Science of the Total Environment 580 (2017) 1205–1213

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Short Communication

Shifts in microbial community structure and function in surface watersimpacted by unconventional oil and gas wastewater revealedby metagenomics

N.L. Fahrenfeld a,⁎, Hannah Delos Reyes a, Alessia Eramo a, Denise M. Akob b,Adam C. Mumford b, Isabelle M. Cozzarelli b

a Rutgers, The State University of New Jersey, Civil and Environmental Engineering, 96 Frelinghuysen Rd, Piscataway, NJ 08504, United Statesb U.S. Geological Survey, National Research Program, 12201 Sunrise Valley Dr., Reston, VA 20192, United States

H I G H L I G H T S G R A P H I C A L A B S T R A C T

• Microbial communities change down-stream from a wastewater disposal fa-cility.

• Deltaproteobacteria andMethanomicrobia are in higher abun-dance in affected sediments.

• Increases in genes for dormancy andsporulation were found downstreamfrom the facility.

• Select efflux pump genes increasedownstream but not total antibiotic re-sistance genes.

E-mail address: nfahrenf@rutgers.edu (N.L. Fahrenfeld

http://dx.doi.org/10.1016/j.scitotenv.2016.12.0790048-9697/© 2016 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 30 September 2016Received in revised form 12 December 2016Accepted 12 December 2016Available online 27 December 2016

Editor: D. Barcelo

Unconventional oil and gas (UOG) production produces large quantities of wastewater with complex geochemistryand largely uncharacterized impacts on surface waters. In this study, we assessed shifts in microbial communitystructure and function in sediments andwaters upstreamanddownstream fromaUOGwastewater disposal facility.To do this, quantitative PCR for 16S rRNA and antibiotic resistance genes alongwithmetagenomic sequencingwereperformed. Elevated conductivity and markers of UOG wastewater characterized sites sampled downstream fromthe disposal facility compared to background sites. Shifts in overall high level functions and microbial communitystructure were observed between background sites and downstream sediments. Increases in DeltaproteobacteriaandMethanomicrobia and decreases in Thaumarchaeotawere observed at downstream sites. Genes related to dor-mancy and sporulation and methanogenic respiration were 18–86 times higher at downstream, impacted sites.The potential for these sediments to serve as reservoirs of antimicrobial resistance was investigated given frequentreports of the use of biocides to control the growth of nuisance bacteria in UOG operations. A shift in resistance pro-files downstream of the UOG facility was observed including increases in acrB andmexB genes encoding for multi-drug efflux pumps, but not overall abundance of resistance genes. The observed shifts in microbial communitystructure and potential function indicate changes in respiration, nutrient cycling, and markers of stress in a streamimpacted by UOG waste disposal operations.

© 2016 Elsevier B.V. All rights reserved.

Keywords:Hydraulic fracturingDormancy and sporulationAntibiotic resistance genesBiocidesSediment

n Rd., Piscataway, NJ 08854, United States.

⁎ Corresponding author at: Rutgers, The State University of New Jersey, 96 Frelinghuyse ).

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1. Introduction

Recent technological advances combining horizontal drilling withhydraulic fracturing have led to a boom in the development of uncon-ventional oil and gas (UOG) resources from low permeability forma-tions (Engle et al., 2014). UOG resources include shale gas, coal bedmethane, and tight oil. UOG production results in large volumes ofwastewater (Gregory et al., 2011), and there are potential environmen-tal risks associated with holding, transporting, and disposing of thesefluids. Improper disposal, treatment (Ferrar et al., 2013; Hladik et al.,2014; Volz et al., 2011) and accidental releases remain a concern. UOGwastewater is a complex mixture with high total dissolved solids(TDS) (Fontenot et al., 2013; Gaudlip and Paugh, 2008; Lester et al.,2013; Murali Mohan et al., 2013a; Murali Mohan et al., 2013b;Olmstead et al., 2013; Rowan et al., 2011b; Vidic et al., 2013; Volzet al., 2011; Warner et al., 2011), naturally occurring radioactive mate-rials (Rowan et al., 2011a; Rowan et al., 2015), organic (Akob et al.,2015; Orem et al., 2014; Strąpoć et al., 2011; Volz et al., 2011), andheavymetal compounds. In the eventwastewater and production fluidsare released to the environment [e.g., (Cozzarelli et al., in press; Laueret al., 2016)] the impact of these chemical components, including addi-tives such as biocides used in hydraulic fracturing fluids (Kahrilas et al.,2015), remains unclear.

The complex biogeochemistry of wastewater generated during UOGproduction is underscored by shifts in microbial communities and or-ganic and inorganic chemical composition observed across the periodof well development (Cluff et al., 2014; Murali Mohan et al., 2013a;Orem et al., 2014; Rowan et al., 2015). Over time, there is an increasein the relative abundance of facultative anaerobes in UOG wastewaterand microorganisms that can tolerate high salt concentrations and bio-cides (Cluff et al., 2014; Liang et al., 2016; Murali Mohan et al., 2013a).Viable H2S-producing, fermenting, and methanogenic microorganismshave been cultured from UOG wastewater (Akob et al., 2015; Dalyet al., 2016; Liang et al., 2016). Interestingly, these microbes were culti-vable despite the use of biocides to control their growth during UOGproduction (Johnson et al., 2008). These shifts in microbial communityhave been associated with microbial functional changes. Increasesacross time in sporulation, dormancy, and stress response and shifts inmetabolism of iron and sulfur have been reported (Murali Mohanet al., 2014).

Releases of UOG wastewater to the environment could present anuncharacterized potential secondary impact of the UOG water cycle bypromoting microbial community functional changes in impacted envi-ronments. For example, releases of high salinity UOG wastewater intofreshwater streams would be expected to alter microbial communitystructure and function, thereby affecting nutrient cycling. Increases insalinity due to deicing of roads have been shown to disrupt nitrogen cy-cling, likely due to alterations ofmicrobial communities in roadside soilsand surface waters (Green and Cresser, 2007; Green et al., 2008). UOGwastewater also contains microbial communities (Akob et al., 2015;Cluff et al., 2014; Daly et al., 2016; Liang et al., 2016; Murali Mohanet al., 2013b)whichmay thrive in impacted environments and are likelyto be adapted to and suited for biodegradation of the organic com-pounds in wastewater.

Of interest is the impact of chemicals used to enhance oil and gasproduction on changes in metabolism, stress, and other toxic responsesresulting from environmental releases. Biocides are frequently used inUOG operations to control corrosion, souring, and biofouling and theirpotential for selecting for antibiotic resistant bacteria has been raisedas a potential secondary impact (Kahrilas et al., 2015). Antibiotic resis-tance is a pressing public health issue and links between environmentalreservoirs of resistance and clinical infections have been observed(Forsberg et al., 2012). A variety of biocides with different mechanismsof actionmay be used in UOGproduction including lytic quaternary am-monium/amine compounds (QAC), electrophilic compounds such asglutaraldehyde, and oxidizers such as peracetic acid (Kahrilas et al.,

2015). Recent investigations associated (1) QAC exposure in river sedi-ments with increases in metagenomic signatures of biodegradationgenes, efflux pumps, cell envelopemodification, chaperones, and oxida-tive stress (Oh et al., 2013), and (2) glutaraldehyde exposure of bacterialisolates in simulated produced waters with osmotic stress, energy pro-duction and conservation,membrane integrity, and protein transport inthe transcriptome (Vikram et al., 2014).

This study aimed to determine (1) if inputs of UOGwastewater intoa surface water resulted in shifts in microbial community structure andfunctional potential in the community metagenome; and (2) whetherimpacts led to elevated levels of antibiotic resistance in surface waterand sediments. To meet these aims, surface water and bed sedimentsfrom an impacted stream adjacent to a Class II underground injectioncontrol (UIC) facility in West Virginia were analyzed usingmetagenomic sequencing and quantitative PCR (qPCR). Impacts to thestreamwere identified using chemical analyses and published previous-ly (Akob et al., 2016). The Class II UICwell is used to dispose ofwastewa-ter fromUOG production, including wastewater from shale gas and coalbed methane wells; additional details about the disposal facility can befound in Akob et al. (2016) and the endocrine disrupting activities ofthese waters are described in Kassotis et al. (2016). Results presentedin this study provide insight into the impacts of UOG wastewater onstream microbial community structure and function.

2. Materials and methods

2.1. Sampling

In June 2014, water and bed sediment samples were collected fromtributaries of Wolf Creek in West Virginia, USA, including an unnamedtributary that runs through the UIC disposal facility and a backgroundsite in a separate drainage (Fig. 1A). The disposal facility includes thedisposal well, which injects wastewater to 792.5 m below surface,brine storage tanks, an access road, and (formerly) two small, lined im-poundment ponds,whichwere used for temporary storage ofwastewa-ter to allow for settling of particulates prior to injection. The pondsoperated from 2002 to spring 2014 when they were removed and thearea re-contoured. A detailed site description is provided in Akob et al.(2016) including information on the production wells contributingwaste to this facility. No records of pre-treatment activities are available.

Four sites were sampled along the stream that runs through the dis-posal facility: up-gradient, background Site 4,mid Site 6 (adjacent to theinjectionwell), and down gradient Sites 3 and 7 (downstream from for-mer impoundment ponds) (Fig. 1 and Table 1). A stream in a separatedrainage (“background drainage”, Site 2) with no known oil and gaswastewater inputs was also sampled to provide an additional control(Table 1, Fig. 1). Both water and sediment were collected at each sam-pling site.

Water sampleswere collected in sterile, one-liter amber glass bottlesby submerging bottles, filling completely, and capping with minimalheadspace. A duplicate biological replicate sample was collected atSite 3 and processed separately as an internal control (Table 1) forboth sediment and water samples. Water samples were stored on icein the field, shipped in coolers overnight to Rutgers where theywere fil-ter concentrated [0.22 μm, mixed cellulose ester (Millipore, Billerica,MA)], then stored at −20 °C for further analysis. Sediment samples(~50 mL) were collected using aseptic technique from the upper 5 cmof the streambed and frozen on dry ice in the field and during shipping.Chemical analyses on water and sediment samples are described inAkob et al. (2016). Water was analyzed for alkalinity, cations, anions,strontium, oxygen and hydrogen isotopes, nonvolatile dissolved organiccarbon (NVDOC), trace inorganic elements, and disinfection byproducts.Sediment was analyzed for carbon, nitrogen, and sulfur elemental anal-ysis, Fe speciation, and total inorganic elements. Sample collection waslimited due to the study area being located on private property.

Fig. 1. a. Location of study area and b. samplingmapofUOGwastewater facilitywastewater injectionwell and the former impoundment ponds (outlined in yellow). Brine storage tanks arealso shown and circled in purple. Sampling site labels include conductivity data.

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2.2. Microbial analyses

DNA was extracted from filter concentrated water samples(~500 mL) and homogenized sediment samples (~0.5 g, wet weight)using a FastDNA Soil Spin Kit (MP Biomedicals, CA, USA) according tomanufacturer instructions. Duplicate to quintuplet extractswere pooledfrom sediments and submitted for Illumina NextSeq500 sequencing to

Table 1Field parameters, non-volatile dissolved organic carbon (NVDOC) andmajor anion and cation coa stream adjacent to a UOG wastewater disposal facility. Site locations are indicated in Fig. 1; D

Sample Type, location Dups + blanks p

Site 2 Background, separate drainage 6Site 4 Background, upstream from disposal facility 6Site 6 Adjacent to the injection well shed 6Site 7 Downstream from former impoundment ponds Dup. 6Site 3 Downstream from the disposal facility Dup. + field blank 6

obtain sufficient DNA (~200 ng) (Waksman Genomic Core Facility,Rutgers). Paired-end (150 bp) sequencing was performed and generat-ed 96 million reads over three separate runs of the same plate(Table S2). Duplicate biological replicate samples collected from Site 3(named Site 3 and Site 3d) were processed separately. Sequenceswere analyzed using the MG-RAST pipeline (Meyer et al., 2008) andpooled following analysis. Pipeline options including removal of

ncentrations ofwater samples collected in June2014 in tributaries ofWolf Creek, includingup. refers to a duplicate field sample. Data courtesy of Akob et al. (2016).

H Conductivity(μS/cm)

NVDOC(mg/L)

Cl−

(mg/L)Na+

(mg/L)Ba+

(mg/L)Field Fe II(mg/L)

.51 109 1.42 1.70 7.02 95 0.1

.47 74.0 1.13 0.88 6.96 136 0.2

.85 82.0 2.20 1.76 6.86 110 0.8

.36 416 2.49 115 63.4 653 8

.09 379 3.24 119 56.0 594 3.5

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artificial replicates produced by sequencing artifacts (Gomez-Alvarezet al., 2009), dynamic trimming using a modified Dynamic Trim (Coxet al., 2010) for sequences with 5 bp below a 15 phred score. Gene call-ing was performed using FragGeneScan (Rho et al., 2010). Taxonomicclassifications of sequences identified in the metagenomes were per-formed on sequences classified by the lowest common ancestor(Huson et al., 2007) with maximum E-value cutoff of 10−5, minimumpercent identity 60%, and minimum alignment length cutoff of 15amino acids. After pooling sequences from the three runs, sequenceswere sub-sampled randomly (N = 1,658,437 for Bacteria, N = 20,498for Archaea) using a custom bootstrap in R to provide an equal numberof sequences for comparing community structure between samples.Proteins were annotated using MG-RAST SEED subsystem hierarchicalclassification (max E-value cutoff 10−5, minimum percent identity60%, and minimum alignment length cutoff of 15 amino acids) forLevel 1–3 functions as defined by SEED and pooled over the three runs(Overbeek et al., 2005). SEED provides a curated hierarchy for annota-tions: Level 1 is the highest classification for subsystems related to astructure (e.g., cell wall) or functional process (e.g., respiration, stressresponse), Level 3 is similar to a KEGG pathway, and Level 4 is the actualfunctional assignment. Relative abundance was determined by normal-izing to total protein annotations for a given sample and these valueswere compared to those from background Site 2, which was located ina separate drainage.

To further investigate the presence of ARG, genes called as proteinsin MG-RAST pooled over the three runs were queried against the Anti-biotic Resistance Genes Database (ARDB) (Liu and Pop, 2009) usingBlastX with an E-value cutoff of 10−5 (Yang et al., 2013). The thresholdfor amino acid identity was ≥90% and sequence alignment set to ≥25amino acids (Kristiansson et al., 2011; Zhang et al., 2011). Resulting se-quences were normalized to total clean reads (sequences passing qual-ity control which included dereplication and trimming describedabove) per sample and reported as parts per million (ppm, Table S2).Three sequencing runs were performed for each sample and joinedprior to data analysis. Sequences are available under accession numbers4606751–4606762, 4614547–4614552, and 4635906–4635911 in theMG-RAST database.

qPCR was performed for select antibiotic resistance genes (ARG)(acrB, sul1, sul2, ermF, tet(G), tet(O)) on diluted (1:100) water and sed-iment DNA extracts using a SybrGreen protocol (Supplementary data;Table S1). All qPCR standard curves were constructed from 10-fold seri-al dilutions of cloned genes ranging from 108 to 102 gene copies per μL.Samples were analyzed in triplicate (technical replicate) with a stan-dard curve and negative control included in each run. Details on qPCRprimers and thermocycling conditions are presented in Table S1.

Results were analyzed with Primer 6 statistical software (PrimerE,Ivy Bridge, UK) and visualized with ggplot2 (Wickham, 2009) from Rstatistical software (R Core Team, 2013), SigmaPlot (Systat Software,Inc., San Jose, CA), and Venny (Oliveros, 2007). qPCR values were com-pared between unimpacted (Sites 2 and 4), minimally impacted Site 6and impacted sites (Sites 3 and 3d, 7) using a Wilcoxon test. Correla-tions between log-normalized gene copy numbers from themetagenomic sequencing and conductivity were tested using a Spear-man rank test. Hierarchical clustering analysis usingBray-Curtis similar-ities was performed on log(X + 1) transformed ARG, bacterialcommunity, and Archaeal community abundance data from themetagenomic sequencing and significantmultivariate structurewas de-termined using a similarity profile (SIMPROF, Primer 6) test. Compari-sons of (a) relative abundance of Archaeal phyla and (b) metagenomicARG annotations normalized by clean reads between unimpacted anddownstream sites was performed by a Kruskal Wallis test followed bya post-hoc pairwise t-test with a Bonferroni correction for multiplecomparisons. Suites of MG-RAST annotated functions were comparedbetween impacted and unimpacted sites usingANOSIM (Primer 6). Rar-efaction curves for 16S rRNA genes and functional annotations weregenerated using mothur (v.1.36.1) (Schloss et al., 2009).

3. Results

Analyses previously described (Table 1) (Akob et al., 2016) demon-strated geochemical impacts consistentwith UOGwastewater to down-stream Sites 7 and 3 due to activities at the disposal facility. BackgroundSites 2 (located in a separate drainage) and 4 (located upstream fromdisposal facility)were not impacted. Site 6, located adjacent to the injec-tion well, wasminimally impacted, e.g., had conductivity andmajor ionconcentrations comparable to background sites, but Sr isotopic analysissuggested small inputs of coalbed methane wastewater (Akob et al.,2016). Sites 7 and 3 were characterized by increased conductivity(Fig. 1) and elevated levels of ions including chloride (two orders ofmagnitude above background), sodium (ten times above background),and barium (five to six times background levels). Based on these obser-vations, Sites 7 and 3were designated as impacted due to the significantgeochemical alterations observed. Akob et al. (2016) described addi-tional geochemical shifts between the impacted and background sites.

3.1. UOG wastewater impacts on microbial community and function

Significantly different bacterial community structures were ob-served between impacted Sites 7 and 3 and between background Sites2 and Sites 4, and minimally impacted Site 6 (p = 0.001–0.005, Fig. 2,with rarefaction curve included as Fig. S1 and operational taxonomicunit table as Table S3). Bacterial community structure at Site 6 wasmore similar to the control sites, consistent with comparable geochem-istry between these sites and the findings of Akob et al. (2016), where16S rRNA gene amplicon sequencing (with a different DNA extractionmethod)was performed on paired samples. Bacterial community struc-tures from replicate sediment samples collected from Site 3 (samples 3and 3d) were 98.6% similar.

Proteobacteria dominated the communities at all sites, withAlphaproteobacteria, Betaproteobacteria, Deltaproteobacteria, andGammaproteobacteria being the major classes represented.Deltaproteobacteria were more abundant at impacted sites (9.8 ±0.1%) compared to background (unimpacted) sites (6.2±1.2%). Unclas-sified bacteria were the next most abundant group (21.9–27.1%). Simi-larly the Archaeal community at Site 7 formed a unique cluster from theother sampling sites (Fig. 3), however Site 3 did not have a significantlydifferent Archaeal community structure compared to the backgroundSite 2 in a separate drainage. Site 7 was dominated by the classMethanomicrobia (59.8%). Methanomicrobia were present at higher(p = 3.8 × 10−8) and unclassified Thaumarchaeota were present atlower (p = 4.5 × 10−5) relative abundance at the downstream sites.

Unimpacted Sites 2, 4, andminimally impacted Site 6 formed a clus-ter with 99.8% similarity for relative abundance of Subsystem Level 1functions (Fig. S2 with functional rarefaction curve included asFig. S3). Site 3 and 3d formed a single significantly different cluster(p = 0.01), as did Site 7. Spikes in select dormancy and sporulationgenes (Subsystem Level 3 functions, similar to a KEGG pathway) wereobserved at Site 7 (Figs. 4, S4) while the levels of these genes at otherbackground sites and impacted Site 3were comparable to Site 2. The el-evated dormancy and sporulation annotations observed at Site 7 in-clude genes for dipicolinate synthesis (29 times higher than Site 2),small acid-soluble spore proteins (36.1 times higher), spore germina-tion (21.2 times higher), and sporulation cluster III A (86.3 timeshigher). Likewise, select genes related to methanogenic respirationwere elevated at Site 7 including methanophenazine hydrogenase andcoenzyme F420 hydrogenase at 25.5 and 17.8 times higher than back-ground Site 2, respectively (Figs. 4, S5). Cadmium resistance geneswere found at double the relative abundance at Site 7 compared tobackground Site 2 (Fig. S6) despite Cd being below detection in watersand sediments. Generally, genes related to stress response (Fig. S7), ar-omatic metabolism (Fig. S8), sulfur metabolism (Fig. S9), and nitrogenmetabolism (Fig. S10) at Site 7 and 3 were less than two times greaterthan the relative abundance in background metagenomes. Select

Fig. 2.Heatmap illustrates relative abundance of different bacterial classes in sedimentwithmajor phyla labeled. Cluster analysis indicated significant shifts in impacted sediment (Site 7 &3) bacterial community compared to background and unimpacted Site 6. Clusters with significant differences are connected with black bars in the cluster analysis. Numbers on heat mapindicate rounded relative abundances (%).

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antibiotic resistance functions were also elevated (7.9–9.4 times back-ground Site 2) at Sites 7 and 3 including bacteriocin-like peptides(Fig. S11).

3.2. Antibiotic resistance assigned by ARDB

Forty-three different resistance genes were identified in themetagenomic sequencing data of sediment samples using the ARDB(Fig. 5). The most frequently detected genes across the sites werebacA, mexB, mexF, and acrB. The highest levels of acrB and mexB wereobserved at downstream sites (p = 0.0003–0.03). No difference be-tween bacA and mexF levels were observed comparing unimpactedand downstream sites (both p=1.0). Cluster analysis performed on re-sistance gene profiles indicated a relationship between resistance pat-terns and sample geographic location. Two of the impacted sites (Sites7 and 3) formed a cluster with 66.8% similarity. Background (Sites 2and 4) and the site located adjacent to the injection well, which wasminimally impacted (Site 6), formed a cluster with 71.1% similarity. Se-quences from duplicate samples from Site 3 (3 and 3d) formed a clusterwith 70% similarity. A relationship between conductivity, used as an

indicator ofwater quality, andARGwasobserved for smeE, afluoroquin-olone resistance gene that also serves as a multidrug efflux pump(Spearman rank p = 0.017). No relationships were observed betweenother observed ARGs and conductivity as an indicator of water quality(p = 0.13–1.0).

The most frequently detected resistance function was multidrug re-sistance with an average relative abundance across sites of 3.1 ±1.0 ppm, followed by bacitracin with an average relative abundance of1.6 ± 0.5 ppm (Fig. 6). Eight of 43 ARGs were above detection at allsites, and 11 were unique to Site 3 (Fig. S12).

3.3. Quantification of select ARG

qPCR for select ARG on water and sediment samples showed thatsul1, tet(G), and acrB were above detection for all samples (Fig. S13and Table S5). No differences in qPCR gene copy numbers were ob-served between the sites (all p = 0.2–0.8). The qPCR analysis detectedARG that were not observed in the metagenomes, implying qPCR wasmore sensitive than the sequencing at the depth performed. For exam-ple, in the metagenomic results sul1 was above detection in two

Fig. 3. a. Cluster analysis and b. heat map illustrating the relative abundance (%) of Archaea counts classified at the class level using the lowest common ancestor method in sediment.Numbers overlaid on the heat map are the relative abundance (%).

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samples (Tables S4) but for qPCR these genes were found at relativelyconstant levels in all samples (Fig. S13 and Table S5). Other resistancegenes tested (sul2, tet(O), ermF) were below detection or quantificationvia qPCR and in the metagenomes.

Fig. 4. Comparison of relative abundance of Level 3 functions in sediment samples forselect dormancy and sporulation and respiration genes to background Site 2. Error barson Site 3 represent replicate samples from Site 3.

4. Discussion

Microbial community composition and potential metabolic activitywere altered in stream sediments due to activities at a UOGwastewaterdisposal facility that resulted in geochemical changes to the stream. Thealterations in impacted stream sediments indicated potential shifts innutrient cycling and redox conditions characterized by the loss ofnitrate-oxidizing Nitrospira, decreases in ammonia oxidizingThaumarchaeota, and increases in anaerobic Methanomicrobia. In addi-tion, members of Firmicutes were elevated at the impacted Site 7(5.3%) compared to Site 3 (2.2 ± 0.7%) and unimpacted sites (0.7 ±0.1%). Organismswithin the Firmicutes phylum are abundant in high sa-linity UOG produced waters from the Marcellus Shale and other UOGformations (Akob et al., 2015; Cluff et al., 2014; Liang et al., 2016;Murali Mohan et al., 2013a; Struchtemeyer and Elshahed, 2012). UOGwastewater potentially contains microbial communities representativeof both production fluids (chemical additives and water taken from avariety of sources) and formation waters (Cluff et al., 2014; Daly et al.,2016; Murali Mohan et al., 2013a), which are different from surficialstream sediment communities. However, the microbial communityshifts in the impacted sediments are likely a result of UOG wastewaterselecting for different communities in stream sediments due to chemi-cal changes given the high dilution of theUOGwastewater in the stream(0.001 part brine to 0.999 parts freshwater) based on previously reportBr- and Cl- concentrations (Akob et al., 2016). Further, UOGwastewater

Fig. 5. a. Cluster analysis of resistance gene profiles for ARDB annotated results and b. heatmap of relative abundance of antibiotic resistance genes, normalized to total clean reads insediment. Site locations are shown in Fig. 1. Sites 3d and 3 are replicate samples from Site 3.

Fig. 6. a. Relative abundance and b. percentage of antibiotic resistance elements insediment by antibiotic target annotated using the ARDB. Specific conductance measuredin water shown on second y-axis in panel a.

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after nine days of production was dominated by Gammaproteobacteria(MuraliMohan et al., 2014), but this signal is not retained in our surficialstream samples indicating that selection and not input of bacteria islikely driving community dynamics. An increase in Deltaproteobacteriaat impacted sites is characteristic of polluted environments and shiftstowards anaerobic conditions. The observation of Methanomicrobiadominating the Archaea community at Site 7 is consistentwith observa-tions of these as the sole Archaea observed in unaerated and biocideamended impoundments for UOG produced waters (Murali Mohanet al., 2013b). Similar to the 16S rRNA gene amplicon sequencing previ-ously reported, shifts in microbial community composition correlatedwith changes in geochemistry in impacted stream sites. However, ourstudy goes beyond this previous work to (1) present themicrobial com-munity structure using a sequencing method without the potential PCRbiases in amplicon sequences, (2) provide the structure of the Archaealcommunity, and (3) show that the potential function of these commu-nities is further altered due to activities at the site.

Increases in select sporulation, dormancy and methanogenesisgenes were observed at the impacted Site 7, showing a shift in the

potential function of communities due to impacts from the disposal fa-cility. Again, this is likely due to the changes in geochemistry due to theinputs of UOG wastewater. Increases in spore forming bacteria (MuraliMohan et al., 2013a) and in genes for these functions (Murali Mohanet al., 2014) have been observed over time in produced waters. At Site7, the Firmicutes phylum contained spore forming Bacillus and Clostridia,which accounted for 10.6% of the microbial community. Increases innitrosative stress at impacted sites are consistentwith observed impactsto nitrogen cycling in soils impacted by road salt application (Green andCresser, 2007; Green et al., 2008). The observed shifts in the microbialcommunity and these taxonomic and functional populationswere asso-ciated with shifts in overall functional annotations. However, genes ele-vated at Site 7were often not elevated at Site 3, despite these both beingimpacted sites. This could be explained by the geochemical variabilityobserved at the two impacted sites, which includes slightly lower con-ductivity and lower concentrations of elements associated with UOGwastewater at Site 3 compared to Site 7. These observations may alsobe impacted by the small sample size used in this study. However,Akob et al. present further sediment analysis with site replicates dem-onstrating that the differences between Sites 3 and 7 are due to geo-chemical impacts and not likely from spatial heterogeneity insediment based on similar C/N/S profiles at both sites.

A shift in antibiotic resistance profiles in sediments was observed indownstream samples. No biocides identified in a recent review(Kahrilas et al., 2015) share the polycyclic and carboxylic chemicalstructures characteristic of fluoroquinolones. While UOG wastewatercan be rich in organic chemicals including polycyclic aromatic hydrocar-bons and heterocyclic compounds (Khan et al., 2016; Orem et al., 2014),elevated NVDOC was not observed at the impacted sites. The highestrelative abundance of multidrug resistance genes was observed at Site7, and many of these resistance elements encoded for efflux pumps.Multidrug efflux pumps transport a range of chemicals including surfac-tants, which can be used as an additive for hydraulic fracturing, andtherefore increases in the presence of efflux pumps may represent a re-sponse to other chemicals in the UOGwastewater matrix. It is also pos-sible these shifts in resistance profiles are due to shifts in the microbial

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community (Martinez et al., 2015). For example, increases in acrB andmexB in impacted sediments may be characteristic of community shiftsthat include increases of E. coli and Pseudomonas aeruginosa (Martinezet al., 2015). However, Gammaproteobacteria were not elevated abovebackground (3.7 ± 0.8%) at impacted Site 7 (3.7%) or Site 3 (4.7 ±0.2%). High relative abundance of efflux pumps has also been observedin saline sediments, with acrB andmexB accounting for 8 and 4% of totalARG in sediments with anthropogenic impacts (Chen et al., 2013).

The impact of biocide use in UOG on environmental antibiotic resis-tance and the fate of biocides in theUOGwater cycle is poorly character-ized (Kahrilas et al., 2015). In this study, specific biocides were notdetected in impacted streamwaters (Keith Loftin, personal communica-tion). However, disclosure of biocides in the FracFocus.org database(Groundwater Protection Council and Interstate Oil and Gas) providesan indication of the biocides used in UOG development for shale gaswhich is a source of wastewater for disposal at this site [site historywas previously described (Akob et al., 2016)]. Using compiled lists ofbiocides in use for UOGdevelopment, one can generate a list of expectedresistances if biocide use was impacting the resistance profile of thecommunity. Interestingly, resistance genes directly related to QAC(qacA, qacB, qacC), which are commonly used by the UOG industry,were all below detection in all samples. This could be explained eitherby lack of QAC use in thewastewater disposed of at the facility, degrada-tion or sorptive losses of QAC, or induction of biocide tolerance throughother mechanisms. Biodegradation and/or abiotic transformations ofQAC have been demonstrated under aerobic, nitrate and fermentingconditions, but not methanogenic conditions (Tezel, 2009). It is alsopossible that complex geochemical conditions in UOG wastewater af-fected bacterial response to any biocides present in the wastewater, aswas observed in a study of the biocide glutaraldehyde on model organ-ism Pseudomonas fluorescens (Vikram et al., 2014).

Given thehypothesis that UOGwastewater could serve as a selectingenvironment for environmental antibiotic resistance, it is important tocompare the ARG profiles and levels observed inWolf Creek to other re-ported environments, particularly those reported to be hot spots of an-tibiotic resistance and therefore potential risks to public health, likemunicipal wastewater. ARG relative abundance for our sites was com-parable to levels observed in the saline, anthropogenic impacted sedi-ments of the Pearl River Estuary (2.8–7 ppm) (Chen et al., 2013).However, more ARG types were observed at in our sites (43 ARG)than in the Pearl River Estuary (27 ARG) (Chen et al., 2013), whichwas dominated by sulfonamide resistance (38%). Generally lower ARGlevels on a ppm basis and fewer ARG types were detected in thisstudy compared to metagenomic studies in municipal wastewaterusing the ARDB (Yang et al., 2013; Yang et al., 2014; Zhang et al.,2011). These differences are likely due to the fact that municipal waste-water is a stronger source of ARG and that the waste inputs in the PearlRiver Estuary study were chemically different than the UOG wastewa-ter. However, differences in DNA extraction method (Morgan et al.,2010), and bioinformatics pipeline can affect results in –omics studiesand care should be takenwhen comparing between studies using differ-ent techniques.

5. Conclusions

This work demonstrates that UOGwastewater releases are associat-ed with a shift in microbial community structure and functions relatedto dormancy and sporulation, respiration, and antimicrobial resistance,which is hypothesized to lead to alterations in microbial activity in situ.Therefore, it provides further evidence ofmicrobiological impacts at thisUOG disposal site. The potential for further downstream impacts re-mains to be demonstrated given that samples here were collected onthe disposal facility property. The increases in dormancy and shifts inrespiration are characteristic of microbial communities responding toenvironmental disturbances, which in this study were characterizedby shifts in the geochemistry. The observed shifts in the microbial

community indicate a need to understand the microbial ecosystem im-pacts from accidental releases or improper treatment of UOGwastewa-ter. Functional shifts in UOGwastewater impacted sediments may haveimplications for the treatment and beneficial reuse of UOGwastewater.In particular, while elevated levels of select multidrug efflux pumpswere observed in UOG impacted sediments the ARG relative abun-dances observed here were comparable to saline sediments impactedby anthropogenic activity (Chen et al., 2013), both of which werelower than municipal wastewater, which is considered a hot spot of re-sistance. Measurements of functional shifts in a range of UOGwastewa-ter from different sources and biocide usages is needed to understandthe full impact of UOG wastes on environmental antibiotic resistanceand ecosystem function.

Funding

This research was supported by a research stipend to HDR from theDouglass Project, graduate fellowship to AE from Rutgers UniversitySchool of Engineering, NLF university startup funds, and funding toDMA, IMC, and ACM from the U.S. Geological Survey Toxic SubstancesHydrology Program.

Any use of trade, firm, or product names is for descriptive purposesonly and does not imply endorsement by the U.S. Government.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.scitotenv.2016.12.079.

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