples were sieved through a 2-mm mesh and thoroughly homogenized. For each subsurface sample, triplicate pHCaCl2 measurements were taken after mixing 1 g of sample with 2 ml of 0.01 M CaCl2. Measurement of tetracycline antibiotics in soil samples. Pretreatment of soil samples and solid-phase extraction (SPE) prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis for antibiotics were similar to the procedures reported in other studies (35, 42). Analyses were conducted using a Waters Alliance 2795 high-perfor-

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mance liquid chromatograph (HPLC) device interfaced with a Waters Micromass Quattro Micro detector with an electrospray ionization source in positive ionization mode. HPLC separation of tetracycline and chlortetracycline was achieved using a Waters XTerra MS C18 column (particle size, 5 ␮m; 4.6 mm by 150 mm) operated at 30°C. The mobile phase consisted of 0.24% (vol/vol) acetic acid in Milli-Q water (solvent A) and acetonitrile (solvent B), with a gradient as follows. Solvent B was increased linearly from 10% to 35% over 7 min, held for 3 min, and then increased to 100% and held for 1 min. Solvent B was then returned to 10%, and equilibration was allowed to occur for 12 min. The flow rate was 0.2 ml/min. The injection volume was 50 ␮l (autosampler at 10°C). Mixed standards of chlortetracycline (Sigma-Aldrich) and tetracycline (Fisher Scientific) (10 ␮g/ml) were infused through an integrated syringe pump at a flow rate of 10 ␮l/min to tune the mass spectrometer and optimize parameters. The multiple-reaction-monitoring mode was used to analyze target compounds. Detection limits were 3.5 and 5.5 ␮g/kg (wet weight) of soil for tetracycline and chlortetracycline, respectively. After spiking 1 g of soil with 125 ng of tetracycline standards (in triplicate), the same extraction, SPE cleanup, and concentration procedures were performed, and recoveries were calculated at 45% for tetracycline and 34% for chlortetracycline. Enumeration and isolation of heterotrophic Tcr bacteria. Enumeration of Tcr bacteria was determined within 36 h of sample collection. Soil samples (5 g wet weight) were thoroughly suspended (in triplicate) in 45 ml of sterile phosphate-buffered saline (pH 7.4) by vortexing and gentle sonication. Samples were then serially diluted and plated onto tryptic soy agar (TSA) containing tetracycline (0, 2, 4, or 8 ␮g/ml) plus nystatin (50 ␮g/ml) (to prevent fungal growth). Plates were incubated at room temperature in the dark for 12 days before colony counting was performed. Resistance levels are reported as the percentage of Tcr bacteria in the total population of cultivatable bacteria. Single colonies with different colors and/or morphologies were picked from TSA plates containing Tc (8 ␮g/ml). Pure cultures were obtained by streaking to single colonies five or more times. The purity of each culture was confirmed microscopically before the identity of each isolate was determined by 16S rRNA gene sequencing. Sequences were analyzed using the Ribosomal Database Project Classifier program (http://rdp.cme .msu.edu/classifier/classifier.jsp). DNA extraction and PCR. Environmental DNA (eDNA) was extracted from subsurface samples by the use of PowerMax soil DNA isolation and PowerSoil DNA isolation kits (MoBio Labs) within 5 days of collection. eDNA extracted from aquifer material was further concentrated using a QIAquick PCR purification kit (Qiagen). Genomic DNA was extracted from pure cultures by the use of a DNeasy blood and tissue kit (Qiagen). Extraction yield and DNA quality were evaluated spectrophotometrically. PCR was performed using the primers listed in Table 1. Typical reaction mixtures contained 1⫻ Taq reaction buffer, 1 U of ExTaq DNA polymerase (TaKaRa), primers (0.48 ␮M each), deoxynucleoside triphosphates (dNTPs) (0.2 mM each), and 10 to 20 ng of the template. Thermal cycling was performed using an initial denaturation at 94°C for 5 min, followed by 30 to 35 cycles of 94°C for 45 s, the annealing temperature (Table 1) for 1 min, and 72°C for 1 min, followed by a final extension at 72°C for 10 min. Positive controls included NC_001393 for tet(K) (24), NC_006372 for tet(M) (20), and sequenced PCR amplicons for other ARGs. Negative controls included reactions using ultrapure water (Quality Biological, Inc.) and genomic DNA of a Tcs Escherichia coli strain as the template. Controls for inhibitory substances were performed when negative results were obtained. First, the eDNA template was diluted 10- and 100-fold prior to use, as suggested previously (45). This approach also proved effective for negating inhibitors in this study. Second, PCR was performed with 16S rRNA gene primers (Table 1) rather than ARG primers. Third, selected eDNA samples were spiked with ⬍2 ng of genomic DNA of a tet(L)-positive strain and subjected to tet(L)-specific PCR.


tet(L)-Carrying Plasmid Persistent in Farm Soil

TABLE 1 Primers used for conventional PCR, qPCR, and DNA sequencing Primer (pairs)

Target

Protein encoded

Sequence (5= ¡ 3=)

TetK-F TetK-R TetL-F TetL-R TetM-F TetM-R TetO-F TetO-R ErmA-F ErmA-R ErmB-F ErmB-R ErmC-F ErmC-R ErmF-F ErmF-R Mob-F Mob-R fD1 rD1 rP2 TetL-qFc TetL-qR TetO-qF TetO-qR ErmB-qF ErmB-qR Mob-qF Mob-qR 16S-qF 16S-qR

tet(K)

Efflux pump

tet(L)

Efflux pump

tet(M)

Ribosome protection protein

tet(O)


erm(A)

rRNA methylase

erm(B)

rRNA methylase

erm(C)

rRNA methylase

erm(F)

rRNA methylase

mobb

Plasmid mobilization protein

16S rRNA gene

NAd

tet(L)

Efflux pump

tet(O)


erm(B)

rRNA methylase

mobb

Plasmid mobilization protein

16S rRNA gene

NA

TTAGGTGAAGGGTTAGGTCC GCAAACTCATTCCAGAAGCA GTTGCGCGCTATATTCCAAA TTAAGCAAACTCATTCCAGC ACAGAAAGCTTATTATATAAC TGGCGTGTCTATGATGTTCAC ACGGARAGTTTATTGTATACC TGGCGTATCTATAATGTTGAC AAGCGGTAAACCCCTCTGAG TCAAAGCCTGTCGGAATTGG GAAAAGGTACTCAACCAAATA AGTAACGGTACTTAAATTGTTTAC ATCTTTGAAATCGGCTCAGG CAAACCCGTATTCCACGATT TGTTCAAGTTGTCGGTTGTG CAGGACCTACCTCATAGACA CAGCGGAGATTGAACAGCAGA AGCACTAACCGGCCTTGAAAT AGAGTTTGATCCTGGCTCA AAGGAGGTGATCCAGCC ACGGCTACCTTGTTACGACTT GGTTTTGAAYGTYTCATTACCTGAT GATAGCTTTCCATATASAGCTGTTCC TTGACGCAGGAAAGACAACA TTGACGCTCCAAATTCATTG GGTTGCTCTTGCACACTCAA CTGTGGTATGGCGGGTAAGT AGACCGAAAAACAGAAAACCATTC CCGATTCATGCAATAAACTTCA CGGTGAATACGTTCYCGG GGWTACCTTGTTACGACTT

Annealing tempa (°C)

Amplicon size (bp)

Reference

56

718

1

52

788

1

55

171

3

52

171

3

52

441

34

52

639

54

52

295

34

52

260

33

56

448

This study

56

⬃1,530

61

60

126

This study

58

119

This study

63

117

This study

63

139

This study

60

142

55

a

Annealing temperatures varied from reference temperatures for some primer pairs. Mobilization genes of a group of broad-host-range plasmids (pSU1, pMA67, pLS55, and pBHS24). c Primers used in real-time quantitative PCR are labeled qF and qR. d NA, not available. b

Plasmid preparation and transformation and restriction enzyme digestion. Plasmids were isolated from pure cultures of soil bacteria grown in tryptic soy broth by the use of a QIAprep Spin Miniprep kit (Qiagen). These plasmids were transformed into E. coli TOP10 (Invitrogen) according to the manufacturer’s protocol. Plasmids encoding functional tet genes were identified by plating transformants on LB agar containing tetracycline (8 ␮g/ml). Tcr transformants were then transferred to LB broth containing tetracycline (8 ␮g/ml), and plasmid DNA was purified from overnight liquid cultures. Plasmids were subjected to restriction digestion with BamHI, EcoRI, HindIII, and SacI (Promega) and HhaI and ScaI (NEB) according to the manufacturers’ protocols. Restriction fragments were separated by agarose gel electrophoresis for size approximations. Real-time quantitative PCR and data normalization. All currently available nucleotide sequences for tet(L), tet(O), and erm(B) genes were downloaded from GenBank, and alignments of these sequences were generated using ClustalX 2.0 (36). Primers (Table 1) for qPCR were designed using the Primer3 program (50) to target consensus sequences, with the PCR product size specified in the range of 100 to 150 bp for amplification efficiency. A primer pair (Mob-qF and Mob-qR) was also designed to amplify a section of the mobilization genes (mob) of the near-identical plasmids pSU1 (NC_014015), pMA67 (NC_010875), pLS55 (NC_ 010375), and pBHS24 (HM235948). The specificity of all primers was examined using Primer-BLAST (http://www.ncbi.nlm.nih.gov/tools /primer-blast/). Mob-qF and Mob-qR primers would not target other

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known plasmids. qPCRs were performed using a Bio-Rad iCycler with iQ SYBR green Supermix (Bio-Rad), 2 ␮l of the eDNA template, and the primers (0.48 ␮M each) in 25-␮l reaction volumes. The thermal program consisted of an initial denaturation at 95°C for 3 min, followed by 40 cycles of 10 s at 95°C, 20 s at the annealing temperature, and 30 s at 72°C. A melt curve analysis was conducted to verify reaction specificity. The PCR product was denatured (95°C for 1 min) and annealed (55°C for 1 min) before melt curve analysis, which consisted of incrementally increasing the reaction temperature (0.5°C/10 s) from 55 to 95°C. Calibration curves (4 to 6 log range in duplicate or triplicate) were generated using transformed pSU1 for tet(L) and mob, cloned PCR products (StrataClone PCR cloning kit; Stratagene) for tet(O) and erm(B), and a cloned 16S rRNA gene (TOPO TA cloning kit; Invitrogen). Correlation coefficients (R2) ⬎ 0.99 were obtained for all calibration curves, with amplification efficiencies of 90% to 110%. For each reaction, detection limits were ⬍85 copies for 16S rRNA genes, ⬍183 copies for the erm(B) gene, and ⬍120 copies for other genes. Dilution of eDNA samples was sufficient to minimize PCR inhibition from soil matrix components. Therefore, 3 to 6 independent 10-fold dilutions (up to 10⫺3) of each eDNA sample were used as the template in reactions. Relative standard deviations of threshold cycle (CT) data were within 2.35% for all reported data. qPCR products were also verified by gel electrophoresis and sequencing. The copy numbers of each gene were further normalized to eubacterial 16S rRNA gene copy numbers to assess their relative abundances in the soil microbial community. This accounts

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FIG 1 Apparent electrical conductivity map of the broiler chicken farm study site. ECa data (collected from depths of up to 1.5 m) are in the vertical dipole orientation. Buildings are shown in gray. Red stars denote sampling sites.

for variations between different environmental samples in eDNA extraction efficiencies and total bacterial population sizes. DNA sequencing and sequence analyses. PCR products and plasmids purified from E. coli transformants were sequenced on both strands by the use of an Applied Biosystems 3730xl DNA Analyzer at the Johns Hopkins University School of Medicine Sequencing Facility. PCR products were sequenced using PCR primers. Plasmids were initially sequenced using TetL-F and TetL-R primers and subsequently by primer walking. SeqMan Pro (DNASTAR) was used for contig assembly. Open reading frames (ORFs) were identified using the NCBI ORF finder (http://www.ncbi.nlm .nih.gov/gorf/gorf.html) and Glimmer3 program (http://www.ncbi.nlm .nih.gov/genomes/MICROBES/glimmer_3.cgi), while BLASTP and conserved domain searches were used to identify potential coding sequences. Transmembrane helices were predicted using TMHMM 2.0 (http://www .cbs.dtu.dk/services/TMHMM/). ClustalX 2.0 was used to align sequences with the BLOSUM protein weight matrix (36). MEGA4 was used to generate neighbor-joining trees with the JTT model (57). The reliability of the resulting trees was assessed by bootstrap analysis of 1,000 replicates. Nucleotide sequence accession numbers. Nucleotide sequences have been deposited into GenBank under accession numbers GU584198 to GU584211 (16S rRNA genes), JN232536 to JN232538 and JN232541 to JN232546 [tet(L) genes], and NC_014015, JN980137, and JN980138 (plasmids).

RESULTS

Geophysical exploration and sample collection. Our electrical conductivity survey of the broiler chicken farm involved 2,364 measurements performed using electromagnetic induction (EMI) and focused on the upper 1.5 to 2 m of the subsurface. The apparent electrical conductivity (ECa) for the whole surveyed area (mapped in Fig. 1) averaged 28.25 mS/m, and the range of ECa measurements fell between ⫺776.36 and 217.62 mS/m. Extreme positive and negative values (such as those at the eastern ends of the poultry barns) represented interference from farm equipment and structures and other metallic objects. Areas of high ECa (⬎28 mS/m) that surrounded the chicken barns and the waste storage shed most likely indicated spots where the soils were exposed to poultry waste (25). The waste-affected zone extended northward from the poultry litter storage shed and across a drainage ditch into a cultivated field, probably as a result of local runoff and groundwater flow. At the time of this survey, the groundwater table within the surveyed area was located 50 to 60 cm below the ground surface, where the temperature was ⬃8°C. According to our soil taxonomic classification, the majority of the soils within the surveyed area represent the Fa (Fallsington sandy loam) series,

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which normally contain 5% to 18% clay and 0.5% to 2.0% organic matter, with a pH range of 3.5 to 5.5 (16). Soil representing the KsA (Klej loamy sand) series is also present. Two sampling sites on the farm were chosen based on their ECa values. One site (Fig. 1, site A) was located south of, and adjacent to, the waste storage shed. Its ECa (⬎60 mS/m) was significantly higher than measurements from other spots in the area and higher than the average ECa value for the whole surveyed area. The other site (Fig. 1, site B) was located 10 m south of site A. It had an ECa (⬃32 mS/m) close to the average value for the whole site. Therefore, site A represented spots with potentially significant exposure to chicken waste, while site B represented spots with only marginal exposure to waste. Here we refer to samples collected during poultry production as A2008, Aq2008, B2008, and Bq2008 (with A or B representing topsoil and Aq or Bq representing aquifer material) and to samples collected 2 years after the operation closed down as A2010 and B2010. More-pristine topsoils were collected from three sites in the Pocomoke State Forest: SF1 (38°7.278=N, 75°25.790=W); SF2 (38°7.364=N, 75°25.745=W); and SF3 (38°7.986=N, 75°27.125=W). According to the USDA soil maps, topsoils from at least one site belonged to the Fa series. The other sites might also contain soils from the KsA and In (Indiantown silt loam) series. The majority (70%) of the regional land is currently zoned for agriculture (broiler production being the largest enterprise), while the forest has not been used for agricultural purposes for decades. Therefore, soils from the state forest, though of various soil series, are considered appropriate background controls for comparison with farm soils. The forest soils all showed pH (3.5 to 3.7) within the typical range of their soil series. Soil samples from farm site B also showed pH within this range: 4.0 to 4.5 for B2008 and B2010. An aquifer material showed similar pH: 4.7 for Bq2008. However, at site A, the topsoil had much higher pH than the aquifer material: 6.6 to 6.7 for A2008 and A2010 versus 4.6 for Aq2008. Such a difference in the soil pH versus the aquifer pH could be due to long-term impact of runoff from composting poultry litter on the local topsoil (25). Detection of low levels of tetracyclines in the waste-impacted farm soil. Antibiotic use in poultry production could have effects on the enteric bacteria of the birds (10, 14) and thus on the ARGs present in their waste. In this study, we used an LC-MS/MS method to determine the presence of tetracycline and chlortetracycline in the farm and forest soils. Neither tetracycline nor chlortetracycline was detected in the forest soils. In comparison, tetracycline and chlortetracycline were detected in sample A2008 at 7.3 ⫾ 1.6 and 5.3 ⫾ 2.0 ␮g/kg (wet weight) of soil, respectively, even though this sample had been stored at 4°C in the dark for 2 years prior to the analysis. The waste-impacted farm soil contained a high proportion of Tcr bacteria. Tetracycline resistance among culturable heterotrophic soil bacteria was analyzed for two forest sites, SF1 and SF2, and the two farm sites, A2010 and B2010, using TSA medium alone or supplemented with tetracycline. With respect to the total number of bacteria per gram of soil, no statistically significant differences (P ⬎ 0.65 by analysis of variance [ANOVA]; P ⬎ 0.749 by Tukey’s honestly significant difference [HSD] test) were observed among these samples: (2.4 ⫾ 1.9) ⫻ 107 CFU/g for A2010, (5.9 ⫾ 4.3) ⫻ 107 CFU/g for B2010, (6.0 ⫾ 5.2) ⫻ 107 CFU/g for SF1, and (3.0 ⫾ 5.2) ⫻ 107 CFU/g for SF2. However, the proportion of Tcr bacteria able to grow in the presence of tetracycline at 2, 4, or 8



tet(O)

(2.55 ⫾ 0.60) ⫻ 103 ND ND ND ND ND

erm(B)

(3.11 ⫾ 0.69) ⫻ 106 (8.17 ⫾ 1.22) ⫻ 105 ND ND ND ND

mob

(2.11 ⫾ 0.73) ⫻ 10⫺3 (1.26 ⫾ 0.45) ⫻ 10⫺4 (2.24 ⫾ 3.89) ⫻ 10⫺6 (4.59 ⫾ 8.18) ⫻ 10⫺6 (7.13 ⫾ 1.02) ⫻ 10⫺6 (7.72 ⫾ 1.90) ⫻ 10⫺6

tet(L)

(4.57 ⫾ 1.31) ⫻ 10⫺6 (3.69 ⫾ 0.91) ⫻ 10⫺6 ND ND ND ND

tet(O)

(5.07 ⫾ 1.69) ⫻ 10⫺8 ND ND ND ND ND

erm(B)

(6.18 ⫾ 2.01) ⫻ 10⫺5 (1.25 ⫾ 0.36) ⫻ 10⫺4 ND ND ND ND

mob

No. of copies per copy of 16S rRNA genea

tet(L)

(2.30 ⫾ 0.36) ⫻ 105 (2.42 ⫾ 0.00) ⫻ 104 NDb ND ND ND

No. of copies/g wet soil

16S rRNA gene

(1.06 ⫾ 0.26) ⫻ 108 (8.27 ⫾ 2.09) ⫻ 105 (1.47 ⫾ 2.54) ⫻ 104 (1.30 ⫾ 2.24) ⫻ 104 (1.65 ⫾ 2.33) ⫻ 104 (2.05 ⫾ 0.48) ⫻ 104

TABLE 2 Abundance of 16S rRNA genes, three ARGs, and the pSU1 mob gene in different soils

Sample

(5.03 ⫾ 1.20) ⫻ 1010 (6.56 ⫾ 1.62) ⫻ 109 (6.57 ⫾ 0.87) ⫻ 109 (2.82 ⫾ 1.19) ⫻ 109 (2.31 ⫾ 0.48) ⫻ 109 (2.65 ⫾ 0.20) ⫻ 109

The relative abundances are represented as the number of copies of each gene per copy of the 16S rRNA gene. Data are presented as means ⫾ standard deviations. ND, not detected.

A2008 A2010 B2010 SF1 SF2 SF3

a


b

␮g/ml was significantly higher in A2010 soil than in any other soil (P ⬍ 0.015 by Welch’s ANOVA): 18.1%, 9.9%, and 6.8% of the total, respectively. In comparison, site B on the farm and the two forest sites showed similar and lower proportions of Tcr bacteria: 0.2% to 0.5%, 0.1% to 0.4%, and 0.1% to 0.2% of the total for the three resistance levels, respectively. Therefore, although the two sites were on the same farm, site A had a significantly higher proportion of Tcr bacteria than site B, which was just 10 m away. The EMI survey, conducted in 2007, originally suggested a difference between these two sites. However, whether this difference played a role in the results of this culture-dependent analysis, conducted 3 years later, was impossible to determine without a wider range of samples. Presence and persistence of tet and erm genes in the wasteimpacted farm soil. The majority of soil bacteria are uncultured and unculturable. To determine the occurrence of ARGs in the entire bacterial population, culture-independent PCR was used to screen total eDNA from the forest (SF1, SF2, and SF3) and the farm (Aq2008, A2008, A2010, and B2010) environmental samples for the presence of tet(K), tet(L), tet(M), tet(O), erm(A), erm(B), erm(C), and erm(F) genes. These ARGs have previously been detected in poultry and poultry litter (1, 17, 23) and hence are potential candidates for detection in waste-impacted soils. None of the ARGs were amplifiable from the state forest topsoils or the B2010 topsoil. In contrast, the tet(L), tet(M), tet(O), erm(A), erm(B), and erm(C) genes were identified in the A2008 topsoil, and a subset of these genes, tet(L), tet(M), tet(O), and erm(C), could still be identified in the A2010 topsoil. In spite of the presence of six ARGs in the A2008 topsoil, no ARGs were identified in the underlying Aq2008 aquifer material. Quantification of ARGs at the waste-impacted site during and after farm operation. Qualitative PCR results from the site A soils suggested a potential decline in the variety of ARGs present between 2008 and 2010. Therefore, qPCR was used to evaluate the changes in the abundances of three ARGs at this site. Two persistent tet genes [tet(L) and tet(O)] and the nonpersistent erm(B) gene (as suggested by conventional PCR assays) were selected for quantification. Results are summarized in Table 2. Between 2008 and 2010, the abundances of all three ARGs in the soils decreased. While tet(L) and tet(O) were still detected in 2010, erm(B) was no longer detectable. This observation was consistent with the qualitative PCR results. Furthermore, tet(L) had the highest copy number among the three ARGs, followed by tet(O) and then erm(B). At site B (B2010) and all forest sites (SF1, SF2, and SF3), only tet(L) was detected in the soils. Interestingly, no significant difference between the B2010 and forest soils (P ⬎ 0.98 by ANOVA) in tet(L) abundances was observed. Compared to the forest soils, the farm soils contained higher 16S rRNA gene copy numbers (6.56 ⫻ 109 versus 2.59 ⫻ 109 copies per gram of soil in 2010 [P ⬍ 1e-7 by ANOVA]), probably due to the differences in soil pH and/or land use. Therefore, the relative abundances of each ARG (copies of gene per copy of the eubacterial 16S rRNA gene) were compared to assess the prevalence of each ARG in the different soils. Farm site A showed much higher tet(L) prevalence than farm site B or any of the forest sites (Table 2). Moreover, at site A, the relative abundances of all three ARGs declined between 2008 and 2010 (Fig. 2). While tet(L) numbers decreased 16.8-fold, tet(O) numbers decreased only 1.2-fold. Thus, of the genes analyzed, tet(L) was the most prevalent and tet(O) was the most persistent (Fig. 2).

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FIG 2 Prevalence of specific ARGs at the waste-impacted site during routine poultry litter deposition (2008) and 2 years after all waste was removed (2010). The prevalences of a group of broad-host-range mobilizable plasmids that carry tet(L) were estimated by quantifying their mobilization gene, mob. Error bars represent the standard deviations of the results from at least three independent qPCR runs. Numbers in parentheses reflect fold changes in the relative abundances of the genes from 2008 to 2010.

Tcr soil bacteria from the waste-impacted site contained tet(L)-carrying plasmids. MGEs, including plasmids, are frequently involved in the transfer of ARGs from animal waste into agricultural soils (8, 30). To determine if MGEs were associated with the occurrence of some of the ARGs identified in this study, the presence of Tcr-encoding plasmids was screened for in 14 Tcr bacteria isolated from the waste-impacted site (A2008 soil). The species of the bacterial isolates were determined by 16S rRNA gene sequencing, and all were indigenous soil bacteria. Seven were strains of Bhargavaea cecembensis, three were Sporosarcina ureae, three were species of Bacillus, and one was a strain of Microbacterium oxydans (Table 3). The absence of certain enteric bacteria in our small collection could be due to a delay between sample collection and the initiation of bacterial isolation, as E. coli strains in particular may not survive beyond 24 h in soils at 4°C (9). The presence or

absence of tet(L), tet(K), tet(M), and tet(O) genes in these soil bacteria was determined by PCR assays. Twelve of the 14 isolates contained tet(L). Two of those 12 also contained tet(M). No isolates contained tet(K) or tet(O) (Table 3). Plasmids in 9 of the 14 Tcr soil isolates were identified using a commercial, alkaline-lysis-based Miniprep technique (Table 3). Eight of the nine plasmids (the exception being pDMV3A) conferred Tcr to E. coli TOP10 after transformation. The eight Tcrencoding plasmids were reisolated from E. coli, and PCR was used to show that all carried tet(L) genes (Table 3). Digestion with restriction enzymes suggested that seven of the eight plasmids were ⬃5 kb in size and were very similar or perhaps identical (for example, the HhaI fragments generated were ⬃2.0 kb, ⬃1.5 kb, ⬃1.0 kb, and ⬃0.5 kb for each plasmid). The eighth plasmid (pBSDMV9) was slightly larger and had a distinctly different HhaI digestion pattern. Among the seven identically sized plasmids, three were isolated from Bhargavaea cecembensis, three were from Sporosarcina ureae, and one was from Bacillus galactosidilyticus. For these plasmids, the PCR-amplified tet(L) gene sequences were identical. Consequently, complete DNA sequences were obtained for three representative plasmids: pBSDMV46A (JN980138) from B. cecembensis strain DMV46A, pSU1 (NC_014015) from S. ureae strain DMV4, and pDMV2 (JN980137) from B. galactosidilyticus strain DMV2 (Table 3). While all three plasmids were 5,031 bp in size, pBSDMV46A had a single-base difference from pSU1 and pDMV2 (which were identical to each other). The pBSDMV46A, pSU1, and pDMV2 sequences were almost identical to those of three recently reported Tcr-encoding mobilizable plasmids, pMA67 (NC_010875) (39), pLS55 (NC_010375) (4), and pBHS24 (HM235948) (46). A detailed comparison of these plasmids, including pSU1, is available in reference 46. In brief, nearly all of the nucleotide differences between the plasmids are located within their tet(L) genes. A phylogenetic analysis showed that their predicted Tet(L) proteins form a clade separate from other previously reported Tet(L) proteins (Fig. 3), reflecting the relatively ancient divergence of this tet(L) gene (39). In pBSDMV46A, pSU1, and pDMV2, a 20-amino-acid putative leader peptide was identified upstream of tet(L), suggesting the possibility of inducible tet(L)

TABLE 3 Characteristics of Tcr bacteria isolated from the waste-impacted site

Isolate

Bacterial phylum

Best phylogenetic match (accession no.)

DMV1 DMV2 DMV3A DMV4 DMV5 DMV6B DMV7 DMV8B DMV9 DMV42A DMV43A DMV44A DMV45A DMV46A

Actinobacteria Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes Firmicutes

Microbacterium oxydans (GQ923776) Bacillus galactosidilyticus (NR_025580) Bacillus galactosidilyticus (NR_025580) Sporosarcina ureae (NR_041782) Sporosarcina ureae (NR_041782) Sporosarcina ureae (NR_041782) Bacillus sp. G2(2006) (DQ667102) Bhargavaea cecembensis (NR_042537) Bhargavaea cecembensis (NR_042537) Bhargavaea cecembensis (NR_042537) Bhargavaea cecembensis (NR_042537) Bhargavaea cecembensis (NR_042537) Bhargavaea cecembensis (NR_042537) Bhargavaea cecembensis (NR_042537)

a b c

Sequenced 16S rRNA gene (bp)

% 16S rRNA gene identity

tet gene(s)

Plasmid

839 1,430 1,430 840 918 972 914 1,445 1,430 1,423 909 946 940 1,432

100 99 99 99 99 100 98 99 99 99 99 99 99 99

NDb tet(L) on plasmid tet(L) tet(L) on plasmid, tet(M) tet(L) on plasmid, tet(M) tet(L) on plasmid ND tet(L) tet(L) on plasmid tet(L) tet(L) tet(L) on plasmid tet(L) on plasmid tet(L) on plasmid

ND pDMV2a pDMV3A pSU1a pDMV5 pDMV6B NAc ND pBSDMV9 ND ND pDMV44A pDMV45A pBSDMV46Aa

Complete sequence obtained for transformed plasmid repurified from E. coli TOP10. ND, not detected. NA, not available.

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FIG 3 Neighbor-joining tree of TetL efflux pumps. The bootstrap consensus tree was inferred from 1,000 replicates. Branches corresponding to partitions reproduced in less than 50% of bootstrap replicates were collapsed. The bar represents 0.02 amino acid substitutions per site. GenBank accession numbers, plasmid names, and host genera are listed. TetL sequences identified in this study are denoted by a star symbol and are shown collectively as being on pSU1.

expression (4). Apart from tet(L), pBSDMV46A, pSU1, and pDMV2 also contain sequences potentially involved in plasmid replication (rep) and mobilization (mob) (4). Quantification of the pBSDMV46A, pSU1, and pDMV2 group of plasmids. The common occurrence (in 7 of 14 isolates) of the tet(L)-carrying plasmids pBSDMV46A, pSU1, and pDMV2 suggested that these plasmids might be the cause of the relatively high prevalence of tet(L) in the soil microbial community at site A. To track the actual prevalence of these plasmids, a primer pair (Mob-qF and Mob-qR; Table 1) was designed to specifically target the mob region of these plasmids. This primer pair would not target the mob genes of other plasmids whose sequences have been deposited in GenBank. Similarly to all ARGs analyzed previously, the copy number of mob per gram of soil declined (3.8-fold) between 2008 and 2010 (Table 2). However, the relative abundance of the mob gene increased by 2.0-fold during the 2-year period of the study (Fig. 2). In 2008, it appeared that there were a number of different tet(L) genes in the soil microbial community, as sug-


gested by various tet(L) sequences identified in the soil bacterial isolates (JN232536 to JN232538 and JN232541 to JN232546) and by the tet(L)/mob ratio of 34:1. However, by 2010 this diversity may have declined to the point where most of the tet(L) genes were present on the same plasmid, resulting in a 1:1 ratio of tet(L)/mob. In contrast to what was observed at site A, the mob gene was not detected at either site B on the farm or any of the forest sites. DISCUSSION

The emergence of antibiotic resistance as a public health concern, and the potential role of industrial-scale food animal production in this process (22, 53), has spawned many studies that survey CAFO sites for the presence and local abundance of ARGs (12, 43, 44). Such studies are essential in analyzing the association of these ARGs with farming practices. This study, however, was aimed at identifying ARG-carrying MGEs that might explain the prevalence and persistence of the associated ARGs in chicken-wasteaffected soils. By isolating a number of Tcr soil bacteria, we

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identified a tet(L)-carrying plasmid in species of Bhargavaea, Sporosarcina, and Bacillus at a conventional chicken farm on the delmarva peninsula. Because no analysis of the poultry litter was performed, no direct connection between the plasmid and the poultry (as its potential source) is suggested here. However, the previous identification of almost identical mobilizable plasmids in Paenibacillus, Lactobacillus, and Bacillus species (4, 39, 46), isolated from a range of different sources, indicates that these plasmids are capable of horizontal transfer between Gram-positive bacteria, an important characteristic in the spread of antibiotic resistance. In this study, to assist the field sampling, an EMI survey was conducted on the farm, at an area surrounding the poultry litter storage shed and the two chicken houses. Based on the ECa map, sites A and B were chosen for analyzing and comparing the occurrence of antibiotic resistance, using both culture-dependent and -independent methods. Site A, adjacent to the waste storage shed, had an ECa value much higher than the average value for the entire surveyed area, probably suggesting a relatively severe impact of litter at this site. Site B, about 10 m south of site A, had an ECa value close to the average, which may imply only a marginally impact of litter at this site. EMI measurements imply differences in hydropedological properties such as the concentration of ions and soluble salts in soils (7). EMI has been successfully used for inferring the relative concentrations, extents, and movements of contaminants from animal waste-holding facilities (6, 18, 19, 28, 37). Poultry litter contains a large amount of trace elements (32), whose leaching can cause increased conductivity of soil due to the presence of accumulated metal salts (25). Being a noninvasive tool, EMI has the advantages of portability, speedy operation, flexible observation with respect to depths, and moderate resolution of subsurface features. Maps prepared using densely sampled, moderate-resolution geophysical data can provide the basis for assessing site conditions, with a comprehensive coverage of sites (37). While interpretation of geophysical data does not substitute for direct-sample analyses, such a method can assist the guidance of sampling strategies, supplement sample analyses, and help researchers to understand the hydropedological heterogeneity on site. Consistent with the ECa difference originally observed in 2007, a disparity still existed in 2010 between site A and B with regard to soil pH, Tcr levels among culturable heterotrophic soil bacteria, and the occurrence and prevalence of selected ARGs in the soil microbial communities. No significant difference was observed between analysis results from site B and those from several sites in a regional state forest. The forest sites were chosen based on soil taxonomic classification and served as a background control for comparison, having been unaffected by agricultural practices for several decades at least. In detail, while site B and all of the forest sites showed pH values within the typical range of the classified soil series, site A showed significantly higher soil pH (2 to 3 units) both in 2008 and in 2010. Such a disparity was most likely due to the impact of chicken waste, as increased pH has also been observed in soils fertilized with poultry litter (25). In 2010, 2 years after all the chicken waste was removed from the farm, cultivation showed that, compared to the other sites, site A contained a much higher proportion of culturable soil bacteria resistant to tetracycline. Soil bacteria are naturally resistant to various antibiotics, and the majority of soil bacteria are not cultured or culturable (15, 38, 47).

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Therefore, our culture-dependent analysis reflects the state of only a small proportion of the overall Tcr soil bacterial population. Despite this limitation, the higher Tcr levels (⬎10-fold at the 8-␮g/ml level) at site A argue for an impact of the chicken waste on the occurrence of ARB in the agricultural soil, an effect that has been frequently observed globally (53, 58, 60). Culture-independent PCR assays performed with eDNA were used to determine the occurrence of several tet and erm genes in all soil bacterial populations, and a variety of these genes were detected at site A but not at site B or at any forest site. The ARGs screened for in this study have been repeatedly found in animal-waste-impacted environments (12, 30, 33, 43, 44), and particularly in poultry and poultry litter (1, 17, 23). Hence, their presence at the litter-impacted site might suggest an input from poultry litter. Unfortunately, no poultry litter samples were made available for this study. Therefore, it is impossible to directly compare the profiles of ARB and ARGs in the litter-impacted soil to those in the poultry litter itself. Some studies suggest that the development of resistance reservoirs may not be an easily reversible event (22), at least within a span of years (51). Our qualitative PCR results showed that only a subset of ARGs was still detectable in the litter-impacted soil 2 years after all the chicken waste was removed from the farm. Such a decline in the variety of ARGs was confirmed quantitatively by qPCR analyses, which showed that all three ARGs identified in 2008 had decreased in abundance by 2010. Therefore, the abundance of several ARGs could have dropped below the detection limits of conventional PCR, as exemplified by the erm(B) analyses. While tet(L) was detected neither at site B nor at any of the forest sites by conventional PCR, it was detected at relatively low copy numbers by qPCR at these sites. This could be attributed to the higher sensitivity of qPCR, compared to conventional PCR, in our assays. The size of soil microbial populations is one factor that can influence ARG abundance in soil. We thus evaluated ARG prevalence by normalizing ARG copy numbers to eubacterial 16S rRNA gene copy numbers. Among the ARGs we quantified, tet(L) was the most prevalent both in 2008 and in 2010, whereas tet(O) had the greatest persistence over the 2-year period. A large part of this study was performed in an effort to understand the mechanisms associated with the prevalence and persistence of tet(L) in the farm soil. Indigenous soil bacteria were isolated from the chicken-waste-impacted site. These isolates came from various bacterial genera typical of soil bacteria. The majority of the isolates possessed tet(L), agreeing with the relatively high prevalence of this gene in the soil microbial community indicated by the qPCR analyses. In 8 of the 12 tet(L)-positive isolates, the tet(L) gene was located on a plasmid that was isolatable using a commercial kit. Restriction enzyme digestion suggested that only two different Tcr plasmids existed. One plasmid, represented by pSU1 (NC_014015), was found in three bacterial species, Sporosarcina ureae, Bacillus galactosidilyticus, and Bhargavaea cecembensis, implying the involvement of horizontal gene transfer (HGT) in its distribution. Sequence analysis of pSU1 predicted genes and genetic elements involved in rolling-circle replication, such as rep, cop, dso, and ssoT. In addition, the identification of a mob gene and an oriT site indicated that pSU1 is a mobilizable plasmid, capable of HGT (39). The prevalence of this plasmid in the different soils was estimated by quantifying its mob gene. This mob gene was detected only at the waste-impacted farm site. Interestingly, the relative abundance of the mob gene increased



2-fold during the 2-year period whereas the relative abundance of tet(L) decreased 17-fold. This led to a 1:1 ratio of mob to tet(L) by 2010, implying that pSU1 might have become the major carrier of the tet(L) gene by that time. It is noteworthy that several recent studies reported the isolation of three plasmids almost identical to pSU1 from entirely different ecosystems: pMA67 (NC_010875) from a U.S. honeybee pathogen (39), pLS55 (NC_010375) from an Italian raw milk product (4), and pBHS24 (HM235948) from an Irish marine sponge isolate (46). In contrast to a previous report on the unsuccessful transformation of pMA67 into E. coli TOP10 (a recA mutant) (39), each of the plasmids described in this study was transformable into E. coli TOP10. The reason for this difference remains unknown. Including the three host species observed in this study, the set of pSU1, pMA67, pLS55, and pBHS24 plasmids seem to have a broad host range, naturally occurring in the orders Bacillales and Lactobacillales, and may have served as a BacillalesLactobacillus vehicle (5). The rapidly expanding database of complete plasmid sequences facilitates network analyses on plasmid populations. Results from such analyses suggest that both taxonomic distances and geographic barriers between bacteria can often be overcome by HGT events, as shown by common antibiotic resistance determinants being shared by phylogenetically unrelated bacteria and/or those inhabiting distinct or distantly separated environments (21). In particular, interclass links between Bacilli and Lactobacilli have been previously observed (56). Plasmids appear to be key vectors of genetic exchange between bacteria in an evolutionary history (26), and their mobility has been shown to be particularly important in spreading genes, including ARGs, in microbial communities (56). While the plasmid pMA67 was stable with respect to segregation in its natural host Paenibacillus larvae in the absence of tetracycline selection (39), whether pBSDMV46A, pSU1, and pDMV2 share this feature remains unknown. Additionally, the extent to which tetracycline selection could have existed in the farm soil environment is unknown. Low levels of tetracycline and chlortetracycline were detected in the waste-impacted site in 2008, despite the extended storage of the soil sample prior to its analysis, and Hamscher et al. (27) previously reported that tetracyclines can be detected in manured soils stored at 4°C for as long as 12 months. Considering the recovery rates in our analysis and the possibility of degradation during storage, higher concentrations of tetracycline antibiotics might have existed at site A. Still, the bioavailability of antibiotics adsorbed to soil materials in general is unclear (52), so further research is needed to understand the potential effects of residual tetracyclines in soil on the abundance of Tcr plasmids, including those that are stable with respect to segregation such as the pSU1 type. Another important aspect of research on possible transmission routes of ARB and ARGs from CAFOs into the environment lies in whether the impact of animal waste extends through the vadose zone into groundwater. While this study did not focus on this topic, some observations imply that the impact of the chicken waste might not have reached the aquifer at site A. First, though soil pH was significantly higher at site A than at site B, the pH values of the aquifer materials at these sites were almost the same. Second, while a variety of ARGs were detected in the site A topsoils, none were detected in the underlying aquifer material, although a difference in the microbial population sizes might also have contributed to this observation.


From an ecological perspective, CAFOs contribute to environmental reservoirs of resistance through deposition of animal waste containing antibiotics, ARB, and ARGs (14, 30, 41). While soil is a natural reservoir for ARGs (15, 38, 47), soil contaminated with animal waste constitutes an enhanced reservoir of these genes (31, 44), the characteristics of which may connect them to food animal production. For example, such ARGs may be grouped on transposable genetic elements, such as transposons, or be present on conjugative plasmids capable of spreading to a broad range of host bacteria (8, 11). Network analyses of completely sequenced bacterial genomes, including sequences associated with MGEs, have revealed the importance of MGEs in the dissemination of ARGs and have highlighted mobile plasmids as key vectors (21, 26, 56). Animal waste is known to contain various ARG-associated MGEs (8, 10, 11, 40). Nevertheless, the ecological effects of exposure to animal waste on soil bacteria communities have not been elucidated (14). Our study has illustrated the persistence of several ARGs, such as tet(L), and a group of tet(L)-carrying mobilizable plasmids in a chicken-waste-impacted farm soil after the farm closed down and all waste was removed. Compared to results from less-affected soil on the same farm and more-pristine soils from a state forest, the abundance of the analyzed ARGs was substantially higher in the waste-impacted soil. In particular, the relatively high prevalence of tet(L) in the soil microbial community might be partially explained by the distribution of the aforementioned broad-host-range plasmids. Further investigations on the origin of similar plasmids and their fate in the environment in the long term are needed. We also propose that geophysical approaches such as EMI may be useful for studying the ecological impact of animal waste on soil microbial communities, especially in largerscale studies where the sampling strategy is of concern. For instance, on a large CAFO site, after ECa values were determined, samples could be taken from locations with defined ECa values. Results from sample analyses could then be used in regression analyses to determine correlations between variables. ACKNOWLEDGMENTS This work was funded by the NSF (grant CBET-0730932) and the Johns Hopkins Center for a Livable Future, Bloomberg School of Public Health. We thank James Doolittle and Susan Demas (USDA-NRCS) for their help in generating and understanding the electrical conductivity map at the chicken farm site and Ellen Silbergeld (Johns Hopkins School of Public Health) for helpful advice and the NC_006372 positive control. We are also grateful to Laura McMurry (Tufts University) for the NC_001393 positive control and Sabeena Nazar (University of Maryland) for a cloned 16S rRNA gene. We are indebted to the owner of the chicken farm for allowing us access to the property and are grateful to Jay Graham, Roland Glantz, and Shao-Yiu Hsu for their help with field trips and sample collection. We thank the anonymous reviewers for their valuable comments on the manuscript.

REFERENCES 1. Aarestrup FM, et al. 2000. Antimicrobial susceptibility and presence of resistance genes in staphylococci from poultry. Vet. Microbiol. 74:353– 364. 2. Aarestrup FM, et al. 2001. Effect of abolishment of the use of antimicrobial agents for growth promotion on occurrence of antimicrobial resistance in fecal enterococci from food animals in Denmark. Antimicrob. Agents Chemother. 45:2054 –2059. 3. Aminov RI, Garrigues-Jeanjean N, Mackie RI. 2001. Molecular ecology of tetracycline resistance: development and validation of primers for detection of tetracycline resistance genes encoding ribosomal protection proteins. Appl. Environ. Microbiol. 67:22–32.

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4. Ammor MS, et al. 2008. Two different tetracycline resistance mechanisms, plasmid-carried tet(L) and chromosomally located transposonassociated tet(M), coexist in Lactobacillus sakei Rits 9. Appl. Environ. Microbiol. 74:1394 –1401. 5. Asteri I-A, et al. 2011. In silico evidence for the horizontal transfer of gsiB, a ␴〉-regulated gene in Gram-positive bacteria, to lactic acid bacteria. Appl. Environ. Microbiol. 77:3526 –3531. 6. Benson AK, Payne KL, Stubben MA. 1997. Mapping groundwater contamination using DC resistivity and VLF geophysical methods—a case study. Geophysics 62:80 – 86. 7. Benson R, Glaccum R, Noel M. 1983. Geophysical techniques for sensing buried wastes and waste migration, report, contract 68-03-3050, p 114. U.S. Environmental Protection Agency, Office of Research and Development, Environmental Monitoring Systems Laboratory, Las Vegas, NV. 8. Binh CTT, Heuer H, Kaupenjohann MK, Smalla K. 2008. Piggery manure used for soil fertilization is a reservoir for transferable antibiotic resistance plasmids. FEMS Microbiol. Ecol. 66:25–37. 9. Bogosian G, et al. 1996. Death of the Escherichia coli K-12 strain W3110 in soil and water. Appl. Environ. Microbiol. 62:4114 – 4120. 10. Bonnet C, et al. 2009. Pathotype and antibiotic resistance gene distributions of Escherichia coli isolates from broiler chickens raised on antimicrobial-supplemented diets. Appl. Environ. Microbiol. 75:6955– 6962. 11. Byrne-Bailey KG, et al. 2011. Integron prevalence and diversity in manured soil. Appl. Environ. Microbiol. 77:684 – 687. 12. Chee-Sanford JC, Aminov RI, Krapac IJ, Garrigues-Jeanjean N, Mackie R. 2001. Occurrence and diversity of tetracycline resistance genes in lagoons and groundwater underlying two swine production facilities. Appl. Environ. Microbiol. 67:1494 –1502. 13. Chopra L, Roberts M. 2001. Tetracycline antibiotics: mode of action, applications, molecular biology, and epidemiology of bacterial resistance. Microbiol. Mol. Biol. Rev. 65:232–260. 14. Davis MF, Price LB, Liu CM-H, Silbergeld EK. 2011. An ecological perspective on U.S. industrial poultry production: the role of anthropogenic ecosystems on the emergence of drug-resistant bacteria from agricultural environments. Curr. Opin. Microbiol. 14:244 –250. 15. D’Costa VM, McGrann KM, Hughes DW, Wright GD. 2006. Sampling the antibiotic resistome. Science 311:374 –377. 16. Demas GP, Burns JL, Hall RL. 2004. Soil survey of Worcester County, Maryland. Natural Resources Conservation Service, Washington, DC. 17. Diarra MS, et al. 2010. Distribution of antimicrobial resistance and virulence genes in Enterococcus spp. and characterization of isolates from broiler chickens. Appl. Environ. Microbiol. 76:8033– 8043. 18. Eigenberg RA, Korthals RL, Nienaber JA. 1998. Geophysical electromagnetic survey methods applied to agricultural waste sites. J. Environ. Qual. 27:215–219. 19. Eigenberg RA, Nienaber JA. 1998. Electromagnetic survey of cornfield with repeated manure applications. J. Environ. Qual. 27:1511–1515. 20. Flannagan SE, Zitzow L, Su YA, Clewell DB. 1994. Nucleotide sequence of the 18-kb conjugative transposon Tn916 from Enterococcus faecalis. Plasmid 32:350 –354. 21. Fondi M, Fani R. 2010. The horizontal flow of the plasmid resistome: clues from inter-generic similarity networks. Environ. Microbiol. 12: 3228 –3242. 22. Gilchrist MJ, et al. 2007. The potential role of concentrated animal feeding operations in infectious disease epidemics and antibiotic resistance. Environ. Health Perspect. 115:313–316. 23. Graham JP, Evans SL, Price LB, Silbergeld EK. 2009. Fate of antimicrobial-resistant enterococci and staphylococci and resistance determinants in stored poultry litter. Environ. Res. 109:682– 689. 24. Guay GG, Khan SA, Rothstein DM. 1993. The tet(K) gene of plasmid pT181 of Staphylococcus aureus encodes an efflux protein that contains 14 transmembrane helices. Plasmid 30:163–166. 25. Gupta G, Charles S. 1999. Trace elements in soils fertilized with poultry litter. Poult. Sci. 78:1695–1698. 26. Halary SB, Leigh JW, Cheaib B, Lopez P, Bapteste E. 2010. Network analyses structure genetic diversity in independent genetic worlds. Proc. Natl. Acad. Sci. U. S. A. 107:127–132. 27. Hamscher G, Sczesny S, Hoper H, Nau H. 2002. Determination of persistent tetracycline residues in soil fertilized with liquid manure by high-performance liquid chromatography with electrospray ionization tandem mass spectrometry. Anal. Chem. 74:1509 –1518. 28. Harter T, Davis H, Mathews MC, Meyer RD. 2002. Shallow groundwa-

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29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39.

40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54.

ter quality on dairy farms with irrigated forage crops. J. Contam. Hydrol. 55:287–315. Hayes JR, English LL, Carr LE, Wagner DD, Joseph SW. 2004. Multipleantibiotic resistance of Enterococcus spp. isolated from commercial poultry production environments. Appl. Environ. Microbiol. 70:6005– 6011. Heuer H, Schmitt H, Smalla K. 2011. Antibiotic resistance gene spread due to manure application on agricultural fields. Curr. Opin. Microbiol. 14:236 –243. Heuer H, Smalla K. 2007. Manure and sulfadiazine synergistically increased bacterial antibiotic resistance in soil over at least two months. Environ. Microbiol. 9:657– 666. Jackson BP, et al. 2003. Trace element speciation in poultry litter. J. Environ. Qual. 32:535–540. Jensen LB, Agersø Y, Sengeløv G. 2002. Presence of erm genes among macrolide-resistant Gram-positive bacteria isolated from Danish farm soil. Environ. Int. 28:487– 491. Jensen LB, Frimodt-Møller N, Aarestrup FM. 1999. Presence of erm gene classes in Gram-positive bacteria of animal and human origin in Denmark. FEMS Microbiol. Lett. 170:151–158. Kim S-C, Carlson K. 2007. Quantification of human and veterinary antibiotics in water and sediment using SPE/LC/MS/MS. Anal. Bioanal. Chem. 387:1301–1315. Larkin MA, et al. 2007. Clustal W and Clustal X version 2.0. Bioinformatics 23:2947–2948. Lee BD, Jenkinson BJ, Doolittle JA, Taylor RS, Tuttle JW. 2006. Electrical conductivity of a failed septic system soil absorption field. Vadose Zone J. 5:757–763. Martínez JL. 2008. Antibiotics and antibiotic resistance genes in natural environments. Science 321:365–367. Murray KD, Aronstein KA, de León JH. 2007. Analysis of pMA67, a predicted rolling-circle replicating, mobilizable, tetracycline-resistance plasmid from the honey bee pathogen, Paenibacillus larvae. Plasmid 58: 89 –100. Nandi S, Maurer JJ, Hofacre C, Summers AO. 2004. Gram-positive bacteria are a major reservoir of class 1 antibiotic resistance integrons in poultry litter. Proc. Natl. Acad. Sci. U. S. A. 101:7118 –7122. Nicole K. 2008. Veterinary antibiotics in the aquatic and terrestrial environment. Ecol. Indic. 8:1–13. O’Connor S. 2007. Development of strategies to improve extraction, clean-up, and detection of tetracycline antibiotics from various soil types. Ph.D. dissertation. State University of New York at Buffalo, Buffalo, NY. Patterson AJ, Colangeli R, Spigaglia P, Scott KP. 2007. Distribution of specific tetracycline and erythromycin resistance genes in environmental samples assessed by macroarray detection. Environ. Microbiol. 9:703–715. Peak N, et al. 2007. Abundance of six tetracycline resistance genes in wastewater lagoons at cattle feedlots with different antibiotic use strategies. Environ. Microbiol. 9:143–151. Pei R, Kim S-C, Carlson KH, Pruden A. 2006. Effect of river landscape on the sediment concentrations of antibiotics and corresponding antibiotic resistance genes (ARG). Water. Res. 40:2427–2435. Phelan RW, et al. 2011. Tetracycline resistance-encoding plasmid from Bacillus sp. strain #24, isolated from the marine sponge haliclona simulans. Appl. Environ. Microbiol. 77:327–329. Riesenfeld CS, Goodman RM, Handelsman J. 2004. Uncultured soil bacteria are a reservoir of new antibiotic resistance genes. Environ. Microbiol. 6:981–989. Roberts AP, Mullany P. 2009. A modular master on the move: the Tn916 family of mobile genetic elements. Trends Microbiol. 17:251–258. Roberts MC, et al. 1999. Nomenclature for macrolide and macrolidelincosamide-streptogramin B resistance determinants. Antimicrob. Agents Chemother. 43:2823–2830. Rozen S, Skaletsky H. 2000. Primer3 on the WWW for general users and for biologist programmers. Methods Mol. Biol. 132:365–386. Sapkota AR, et al. 2011. Lower prevalence of antibiotic-resistant enterococci on U.S. conventional poultry farms that transitioned to organic practices. Environ. Health Perspect. 119:1622–1628. Sarmah AK, Meyer MT, Boxall ABA. 2006. A global perspective on the use, sales, exposure pathways, occurrence, fate and effects of veterinary antibiotics (VAs) in the environment. Chemosphere 65:725–759. Silbergeld EK, Graham J, Price LB. 2008. Industrial food animal production, antimicrobial resistance, and human health. Annu. Rev. Public Health 29:151–169. Sutcliffe J, Grebe T, Tait-Kamradt A, Wondrack L. 1996. Detection of



55. 56. 57. 58.

erythromycin-resistant determinants by PCR. Antimicrob. Agents Chemother. 40:2562–2566. Suzuki MT, Taylor LT, DeLong EF. 2000. Quantitative analysis of smallsubunit rRNA genes in mixed microbial populations via 5=-nuclease assays. Appl. Environ. Microbiol. 66:4605– 4614. Tamminen M, Virta M, Fani R, Fondi M. 29 November 2011, posting date. Large-scale analysis of plasmid relationships through gene-sharing networks. Mol. Biol. Evol. doi:10.1093/molbev/msr292. Tamura K, Dudley J, Kumar S. 2007. Molecular Evolutionary Genetic Analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24:1596 –1599. Teuber M. 2001. Veterinary use and antibiotic resistance. Curr. Opin. Microbiol. 4:493– 499.


59. van den Bogaard AE, Bruinsma N, Stobberingh EE. 2000. The effect of banning avoparcin on VRE carriage in the Netherlands. J. Antimicrob. Chemother. 46:146 –148. 60. Wegener HC. 2003. Antibiotics in animal feed and their role in resistance development. Curr. Opin. Microbiol. 6:439 – 445. 61. Weisburg WG, Barns SW, Pelletier DA, Lane DJ. 1991. 16S ribosomal DNA amplification for phylogenetic study. J. Bacteriol. 173:697–703. 62. Witte W. 1998. Medical consequences of antibiotic use in agriculture. Science 279:996 –997. 63. Zhao L, Dong YH, Wang H. 2010. Residues of veterinary antibiotics in manures from feedlot livestock in eight provinces of China. Sci. Total Environ. 408:1069 –1075.

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