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Abundance of class 1–3 integrons in South Carolina estuarine ecosystems under high and low levels of anthropogenic influence
Marine Pollution Bulletin 76 (2013) 77–84
Contents lists available at ScienceDirect
Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul
Abundance of class 1–3 integrons in South Carolina estuarine ecosystems under high and low levels of anthropogenic influence Miguel I. Uyaguari a,1, Geoffrey I. Scott a,b, R. Sean Norman a,⇑ a
Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Center for Coastal Environmental Health and Biomolecular Research, Charleston, SC 29412, USA b
a r t i c l e
i n f o
Keywords: Integrons Integrase Antibiotic resistance Urbanization Wastewater treatment
a b s t r a c t The impact of human activity on the spread of antibiotic resistant bacteria throughout coastal estuarine ecosystems is not well characterized. It has been suggested that laterally transferred genetic agents, such as integrons, play a role in the spread of resistant bacteria throughout ecosystems. This study compares the distribution of three integron classes throughout a coastal estuarine ecosystem. To determine integron distribution patterns, DNA was extracted from sediment and water collected at seven sites throughout two estuaries with different levels of anthropogenic input and integrons analyzed using quantitative PCR. The data show that while all three integron classes are present, the relative abundance is different, with class 2 integrons significantly elevated in areas of high anthropogenic input and class 1 integrons elevated in areas of low input. Our results provide a foundation for using integron gene distribution as a biomarker of urban impact on antibiotic resistance gene flow and ecosystem health. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction It has been estimated that 40% of the global population lives within 100 km of coastlines (UNEP, 2006), with 33 of the 50 world’s largest cities located in coastal zones (Dean, 1997). A similar pattern has been observed in the United States where half of the population resides within 80 km of the coastline (Crossett et al., 2004), with this proportion projected to increase to 70% by the year 2025 (Hinrichsen, 1998). Increases in coastal migration and changes in land use patterns have been linked to the degradation of many estuarine ecosystems resulting in reduced resources provided from these areas for sustainability and recreation (Comeleo et al., 1996; Vernberg et al., 1996; Bricker et al., 1999; EPA, 2004; Dauer et al., 2000; Paul et al., 2002; Nelson et al., 2005; Van Dolah et al., 2008). In addition to the chemical and biological agents commonly associated with ecosystem degradation, it has been suggested that bacterial antibiotic resistance genes be included as an emerging contaminant of great public health concern that may also serve as bioindicators of ecosystem quality (Pruden et al., 2006). However, before antibiotic resistance genes
⇑ Corresponding author. Address: University of South Carolina, Department of Environmental Health Sciences, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA. Tel.: +1 (803) 777 0940; fax: +1 (803) 777 3391. E-mail address: [email protected] (R.S. Norman). 1 Current address: University of British Columbia, Department of Pathology and Laboratory Medicine. British Columbia Center for Disease Control Laboratories, 655 West 12th Avenue, Room 3116, Vancouver, BC V5Z 4R4, Canada. 0025-326X/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpolbul.2013.09.027
can be used as an indicator of coastal estuarine ecosystem health, it is important to examine the anthropogenic impact on microbial resistance gene patterns. While selective pressure may result in independent evolution of genetic point mutations, giving rise to bacterial antibiotic resistance genes, it is the location of these genes within mobile elements that allows them to be readily and quickly transferred horizontally throughout an ecosystem (Mazel, 2006; Cambray et al., 2010). Integrons are one such microbial mobile element that plays a role in the dissemination of antibiotic resistance genes. Integrons are genetic elements often associated with pathogenic and commensal bacteria that confer the ability to capture and express exogenous and promoterless gene cassettes, which encode a number of adaptive functions including antibiotic resistance (Mazel, 2006; Boucher et al., 2007; Rodriguez-Minguela et al., 2009). Four elements define an integron structure: a tyrosine recombinase or integron integrase (intI) which is responsible for driving the gene cassette insertion; a recombination site (attI); a promoter (Pc) located upstream of the cassette region and responsible for the expression of gene cassettes; and the actual gene cassettes, many of which confer resistance to a wide range of antibiotics (Jones et al., 2003; Diaz-Mejia et al., 2008). Among these elements, differences in the intI gene sequence are used to differentiate unique integron classes (Sá et al., 2010). While integrons are phylogenetically diverse, three major groups (classes 1–3) are known to be associated with horizontally transferred elements that contribute significantly to the spread of antibiotic resistance (Partridge et al., 2009). Class 1 integrons are typically
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linked to replicative Tn21 transposons and are the most abundant integron class found in clinical isolates (Rosser and Young, 1999; Mazel, 2006; Solberg et al., 2006; Diaz-Mejia et al., 2008; Wright et al., 2008). More than 80 different gene cassettes of class 1 integrons have been described and shown to confer resistance to a wide range of antibiotics such as b-lactams, fluoroquinolones, aminoglycosides, chloramphenicol, trimethoprim, streptothricin, rifampin, erythromycin, fosfomycin, lincomycin, and antiseptics and disinfectants (Rowe-Magnus and Mazel, 2002; Fluit and Schmitz, 2004). Class 2 integrons have been reported most often in isolates within the Enterobacteriaceae family and less frequently in other isolates affiliated with the beta, gamma, and epsilon subdivisions of the Proteobacteria (Fluit and Schmitz, 2004; Ramirez et al., 2005; Rodriguez-Minguela et al., 2009). These integrons are associated with nonreplicative Tn7 transposons with up to 12 different gene cassette arrays described as conferring resistance to aminoglycosides, chloramphenicol, trimethoprim, streptothricin (Biskri and Mazel, 2003; Ramirez et al., 2005; Barlow and Gobius, 2006; Mazel, 2006). As compared to class 1 and 2, less is known about class 3 integrons which have been described as rare and found only in a limited number of isolates including Serratia marcescens, Klebsiella pneumoniae, Pseudomonas aeruginosa, Pseudomonas putida, Alcaligenes xylosoxidans, and Delftia spp. (Collis et al., 2002; Correia et al., 2003; Shibata et al., 2003; Fluit and Schmitz, 2004; Xu et al., 2007). Currently, gene cassettes within class 3 integrons have been shown to confer resistance to ceftazimide, sulbactam, and cefoperazone (Shibata et al., 2003; Fluit and Schmitz, 2004.). These integron classes, commonly containing antibiotic resistance genes, have been documented in a wide variety of environments such as hospitals, soils, sediments, aqua culture facilities, oyster beds, and wastewater treatment plants (Schmidt et al., 2001; White et al., 2001; Roe et al., 2003; Solberg et al., 2006; Rao et al., 2006; Diaz-Mejia et al., 2008; Gillings et al., 2008; Ozgumus et al., 2009; Barkovskii et al., 2010). Most of these studies have been conducted on bacterial isolates using culture-dependent methods or focused on a particular integron class, thus underestimating overall integron abundance and complexity within these ecosystems. However, a recent study surveyed the presence of class 1–3 integrons within oyster beds and found that integron distribution may be correlated with agricultural and municipal run-offs (Barkovskii et al., 2010). This study focused on an area of low human population density and high agricultural use and found a higher incidence of class 3 integrons within oysters as compared to class 1 and 2. Currently, no quantitative culture-independent studies have simultaneously compared the difference in the distribution of the three major classes of integrons within highly urbanized and pristine coastal estuarine ecosystems. To determine the urban impact on integron distribution, we used quantitative PCR to examine the abundance of class 1–3 integrase genes in sediments and water collected from sites within Charleston Harbor, an area of high anthropogenic input, and a less impacted site listed within NOAA’s National Estuarine Research Reserve System. For further comparison, we also examined the distribution of integrons within a wastewater treatment plant (WWTP) that discharges into Charleston Harbor. A better understanding of the anthropogenic impact on integron distribution will provide insight on one possible mechanism for the spread of antibiotic resistant genes throughout an ecosystem and may provide an additional indicator of overall ecosystem health with potential public health consequences. 2. Materials and methods 2.1. Coastal estuarine ecosystem study sites The urban-impacted coastal estuarine ecosystem examined in this study is located along the southern coast of South Carolina,
USA and has an average yearly salinity of 27 psu and surface water temperature of 22.6 °C (Fig. 1A). The Charleston Harbor estuary covers approximately 3300 km2 and is composed of three tributaries: the Cooper, Wando, and Ashley Rivers (Yassuda et al., 2000). As the second largest container port on the East Coast, this ecosystem supports a rapidly growing economy with a concurrent 7% annual urban area expansion rate (Allen and Lu, 2003) consisting of mixed residential, urban, and light industrial use. This area also supports a growing population through its use as a recreational site for swimming, boating, and fishing. Sediment and water sampling sites were located in the lower portion of the Charleston Harbor estuary at 32°460 2.9900 N; 79°560 22.9200 W (site 2), 32°460 56.5600 N; 79°570 36.6800 W (site 3), 32°460 0.4400 N; 79°540 23.7500 W (site 4), 32°470 38.9400 N; 79°540 51.3700 W (site 5), 32°450 13.7100 N; 0 00 0 00 0 79°52 18.22 W (site 6), and 32°46 13.72 N, 79°52 31.6000 W (site 7). As a non-urbanized control site, sediment and water samples were also collected near the Oyster Landing monitoring station at North Inlet, Winyah Bay, SC (Fig. 1B, site 8; 33°210 0.3600 N; 79°110 24.1800 W). North Inlet is located 96 km northeast of Charleston Harbor and is a bar-built estuary bounded by Debidue Island to the northeast and North Island to the southeast. This site is part of the NOAA’s National Estuarine Research Reserve System (NERRS) and while experiencing similar environmental conditions as Charleston Harbor, it is less developed resulting in reduced urban influence. Furthermore, as a potential point source of contamination in Charleston Harbor, we also examined a wastewater treatment facility located in Charleston, SC (Fig. 1A, site 1; 32°450 36.8400 N; 79°560 57.8900 W). With an optimal operating capacity of 136 million l day1 of treated wastewater, the facility uses primary treatment involving physical removal of debris and large particles from the wastewater prior to secondary biological treatment and final chlorination. The outfall (site 2) is located 1219.20 m from the shore in Charleston Harbor. 2.2. Sample collection Charleston Harbor samples were collected during a flood tide in August 2010. Three one-liter seawater samples were taken at a depth of 2 m using a Niskin bottle and stored in sterile polyethylene bottles for further processing. Three sediment samples (1 kg) were collected at the same geographical sites using an Ekman dredge and stored in one-liter sterile polyethylene bottles. The Ekman dredge was rinsed with nitric acid, acetone, and de-ionized water between stations. The same protocol was employed to collect seawater and sediment samples in the Oyster landing station in North Inlet. Water quality parameters were measured at each site using a YSI 556 Multiparameter System with probe placed mid-water column. Wastewater samples were collected immediately prior to Charleston Harbor sampling using sterile polyethylene one-liter bottles (n = 2) from 3 different stages of the wastewater treatment process: raw sewage (RS), activated sludge (AS), and principal effluent (PE). Once samples were collected, they were immediately stored on ice and transported to the laboratory for processing and storage (within 3 h). 2.3. DNA extraction Seawater and sediment samples were extracted using the UltraClean Soil DNA kit (MoBio, Carlsbad, CA) following the manufacturer’s instructions, but due to low cell density, 1000 ml of seawater samples were first concentrated by filtration using a 0.22 lm Sterivex filter unit (Millipore Corporation, Billerica, MA) then washed with phosphate buffer solution to remove the cells from the filter before DNA extraction. DNA extracted from
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Fig. 1. Sampling site locations: (A) Urban-impacted coastal estuarine ecosystem sample collection sites in Charleston Harbor (Charleston, SC). Site 1: WWTP (sites for raw sewage, activated sludge, and principal effluent collection); Site 2: WWTP outfall/discharge site; Site 3: Ashley River; Site 4: Ashley and Cooper River mixing zone; Site 5: Cooper/Wando River confluence; Site 6: Charleston Harbor mouth; and Site 7: Mount Pleasant. (B) Site 8: Non-urbanized control site located at the Oyster landing station, North Inlet, SC. GIS was used to indicate areas of urban land cover (dark gray shading).
environmental samples required further purification by gel electrophoresis. DNA bands ranging between 33 and 48 kb were excised and isolated using GELase (Epicentre Biotechnologies, Madison, WI) following the manufacturer’s protocol. DNA from WWTP samples (RS, AS, and PE) were extracted using a modified freeze–thaw protocol based on organic extraction and PEG precipitation (Bey et al., 2010), and the final DNA pellet was resuspended in DNase-free water. Due to the low cell numbers in PE 1000 ml of these samples were concentrated and DNA extracted as described above. 2.4. Isolation and characterization of class 1–3 integrase genes for quantitative polymerase chain reaction (qPCR) To generate int1–3 standard curves to be used in quantitative PCR, DNA extracted from RS was used as template to generate amplicons for each integrase class. Each PCR reaction consisted of 1.5 mM MgCl2, 0.2 mM nucleotides, 0.4 lM of intI primers (Table 1), 1.25 U of Hot start polymerase (Promega), 10 ng of template DNA, and water in a 25 ll volume. PCR conditions were conducted as follows: 94 °C for 5 min, followed by 35 cycles of 94 °C for 45 s, 62 °C for 45 s, 72 °C for 1 min and a final extension at 72 °C for 10 min. PCR amplicons were purified with a QIAQuick PCR Purification Kit (Qiagen Sciences, Maryland, MD) according to the manufacturer’s instructions. These purified amplicons were ligated into pCR2.1-TOPO cloning vectors (Invitrogen, Carlsbad, CA), and trans-
formed into One Shot Escherichia coli DH5a-T1R competent cells following the manufacturer’s protocol. Ten transformants were picked for each integrase class and grown overnight at 37 °C in LB broth containing 50 lg ml1 kanamycin. Plasmids were extracted and purified using QIAprep Spin Miniprep kit (Qiagen Sciences), and quantified with a NanoDrop spectrophotometer (NanoDrop Technologies, Inc., Wilmington, DE). To validate the integrase class contained in each plasmid, plasmids were end-sequenced using M13 reverse primer (50 -CAGGAAACAGCTATGACC30 ) at EnGenCore, LLC using BigDye Terminator version 3.1 cycle sequencing kit (Applied Biosystems, Warrington, UK). The resultant set of DNA sequences for each class was aligned using Geneious 3.6.1 software (Drummond et al., 2008), and searched against the GenBank database using BLASTX with default settings. 2.5. Quantitative polymerase chain reaction of class 1–3 intI gene fragments Plasmids harboring class 1–3 integrase gene fragments were linearized by digestion with the Hind III endonuclease (New England BioLabs Inc., Ipswich, MA). Serial dilutions of the linearized plasmid were used as templates to generate standard curves for qPCR. Each 25 ll real-time PCR reaction consisted of 12.5 ll of SYBR green I PCR master mix (Applied Biosystems), 250 nM of each intI primer (Table 1), and 10 ng of template DNA. Standard curve and environmental sample reactions were conducted on an iCycler
Table 1 Description of the primers used in PCR and qPCR of class 1, 2, 3 integrase genes. Target gene
Primer name
Primer sequences (50 ? 30 )
Amplicon size (bp)
Reference
intI1
qlntllF qlntllR intI2-LC2 intI2-LC3 int3-LC1 intI3-LC2
ACCAACCGAACAGGCTTATG GAGGATGCGAACCACTTCCAT TGCTTTTCCCACCCTTACC GACGGCTACCCTCTG TTATCTC GCCACCACTTGTTTGAGGA GGATGTCTGTGCCTGCTTG
286
Wright et al. (2008)
195
Barraud et al. (2010)
138
Barraud et al. (2010)
intI2 intI3
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iQ™ Real-Time PCR Detection System (Bio-Rad Laboratories, Inc., Hercules, CA). The thermal cycling conditions consisted of incubation for 2 min at 50 °C, initial denaturation for 10 min at 95 °C followed by 40 cycles of 30 s at 95 °C and 60 s at 60 °C. Gene copy numbers for environmental samples and WWTP samples (RS, AS, PE) were run in triplicate. To verify the absence of non-specific amplification, a dissociation step was included, and final amplicons were resolved on a 2% agarose gel. 2.6. Data analysis Gene copy numbers were transformed using log10 function for analysis. Generalized linear models (GLM) were performed using Statistical Analysis System (SASÒ, version 9.1.3 for Windows) on the qPCR data to detect differences between gene copy numbers in environmental samples and wastewater treatment processes (RS, AS, and PE). Tukey’s test was used to determine statistical differences among the different sites (Fig. 1A and B). A p-value of 0.05 was assumed for the test as a minimum level of significance. 3. Results and discussion 3.1. Quantitation of class 1–3 integrons in urban and non-urban impacted coastal sediments To determine how differences in land use patterns may influence the selection for and propagation of specific integron classes, we quantified the three most common classes of integrase genes (class 1–3) within urban and non-urban influenced coastal sediments. While this study provides a quantitative comparative assessment of the three major classes of integrons within a coastal estuarine ecosystem, previous studies have used different approaches to document the occurrence of integrons within a range of environments (Schmidt et al., 2001; White et al., 2001; Roe et al., 2003; Solberg et al., 2006; Rao et al., 2006; Diaz-Mejia et al., 2008; Gillings et al., 2008; Laroche et al., 2009; Ozgumus et al., 2009; Barkovskii et al., 2010; Stalder et al., 2012). In our study, quantitation of integrase gene copy numbers (GCNs) g1 sample indicated the presence of the main three integron classes across all urban and non-urban influenced sediments (Fig. 2A; Sites 2–8). Within these environments, integrons may be providing an environmental reservoir of antibiotic resistance genes and playing a role in overall microbial evolution by providing access to a set of mobile adaptive genes. When the abundance of class 1–3 integrase genes were compared within each urban-impacted site, a significantly (p < 0.0001) higher GCN of class 2 integrase genes was observed in all but site 3 sediment samples, suggesting a selection of class 2 integrons within these sites. This is similar to another study that demonstrated an enrichment of class 2 integrons in soils with high fecal waste input as compared to pristine soils (Rodriguez-Minguela et al., 2009). However, our results are different from another study that suggested that in a polluted riverine system, class 2 integrons are less prevalent than class 1 integrons (Luo et al., 2010). While the culture-independent approach of the current study cannot link the integrons to specific bacteria, it is possible that the selection of class 2 integrons within the urban-impacted Charleston Harbor is due to fecal loading through point and nonpoint source runoff into the harbor. When comparing the abundance of class 1–3 integrase genes between sites, significantly higher class 2 integrase gene copy numbers were observed at site 5 (2.6 105 g1 sediment) compared to other sites in the Charleston Harbor area. This site receives a higher stream flow due to the increased rate of runoff from two major river systems (Cooper and Wando rivers). When comparing
the abundance of class 1 and 3 integrase genes, no differences could be detected for sites 4–7, while class 1 integrons were significantly higher than class 3 genes at sites 2 and 3. While class 1 integrons have been observed in numerous environments (Wright et al., 2008; Byrne-Bailey et al., 2011; Gaze et al., 2011; Stalder et al., 2012), few studies have examined class 3 integrons within an environmental context. In one study conducted in an estuarine ecosystem with low anthropogenic input, class 3 integrons were found to be the predominant class in oyster mantle fluid (Barkovskii et al., 2010). Similarly, while class 3 integrons are often considered ‘rare’ (Xu et al., 2007; Barkovskii et al., 2010), our data suggests that this integron class is more widely distributed than previously thought. Furthermore, no pattern of integron distribution was recognized in relation to collected water quality parameters at each site (Table 2). When comparing urban versus nonurban-impacted sediments, integrase genes quantified in nonurban-impacted North Inlet samples (Site 8) had a different gene profile when compared to Charleston Harbor samples. In these sediments, class 1 integrase genes were significantly more abundant than class 2 or 3 integrases. Other studies have suggested similar abundances of class 1 integrons in a wide range of ecosystems (Stalder et al., 2012). Given that this site receives minimum anthropogenic input, the observed integron abundances may represent the true environmental background distribution as influenced by wildlife and agricultural runoff. Overall, these data suggest that within these nonurban-impacted sediments there is a strong selection for class 1 integrons as compared to the selection of class 2 integrons in the urban-impacted sediments. Integrase GCNs were also normalized against the concentration of genomic DNA extracted from the sediment at each site. This normalization provides a comparison of the relative concentration of integrase genes in terms of the overall community metagenome and, unlike the GCN g1 and ml1, is independent of bacterial concentration. Similar to the distribution pattern observed in terms of g1 sediment, the sediment metagenome is also significantly enriched in class 2 integrase genes in most urban-impacted sites while the metagenome in the nonurban-impacted site is enriched in class 1 integrase genes (Fig. 2B). 3.2. Quantitation of class 1–3 integrons in urban and non-urban impacted coastal water As a comparison to the sediment integron distribution, which represents a longer-term reservoir, the concentration of integrase gene classes was also measured in the tidally influenced transient water above each sediment sampling location (Fig. 2C and D Sites 2–8). The concentration of integrase genes within water samples measured in terms of ml of sample and ng of DNA was several fold lower than the corresponding sediment samples. However, the overall integrase gene class distribution was similar to urban-impacted Charleston Harbor sediments (sites 2–7) with class 2 integrase genes enriched as compared to class 1 and 3 genes. The integrase gene distribution observed in water obtained from the nonurban-impacted North Inlet site (site 8) also showed a similar profile as compared to sediment samples with significant enrichment in class 1 integrase genes. 3.3. Occurrence of integrons within a WWTP As a potential point source of contamination in Charleston Harbor, we also characterized the integron distribution within different stages of a wastewater treatment facility that discharges up to 136 million l day1 of treated wastewater directly into Charleston Harbor (Fig. 1, sites 1, 2). Similar to a previous study that observed class 1–3 integrons in both urban and slaughterhouse wastewater treatment facilities (Moura et al., 2010), we also
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Fig. 2. Integrase gene copy numbers (GCN) in sediment and water samples collected from urban-impacted and nonurban-impacted sites. (A) GCN g1 of sediment; (B) GCN ng1 of sediment DNA; (C) GCN ml1 estuarine water; and (D) GCN ng1 water DNA. Copy numbers were quantified by qPCR using HMW-DNA extracted from 6 different sites in the urban-impacted Charleston Harbor area (Sites 2–7) and one in the North Inlet control site having less urban impact (Site 8). Bars represent the mean GCN for each treatment (n = 3). Error bars indicate standard deviations. Black, light and dark gray bars correspond to class 1, 2, and 3 integrase genes, respectively. Different lower case letters located above the bars indicate significant differences between integrase classes within each sample site, while different upper case letters located inside the bars indicate significant differences of that integrase class between the sample sites. Statistical significance used was at the 0.05 level. Please note the differences in scale for water versus sediment samples.
Table 2 Charleston Harbor and North Inlet water quality parameters Sample site
Temp (°C)
Salinity (PPt)
pH
DO (mg/l)
SpCond (ms/cm)
Site Site Site Site Site Site Site
30.7 ± 0.5 30.6 ± 0.4 30.1 ± 0.4 30.4 ± 0.5 29.9 ± 0.1 30.0 ± 0.4 31.3 ± 0.5
26.0 ± 0.2 25.8 ± 0.5 30.1 ± 0.4 26.3 ± 0.4 29.8 ± 0.5 30.8 ± 0.7 31.7 ± 0.5
7.8 ± 0.1 7.8 ± 0.1 7.9 ± 0.2 7.9 ± 0.1 7.9 ± 0.3 8.0 ± 0.1 7.7 ± 0.2
5.1 ± 0.3 4.8 ± 0.1 5.2 ± 0.4 5.4 ± 0.3 6.1 ± 0.2 6.2 ± 0.5 5.4 ± 0.3
40.4 ± 0.5 40.2 ± 0.5 45.5 ± 0.6 41.7 ± 0.4 45.5 ± 0.5 47.2 ± 0.5 49.7 ± 0.7
2 3 4 5 6 7 8
observed class 1–3 integrase genes in all examined wastewater stages (Fig. 3A and B). Among the wastewater treatment processes, the activated sludge (AS) contained the highest GCN ml1 of all three classes of integrase genes as compared to raw sewage (RS) and the principal effluent (PE) (Fig. 3A). The high metabolic activity and growth of microorganisms contained in activated sludge (Burgess et al., 1999; Vanrolleghem et al., 2004), combined with the potential presence of antibiotics and other agents such as quaternary ammonium compounds, may provide a selective environment for the enrichment of integrons resulting in the highest GCN within the treatment process (Gaze et al., 2011). Comparison of the integrase gene class distribution throughout treatment shows that class 2 integrase genes are the most abundant class in the RS and AS followed by class 3 and class 1 integrase genes, respectively (Fig. 3A). This contradicts results found in other urban wastewater studies, where isolates harboring class 1 integr-
ase genes were observed in higher proportion to isolates harboring class 2 integrases (Moura et al., 2007; Pellegrini et al., 2011). This discrepancy may be due to the inherent differences in the culture-dependent methodologies used in previous studies and the culture-independent methodologies used in our study. Overall, our data suggest that a large fraction of the microbial population entering the facility is made up of organisms harboring class 2 and 3 integrons. Fecal enterobacteria have been described as a sub-dominant group inhabiting the gut flora and human intestinal microbiota (Mariat et al., 2009), with E. coli as the major representative isolate (Chen et al., 2004). As these microorganisms often harbor class 2 integrons, results from the present research suggest the highest numbers of class 2 integrons may be correlated to the high loads of enterobacteriacea as previously reported in hospitals and activated sludge of wastewater treatment plants (Schwartz et al., 2003). Interestingly, the presence of high GCN of
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The widespread dissemination of bacterial antibiotic resistance genes (ARGs) remains a great public and ecosystem health concern. To better understand how ARGs are selected, propagated, and disseminated, it is important to examine the anthropogenic impact on microbial resistance gene patterns. As reservoirs of ARGs, integrons are mobile elements that may enhance the horizontal transfer of resistance genes throughout an ecosystem. Therefore, examining the distribution of integrons throughout urban-impacted and nonurban-impacted ecosystems may provide a better understanding of how changes in land use patterns will influence ARG flow through an ecosystem, possibly resulting in the rapid spread of antibiotic resistant bacteria. The data from this study show that while all three integron classes are present in both urban-impacted and nonurban-impacted ecosystems, class 2 integrons are significantly enriched in urban-impacted Charleston Harbor sites and class 1 integrons were enriched at a less urbanized site. Furthermore, the occurrence of class 3 integrons in all tested samples suggests that their overall distribution and contribution to the spread of antibiotic resistance traits is greater than previously thought. While further culture-independent studies are needed at different coastal locations to determine whether these patterns of integron abundance are generalizable and to characterize integron gene cassettes within these ecosystems, our results provide a foundation for using integron distribution as a potential biomarker of urban impact on antibiotic resistance gene flow and ecosystem health. Acknowledgements
Fig. 3. WWTP integrase gene copy number (GCN) ml1 of sample (A), and ng1 of DNA (B). Copy numbers were quantified by qPCR using genomic DNA extracted from 3 different stages in the Plum Island WWTP: Raw sewage (RS), Activated sludge (AS), and Principal effluent (PE). Bars represent the mean GCN for each treatment (n = 3). Error bars indicate standard deviations. Black, light and dark gray bars correspond to class 1, 2, and 3 integrase genes, respectively. Different lower case letters located above the bars indicate significant differences between integrase classes within each sample site, while different upper case letters located inside the bars indicate significant differences of that integrase class between the sample sites. Statistical significance used was at the 0.05 level.
class 3 integrons within the WWTP suggests that this understudied integron class may be more widespread than previously considered. Furthermore, similar to other studies (Andersen, 1993; Guardabassi et al., 2002; Auerbach et al., 2007; Lachmayr et al., 2009; Zhang et al., 2009), a significant decrease in the concentration of all three integrase classes was observed in the PE as compared to the RS and AS. This reduction in integrase GCN ml1 is expected due to the efficient removal of bacterial cells as part of wastewater processing subsequent to the AS process. Within the PE, a different integrase gene class profile was observed as compared to RS and AS with class 3 integrase genes found to be significantly higher (p < 0.0001) than classes 1 and 2. Integrase GCNs were also normalized against the concentration of genomic DNA extracted from the WWTP samples (Fig. 3B). While the concentrations were lower than the ml1 concentrations, the integrase gene class distribution pattern was similar with class 2 integrase genes being the most abundant in the RS and AS while class 3 genes were the most abundant in the PE. Overall, while significant reductions of integrons were achieved through the wastewater treatment process, the WWTP releases up to 136 million liters of treated effluent daily, which represents 2.4 1013, 2.7 1013, and 1.0 1014 GCNs of class 1, 2, and 3 integrons, respectively, discharged into the Charleston Harbor and likely contributing to the ecosystem integron pool.
This work was supported by the South Carolina Sea Grant Consortium and a Slocum-Lunz Grant No. 21600-KA43. Academic support and scholarship for MIU was granted by an Arnold Fellowship (USC, School of Public Health). Arnold School of Public Health Seed grant was provided for RSN. The authors would like to thank anonymous reviewers for insightful comments and suggestions that enhanced the manuscript. We would also like to thank E.B. Fichot and D.E. Ross for valuable comments to this manuscript, J.D. Hibbert for GIS assistance, and J.W. Daugomah and J.B. West for Charleston Harbor sediment and water sample collection. A special acknowledgment to Dr. Vivian Miao and her laboratory members for providing integrase control strains. We also thank the staff at EnGenCore, LLC for their sequencing expertise, and the Instrument Research Facility (USC, School of Medicine) for use of the iCycler iQ™ Real-Time PCR Detection System. The National Ocean Service (NOS) does not approve, recommend, or endorse any proprietary product or material mentioned in this publication. No reference shall be made to NOS, or to this publication furnished by NOS, in any advertising or sales promotion that would indicate or imply that NOS approves, recommends, or endorses any proprietary product or proprietary material mentioned herein or that has as its purpose any intent to cause directly or indirectly the advertised product to be used or purchased because of NOS publication. References Allen, J., Lu, K., 2003. Modeling and prediction of future urban growth in the Charleston region of South Carolina: a GIS based integrated approach. Conserv. Ecol. 8 (2), 1–2. Andersen, S.R., 1993. Effects of waste water treatment on the species composition and antibiotic resistance of coliform bacteria. Curr. Microbiol. 26 (2), 97–103. Auerbach, E.A., Seyfried, E.E., McMahon, K.D., 2007. Tetracycline resistance genes in activated sludge wastewater treatment plants. Water Res. 41 (5), 1143–1151. Barkovskii, A.L., Green, C., Hurley, D., 2010. The occurrence, spatial and temporal distribution, and environmental routes of tetracycline resistance and integrase genes in Crassostrea virginica beds. Mar. Pollut. Bull. 60 (12), 2215–2224.
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Contents lists available at ScienceDirect
Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul
Abundance of class 1–3 integrons in South Carolina estuarine ecosystems under high and low levels of anthropogenic influence Miguel I. Uyaguari a,1, Geoffrey I. Scott a,b, R. Sean Norman a,⇑ a
Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Center for Coastal Environmental Health and Biomolecular Research, Charleston, SC 29412, USA b
a r t i c l e
i n f o
Keywords: Integrons Integrase Antibiotic resistance Urbanization Wastewater treatment
a b s t r a c t The impact of human activity on the spread of antibiotic resistant bacteria throughout coastal estuarine ecosystems is not well characterized. It has been suggested that laterally transferred genetic agents, such as integrons, play a role in the spread of resistant bacteria throughout ecosystems. This study compares the distribution of three integron classes throughout a coastal estuarine ecosystem. To determine integron distribution patterns, DNA was extracted from sediment and water collected at seven sites throughout two estuaries with different levels of anthropogenic input and integrons analyzed using quantitative PCR. The data show that while all three integron classes are present, the relative abundance is different, with class 2 integrons significantly elevated in areas of high anthropogenic input and class 1 integrons elevated in areas of low input. Our results provide a foundation for using integron gene distribution as a biomarker of urban impact on antibiotic resistance gene flow and ecosystem health. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction It has been estimated that 40% of the global population lives within 100 km of coastlines (UNEP, 2006), with 33 of the 50 world’s largest cities located in coastal zones (Dean, 1997). A similar pattern has been observed in the United States where half of the population resides within 80 km of the coastline (Crossett et al., 2004), with this proportion projected to increase to 70% by the year 2025 (Hinrichsen, 1998). Increases in coastal migration and changes in land use patterns have been linked to the degradation of many estuarine ecosystems resulting in reduced resources provided from these areas for sustainability and recreation (Comeleo et al., 1996; Vernberg et al., 1996; Bricker et al., 1999; EPA, 2004; Dauer et al., 2000; Paul et al., 2002; Nelson et al., 2005; Van Dolah et al., 2008). In addition to the chemical and biological agents commonly associated with ecosystem degradation, it has been suggested that bacterial antibiotic resistance genes be included as an emerging contaminant of great public health concern that may also serve as bioindicators of ecosystem quality (Pruden et al., 2006). However, before antibiotic resistance genes
⇑ Corresponding author. Address: University of South Carolina, Department of Environmental Health Sciences, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA. Tel.: +1 (803) 777 0940; fax: +1 (803) 777 3391. E-mail address: [email protected] (R.S. Norman). 1 Current address: University of British Columbia, Department of Pathology and Laboratory Medicine. British Columbia Center for Disease Control Laboratories, 655 West 12th Avenue, Room 3116, Vancouver, BC V5Z 4R4, Canada. 0025-326X/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpolbul.2013.09.027
can be used as an indicator of coastal estuarine ecosystem health, it is important to examine the anthropogenic impact on microbial resistance gene patterns. While selective pressure may result in independent evolution of genetic point mutations, giving rise to bacterial antibiotic resistance genes, it is the location of these genes within mobile elements that allows them to be readily and quickly transferred horizontally throughout an ecosystem (Mazel, 2006; Cambray et al., 2010). Integrons are one such microbial mobile element that plays a role in the dissemination of antibiotic resistance genes. Integrons are genetic elements often associated with pathogenic and commensal bacteria that confer the ability to capture and express exogenous and promoterless gene cassettes, which encode a number of adaptive functions including antibiotic resistance (Mazel, 2006; Boucher et al., 2007; Rodriguez-Minguela et al., 2009). Four elements define an integron structure: a tyrosine recombinase or integron integrase (intI) which is responsible for driving the gene cassette insertion; a recombination site (attI); a promoter (Pc) located upstream of the cassette region and responsible for the expression of gene cassettes; and the actual gene cassettes, many of which confer resistance to a wide range of antibiotics (Jones et al., 2003; Diaz-Mejia et al., 2008). Among these elements, differences in the intI gene sequence are used to differentiate unique integron classes (Sá et al., 2010). While integrons are phylogenetically diverse, three major groups (classes 1–3) are known to be associated with horizontally transferred elements that contribute significantly to the spread of antibiotic resistance (Partridge et al., 2009). Class 1 integrons are typically
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linked to replicative Tn21 transposons and are the most abundant integron class found in clinical isolates (Rosser and Young, 1999; Mazel, 2006; Solberg et al., 2006; Diaz-Mejia et al., 2008; Wright et al., 2008). More than 80 different gene cassettes of class 1 integrons have been described and shown to confer resistance to a wide range of antibiotics such as b-lactams, fluoroquinolones, aminoglycosides, chloramphenicol, trimethoprim, streptothricin, rifampin, erythromycin, fosfomycin, lincomycin, and antiseptics and disinfectants (Rowe-Magnus and Mazel, 2002; Fluit and Schmitz, 2004). Class 2 integrons have been reported most often in isolates within the Enterobacteriaceae family and less frequently in other isolates affiliated with the beta, gamma, and epsilon subdivisions of the Proteobacteria (Fluit and Schmitz, 2004; Ramirez et al., 2005; Rodriguez-Minguela et al., 2009). These integrons are associated with nonreplicative Tn7 transposons with up to 12 different gene cassette arrays described as conferring resistance to aminoglycosides, chloramphenicol, trimethoprim, streptothricin (Biskri and Mazel, 2003; Ramirez et al., 2005; Barlow and Gobius, 2006; Mazel, 2006). As compared to class 1 and 2, less is known about class 3 integrons which have been described as rare and found only in a limited number of isolates including Serratia marcescens, Klebsiella pneumoniae, Pseudomonas aeruginosa, Pseudomonas putida, Alcaligenes xylosoxidans, and Delftia spp. (Collis et al., 2002; Correia et al., 2003; Shibata et al., 2003; Fluit and Schmitz, 2004; Xu et al., 2007). Currently, gene cassettes within class 3 integrons have been shown to confer resistance to ceftazimide, sulbactam, and cefoperazone (Shibata et al., 2003; Fluit and Schmitz, 2004.). These integron classes, commonly containing antibiotic resistance genes, have been documented in a wide variety of environments such as hospitals, soils, sediments, aqua culture facilities, oyster beds, and wastewater treatment plants (Schmidt et al., 2001; White et al., 2001; Roe et al., 2003; Solberg et al., 2006; Rao et al., 2006; Diaz-Mejia et al., 2008; Gillings et al., 2008; Ozgumus et al., 2009; Barkovskii et al., 2010). Most of these studies have been conducted on bacterial isolates using culture-dependent methods or focused on a particular integron class, thus underestimating overall integron abundance and complexity within these ecosystems. However, a recent study surveyed the presence of class 1–3 integrons within oyster beds and found that integron distribution may be correlated with agricultural and municipal run-offs (Barkovskii et al., 2010). This study focused on an area of low human population density and high agricultural use and found a higher incidence of class 3 integrons within oysters as compared to class 1 and 2. Currently, no quantitative culture-independent studies have simultaneously compared the difference in the distribution of the three major classes of integrons within highly urbanized and pristine coastal estuarine ecosystems. To determine the urban impact on integron distribution, we used quantitative PCR to examine the abundance of class 1–3 integrase genes in sediments and water collected from sites within Charleston Harbor, an area of high anthropogenic input, and a less impacted site listed within NOAA’s National Estuarine Research Reserve System. For further comparison, we also examined the distribution of integrons within a wastewater treatment plant (WWTP) that discharges into Charleston Harbor. A better understanding of the anthropogenic impact on integron distribution will provide insight on one possible mechanism for the spread of antibiotic resistant genes throughout an ecosystem and may provide an additional indicator of overall ecosystem health with potential public health consequences. 2. Materials and methods 2.1. Coastal estuarine ecosystem study sites The urban-impacted coastal estuarine ecosystem examined in this study is located along the southern coast of South Carolina,
USA and has an average yearly salinity of 27 psu and surface water temperature of 22.6 °C (Fig. 1A). The Charleston Harbor estuary covers approximately 3300 km2 and is composed of three tributaries: the Cooper, Wando, and Ashley Rivers (Yassuda et al., 2000). As the second largest container port on the East Coast, this ecosystem supports a rapidly growing economy with a concurrent 7% annual urban area expansion rate (Allen and Lu, 2003) consisting of mixed residential, urban, and light industrial use. This area also supports a growing population through its use as a recreational site for swimming, boating, and fishing. Sediment and water sampling sites were located in the lower portion of the Charleston Harbor estuary at 32°460 2.9900 N; 79°560 22.9200 W (site 2), 32°460 56.5600 N; 79°570 36.6800 W (site 3), 32°460 0.4400 N; 79°540 23.7500 W (site 4), 32°470 38.9400 N; 79°540 51.3700 W (site 5), 32°450 13.7100 N; 0 00 0 00 0 79°52 18.22 W (site 6), and 32°46 13.72 N, 79°52 31.6000 W (site 7). As a non-urbanized control site, sediment and water samples were also collected near the Oyster Landing monitoring station at North Inlet, Winyah Bay, SC (Fig. 1B, site 8; 33°210 0.3600 N; 79°110 24.1800 W). North Inlet is located 96 km northeast of Charleston Harbor and is a bar-built estuary bounded by Debidue Island to the northeast and North Island to the southeast. This site is part of the NOAA’s National Estuarine Research Reserve System (NERRS) and while experiencing similar environmental conditions as Charleston Harbor, it is less developed resulting in reduced urban influence. Furthermore, as a potential point source of contamination in Charleston Harbor, we also examined a wastewater treatment facility located in Charleston, SC (Fig. 1A, site 1; 32°450 36.8400 N; 79°560 57.8900 W). With an optimal operating capacity of 136 million l day1 of treated wastewater, the facility uses primary treatment involving physical removal of debris and large particles from the wastewater prior to secondary biological treatment and final chlorination. The outfall (site 2) is located 1219.20 m from the shore in Charleston Harbor. 2.2. Sample collection Charleston Harbor samples were collected during a flood tide in August 2010. Three one-liter seawater samples were taken at a depth of 2 m using a Niskin bottle and stored in sterile polyethylene bottles for further processing. Three sediment samples (1 kg) were collected at the same geographical sites using an Ekman dredge and stored in one-liter sterile polyethylene bottles. The Ekman dredge was rinsed with nitric acid, acetone, and de-ionized water between stations. The same protocol was employed to collect seawater and sediment samples in the Oyster landing station in North Inlet. Water quality parameters were measured at each site using a YSI 556 Multiparameter System with probe placed mid-water column. Wastewater samples were collected immediately prior to Charleston Harbor sampling using sterile polyethylene one-liter bottles (n = 2) from 3 different stages of the wastewater treatment process: raw sewage (RS), activated sludge (AS), and principal effluent (PE). Once samples were collected, they were immediately stored on ice and transported to the laboratory for processing and storage (within 3 h). 2.3. DNA extraction Seawater and sediment samples were extracted using the UltraClean Soil DNA kit (MoBio, Carlsbad, CA) following the manufacturer’s instructions, but due to low cell density, 1000 ml of seawater samples were first concentrated by filtration using a 0.22 lm Sterivex filter unit (Millipore Corporation, Billerica, MA) then washed with phosphate buffer solution to remove the cells from the filter before DNA extraction. DNA extracted from
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Fig. 1. Sampling site locations: (A) Urban-impacted coastal estuarine ecosystem sample collection sites in Charleston Harbor (Charleston, SC). Site 1: WWTP (sites for raw sewage, activated sludge, and principal effluent collection); Site 2: WWTP outfall/discharge site; Site 3: Ashley River; Site 4: Ashley and Cooper River mixing zone; Site 5: Cooper/Wando River confluence; Site 6: Charleston Harbor mouth; and Site 7: Mount Pleasant. (B) Site 8: Non-urbanized control site located at the Oyster landing station, North Inlet, SC. GIS was used to indicate areas of urban land cover (dark gray shading).
environmental samples required further purification by gel electrophoresis. DNA bands ranging between 33 and 48 kb were excised and isolated using GELase (Epicentre Biotechnologies, Madison, WI) following the manufacturer’s protocol. DNA from WWTP samples (RS, AS, and PE) were extracted using a modified freeze–thaw protocol based on organic extraction and PEG precipitation (Bey et al., 2010), and the final DNA pellet was resuspended in DNase-free water. Due to the low cell numbers in PE 1000 ml of these samples were concentrated and DNA extracted as described above. 2.4. Isolation and characterization of class 1–3 integrase genes for quantitative polymerase chain reaction (qPCR) To generate int1–3 standard curves to be used in quantitative PCR, DNA extracted from RS was used as template to generate amplicons for each integrase class. Each PCR reaction consisted of 1.5 mM MgCl2, 0.2 mM nucleotides, 0.4 lM of intI primers (Table 1), 1.25 U of Hot start polymerase (Promega), 10 ng of template DNA, and water in a 25 ll volume. PCR conditions were conducted as follows: 94 °C for 5 min, followed by 35 cycles of 94 °C for 45 s, 62 °C for 45 s, 72 °C for 1 min and a final extension at 72 °C for 10 min. PCR amplicons were purified with a QIAQuick PCR Purification Kit (Qiagen Sciences, Maryland, MD) according to the manufacturer’s instructions. These purified amplicons were ligated into pCR2.1-TOPO cloning vectors (Invitrogen, Carlsbad, CA), and trans-
formed into One Shot Escherichia coli DH5a-T1R competent cells following the manufacturer’s protocol. Ten transformants were picked for each integrase class and grown overnight at 37 °C in LB broth containing 50 lg ml1 kanamycin. Plasmids were extracted and purified using QIAprep Spin Miniprep kit (Qiagen Sciences), and quantified with a NanoDrop spectrophotometer (NanoDrop Technologies, Inc., Wilmington, DE). To validate the integrase class contained in each plasmid, plasmids were end-sequenced using M13 reverse primer (50 -CAGGAAACAGCTATGACC30 ) at EnGenCore, LLC using BigDye Terminator version 3.1 cycle sequencing kit (Applied Biosystems, Warrington, UK). The resultant set of DNA sequences for each class was aligned using Geneious 3.6.1 software (Drummond et al., 2008), and searched against the GenBank database using BLASTX with default settings. 2.5. Quantitative polymerase chain reaction of class 1–3 intI gene fragments Plasmids harboring class 1–3 integrase gene fragments were linearized by digestion with the Hind III endonuclease (New England BioLabs Inc., Ipswich, MA). Serial dilutions of the linearized plasmid were used as templates to generate standard curves for qPCR. Each 25 ll real-time PCR reaction consisted of 12.5 ll of SYBR green I PCR master mix (Applied Biosystems), 250 nM of each intI primer (Table 1), and 10 ng of template DNA. Standard curve and environmental sample reactions were conducted on an iCycler
Table 1 Description of the primers used in PCR and qPCR of class 1, 2, 3 integrase genes. Target gene
Primer name
Primer sequences (50 ? 30 )
Amplicon size (bp)
Reference
intI1
qlntllF qlntllR intI2-LC2 intI2-LC3 int3-LC1 intI3-LC2
ACCAACCGAACAGGCTTATG GAGGATGCGAACCACTTCCAT TGCTTTTCCCACCCTTACC GACGGCTACCCTCTG TTATCTC GCCACCACTTGTTTGAGGA GGATGTCTGTGCCTGCTTG
286
Wright et al. (2008)
195
Barraud et al. (2010)
138
Barraud et al. (2010)
intI2 intI3
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iQ™ Real-Time PCR Detection System (Bio-Rad Laboratories, Inc., Hercules, CA). The thermal cycling conditions consisted of incubation for 2 min at 50 °C, initial denaturation for 10 min at 95 °C followed by 40 cycles of 30 s at 95 °C and 60 s at 60 °C. Gene copy numbers for environmental samples and WWTP samples (RS, AS, PE) were run in triplicate. To verify the absence of non-specific amplification, a dissociation step was included, and final amplicons were resolved on a 2% agarose gel. 2.6. Data analysis Gene copy numbers were transformed using log10 function for analysis. Generalized linear models (GLM) were performed using Statistical Analysis System (SASÒ, version 9.1.3 for Windows) on the qPCR data to detect differences between gene copy numbers in environmental samples and wastewater treatment processes (RS, AS, and PE). Tukey’s test was used to determine statistical differences among the different sites (Fig. 1A and B). A p-value of 0.05 was assumed for the test as a minimum level of significance. 3. Results and discussion 3.1. Quantitation of class 1–3 integrons in urban and non-urban impacted coastal sediments To determine how differences in land use patterns may influence the selection for and propagation of specific integron classes, we quantified the three most common classes of integrase genes (class 1–3) within urban and non-urban influenced coastal sediments. While this study provides a quantitative comparative assessment of the three major classes of integrons within a coastal estuarine ecosystem, previous studies have used different approaches to document the occurrence of integrons within a range of environments (Schmidt et al., 2001; White et al., 2001; Roe et al., 2003; Solberg et al., 2006; Rao et al., 2006; Diaz-Mejia et al., 2008; Gillings et al., 2008; Laroche et al., 2009; Ozgumus et al., 2009; Barkovskii et al., 2010; Stalder et al., 2012). In our study, quantitation of integrase gene copy numbers (GCNs) g1 sample indicated the presence of the main three integron classes across all urban and non-urban influenced sediments (Fig. 2A; Sites 2–8). Within these environments, integrons may be providing an environmental reservoir of antibiotic resistance genes and playing a role in overall microbial evolution by providing access to a set of mobile adaptive genes. When the abundance of class 1–3 integrase genes were compared within each urban-impacted site, a significantly (p < 0.0001) higher GCN of class 2 integrase genes was observed in all but site 3 sediment samples, suggesting a selection of class 2 integrons within these sites. This is similar to another study that demonstrated an enrichment of class 2 integrons in soils with high fecal waste input as compared to pristine soils (Rodriguez-Minguela et al., 2009). However, our results are different from another study that suggested that in a polluted riverine system, class 2 integrons are less prevalent than class 1 integrons (Luo et al., 2010). While the culture-independent approach of the current study cannot link the integrons to specific bacteria, it is possible that the selection of class 2 integrons within the urban-impacted Charleston Harbor is due to fecal loading through point and nonpoint source runoff into the harbor. When comparing the abundance of class 1–3 integrase genes between sites, significantly higher class 2 integrase gene copy numbers were observed at site 5 (2.6 105 g1 sediment) compared to other sites in the Charleston Harbor area. This site receives a higher stream flow due to the increased rate of runoff from two major river systems (Cooper and Wando rivers). When comparing
the abundance of class 1 and 3 integrase genes, no differences could be detected for sites 4–7, while class 1 integrons were significantly higher than class 3 genes at sites 2 and 3. While class 1 integrons have been observed in numerous environments (Wright et al., 2008; Byrne-Bailey et al., 2011; Gaze et al., 2011; Stalder et al., 2012), few studies have examined class 3 integrons within an environmental context. In one study conducted in an estuarine ecosystem with low anthropogenic input, class 3 integrons were found to be the predominant class in oyster mantle fluid (Barkovskii et al., 2010). Similarly, while class 3 integrons are often considered ‘rare’ (Xu et al., 2007; Barkovskii et al., 2010), our data suggests that this integron class is more widely distributed than previously thought. Furthermore, no pattern of integron distribution was recognized in relation to collected water quality parameters at each site (Table 2). When comparing urban versus nonurban-impacted sediments, integrase genes quantified in nonurban-impacted North Inlet samples (Site 8) had a different gene profile when compared to Charleston Harbor samples. In these sediments, class 1 integrase genes were significantly more abundant than class 2 or 3 integrases. Other studies have suggested similar abundances of class 1 integrons in a wide range of ecosystems (Stalder et al., 2012). Given that this site receives minimum anthropogenic input, the observed integron abundances may represent the true environmental background distribution as influenced by wildlife and agricultural runoff. Overall, these data suggest that within these nonurban-impacted sediments there is a strong selection for class 1 integrons as compared to the selection of class 2 integrons in the urban-impacted sediments. Integrase GCNs were also normalized against the concentration of genomic DNA extracted from the sediment at each site. This normalization provides a comparison of the relative concentration of integrase genes in terms of the overall community metagenome and, unlike the GCN g1 and ml1, is independent of bacterial concentration. Similar to the distribution pattern observed in terms of g1 sediment, the sediment metagenome is also significantly enriched in class 2 integrase genes in most urban-impacted sites while the metagenome in the nonurban-impacted site is enriched in class 1 integrase genes (Fig. 2B). 3.2. Quantitation of class 1–3 integrons in urban and non-urban impacted coastal water As a comparison to the sediment integron distribution, which represents a longer-term reservoir, the concentration of integrase gene classes was also measured in the tidally influenced transient water above each sediment sampling location (Fig. 2C and D Sites 2–8). The concentration of integrase genes within water samples measured in terms of ml of sample and ng of DNA was several fold lower than the corresponding sediment samples. However, the overall integrase gene class distribution was similar to urban-impacted Charleston Harbor sediments (sites 2–7) with class 2 integrase genes enriched as compared to class 1 and 3 genes. The integrase gene distribution observed in water obtained from the nonurban-impacted North Inlet site (site 8) also showed a similar profile as compared to sediment samples with significant enrichment in class 1 integrase genes. 3.3. Occurrence of integrons within a WWTP As a potential point source of contamination in Charleston Harbor, we also characterized the integron distribution within different stages of a wastewater treatment facility that discharges up to 136 million l day1 of treated wastewater directly into Charleston Harbor (Fig. 1, sites 1, 2). Similar to a previous study that observed class 1–3 integrons in both urban and slaughterhouse wastewater treatment facilities (Moura et al., 2010), we also
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Fig. 2. Integrase gene copy numbers (GCN) in sediment and water samples collected from urban-impacted and nonurban-impacted sites. (A) GCN g1 of sediment; (B) GCN ng1 of sediment DNA; (C) GCN ml1 estuarine water; and (D) GCN ng1 water DNA. Copy numbers were quantified by qPCR using HMW-DNA extracted from 6 different sites in the urban-impacted Charleston Harbor area (Sites 2–7) and one in the North Inlet control site having less urban impact (Site 8). Bars represent the mean GCN for each treatment (n = 3). Error bars indicate standard deviations. Black, light and dark gray bars correspond to class 1, 2, and 3 integrase genes, respectively. Different lower case letters located above the bars indicate significant differences between integrase classes within each sample site, while different upper case letters located inside the bars indicate significant differences of that integrase class between the sample sites. Statistical significance used was at the 0.05 level. Please note the differences in scale for water versus sediment samples.
Table 2 Charleston Harbor and North Inlet water quality parameters Sample site
Temp (°C)
Salinity (PPt)
pH
DO (mg/l)
SpCond (ms/cm)
Site Site Site Site Site Site Site
30.7 ± 0.5 30.6 ± 0.4 30.1 ± 0.4 30.4 ± 0.5 29.9 ± 0.1 30.0 ± 0.4 31.3 ± 0.5
26.0 ± 0.2 25.8 ± 0.5 30.1 ± 0.4 26.3 ± 0.4 29.8 ± 0.5 30.8 ± 0.7 31.7 ± 0.5
7.8 ± 0.1 7.8 ± 0.1 7.9 ± 0.2 7.9 ± 0.1 7.9 ± 0.3 8.0 ± 0.1 7.7 ± 0.2
5.1 ± 0.3 4.8 ± 0.1 5.2 ± 0.4 5.4 ± 0.3 6.1 ± 0.2 6.2 ± 0.5 5.4 ± 0.3
40.4 ± 0.5 40.2 ± 0.5 45.5 ± 0.6 41.7 ± 0.4 45.5 ± 0.5 47.2 ± 0.5 49.7 ± 0.7
2 3 4 5 6 7 8
observed class 1–3 integrase genes in all examined wastewater stages (Fig. 3A and B). Among the wastewater treatment processes, the activated sludge (AS) contained the highest GCN ml1 of all three classes of integrase genes as compared to raw sewage (RS) and the principal effluent (PE) (Fig. 3A). The high metabolic activity and growth of microorganisms contained in activated sludge (Burgess et al., 1999; Vanrolleghem et al., 2004), combined with the potential presence of antibiotics and other agents such as quaternary ammonium compounds, may provide a selective environment for the enrichment of integrons resulting in the highest GCN within the treatment process (Gaze et al., 2011). Comparison of the integrase gene class distribution throughout treatment shows that class 2 integrase genes are the most abundant class in the RS and AS followed by class 3 and class 1 integrase genes, respectively (Fig. 3A). This contradicts results found in other urban wastewater studies, where isolates harboring class 1 integr-
ase genes were observed in higher proportion to isolates harboring class 2 integrases (Moura et al., 2007; Pellegrini et al., 2011). This discrepancy may be due to the inherent differences in the culture-dependent methodologies used in previous studies and the culture-independent methodologies used in our study. Overall, our data suggest that a large fraction of the microbial population entering the facility is made up of organisms harboring class 2 and 3 integrons. Fecal enterobacteria have been described as a sub-dominant group inhabiting the gut flora and human intestinal microbiota (Mariat et al., 2009), with E. coli as the major representative isolate (Chen et al., 2004). As these microorganisms often harbor class 2 integrons, results from the present research suggest the highest numbers of class 2 integrons may be correlated to the high loads of enterobacteriacea as previously reported in hospitals and activated sludge of wastewater treatment plants (Schwartz et al., 2003). Interestingly, the presence of high GCN of
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The widespread dissemination of bacterial antibiotic resistance genes (ARGs) remains a great public and ecosystem health concern. To better understand how ARGs are selected, propagated, and disseminated, it is important to examine the anthropogenic impact on microbial resistance gene patterns. As reservoirs of ARGs, integrons are mobile elements that may enhance the horizontal transfer of resistance genes throughout an ecosystem. Therefore, examining the distribution of integrons throughout urban-impacted and nonurban-impacted ecosystems may provide a better understanding of how changes in land use patterns will influence ARG flow through an ecosystem, possibly resulting in the rapid spread of antibiotic resistant bacteria. The data from this study show that while all three integron classes are present in both urban-impacted and nonurban-impacted ecosystems, class 2 integrons are significantly enriched in urban-impacted Charleston Harbor sites and class 1 integrons were enriched at a less urbanized site. Furthermore, the occurrence of class 3 integrons in all tested samples suggests that their overall distribution and contribution to the spread of antibiotic resistance traits is greater than previously thought. While further culture-independent studies are needed at different coastal locations to determine whether these patterns of integron abundance are generalizable and to characterize integron gene cassettes within these ecosystems, our results provide a foundation for using integron distribution as a potential biomarker of urban impact on antibiotic resistance gene flow and ecosystem health. Acknowledgements
Fig. 3. WWTP integrase gene copy number (GCN) ml1 of sample (A), and ng1 of DNA (B). Copy numbers were quantified by qPCR using genomic DNA extracted from 3 different stages in the Plum Island WWTP: Raw sewage (RS), Activated sludge (AS), and Principal effluent (PE). Bars represent the mean GCN for each treatment (n = 3). Error bars indicate standard deviations. Black, light and dark gray bars correspond to class 1, 2, and 3 integrase genes, respectively. Different lower case letters located above the bars indicate significant differences between integrase classes within each sample site, while different upper case letters located inside the bars indicate significant differences of that integrase class between the sample sites. Statistical significance used was at the 0.05 level.
class 3 integrons within the WWTP suggests that this understudied integron class may be more widespread than previously considered. Furthermore, similar to other studies (Andersen, 1993; Guardabassi et al., 2002; Auerbach et al., 2007; Lachmayr et al., 2009; Zhang et al., 2009), a significant decrease in the concentration of all three integrase classes was observed in the PE as compared to the RS and AS. This reduction in integrase GCN ml1 is expected due to the efficient removal of bacterial cells as part of wastewater processing subsequent to the AS process. Within the PE, a different integrase gene class profile was observed as compared to RS and AS with class 3 integrase genes found to be significantly higher (p < 0.0001) than classes 1 and 2. Integrase GCNs were also normalized against the concentration of genomic DNA extracted from the WWTP samples (Fig. 3B). While the concentrations were lower than the ml1 concentrations, the integrase gene class distribution pattern was similar with class 2 integrase genes being the most abundant in the RS and AS while class 3 genes were the most abundant in the PE. Overall, while significant reductions of integrons were achieved through the wastewater treatment process, the WWTP releases up to 136 million liters of treated effluent daily, which represents 2.4 1013, 2.7 1013, and 1.0 1014 GCNs of class 1, 2, and 3 integrons, respectively, discharged into the Charleston Harbor and likely contributing to the ecosystem integron pool.
This work was supported by the South Carolina Sea Grant Consortium and a Slocum-Lunz Grant No. 21600-KA43. Academic support and scholarship for MIU was granted by an Arnold Fellowship (USC, School of Public Health). Arnold School of Public Health Seed grant was provided for RSN. The authors would like to thank anonymous reviewers for insightful comments and suggestions that enhanced the manuscript. We would also like to thank E.B. Fichot and D.E. Ross for valuable comments to this manuscript, J.D. Hibbert for GIS assistance, and J.W. Daugomah and J.B. West for Charleston Harbor sediment and water sample collection. A special acknowledgment to Dr. Vivian Miao and her laboratory members for providing integrase control strains. We also thank the staff at EnGenCore, LLC for their sequencing expertise, and the Instrument Research Facility (USC, School of Medicine) for use of the iCycler iQ™ Real-Time PCR Detection System. The National Ocean Service (NOS) does not approve, recommend, or endorse any proprietary product or material mentioned in this publication. No reference shall be made to NOS, or to this publication furnished by NOS, in any advertising or sales promotion that would indicate or imply that NOS approves, recommends, or endorses any proprietary product or proprietary material mentioned herein or that has as its purpose any intent to cause directly or indirectly the advertised product to be used or purchased because of NOS publication. References Allen, J., Lu, K., 2003. Modeling and prediction of future urban growth in the Charleston region of South Carolina: a GIS based integrated approach. Conserv. Ecol. 8 (2), 1–2. Andersen, S.R., 1993. Effects of waste water treatment on the species composition and antibiotic resistance of coliform bacteria. Curr. Microbiol. 26 (2), 97–103. Auerbach, E.A., Seyfried, E.E., McMahon, K.D., 2007. Tetracycline resistance genes in activated sludge wastewater treatment plants. Water Res. 41 (5), 1143–1151. Barkovskii, A.L., Green, C., Hurley, D., 2010. The occurrence, spatial and temporal distribution, and environmental routes of tetracycline resistance and integrase genes in Crassostrea virginica beds. Mar. Pollut. Bull. 60 (12), 2215–2224.
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