Pruden Arabi Es t 2012 Reprint

8/13/2019 Pruden Arabi Es t 2012 Reprint

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Correlation Between Upstream Human Activities and RiverineAntibiotic Resistance Genes Amy Pruden,* , , , Mazdak Arabi, , and Heather N. Storteboom

Via Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, U.S.A., 24061Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, U.S.A., 80523

*S Supporting Information

ABSTRACT: Antimicrobial resistance remains a serious and growing human healthchallenge. The water environment may represent a key dissemination pathway of resistance elements to and from humans. However, quantitative relationships betweenlandscape features and antibiotic resistance genes (ARGs) have not previously beenidenti ed. The objective of this study was to examine correlations between ARGs andputative upstream anthropogenic sources in the watershed. sul1 (sulfonamide) and tet (W)(tetracycline) were measured using quantitative polymerase chain reaction in bed andsuspended sediment within the South Platte River Basin, which originates from a pristineregion in the Rocky Mountains and runs through a gradient of human activities. A geospatial database was constructed to delineate surface water pathways from animalfeeding operations, wastewater treatment plants, and sh hatchery and rearing units toriver monitoring points. General linear regression models were compared. Riverine sul1correlated with upstream capacities of animal feeding operations (R 2 = 0.35, p < 0.001)and wastewater treatment plants (R 2 = 0.34, p < 0.001). Weighting for the inverse distances from animal feeding operations alongtransport pathways strengthened the observed correlations (R 2 = 0.600.64, p < 0.001), suggesting the importance of thesepathways in ARG dissemination. Correlations were upheld across the four sampling events during the year, and averaging sul1measurements in bed and suspended sediments over all events yielded the strongest correlation (R 2 = 0.92, p < 0.001).Conversely, a signicant relationship with landscape features was not evident for tet (W), which, in contrast to sul1, is broadly distributed in the pristine region and also relatively more prevalent in animal feeding operation lagoons. The ndings highlightthe need to focus attention on quantifying the contribution of water pathways to the antibiotic resistance disease burden

humans and off er insight into potential strategies to control the spread of ARGs.

INTRODUCTION Antibiotic resistance represents a serious human healthchallenge and threatens the present and future eff ectivenessof antibiotics to treat life-threatening infections. Antibioticresistance has been identi ed as a key factor in emerginginfectious disease.1 The emergence of multiantibiotic resistant superbugs , such as those carrying the New Delhi metal-lobetalactamase-1 blaNDM1 gene,

2 is cause for particularconcern. Antibiotic resistance is encoded by antibioticresistance genes (ARGs), which, as has been well-illustratedin the case of bla

NDM

1 , can be readily shared even among

unrelated bacteria.3 Thus, ideally, strategies for the containmentof antibiotic resistance may benet from a focus directly on the ARGs that confer resistance.

Surface water pathw a y s may represent a key route of dissemination of ARGs.4

6 However, the lack of a denedquantitative relationship between ARGs and human-inuenced watershed features has shed doubt on the importance of suchpathways. Recently, human population density 1 and con-struction of roads to remote villages7 have been demonstratedto contribute to the emergence and spread of antibioticresistant bacteria. It is also known that human activities alter thedistribution and magnitudes of ARGs in various environmental

compartments, including soil,8 10 groundwater,11 surface water,12,13 and sediment.12,13 In particular, animal feedingoperation lagoons and wastewater treatment plants receiv e bothexcreted antibiotics and resistant gastrointestinal ora,14 whilepossessing their ow n distinct microbial ecologies that drivegene exchange,15

17 and thus are prime candidates of interestas nodes of dissemination to the greater environment.4 ,18 21 Although broad patterns of human activity related to ampliedlevels of antibiotic resistant bacteria and ARGs in theenvironment have been noted;7 9 ,11 13 precise sources,activities, and abiotic and biotic phenomena driving dissem-ination have not previously been quantied. Others haveobserv ed clear inuences of human activities on ARG levels inrivers,6 ,12 but the landscape complexity has precludedidenti cation of quantitative relationships.

The South Platte River Basin, including the South Platte(SP) and Cache la Poudre (Poudre) (PR) rivers, represents anideal system for gaining insight into geospatial factors

Received: July 2, 2012Revised: October 4, 2012 Accepted: October 4, 2012

Article

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contributing to the dissemination of antibiotic resistance(Figure 1). In addition to being well-zonated in terms of adjacent urban and agricultural land-use and possessing few tributaries, the PR is characterized by a pristine origin in theRocky Mountains devoid of major human activities.22Metagenomic investigations of other pristine environments,such as Arctic soil,23 ,24 have brought attention to an ancientarray of resistance elements comprising the backgroundantibiotic resistome25 that must be taken into account whenassessing human inuences.5 Thus, in this study, sampling inthe pristine region of the PR provided contrast for identifyinganthropogenic sources of ARGs.

The aim of this study was to evaluate potential correlations between riverine ARG magnitudes and upstream capacities of animal feeding operations, wastewater treatment plants, andsh hatchery and rearing units while taking into account their

spatial distances from river monitoring points. Suspended and bed sediment were sampled spanning river sites classied aspristine (PR0a, PR0b, and PR1), increasingly impacted (PR2,PR3a, PR3b, and PR4), and highly impacted (PR5, SP2, andSP3). Notably, SP receives up to 90% of its ow frommetropolitan Denver wastewater treatment plant discharge. Tocharacterize the relationship between geospatial features and ARGs, an extensive geospatial database was developedincluding locations and capacities of eighty-nine wastewater

treatment plants, one hundred animal feeding operations (fty beef, forty-seven dairy, and three sheep), and three trout shhatchery and rearing units (Figure 1). The database enabledprecise delineation of runoff and stream discharge pathwaysupgradient of the river sampling sites. Quantitative polymerasechain reaction (Q-PCR) was used to directly measure the target ARGs, including extracellular forms and those harbored byunculturable bacteria, a characteristic feature of the vastmajority of environmental microbes.26 The analysis includedfour time points spanning a range of hydrologic and climaticconditions (Supporting Information Figure S1). sul1 waschosen as a tracer of anthropogenic sources based on recent

examination of the watershed, where sul1 was detected by PCR in 100% of wastewater treatment plant ( N = 11) and animalfeeding operation lagoon ( N = 47) samples, but only in 4% of pristine samples ( N = 24).27 To explore the extent to which asimilar correlation may exist for a more broad geographicallydistributed ARG, the tet (W) tetracycline ARG was quantied.tet (W) had previously been observed to most strongly correspond with pristine sites, relative to eleven other tet andsul ARGs investigated.27 It was hypothesized that a signicantportion of the variation in sul1 in river samples could beexplained by upstream capacities of animal feeding operationsand wastewater treatment plants, while tet (W) would not alter with these geospatial factors. Overall, the experimental

Figure 1. Map of the South Platte River Basin, corresponding land cover, and distributions of animal feeding operations (AFOs), wasttreatment plants (WWTPs), and sh hatchery and rearing units (FHRUs). (A) Poudre River (PR) and South Platte River (SP) sampling sit

indicated. (B) Distribution and capacities of AFOs, WWTPs, and FHRUs.

Environmental Science & Technology Article

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approach provided a means to quantitatively assess therelationship between ARGs and human-inuenced watershedfeatures and to compare the behavior of two ecologically distinct ARGs.

METHODSSite Selection and Sample Collection. River sampling

locations were selected prior to the data collection campaign toencompass a gradient of anthropogenic inuences from pristinesites devoid of major human activities, impacted by smallanimal feeding operations, impacted by small wastewatertreatment plants, and heavily impacted by both animal feedingoperations and wastewater treatment plants. Bed andsuspended sediment grab samples were collected from tenriver sites within the South Platte River Basin (Figure 1) onOctober 20, 2006; February 23, 2007; May 22, 2007; andOctober 23, 2007. Sampling dates encompassed hydrologicconditions ranging from high ow to low ow conditions(Supporting Information Figure S1). Activated sludge samplesfrom three conventional wastewater treatment plants andsediment from one sh hatchery and rearing unit within the

watershed were also sampled.Measurement of ARGs. DNA was extracted fromsediments, suspended sediments concentrated onto 0.22 mlters, or sludge samples using an UltraClean Soil DNA Kit

(MoBio Laboratories, Inc.) according to manufacturerinstructions. 16S rRNA genes, sul1 and tet (W) were quantiedin triplicate Q-PCR reactions on a 7300 Real-Time PCR System (Applied Biosystems, Foster City, CA) includingnegative controls and seven point standard curves in eachrun, as described previously.28

Several control measures were taken to ensure the quality of the Q-PCR data. Dilution series were carried out on randomsubsets of each sample type (10% of samples) to identify theoptimal dilution for minimizing threshold cycle suppression by inhibitors for that sample type (typically 1:10 to 1:50). To verify positive detections, melt curve analysis was included inevery run and a subset of Q-PCR products (10% selected atrandom, plus any samples with anomalous melt curves) werefurther analyzed by gel electrophoresis to verify expected size.Measurements were excluded from further analysis if they didnot pass these screening tests. To validate the quantitative valueof the data, the template amplication efficiencies of positivesamples w ere compared to those of standards using the LinRegapproach 29 and were not found to be signicantly diff erent. Variance among triplicate estimates in gene quantities greaterthan 20%, or failure of one or more of the triplicates to amplify,triggered reanalysis of that sample. Two or more positivedetections were scored as positives and the mean value of allpositive replicates were employed in subsequent analyses, ARGs were normalized to 16S rRNA genes throughout thisstudy.

Geospatial Analysis. For each river site, the boundary of the corresponding drainage area was delineated using terrainanalysis with the ArcHydro toolbox in ArcGIS version 9.3(ESRI Inc., Redlands, CA), which entailed processing of a 30-mdigital elevation model (DEM) from national elevation data set(NED) of the U.S. Geological Survey (USGS). The locationsand capacities of animal feeding operations, wastewatertreatment plants and sh hatchery and rearing units withineach drainage area were identied from the Envirofacts Warehouse tool available from the EPA s Web site (http:// www.epa.gov/enviro/), queried to obtain a list of National

Pollutant Discharge Elimination System permits issued.Because Colorado law does not require animal feedingoperations to obtain permits, beef feedlots and dairies werecon rmed within the watershed via satellite imagery andmanually digitized as polygons using the Environmental Risk Assessment Management System (eRAMS) tool (Departmentof Civil Engineering, Colorado State University) availableonline: http://erams9.engr.colostate.edu. Polygon area wascalculated using ArcGIS, version 9.2 (ESRI, Inc., RedlandsCA). Surface water distances along overland ow paths,irrigation ditches, and streams from upstream animal feedingoperation, wastewater treatment plant, and sh hatchery andrearing unit sources were also determined using terrain analysis.Geospatial drivers considered were (a) capacity of upstreamanimal feeding operations in number of animals, (b) capacity of upstream wastewater treatment plants in million gallons perday of effluent discharge (a proxy for human populationdensity), (c) capacity of upstream sh hatchery and rearingunits in number of sh, (d) overland ow distance fromupstream sources to the river sampling site in kilometers, and(e) channelized ow distance from upstream sources to theriver sampling site in kilometers.

Regression Analysis. The quantities of sul1 and tet (W)genes (normalized to 16S rRNA genes) were modeled as afunction of capacities of upstream wastewater treatment plants,animal feeding operations, and sh hatchery and rearing unitsas the explanatory variables using a GLR model with log-transformed response variables [i.e., sul1 or tet (W)]. Anexhaustive set or GLR models comprising various combinationsof the capacities of animal feeding operations, wastewatertreatment plants, and sh hatchery and rearing units, with and without inverse distance weighting, was evaluated. Akaikeinformation criteria were used to evaluate the trade-off between bias and variance, determine the relative goodness of t, andselect the most appropriate model. The lack of t F -test wasused to test the overall signicance of the regression modelsand whether the GLR functions were appropriate responsesurfaces. Models with P -values less than 0.05 were judgedsigni cant. Coefficient of multiple determination (R 2) andadjusted coefficient of multiple determination (Adj R 2) werecomputed to judge and compare the strength of the GLR models. The Shapiro Wilk test was used to examine thenormality of the error terms. The constancy of the error variance (i.e., homoscedasticity) was assessed using theBrownForsythe test statistic. The randomness of the errors was tested using the Durbin Watson test. The variancein ation factor (VIF) was used to identify multicolinearity inthe matrix of predictor variables for each GLR model. Models with the largest VIF value among all predictor variable in excesof 10 or mean VIF values considerable larger than 1 were

considered inappropriate for explaining the relationship between ARGs and geospatial factors. The correlation between ARGs and geospatial variables was investigated using a GLRmodel, with the log transformed quantities of sul1 and tet (W)normalized to 16S rRNA genes as response variables and theinverse distance weighted capacities of upstream wastewatertreatment plants, animal feeding operations, and sh hatchery and rearing units, as the explanatory variables.

RESULTSRelationship Between sul 1 and Landscape Features. A

striking trend of sul1 ampli cation was observed from pristineregions to downstream areas highly impacted by human


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activities (Figure 2). To explore correlations between landscapefeatures and ARGs, forty general linear regression (GLR)models were evaluated, which are described in SupportingInformation Table S1. Key GLR models that best illustrated therole of geospatial factors in the dissemination of ARGs are

summarized in Table 1. It was noted that sul1 displayed astrong and signicant relationship with upstream animalfeeding operation capacities weighted for inverse distancesalong surface water pathways, including overland ow, ditches,and stream segments [GLR model # 3 F = 64.4, P < 0.001, df . =

Figure 2. ARGs in the South Platte River (SP) and the Poudre River (PR). (A) Sites classied according to relative level of upstream human impact, with ARGs in bed and suspended sediments averaged over the four sampling dates and plotted according to upstream distance from the mosimpacted SP3. (B) Boxplot of ARG measurements within each classication group, including both suspended and bed sediment measurements.Observed mean of sul1/16S rRNA genes were signicantly diff erent among the classes (ANOVA, F = 6.3, P = 0.0044, df = 39).

Table 1. Key General Linear Regression Models Illustrating ARG Transport in the Watersheda

a AFO = Animal feeding operation. WWTP = Wastewater treatment plant. See Supporting Information Table S1 for full list of GLR modelsinvestigated.

Figure 3. General linear regression (GLR) model with log transformed sul1/16S rRNA gene magnitude response variable with (A) upstream inversedistance-weighted (IDW) animal feeding operation (AFO) animal counts predictor variable (F = 64.4, P < 0.001, df = 38, R 2 = 0.63); (B) upstream AFO animal counts predictor variable (F = 20.1, P < 0.001, df = 38, R 2 = 0.35); and (C) upstream IDW wastewater treatment plant (WWTP)capacity predictor variable (F = 19.2, P < 0.001, df = 38, R 2 = 0.34). Each data point represents the average of bed and suspended sediment ARGmagnitude at a sampling site (Figure 1). Each data point represents the average of triplicate Q-PCR measurements of a single DNA extract. The slines represent the GLR model and the dashed lines represent 95% condence intervals.


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38, R 2 = 0.63] (Figure 3 A). Animal feeding operation capacity upstream of each sampling location by itself was a predictor of sul1, but not as strong (GLR model # 1 F = 20.1, P < 0.001, df =38, R 2 = 0.35) (Figure 3B). The analysis also indicated a rise insul1 with increasing upstream wastewater treatment plantcapacity (GLR model #5 F = 19.2, P < 0.001, df = 38, R 2 =0.34) (Figure 3C), but weighting for inverse distances did notimprove model performance (GLR model #6) (SupportingInformation Table S2). Capacities of trout sh hatchery andrearing units did not alter sul1.

Eff ect of Normalizing Across Seasons and HydrologicRegimes. To normalize the eff ect of variation in season andhydrologic regime and emphasize the inuence of geospatial

factors, ARG measurements were averaged between the bedand suspended sediment and across the four sampling events.This analysis yielded a very strong correlation between riverinesul1 quantities and inverse distance weighted capacities of upstream animal feeding operations and wastewater treatmentplants (GLR model # 9 F = 40.2, P < 0.001, df = 7, R 2 = 0.92)(Table 1 , Figure 4 A, Supporting Information Table S3). Thisindicates that geospatial features control the variability of sul1 inthe watershed under varying climatic and hydrologic con-ditions.

Sampling Dates, Matrices, and Correlation withAntibiotics. sul1 correlations with upstream capacities of animal feeding operations and wastewater treatment plants were examined over each individual sampling date in both

sediment and water matrices. The correlations were consis-tently upheld, except February 2007 bed sediment and October2007 suspended sediment (Supporting Information Tables S4and S5). Furthermore, a consistent increasing trend in themagnitude of sul1 was observed for three of the four samplingevents from upstream to downstream sites (SupportingInformation Figure S2). Although the same overall trend wasmaintained in February 2007, sul1 bed sediment measurements were nearly 2 orders of magnitude greater than the otherevents. Correlations of sul1 with antibiotics previously measured at the river sites 30 was of interest as an indicatorof cotransport and/or selection of ARGs. A strong correlation was identied between sul1 and the total of six sulfonamides

measured previously (R 2=0.65, 0.94 for water and sediments,respectively) (Supporting Information Figure S3).

Relationship Between tet (W) and Landscape Featuresand Antibiotics. In contrast to sul1, tet (W) did not exhibit anincreasing trend with downstream distance (Figure 2C), anddid not correlate with upstream capacities of animal feedingoperations or wastewater treatment plants (SupportingInformation Table S6), even when normalized across seasonand hydrologic regime (Figure 4B; Supporting InformationTable S7). However, signicant correlations were noted in twoindividual samplings: February 2007 in the bed sediment(Supporting Information Table S8) and October 2007 in thesuspended sediments (Supporting Information Table S9).

Thus, tet (W) may at times also be subject to signicanttransport in the watershed. Tet (W) exhibited no correlation(water) or a negative correlation (bed sediment) with the totalof six tetracycline antibiotics measured previously 30-(Supporting Information Figure S3).

Conceptual Mass Balance Model and Ratio of tet (W):sul 1. The relative quantities of sul1 and tet (W) werecompared in a subset of animal feeding operations and wastewater treatment plants in the watershed to aid in theconstruction of a conceptual ARG mass balance model (Figure5 , see Supporting Information Table S10). Previously publishedmagnitudes of sul1 and tet (W) were examined in four dairy andtwo beef cattle lagoons within the South Platte River Basin 31and additional measurements of these ARGs were made at

three wastewater treatment plants. It was noted that tet (W) washigher than sul1 on average in upstream animal feedingoperation lagoon and pristine environments, while sul1 washigher in wastewater treatment plants and the sh hatchery andrearing units, suggesting that the tet (W):sul1 ratio may beindicative of the relative contributions of these ARG sources.Plotting these ratios spatially with respect to the SP and PR monitoring points revealed a pattern of predominant animalfeeding operation inuence consistent with the GLR models(Figure 5). Remarkably, the ratio shifts in favor of sul1 precisely when wastewater treatment plant inuence becomes prominentat PR3b, before shifting back to a ratio dominated by tet (W) atthe animal feeding operation-dominated SP2 and SP3.

Figure 4. Measured and simulated ordinary least-squares data for the full general linear regression (GLR) models. GLR model (log( y) = aX + )reported in Table 1 , model 9. ARG measurements averaged between suspended and bed sediment samples over four events served as res variables and inverse distance-weighted (IDW) upstream capacities of animal feeding operations (AFOs) and wastewater treatment (WWTPs) as explanatory variables. (A) sul1 / 16S rRNA genes. (B) tet (W) / 16S rRNA genes.


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DISCUSSION Antibiotic resistance represents a major human healthchallenge, and despite diligent eff orts in improving antibioticuse practices and hygiene in the clinical realm, rates of antibiotic resistance continue to increase.32 Infections originat-ing outside the clinical realm are also increasing,33 whichhighlights the need for innovative strategies for minimizing thespread of resistance. Overall, the results bring to light the waterenvironment as an important front in the battle againstantibiotic resistance. The results of this study unambiguously demonstrate a quantitative relationship between upstreamcapacities of wastewater treatment plants and animal feedingoperations and sul1 in riverine environments. The fact thatcorrelations were strengthened when upstream capacities were weighted for inverse distance between these features along

overland ow paths, irrigation ditches, and stream segmentssuggests that these are important pathways for the dissem-

ination of ARGs. Furthermore, averaging ARG magnitudesacross the four sampling events and between the water and bedsediment matrices resulted in a very strong correlation (R 2 =0.92). Considering that ows, and thus advection of ARGs, will vary signicantly with season, the strong correlation achieved when averaged over the seasons highlights the dominantin uence of geospatial factors relative to variation in hydrologicregime.

It is proposed that a complex interplay of processes governfate and transport of ARGs in the watershed. Figure 5 illustratesa framework for conceptualizing ARG mass balance in the watershed and the inuence of abiotic (e.g., advection,adsorption, dilution, photolysis) and biotic (e.g., selection,

Figure 5. Conceptual mass balance model of ARGs reaching impacted South Platte River Basin sites. Fate and transport processes thacontribute to amplication, attenuation, or persistence of ARGs upstream from sampling sites are indicated. Primary dissemination mechanconsistent with selection of ARGs by ambient antibiotics or other factors versus direct ARG transport are also noted. The average tet (W) and sul1magnitudes and their ratios in the animal feeding operation (AFO) cattle lagoons were determined from a concurrent study 31 as described inSupporting Information Table S10. Wastewater treatment plant (WWTP) magnitudes were determined in this study. Fish hatchery and rearing uare not shown as they did not signicantly contribute to the models.


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ampli cation, persistence, and attenuation) processes and theexpected characteristics. Consistent with this model, weightingupstream capacities of wastewater treatment plants with inversedistance did not improve correlations with sul1, likely becauseattenuating processes are less of an inuence for point-sources(e.g., wastewater treatment plants) than along ow paths of nonpoint sources (e.g., animal feeding operations).

The distinct distribution of sul1 versus tet (W) in the SouthPlatte River Basin provides new insight into the underlyingphenomena driving amplied ARGs in human-impactedenvironments. If the processes driving the correlation between ARGs and landscape were solely abiotic, then tet (W) and sul1should have yielded similar overall trends, which was not thecase. This highlights inherent diff erences in the biotic responsesof these two ARGs to the environment. An obvious distinction between tet (W) and sul1 is that sul1 is carried within the 3conserved region of class 1 integrons, which adeptly transferamong a broad range of host bacteria, including both Grampositives and Gram negatives.34 Such an association may facilitate the establishment of sul1 within native environmental bacterial populations and enhance its persistence. Theassociation of sul1 with class 1 integrons also subjects it togreater coselective action by other antibiotics or pollutants,such as heavy metals, which may act directly on genes present within cassette regions. Collectively, these factors couldcontribute to sul1 maintaining the strong correlations withlandscape features observed in this study. Although tet (W) has been estimated to be the third most widely distributed tet ARGand also tends to be associated with promiscuous geneticelements, particularly conjugative transposons,35 the resultssuggest that its promiscuity may pale in comparison with that of sul1. Indeed, class 1 integrons are recognized as the most widespread among clinical isolates and most known ARGcassettes belong to this class.34 While the present study focusedon two model ARGs, future studies would benet fromapplication of metagenomic approaches to more broadly capture the array of ARG behaviors in the watershed.

It was observed that the February sediment sul1 magnitudes were about an order of magnitude higher than the other events.Interestingly, previous researchers noted that the highestconcentrations of all six sulfonamides and six tetracyclinesmonitored in the Poudre river also occurred in February 30(Supporting Information Table S11). February is typically characterized by low ow at the Poudre Canyon mouth, whiledownstream ows are augmented by irrigation return ows(Supporting Information Figure S1). This may contribute toantibiotic and ARG transport, while incurring less antibioticdilution from snowmelt,30 enhancing likelihood of selection of resistant strains. The strong correlation between sul1 andsulfonamides measured previously (Supporting InformationFigure S3) suggests that selective pressures may have been atplay (Figure 5), w hich is possible even at subinhibitory concentrations.4 ,36,37 Intriguingly, tet (W) and tetracyclinesactually exhibited a negative correlation, clearly indicating thatthese two entities have distinct, and surprisingly evenantagonistic, transport behavior in the environment. This resultdemonstrates that antibiotic and ARG transport are not alwaysdirectly linked and illustrates the utility of devoting specicattention to the transport of ARGs as the contaminants of interest.

In this study, the ARG data presented were normalized to thecorresponding number of 16S rRNA gene copies, which arehousekeeping genes present in all bacteria. Interestingly, the

signi cance of all models examined in this study werestrengthened when applied to the normalized ARG data,relative to the absolute measurements (data not shown). Thissuggests that the relationship between landscape and ARGstruly was best reected in the gene ratios. Gene ratios serve as aproxy for the proportion of bacteria carrying ARGs, although itis an imperfect indicator because bacteria range in the numbersof 16S rRNA gene copes and ARG copies that they carry.Important to note is that 16S rRNA genes did vary among theDNA extracts, tending to be lower in concentration in thepristine samples and increasing downstream by factors rangingfrom about 2 to 10 . Because normalizing ARGs by thesmaller number in pristine samples acted to boost thenormalized ARG calculation, normalizing to 16S rRNA genes was a conservative approach to tracking relative inuence of human land-use on ARGs. Normalizing to 16S rRNA genesalso likely aided in correcting for minor variations in DNAextraction efficiency, assuming that the efficiencies of extractionof ARGs and 16S genes were comparable.

The present study suggests that animal feeding operationsare a more dominant source of sul1 to the PR and SP, withmodest contribution from wastewater treatment plants. Thisriver system was recently examined using a qualitative molecular signatures approach, which indicated that ARG molecularsignatures were more similar to those of wastewater treatmentplants at all impacted sites, except SP3, which aligned withanimal feeding operations.38 The ARG molecular signatureapplied in the previous study was based solely on tet ARGs[combined tet (W) phylogenetics and frequency of detection of tet (C), tet (E), and tet (O) (wastewater treatment plant) versustet (H), tet (Q), tet (S) and tet (T) (animal feeding operation)]and did not consider sul ARGs. This suggests that source-tracking approaches employing tet ARGs may be biased toward wastewater treatment plants relative to animal feedingoperations. Such a bias would be particularly interesting,given that tet (W) was observed to be dominant relative to sul1in the cattle lagoons in this study. It is suggested that tet (W)may be more sensitive than sul1 to attenuating processes, whichare of greater inuence when emanating along ow-paths fromnonpoint source animal feeding operations. Nonetheless, tet ARGs persist in riverine environments and remain traceable totheir original sources.27 Overall it is suggested that standardizedapproaches for tracking anthropogenic sources of ARGs will bene t from consideration of an array of ARGs representing various classes, horizontal gene transfer capabilities, and relativdistribution in the background. The need for such a method isreceiving increasing attention4 ,5 ,20 and could potentially beaddressed with metagenomic approaches.

This study is the rst to reveal a quantitative relationship between animal feeding operation and wastewater treatmentplant sources and riverine ARG magnitudes. The ndingshighlight the importance of proximity and hydrologic transportpathways between animal feeding operations and streams asdrivers of ARG dissemination. It is expected that dominantprocesses governing ARG transport vary across watersheds,particularly with respect to regional climactic conditions. Also,the extent of antibiotic use, relative hospital inuence, etc., will vary widely with respect to regional and local factors.Therefore, the relative inuence of animal feeding operationsand wastewater treatment plants observed in this study cannot be directly extrapolated to other watersheds. Likewise, it isimportant to point out that the sh hatchery and rearing unitspresent in this watershed, which did not have measurable


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in uence on riverine ARGs, were intended for the rearing of trout stocks for game. Thus, they were not representative of intensive aquaculture ponds that have attracted attention assources of ARGs in other studies.39 Antibiotics also likely play an even stronger selective role in extremely antibiotic-pollutedenvironments, such as rivers in India where exceptional levels of antibiotics, AR Gs, and gene transfer elements have beendocumented.40 Similar to sul1, bla

NDM

1 is also associated w ith a

class 1 integron, has been observed to be highly mobile,2 ,34 andalso has recently been found in human-impacted surface waters.41 This suggests that sul1 may serve as an appropriatesurrogate foreshadowing the transport of resistance elements of imminent human concern and provide an important baselineunderstanding of ARG transport in watersheds. Furthermore,sulfonamide and tetracycline antibiotics themselves, continue toserve as a front-line of defense against methicillin-resistantStaphylococcus aureus infections.42 Advanced understanding of the human antibiotic resistome (e.g., ref 14) will also furtheradvance knowledge of human sources and receptors. Thendings described in this study suggest that appropriate actions

are warranted at wastewater treatment plants and animalfeeding operations to curtail the dissemination of ARGs to the water environment. Potential options include vigilant manage-ment of runoff from animal feeding operations and moreaggressive disinfection measures that remove or destroy ARGsat wastewater treatment plants.43

ASSOCIATED CONTENT*S Supporting InformationFigures summarizing river ow conditions (Figure S1),individual sampling dates (Figure S2), and correlations withantibiotics (Figure S3), and tables reporting GLR models(Tables S1) and the sul1 results for all bed and sedimentmeasurements individually (Table S2), both averaged over allsample dates (Table S3), bed sediment (Table S4), and

suspended sediment (Table S5), as well as summaries of thesame information for tet (W) (Tables S6S9), tet (W)/ sul1ratios (Table S10), and previously reported antibiotic data(Table S11). This material is available free of charge via theInternet at http://pubs.acs.org.

AUTHOR INFORMATIONCorresponding Author* Address: Environmental and Water Resources Program, ViaDepartment of Civil and Environmental Engineering, 418Durham Hall, Blacksburg, VA 24061. Phone: (540) 231-3980.Fax: (540) 231-7916. E-mail: [email protected] Contributions

These authors contributed equally to this work.NotesThe authors declare no competing nancial interest.

ACKNOWLEDGMENTSFunding for this research was provided by the Colorado WaterResources Research Institute, the USDA Agricultural Exper-imental Station at Colorado State University, the Virginia TechInstitute for Critical Technology and Applied Science AwardTSTS 11-26, and the National Science Foundation CBETCAREER award # 0547342. The ndings do not represent the views of the funding sponsors.

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