Dissemination of Antibiotic Resistance Genes in ... - ACS Publications

Oct 22, 2014 - Copyright © 2014 American Chemical Society. *Phone/fax: (8620) 85290200; e-mail: [email protected], [email protected]...
0 downloads 0 Views 3MB Size
Download PDF
Article pubs.acs.org/est

Dissemination of Antibiotic Resistance Genes in Representative Broiler Feedlots Environments: Identification of Indicator ARGs and Correlations with Environmental Variables Liang-Ying He, You-Sheng Liu, Hao-Chang Su, Jian-Liang Zhao, Shuang-Shuang Liu, Jun Chen, Wang-Rong Liu, and Guang-Guo Ying* State Key Laboratory of Organic Geochemistry, CAS Centre for Pearl River Delta Environmental Pollution and Control Research, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China S Supporting Information *

ABSTRACT: Livestock operations are known to harbor elevated levels of antibiotic resistance genes (ARGs) that may pose a threat to public health. Broiler feedlots may represent an important source of ARGs in the environment. However, the prevalence and dissemination mechanisms of various types of ARGs in the environment of broiler feedlots have not previously been identified. We examined the occurrence, abundance and variation of ARGs conferring resistance to chloramphenicols, sulfonamides and tetracyclines in the environments of two representative types of broiler feedlots (free range and indoor) by quantitative PCR, and assessed their dissemination mechanisms. The results showed the prevalence of various types of ARGs in the environmental samples of the broiler feedlots including manure/litter, soil, sediment, and water samples, with the first report of five chloramphenicol resistance genes (cmlA, f loR, fexA, cf r, and fexB) in broiler feedlots. Overall, chloramphenicol resistance genes and sulfonamides sul genes were more abundant than tetracyclines tet genes. The ARG abundances in the samples from indoor boiler feedlots were generally different to the free range feedlots, suggesting the importance of feeding operations in ARG dissemination. Pearson correlation analysis showed significant correlations between ARGs and mobile genetic element genes (int1 and int2), and between the different classes of ARGs themselves, revealing the roles of horizontal gene transfer and coselection for ARG dissemination in the environment. Further regression analysis revealed that fexA, sul1 and tetW could be reliable indicator genes to surrogate anthropogenic sources of ARGs in boiler feedlots (correlations of fexA, sul1 and tetW to all ARGs: R = 0.95, 0.96 and 0.86, p < 0.01). Meanwhile, significant correlations were also identified between indicator ARGs and their corresponding antibiotics. In addition, some ARGs were significantly correlated with typical metals (e.g., Cu, Zn, and As with fexA, fexB, cf r, sul1, tetW, tetO, tetS: R = 0.52−0.71) and some environmental parameters (e.g., TOC, TN, TP, NH3−N with fexA, fexB, cf r, sul1, tetW, tetO, tetQ, tetS: R = 0.53−0.87) (p < 0.01). Further redundancy analysis demonstrated that the distribution and transportation of ARGs from the boiler feedlots to the receiving environments were correlated with environmental variables. The findings highlight the contribution of some chemicals such as antibiotics and metals to the development of ARGs in broiler feedlots environments; and the observed ARG dissemination mechanism in the broiler feedlots facilitates the development of effective mitigation measures.

■

INTRODUCTION

livestock operations and their dissemination mechanisms to the environment still remain to be explored. Some previous studies have investigated ARGs in diverse livestock operations such as swine feedlots by cultureindependent method,7−11 with tet tetracycline resistance genes and sul sulfonamide resistance genes being the most frequently reported ARGs. Noteworthy, although chloramphenicol has been banned in food-producing animals in the

Antibiotic resistance has become a major global public health issue in recent years.1,2 As a result, antibiotic resistance genes (ARGs) are increasingly regarded as emerging environmental contaminants.3 ARGs have been found to be able to spread among bacteria via vertical transfer and horizontal transfer, and distribute from human and animal sources to receiving environments. Growing scientific evidence show that antibiotics used in livestock industry may increase the development and abundance of ARGs, which will be transferred into the receiving environments through waste disposal processes such as manure application on land.4−6 However, the diversity of ARGs in © 2014 American Chemical Society

Received: Revised: Accepted: Published: 13120

August 22, 2014 October 20, 2014 October 22, 2014 October 22, 2014 dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

■

Article

MATERIALS AND METHODS Site Selection and Sample Collection. Two types of chicken feedlots (free range broilers, and indoor broilers) were selected for this study. The free range chicken feedlots (defined as Farm A, B, C, D, E, and F) are located in Kaiping city of Guangdong Province; whereas the indoor chicken feedlots (defined as Farm J, K, L, M, and N) are located in Changsha city of neighboring Hunan Province, South China (Supporting Information (SI) Figure S1). Samples collected for this study included feed, manure and litter in the broiler houses, pasture soils, and those soils with manure and litter application, well water, pond water and sediment in the surrounding areas. Detailed information about the two types of chicken feedlots and collected samples from the feedlots environments is given in Table 1, Text S1 and Text S2 (SI). In addition, field control

European Union (EU) since 1994 because of its adverse sideeffect,12 its resistance genes (cmlA, f loR, fexA, cf r, and fexB) were detected at high abundances in swine feedlots and their surrounding environments.13 To date, most studies focused on the ARGs in swine feedlots and aquaculture environments, few studies have been conducted in chicken feedlots with different operations. Development and dissemination of ARGs have been attributed to various driving factors.14 Among these, use of antibiotics in livestock for prophylactic, therapeutic and growth promoting purposes has been reported as a major driver of antibiotic resistance worldwide.15−17 Routine administration of antibiotics to animals at low-doses could lead to development of antibiotic resistant bacteria and spread of antibiotic resistance determinants.18,19 Furthermore, ARGs could persist in the absence of antibiotic selective pressure.20−22 Other factors such as heavy metals could also exert a selective pressure and act as complementary factors for resistance retention and dissemination23,24 Previous studies showed certain positive correlations between ARGs and antibiotics or metals in some swine feedlots,7,11,13,25−27 indicating potential coselection of antibiotic and metal resistance. However, further research is still needed to understand the influences of various environmental variables (e.g., antibiotics, metals, and nutrients) on the dissemination of ARGs in chicken farms with different feeding operations (free range vs caged/indoor broilers). For the dissemination of ARGs, mobile genetic elements such as class 1 and class 2 integrons and genetic linkage of different resistance genes on the same mobile genetic elements are usually involved.28,29 However, correlations among the ARGs of the same or different resistance mechanisms remain to be investigated in order to understand ARG dissemination mechanisms in the environment. On the other hand, disposal of animal wastes is recognized as a major pathway for the spread of ARGs in the environment.30 It is always a challenge to distinguish anthropogenic impacts from the backrgound level of antibiotic resistance for the reason that antibiotic resistance is a natural phenomenon.31 Some previous studies have attempted to trace possible sources of ARGs in complex aquatic environments based on molecular signatures of tetW or along with relative distribution patterns of ARG in forms of frequency of detection of tet genes and sul1, or of the tet(W):sul1 ratio.8,30,32,33 It is suggested that consideration of an array of ARGs representing various classes will be of benefit to tracking anthropogenic sources of ARGs.32 This should be explored further in chicken feedlots impacted environments with chicken wastes as the pollution source. The objectives of this study were to investigate the occurrence and diversity of ARGs in two types of chicken feedlots environments (free range and indoor feeding operations), to identify indicator genes for various classes of ARGs in source tracing, and further to evaluate potential correlations between the ARGs and environmental variables (antibiotics, metals, and environmental quality parameters). The target ARGs selected in this study include various types of ARGs (chloramphenicols: fexA, fexB, cmlA, cf r and f loR; sul genes: sul1, and sul2; tet genes: tetC, tetG, tetH, tetM, tetO, tetQ, tetS, tetW, tetB/P, tetT, and tetX; and integrase genes of int1 and int2). An understanding of the dissemination mechanism for ARGs from chicken feedlots to the receiving environment can facilitate the development of environmentally friendly livestock waste management practices in order to control the proliferation of ARGs from livestock operations.

Table 1. Characteristics of the Broiler Feedlots and Collected Samples farms

chicken breeds

age of flock (days)

no. of broiler chicks when flock arrived

Kaiping Chicken Farms: Free Range Broilers (KP) A Wenchang Down 50000 chicken timeb B Wenchang 56 60000 chicken C Wenchang 28 60 000 chicken D Wenchang 20 130 000 chicken E Cenxi 60 100 000 chicken Qingyuan 120 50 000 Ma Changsha Chicken Farms: Indoor Broilers (CS) J Yellow 67 10 094 bantam 61 12 840 K Guangxi local chicken L Yellow 22 16 000 bantam M Yellow 46 19 800 bantam N Yellow 51 16 000 bantam F

collected samplesa F, M, S, WW, PW, PS F, M, S, WW, PW, PS F, M, S, WW, PW, PS F, M, S, WW, PW, PS F, M, S, WW, PW, PS, SC, WC F, M, S, WW, PW, PS F, M, S, SC F, M, S, SC F, M, S, SC F, M, S, SC F, M, S, SC

a

Collected environmental samples: F, feed; M, manure or litter; S, soil; WW, well water, PW; pond water; PS, pond sediment; SC, soil control; WC, water control. bDown time: the time between batches of all−in all−out approach. All−in all−out approach: Chickens of the same age are kept in one house. Between batches the house should be thoroughly cleaned and disinfected and left to dry out completely.

samples including soil and water control samples were also collected from sites away from the broiler feedlots without contamination of broiler feedlot wastes. After collection, the solid samples were freeze-dried and sieved through a 2 mm mesh, then stored at −80 °C for DNA, antibiotics and metal extraction. The water samples (1 L for antibiotics analysis, and 500 mL for ARG analysis) were processed within 24 h. For ARG analysis, the water samples were filtered through 0.45 μm filter papers which were stored at −80 °C for later DNA extraction. DNA Extraction and ARG Determination. Individual water samples (filters) and homogeneous solid samples 13121

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

Figure 1. Levels of ARGs in solid wastes (manure and litter) and soil samples of the 11 broiler farms. Farm A, B, C, D, E, and F represents the free range broiler farms from KP (Kaiping city); Farm J, K, L, M, and N represents the indoor broiler farms from CS (Changsha city). (a) Absolute concentrations (copies/g dw) in manure and litter samples. Number on the top of each bar means age of flock (days). (b) Relative abundance (copies of ARGs/copies of 16S rRNA) in manure and litter samples. (c) Absolute concentrations in soil samples. (d) Relative abundance in soil samples. Dotted line in each bar of the graphs (a and c) represents absolute concentration of 16S rRNA. M = manure (in farm A, B, C, D, E, and F) or litter (in farm J, K, L, M, and N); S = soil; SC = control soil.

sulfameter, SM; sulfamethoxazole, SMX and trimethoprim, TMP), five tetracyclines (oxytetracycline, OTC; chlortetracycline, CTC; doxycycline, DC; tetracycline, TE and methacycline, MT) and two chloramphenicols (florfenicol, FF and chloramphenicol, CAP), were analyzed for the collected samples. The analytical proccedures for the target antibiotics in various samples were followed according to our previous method.35 Nine metals including Cr, Mn, Co, Ni, Cu, Zn, Sr, Cd, and As in the collected samples were measured by using inductively coupled plasma-mass spectrometry (ICP-MS, Agilent 7500, Agilent).36 Environmental quality parameters including total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), ammonium-nitrogen (NH3−N), biochemicaloxygen demand (BOD5) and chemical oxygen demand (COD) were also analyzed according to the standard methods.37 Statistical Analysis. Pearson correlation and redundancy analysis (RDA) were conducted to identify the association between the distribution of ARGs and various environmental

(approximately 0.2 g dry weight) were used to extract total DNA using the PowerSoil DNA Isolation Kit (MoBio Laboratories, USA) following the manufacturer’s protocol. Quantitative PCR (qPCR) was used to quantify 18 target genes including sulfonamide genes (sul1 and sul2), tetracycline genes (tetC, tetG, tetH, tetM, tetO, tetQ, tetS, tetW, tetB/P, tetT and tetX), and chloramphenicol genes ( fexA, fexB, cmlA, cf r and f loR) and two integrase genes (int1 and int2). The 16S rRNA (16S rRNA) gene was included to quantify the total bacterial load and to normalize the abundance of ARGs in the collected samples. The specific primers used in this study for qPCR are listed in SI Table S1. All qPCR assays were performed on ViiA 7 Real-Time PCR System (ABI, USA) using SYBR Green Real Time QPCR Kit (TOYOBO, Japan). The detailed DNA extraction and ARG determination methods can be referred to Text S2 and our previous study.34 Chemical Analysis. Fourteen target antibiotics, including seven sulfonamides (sulfamethazine, SMZ; sulfamonomethoxine, SMM; sulfaquinoxaline, SQX; sulfaguanidine, SG; 13122

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

Figure 2. Levels of antibiotics (ng/g dw) in the manure, litter and soil samples of the 11 broiler farms from KP and CS broiler feedlots. Number on the top of each bar means age of flock (days); SC = soil control.

was the lowest (Figure 1). The detected ARGs in soil and water from the feedlots environments were obviously more abundant than in their corresponding control soil and control water, respectively (Figure 1 and SI Figure S2). The results of average ARG levels revealed that fexA, fexB, cfr, sul1, and tetW were dominant in the manure samples, whereas in the soil samples fexA, f loR, cmlA, sul1and sul2 were dominant (SI Figure S2). As for the water and sediment, the most abundant ones were fexA, f loR, sul1, sul2, and tetG (SI Figure S1). The levels of tet genes varied greatly according to their different resistance mechanisms (SI Figure S2). The average concentrations of ribosomal protection genes (tetM, tetO, tetQ and tetW) were higher than those of most efflux pump genes (tetC, tetG, and tetH) and enzymatic modification gene (tetX) in the manure, litter and soil samples. However, in the water samples, the efflux pump genes (tetC, tetG) and enzymatic modification gene (tetX) were detected higher than most of the ribosomal protection genes. Interestingly, in terms of absolute concentration and relative abundance which served as indicative of the proportion of bacteria carrying ARGs, similar ARG diversity was observed in the manure and litter samples (Figure 1), showing variations of ARGs with age and broiler breeds. However, in the soil samples (Figure 1), the free range broiler feedlots had similar occurrence of ARGs, while the indoor broiler feedlots showed very different ARG distributions among them.

variables (antibiotics, metals and environmental parameters). Data analyses were performed with software SPSS 13.0, Sigma Plot 10.0 and Canoco for Windows (Version 4.5).

■

RESULTS ARGs in the Broiler Feedlots Environments. Among the 18 ARGs and two mobile genetic elements genes, five chloramphenicol resistance genes (fexA, fexB, cf r, cmlA, and f loR), two sul genes (sul1 and sul2), four tet genes (tetM, tetQ, tetS, and tetW) and the two mobile genetic elements (int1and int2) were detected in all manure (including litter) samples (Figure 1), whereas eight of them (fexA, cf r, cmlA, sul1, sul2, int1, tetO, and tetG) were found in all soil samples (Figure 1). In addition, target ARGs except for int2, tetC and tetT, were positively detected in all pond water and well water (SI Figure S2). All five chloramphenicol resistance genes and two sul genes, int1, and tetT were observed in the pond sediment. In general, fexA, cfr, cmlA, sul1, sul2, and int1 were the most detected ARGs (detection frequency 100%, n = 29) in all solid samples from the 11 broiler feedlots, followed by fexB, f loR, tetG (detection frequency 97%, n = 29) and tetO, tetX (detection frequency 93%, n = 29). Among the three classes of ARGs detected in manure and litter samples, chloramphenicol resistance genes (fexA, fexB, cf r, cmlA and f loR) were found the most abundant, followed by sul genes (sul1, sul2). The total absolute concentration of tet genes 13123

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

Figure 3. Redundancy analysis (RDA) of antibiotic resistance genes (ARGs) and the environmental variables in solid samples based on the sample scores that are linear combinations of ARGs compositions (a) or of the environmental values (b). Circle and diamond symbols represent the ARGs concentrations in the solid samples of Kaiping and Changsha broiler farm systems, respectively. Up-triangle symbols in orange represent the ARGs concentrations in pond sediments of Kaiping broiler farms. Dark cyan, magenta and light gray symbols represent the concentrations of ARGs in manure or litter, soil and control soil samples. Environmental variables in blue arrows represent the total concentrations of three classes of antibiotics, nine heavy metals and four environmental parameters. The size of the sample symbols corresponding to the ARGs richness (number of ARGs in the sample). The lengths of the arrows reveal the strength of the relationship and the angles between arrows indicate the correlation between individual environmental variables. The percentage of variation explained by each axis is shown, and the relationship is significant (p < 0.01). RDA was performed with Canoco for Windows (Version 4.5).

Pearson correlation analysis was conducted to study the correlations among the various types of ARGs including integrase gene for class 1 and class 2 integrons (int1 and int2) in solid samples (manure, litter, soil, sediment and control soil) (SI Table S2). Significant positive correlations were identified between int1 and the three classes of ARGs including chloramphenicol resistance genes (fexA, fexB, and cfr), sul1 and ribosomal protein protection tet genes (tetO, tetQ, tetS, tetW) (R = 0.55−0.74, p < 0.01). Interestingly, int1 displayed strong and significant relationships with the total concentrations of the three classes of ARGs (∑cml, ∑sul and ∑tet) and all ARGs (∑ARGs) (R = 0.74−0.82, p < 0.01), respectively. In addition, int2 was found significantly correlated with floR, sul2, tetG, and tetX (R = 0.56−0.75, p < 0.01), as well as with the total concentrations of tet genes and all ARGs (p < 0.05). The results indicate that class 1 and class 2 integrons play certain roles in the prevalence of ARGs in the manure of broiler feedlots and their receiving environments through horizontal gene transfer. It is noteworthy that strong and signficant correlations existed between different classes of ARGs (SI Table S2). Significant correlations were observed between chloramphenicol resistance genes ( fexA, fexB and cf r) with tetracycline ribosomal protein protection genes (tetO, tetQ, tetS, tetW) (R = 0.55−0.90, p < 0.01), and with sul1 gene (R = 0.82−0.88, p < 0.01). Regardless of resistance mechanisms, the eight genes appeared to be significantly associated with total concentrations of the three classes of ARGs (∑cml, ∑sul and∑tet) (R = 0.55− 1.00, p < 0.01) and all ARGs (∑ARGs) (R = 0.75−0.96, p < 0.01). This result further indicates that the prevalence and dissemination of ARGs in the broiler feedlots environments may be due to the genetic linkage which results in coselection of ARGs. Antibiotics and Metals in the Broiler Feedlots Environments. The collected environmental samples from different feedlots were also characterized for antibiotics and

metals as well as some environmental quality parameters (SI Table S3 and Table S4). Ten antibiotics from sulfonamides (SMZ, SMM, SQX, SMX, and TMP) and tetracyclines classes (OTC, TE, CTC, DC, and MT) were detected in the broiler feeds, but no chloramphenicols were found in the feeds. OTC, TE, and TMP were found with higher concentrations (up to 67 200 ng/g) than the other antibiotics in the feeds samples. In comparison, relatively lower concentrations of those antibiotics were found in the feeds of indoor broiler feedlots (CS) than in the feeds of free range broiler feedlots (KP). Interestingly, similar occurrence patterns for antibiotics were observed in the manure and soil samples of the broiler feedlots (Figure 2). Total 14 antibiotics were detected in all manure (and litter) samples, with two more compounds (FF and CAP) of chloramphenicols that were not detected in the collected feeds. OTC was detected with the highest mean concentration of 46 100 ng/g dry weight (dw) in manure, followed by SMM (2570 ng/g dw), TMP (2480 ng/g dw), DC (2440 ng/g dw) and FF (529 ng/g dw) (SI Table S2). Some antibiotics such as SMM, TMP, CTC, and CAP were also frequently detected in the pond water samples from the free range broiler feedlots (KP), while the antibiotics like SMM, OTC, CTC and DC were detected in the corresponding pond sediments (SI Figure S3; Table S3). It should be noted that significant differentiation in antibiotics concentrations was observed among the manure samples from chickens with different ages and broiler breeds (Figure 2). For Wenchang chickens from KP free range chicken farms, the total concentrations of antibiotics in manure decreased as the age of broilers increased, suggesting a decreased usage with age. Relatively low concentrations of antibiotics were found in the manure samples of broiler feedlot A, which was at down time during the sampling campaign. All the nine metals (Cr, Mn, Co, Ni, Cu, Zn, As, Sr, and Cd) were detected in manure and soil at a wide concentration range, 13124

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

the five chloramphenicol resistance genes in the broiler feedlots by culture-independent method although they were quantified in swine feedlots before.13 Previous studies demonstrated that these five genes are located on transposon (fexA)38,39 and plasmid ( fexB, cmlA, cf r, and f loR).40−42 Therefore, possible dissemination mechanisms are horizontal transfer and coselection of chloramphenicol resistance genes among bacteria in poultry based on their location on mobile genetic elements and their linkage to other resistance determinants such as cmlA being located with sul3 and aadA; f loR being located with tetA, sul2, strA/strB, and blaCMY‑2 on the same plasmid43,44 Among the five genes, the multidrug resistance gene cf r and florfenicol/ chloramphenicol resistance gene fexA had higher abundances in manure and litter samples. This could be explained by generally low fitness cost of cf r acquisition and coexpression with the erm gene on one hand. On the other hand, cf r and fexA were located on a plasmid carried transposon in Staphylococcus isolates from different animal sources.45,46 Two plasmid-borne sul genes sul1 and sul2 were detected in all samples of the 11 broiler feedlots, indicating that sul genes are distributed widely in broiler feedlots environments. The sul1 gene had higher abundance than sul2 in almost all samples, which is similar to the distribution of sul genes in sulfonamideresistant bacteria from swine farm wastewaters.47 This different distribution between the two genes can be attributed to different dissemination mechanisms.48 The sul1 has a broad range of host bacteria for it is normally linked to integrons as demonstrated by good correlations between sul1 and int1 (SI Table S2), while sul2 is usually located on small plasmids of the Inc.Q family.48 Tetracycline resistance genes were also found abundant in all samples. This is similar to the previous findings about the abundance of tet genes obtained from chicken manures, swine lagoons and from soils adjacent to swine feedlots.9,11 One reason could be due to the fact that tet genes were found dominant in the gastrointestinal tracts of chicken,49 pigs and steers.50 Another reason is that tet genes have spread in both Gram-negative and Gram-positive genera, and the majority of tet genes in bacteria have been associated with mobile plasmids, transposons, conjugative transposons, and integrons (gene cassettes).16 The ribosomal protection genes such as tetW, tetM and tetQ are believed to originate from Gram-positive bacteria, and there is a hypothesis that these ARGs can transfer among bacterial population regardless of species or genus.16 The wide detection and high abundance of ribosomal protection protein tet genes in the present study reflect that they have spread widely in the environment of broiler feedlots. The enzymatic inactivation tet gene tetX was more abundant in soil than in manure and litter samples both at absolute and relative concentration levels, even in the pond sediment and water, it was prevalent. That may be due to the fact that tetX gene encodes for an NADPH-requiring oxidoreductases but has only been found in a strict anaerobe Bacteroides and its clinical relevance is unclear.51,52 Interestingly, the significant correlations between ARGs and integrase genes indicate that mobile genetic elements played roles in the dissemination of ARGs in the broiler feedlot environment. Furthermore, the strong correlations among the ARGs of different/the same resistance mechanisms indicate the genetic linkage driven by co-occurrence and cotransfer of ARGs, which results in coresistance or multidrug resistance. It is noteworthy that the present study first report the correlations among the detected ARGs. In general, the results fit the above

as shown in SI Table S4. The mean concentrations ranged from 0.04 mg/kg (Cd) to 476 mg/kg (Mn) in the solid samples. Mn was found to have the highest mean concentrations in most samples, followed by Zn, As, Cu, and Cr. All target metals except for Cr were observed in the water samples with concentrations ranging from ND to 98.7 μg/L (Mn). Most of the metals detected in the well water and pond water samples were significantly higher than in the control water samples. Correlations between ARGs and Environmental Variables. Correlation analysis was performed between ARGs and environmental variables (antibiotics, metals, and environmental parameters) for solid samples from the feedlots environments (SI Table S5). Some specific ARGs (sul1, cf r, tetH, tetM, tetO, and tetS) were found significantly correlated with the corresponding antibiotics (SOX, FF, OTC, TE, and DC) (R = 0.55−0.82, p < 0.01), suggesting the direct selective pressure from related antibiotics used in the broiler feedlots; while some other ARGs (fexA, fexB, cfr, sul1, tetO, tetS, and tetW) were significantly correlated with other classes of antibiotics (SQX, OTC, DC, and FF) (R = 0.55−0.88, p < 0.01), suggesting coselection by different classes of antibiotic in the broiler feedlots. As shown in SI Table S5, positive correlations were also identified between several target metals (Mn, Cu, Zn, As, and Sr) with some ARGs ( fexA, fexB, cf r, sul1, tetO, tetQ, and tetW) (R = 0.52−0.71, p < 0.01). This suggests that the presence of metals in feeds or environmental medium could be one of the important driving factors in the selection of ARGs in the feedlot environments. Notably, most target ARGs were positively correlated (p < 0.01) to TOC, TN, TP, and NH3−N, indicating that coattenuation of total organic carbon and nutrients with these ARGs. Moreover, the total concentrations of three different classes of ARGs (chloramphenicol resistance genes, sul genes, and tet genes) and even the total concentrations of the all target ARGs were found well correlated with the concentrations of antibiotics, metals and environmental parameters (p < 0.01). RDA analysis was conducted to assess the potential relationship between the distribution of various ARGs and environmental variables (Figure 3). The RDA diagram used the sample scores that were linear combinations of ARG compositions (Figure 3a) or of the environmental values (Figure 3b) to display the variability in ARG compositions and sample characteristics, with the size of each symbol corresponding to the number of ARGs. The RDA results displayed that 77% of the variation was explained by the environmental variables. The first axis was positively correlated with chloramphenicols, sulfonamides, tetracyclines, metals, and environmental parameters. The first axis displayed a separation of sample types, in which pond sediment, soil, manure, and litter samples were grouped together along the first axis, while the control soils were clearly separated from the manure, litter, and soil samples. In general, the RDA diagrams reflect the different contamination degrees and distribution characteristics of ARGs in the broiler feedlots environments.

■

DISCUSSION Dissemination of ARGs in the Broiler Feedlots Environments. The present study presented three classes of ARGs conferring resistance to chloramphenicols ( fexA, fexB, cmlA, cf r, and f loR), sulfonamides (sul1 and sul2), and tetracyclines (tetC, tetG, tetH, tetM, tetO, tetQ, tetS, tetW, tetB/P, tetT, and tetX) in the 11 broiler feedlots with two different feeding operations. The present study first reported 13125

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

Figure 4. Correlation analysis between the total absolute concentrations (copies/g dw) of chloramphenicols resistance genes (∑cml) (A), sul genes (∑sul) (B), tet genes (∑tet) (C) and all ARGs (∑ARGs) (D) detected in this study with the absolute concentration (copies/g) of fexA, sul1, and tetW in solid samples (manure, litter, soil, sediment, and control soil, n = 35). Solid lines represent regression curve. Dotted lines represent 95% prediction band. Values of the Pearson correlation coefficient (r) were indicated respectively (p < 0.01). Linear regression analysis was performed with Sigma Plot 10.0.

litter varied from feedlot to feedlot. With continued reuse, the litter environment becomes more complex,57 which may have a profound impact on distribution of antibiotic resistant bacteria (ARB) and ARGs in litter and even the subsequent litterapplied soils. The present study and a previous study58 indicated that the dissemination of ARGs in surrounding environments of broiler feedlots is connected to the commercial broiler production nearby. It is a fact that manure from animal husbandry has become a reservoir of ARGs and ARB.4−6,59 The present study showed that disposal of animal manure could lead to dissemination of ARGs into soils, surface water as well as groundwater (Figure 5). Therefore, proper waste management is essential in order to reduce the contamination of antibiotic resistance determinants in the receiving environment. Identification of Indicators for ARGs in Feedlot Environments. Based on the results from the present study (Figure 4), three genes fexA, tetW and sul1 were identified as potential indicators for ARGs from chicken feedlots. Previous studies have demonstrated that both sul1 and tetW were frequently detected and persisted at high levels in different livestock waste lagoons,7,9 and they have also been used for tracking anthropogenic sources of ARGs.8,32,33 This suggests that the selected three genes fexA, sul1 and tetW are suitable to indicate the overall levels of individual ARGs and different classes of resistance genes.

interpretation and highlight the importance of horizontal transfer, and cotransfer of ARGs contributed to the ARG dissemination in the environment. However, further studies should explore the broader resistome in order to better understand dissemination mechanisms. The present study and previous studies55,67 noticed that the development and dissemination of ARGs in feedlot environments could be influenced by production conditions such as feed, henhouse environment, chicken breed and age in the broiler feedlots as those factors can affect the evolution of the intestinal microbiome. The abundance and distribution of bacteria and antibiotic resistance may vary according to different rearing systems.53,54 Under a common diet and husbandry, breed has a significant effect on gut microbiota composition.55 Moreover, as shown in the present study, the abundance of bacteria (16S rRNA) and ARGs in chicken manure increased with the age of broilers (Wenchang chicken) under the free range feeding operation (Figure 1), suggesting that resistant bacteria increase as the broilers mature. This could be partly explained by the fact that successions occur from a transient community to one of increasing complexity as the broilers mature.56 But no such phenomenon was found in chicken litter of the indoor broiler feedlots regardless of broiler age or breeds (Yellow bantam and Guangxi local chicken). It should be noted that the broiler litter is primarily a mixture of bedding materials and bird excreta, and the management of 13126

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

Furthermore, the three genes fexA, sul1 and tetW as well as total ARGs in solid samples could be used to differentiate environmental sample types using the three-dimensional Scatter Plot (Figure 5). The results showed that manure and

contamination from chicken farm wastes. Further metagenomic analysis can assist to elucidate the resistance mechanisms behind these three indicator genes. Linking ARG Distribution to Environmental Variables. The present study also found good correlations of ARG concentrations to the environmental variables (antibiotics, metals and environmental quality parameters), indicating that these environmental variables had effects on the distribution of ARGs in manure, litter and soil in the two types of broiler feedlots (SI Table S5 and Figure 3). The present study and previous studies showed that broad-spectrum antibiotics such as tetracyclines, sulfonamides and chloramphenicols15,16 as well as metal supplements60 have been used extensively as growth promoters in feedlots. Those antibiotics used in feedlots have been known to affect the development of antibiotic resistance.17,61 In-feed supplementation of trace minerals such as Cu, Zn, As, and Mn can modulate the growth performance and immune responses of broilers.62 It has been recognized that metals can serve as a selective agent in the proliferation of antibiotic resistance,63 and in fact some evidence for coselection of metals and antibiotics on bacteria was available in the literature.23,24,64 Thus, antibiotics and metals in feedlot environments could jointly contribute to the maintenance and spread of antibiotic resistance determinants via coselection mechanisms either by coresistance or cross-resistance. This provides valuable insights into dissemination mechanisms, and assists developing future mitigation strategies for ARGs in broiler feedlots.

■

ASSOCIATED CONTENT

S Supporting Information *

Broiler production systems and their locations in this study; Sample collection and ARG determination; Primers used in qPCR analysis; Concentrations of antibiotics, metals and environmental parameters in the collected samples; Correlation analysis for ARGs and environmental variables; Average absolute and relative concentrations of ARGs; Mean concentrations of antibiotics in the collected samples. This material is available free of charge via the Internet at http://pubs.acs.org/.

■

AUTHOR INFORMATION

Corresponding Author

*Phone/fax: (8620) 85290200; e-mail: guangguo.ying@gmail. com, [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We acknowledge the financial support from the Ministry of Environmental Protection of China (201309031), Chinese Academy of Sciences (KZCX2-EW-108 and KZZD-EW-09) and National Natural Science Foundation of China (NSFC U113305 and 41303077). This is a Contribution No. 1976 from GIG CAS.

Figure 5. Three dimensional scatter plot with log (common) transformed response variables of absolute concentration (copies/g dw) of fexA, sul1, and tetW (a) or fexA, sul1 and all ARGs (b) in solid samples (n = 35). Some pond sediment and control soil samples are excluded in fexA: sul1: tetW plot (a) because tetW was negatively detected.

■

litter, impacted soil, pond sediment and control soil were grouped based on the three indicator genes and total ARGs since tetW was not detectable in some control soils. It should be noted that some soil samples were shifted closer to manure and litter since these soils received more broiler wastes. This indicates the transfer of ARGs from animal sources to the receiving environments. Furthermore, the combined results from the statistical analysis and 3D Scatter Plot suggest that fexA, sul1, and tetW could serve as reliable indicators for ARG

REFERENCES

(1) Wright, G. D. Antibiotic resistance in the environment: A link to the clinic? Curr. Opin Microbiol. 2010, 13 (5), 589−94. (2) Spellberg, B.; Guidos, R.; Gilbert, D.; Bradley, J.; Boucher, H. W.; Scheld, W. M.; Bartlett, J. G.; Edwards, J. The epidemic of antibioticresistant infections: A call to action for the medical community from the infectious diseases society of America. Clin. Infect. Dis. 2008, 46 (2), 155−164.

13127

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

(3) Pruden, A.; Pei, R.; Storteboom, H.; Carlson, K. H. Antibiotic resistance genes as emerging contaminants: Studies in northern Colorado. Environ. Sci. Technol. 2006, 40 (23), 7445−50. (4) Heuer, H.; Smalla, K. Manure and sulfadiazine synergistically increased bacterial antibiotic resistance in soil over at least two months. Environ. Microbiol. 2007, 9 (3), 657−66. (5) Jechalke, S.; Kopmann, C.; Rosendahl, I.; Groeneweg, J.; Weichelt, V.; Krogerrecklenfort, E.; Brandes, N.; Nordwig, M.; Ding, G. C.; Siemens, J.; Heuer, H.; Smalla, K. Increased abundance and transferability of resistance genes after field application of manure from sulfadiazine-treated pigs. Appl. Environ. Microbiol. 2013, 79 (5), 1704− 11. (6) Heuer, H.; Schmitt, H.; Smalla, K. Antibiotic resistance gene spread due to manure application on agricultural fields. Curr. Opin. Microbiol. 2011, 14 (3), 236−43. (7) McKinney, C. W.; Loftin, K. A.; Meyer, M. T.; Davis, J. G.; Pruden, A. tet and sul antibiotic resistance genes in livestock lagoons of various operation type, configuration, and antibiotic occurrence. Environ. Sci. Technol. 2010, 44 (16), 6102−9. (8) Koike, S.; Krapac, I. G.; Oliver, H. D.; Yannarell, A. C.; CheeSanford, J. C.; Aminov, R. I.; Mackie, R. I. Monitoring and source tracking of tetracycline resistance genes in lagoons and groundwater adjacent to swine production facilities over a 3-year period. Appl. Environ. Microbiol. 2007, 73 (15), 4813−4823. (9) Cheng, W.; Chen, H.; Su, C.; Yan, S. Abundance and persistence of antibiotic resistance genes in livestock farms: A comprehensive investigation in eastern China. Environ. Int. 2013, 61 (0), 1−7. (10) Zhang, Y.; Snow, D. D.; Parker, D.; Zhou, Z.; Li, X. Intracellular and extracellular antimicrobial resistance genes in the sludge of livestock waste management structures. Environ. Sci. Technol. 2013, 47 (18), 10206−13. (11) Wu, N.; Qiao, M.; Zhang, B.; Cheng, W. D.; Zhu, Y. G. Abundance and diversity of tetracycline resistance genes in soils adjacent to representative swine feedlots in China. Environ. Sci. Technol. 2010, 44 (18), 6933−9. (12) Martelo, O. J.; Manyan, D. R.; Smith, U. S.; Yunis, A. A. Chloramphenicol and bone marrow mitochondria. J. Lab. Clin. Med. 1969, 74 (6), 927−40. (13) Li, J.; Shao, B.; Shen, J.; Wang, S.; Wu, Y. Occurrence of chloramphenicol-resistance genes as environmental pollutants from swine feedlots. Environ. Sci. Technol. 2013, 47 (6), 2892−7. (14) Levy, S. B. Factors impacting on the problem of antibiotic resistance. J. Antimicrob. Chemother. 2002, 49 (1), 25−30. (15) Silbergeld, E. K.; Graham, J.; Price, L. B. Industrial food animal production, antimicrobial resistance, and human health. Annu. Rev. Public. Health 2008, 29, 151−69. (16) Chopra, I.; Roberts, M. Tetracycline antibiotics: Mode of action, applications, molecular biology, and epidemiology of bacterial resistance. Microbiol. Mol. Biol. Rev. 2001, 65 (2), 232−260. (17) Ghosh, S.; LaPara, T. M. The effects of subtherapeutic antibiotic use in farm animals on the proliferation and persistence of antibiotic resistance among soil bacteria. ISME J. 2007, 1 (3), 191−203. (18) Diarra, M. S.; Silversides, F. G.; Diarrassouba, F.; Pritchard, J.; Masson, L.; Brousseau, R.; Bonnet, C.; Delaquis, P.; Bach, S.; Skura, B. J.; Topp, E. Impact of feed supplementation with antimicrobial agents on growth performance of broiler chickens, Clostridium perfringens and enterococcus counts, and antibiotic resistance phenotypes and distribution of antimicrobial resistance determinants in Escherichia coli isolates. Appl. Environ. Microbiol. 2007, 73 (20), 6566−76. (19) Bonnet, C.; Diarrassouba, F.; Brousseau, R.; Masson, L.; Topp, E.; Diarra, M. S. Pathotype and antibiotic resistance gene distributions of Escherichia coli isolates from broiler chickens raised on antimicrobial-supplemented diets. Appl. Environ. Microbiol. 2009, 75 (22), 6955−6962. (20) Tamminen, M.; Karkman, A.; Lohmus, A.; Muziasari, W. I.; Takasu, H.; Wada, S.; Suzuki, S.; Virta, M. Tetracycline resistance genes persist at aquaculture farms in the absence of selection pressure. Environ. Sci. Technol. 2011, 45 (2), 386−91.

(21) Andersson, D. I.; Hughes, D. Persistence of antibiotic resistance in bacterial populations. FEMS Microbiol. Rev. 2011, 35 (5), 901−911. (22) Enne, V. I.; Livermore, D. M.; Stephens, P.; Hall, L. M. Persistence of sulphonamide resistance in Escherichia coli in the UK despite national prescribing restriction. Lancet 2001, 357 (9265), 1325−8. (23) Baker-Austin, C.; Wright, M. S.; Stepanauskas, R.; McArthur, J. V. Co-selection of antibiotic and metal resistance. Trends Microbiol. 2006, 14 (4), 176−182. (24) Seiler, C.; Berendonk, T. U. Heavy metal driven co-selection of antibiotic resistance in soil and water bodies impacted by agriculture and aquaculture. Front. Microbiol. 2012, 3, 399. (25) Ji, X.; Shen, Q.; Liu, F.; Ma, J.; Xu, G.; Wang, Y.; Wu, M. Antibiotic resistance gene abundances associated with antibiotics and heavy metals in animal manures and agricultural soils adjacent to feedlots in Shanghai; China. J. Hazard. Mater. 2012, 235−236, 178− 85. (26) Li, J.; Wang, T.; Shao, B.; Shen, J.; Wang, S.; Wu, Y. Plasmidmediated quinolone resistance genes and antibiotic residues in wastewater and soil adjacent to swine feedlots: Potential transfer to agricultural lands. Environ. Health. Perspect 2012, 120 (8), 1144−9. (27) Zhu, Y. G.; Johnson, T. A.; Su, J. Q.; Qiao, M.; Guo, G. X.; Stedtfeld, R. D.; Hashsham, S. A.; Tiedje, J. M. Diverse and abundant antibiotic resistance genes in Chinese swine farms. Proc. Natl. Acad. Sci. U S A 2013, 110 (9), 3435−40. (28) Levy, S. B.; Marshall, B. Antibacterial resistance worldwide: Causes, challenges and responses. Nat. Med. 2004, 10 (12 Suppl), S122−9. (29) Andersson, D. I. Persistence of antibiotic resistant bacteria. Curr. Opin. Microbiol. 2003, 6 (5), 452−456. (30) Storteboom, H.; Arabi, M.; Davis, J. G.; Crimi, B.; Pruden, A. Identification of antibiotic-resistance-gene molecular signatures suitable as tracers of pristine river, urban, and agricultural sources. Environ. Sci. Technol. 2010, 44 (6), 1947−53. (31) D’Costa, V. M.; King, C. E.; Kalan, L.; Morar, M.; Sung, W. W.; Schwarz, C.; Froese, D.; Zazula, G.; Calmels, F.; Debruyne, R.; Golding, G. B.; Poinar, H. N.; Wright, G. D. Antibiotic resistance is ancient. Nature 2011, 477 (7365), 457−61. (32) Pruden, A.; Arabi, M.; Storteboom, H. N. Correlation between upstream human activities and riverine antibiotic resistance genes. Environ. Sci. Technol. 2012, 46 (21), 11541−11549. (33) Storteboom, H.; Arabi, M.; Davis, J. G.; Crimi, B.; Pruden, A. Tracking antibiotic resistance genes in the South Platte River Basin using molecular signatures of urban, agricultural, and pristine sources. Environ. Sci. Technol. 2010, 44 (19), 7397−7404. (34) Su, H. C.; Pan, C. G.; Ying, G. G.; Zhao, J. L.; Zhou, L. J.; Liu, Y. S.; Tao, R.; Zhang, R. Q.; He, L. Y. Contamination profiles of antibiotic resistance genes in the sediments at a catchment scale. Sci. Total Environ. 2014, 490, 708−14. (35) Zhou, L. J.; Ying, G. G.; Liu, S.; Zhao, J. L.; Chen, F.; Zhang, R. Q.; Peng, F. Q.; Zhang, Q. Q. Simultaneous determination of human and veterinary antibiotics in various environmental matrices by rapid resolution liquid chromatography-electrospray ionization tandem mass spectrometry. J. Chromatogr., A 2012, 1244, 123−138. (36) Yuan, C. G.; Shi, J. B.; He, B.; Liu, J. F.; Liang, L. N.; Jiang, G. B. Speciation of heavy metals in marine sediments from the East China Sea by ICP-MS with sequential extraction. Environ. Int. 2004, 30 (6), 769−83. (37) Cleceri, L.; Greenberg, A.; Eaton, A. Standard Methods for the Examination of Water and Wastewater; American Public Health Association, American Water Works Association, and Water Environment Association: Washington, DC, 1998. (38) Kehrenberg, C.; Schwarz, S. fexA, a novel Staphylococcus lentus gene encoding resistance to florfenicol and chloramphenicol. Antimicrob. Agents Chemother. 2004, 48 (2), 615−8. (39) Kehrenberg, C.; Schwarz, S. Florfenicol-chloramphenicol exporter gene fexA is part of the novel transposon Tn558. Antimicrob. Agents Chemother. 2005, 49 (2), 813−5. 13128

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129

Environmental Science & Technology

Article

bacteria from agricultural environments. Curr. Opin. Microbiol. 2011, 14 (3), 244−250. (59) Binh, C. T. T.; Heuer, H.; Kaupenjohann, M.; Smalla, K. Piggery manure used for soil fertilization is a reservoir for transferable antibiotic resistance plasmids. FEMS Microbiol. Ecol. 2008, 66 (1), 25− 37. (60) Nicholson, F. A.; Chambers, B. J.; Williams, J. R.; Unwin, R. J. Heavy metal contents of livestock feeds and animal manures in England and Wales. Bioresour. Technol. 1999, 70 (1), 23−31. (61) Looft, T.; Johnson, T. A.; Allen, H. K.; Bayles, D. O.; Alt, D. P.; Stedtfeld, R. D.; Sul, W. J.; Stedtfeld, T. M.; Chai, B.; Cole, J. R.; Hashsham, S. A.; Tiedje, J. M.; Stanton, T. B. In-feed antibiotic effects on the swine intestinal microbiome. Proc. Natl. Acad. Sci. U S A 2012, 109 (5), 1691−6. (62) Richards, J. D.; Zhao, J.; Harrell, R. J.; Atwell, C. A.; Dibner, J. J. Trace mineral nutrition in poultry and swine. Asian-Australas. J. Anim. Sci. 2010, 23 (11), 1527−1534. (63) Baker-Austin, C.; Wright, M. S.; Stepanauskas, R.; McArthur, J. V. Co-selection of antibiotic and metal resistance. Trends. Microbiol. 2006, 14 (4), 176−82. (64) Kim, J.; Lee, S.; Choi, S. Copper resistance and its relationship to erythromycin resistance in Enterococcus isolates from bovine milk samples in Korea. J. Microbiol. 2012, 50 (3), 540−3.

(40) Liu, H.; Wang, Y.; Wu, C.; Schwarz, S.; Shen, Z.; Jeon, B.; Ding, S.; Zhang, Q.; Shen, J. A novel phenicol exporter gene, fexB, found in enterococci of animal origin. J. Antimicrob. Chemother. 2012, 67 (2), 322−5. (41) Bischoff, K. M.; White, D. G.; Hume, M. E.; Poole, T. L.; Nisbet, D. J. The chloramphenicol resistance gene cmlA is disseminated on transferable plasmids that confer multiple-drug resistance in swine Escherichia coli. FEMS Microbiol. Lett. 2005, 243 (1), 285−91. (42) Schwarz, S.; Werckenthin, C.; Kehrenberg, C. Identification of a plasmid-borne chloramphenicol-florfenicol resistance gene in Staphylococcus sciuri. Antimicrob. Agents Chemother. 2000, 44 (9), 2530− 2533. (43) Schwarz, S.; Kehrenberg, C.; Doublet, B. t.; Cloeckaert, A. Molecular basis of bacterial resistance to chloramphenicol and florfenicol. FEMS Microbiol. Rev. 2004, 28 (5), 519−542. (44) Travis, R. M.; Gyles, C. L.; Reid-Smith, R.; Poppe, C.; McEwen, S. A.; Friendship, R.; Janecko, N.; Boerlin, P. Chloramphenicol and kanamycin resistance among porcine Escherichia coli in Ontario. J. Antimicrob. Chemother. 2006, 58 (1), 173−7. (45) LaMarre, J. M.; Locke, J. B.; Shaw, K. J.; Mankin, A. S. Low fitness cost of the multidrug resistance gene cfr. Antimicrob. Agents Chemother. 2011, 55 (8), 3714−9. (46) Kehrenberg, C.; Schwarz, S. Distribution of florfenicol resistance genes fexA and cfr among chloramphenicol-resistant Staphylococcus isolates. Antimicrob. Agents Chemother. 2006, 50 (4), 1156−63. (47) Phuong Hoa, P. T.; Nonaka, L.; Hung Viet, P.; Suzuki, S. Detection of the sul1, sul2, and sul3 genes in sulfonamide-resistant bacteria from wastewater and shrimp ponds of north Vietnam. Sci. Total Environ. 2008, 405 (1−3), 377−384. (48) Sköld, O. Sulfonamide resistance: Mechanisms and trends. Drug Resist. Updates 2000, 3 (3), 155−160. (49) Sergeant, M. J.; Constantinidou, C.; Cogan, T. A.; Bedford, M. R.; Penn, C. W.; Pallen, M. J. Extensive microbial and functional diversity within the chicken cecal microbiome. PloS one 2014, 9 (3), e91941. (50) Aminov, R. I.; Garrigues-Jeanjean, N.; Mackie, R. I. Molecular ecology of tetracycline resistance: Development and validation of primers for detection of tetracycline resistance genes encoding ribosomal protection proteins. Appl. Environ. Microbiol. 2001, 67 (1), 22−32. (51) Roberts, M. C. Update on acquired tetracycline resistance genes. FEMS Microbiol. Lett. 2005, 245 (2), 195−203. (52) Speer, B. S.; Shoemaker, N. B.; Salyers, A. A. Bacterial resistance to tetracycline: Mechanisms, transfer, and clinical significance. Clin. Microbiol. Rev. 1992, 5 (4), 387−399. (53) El-Shibiny, A.; Connerton, P. L.; Connerton, I. F. Enumeration and diversity of Campylobacters and Bacteriophages isolated during the rearing cycles of free-range and organic chickens. Appl. Environ. Microbiol. 2005, 71 (3), 1259−1266. (54) Bojesen, A. M.; Nielsen, S. S.; Bisgaard, M. Prevalence and transmission of haemolytic Gallibacterium species in chicken production systems with different biosecurity levels. Avian Pathol. 2003, 32 (5), 503−510. (55) Zhao, L.; Wang, G.; Siegel, P.; He, C.; Wang, H.; Zhao, W.; Zhai, Z.; Tian, F.; Zhao, J.; Zhang, H.; Sun, Z.; Chen, W.; Zhang, Y.; Meng, H. Quantitative genetic background of the host influences gut microbiomes in chickens. Sci. Rep. 2013, 3, 1163. (56) Lu, J.; Idris, U.; Harmon, B.; Hofacre, C.; Maurer, J. J.; Lee, M. D. Diversity and succession of the intestinal bacterial community of the maturing broiler chicken. Appl. Environ. Microbiol. 2003, 69 (11), 6816−6824. (57) Cressman, M. D.; Yu, Z. T.; Nelson, M. C.; Moeller, S. J.; Lilburn, M. S.; Zerby, H. N. Interrelations between the microbiotas in the litter and in the intestines of commercial broiler chickens. Appl. Environ. Microbiol. 2010, 76 (19), 6572−6582. (58) Davis, M. F.; Price, L. B.; Liu, C. M.-H.; Silbergeld, E. K. An ecological perspective on U.S. industrial poultry production: The role of anthropogenic ecosystems on the emergence of drug-resistant 13129

dx.doi.org/10.1021/es5041267 | Environ. Sci. Technol. 2014, 48, 13120−13129