Copper Nanoparticle Induced Cytotoxicity to Nitrifying Bacteria in

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Copper Nanoparticle Induced Cytotoxicity to Nitrifying Bacteria in Wastewater Treatment: A Mechanistic Copper Speciation Study by X-ray Absorption Spectroscopy Justin G Clar, Xuan Li, Christopher Allen Impellitteri, Christina Bennett-Stamper, and Todd Peter Luxton Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b01910 • Publication Date (Web): 28 Jul 2016 Downloaded from http://pubs.acs.org on August 5, 2016

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Environmental Science & Technology

Copper Nanoparticle Induced Cytotoxicity to Nitrifying Bacteria in Wastewater Treatment: A Mechanistic Copper Speciation Study by X-ray Absorption Spectroscopy Justin G. Clar,†‡¥ Xuan Li,†‡ ¥ Christopher A. Impellitteri,‡ Christina Bennett-Stamper‡, Todd P. Luxton,‡* ‡

National Risk Management Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 5995 Center Hill Avenue, Cincinnati, OH 45224, USA †

Oak Ridge Institute for Science and Education (ORISE) Postdoctoral Research Associate Authors contributed equally to this work * Phone: (513) 569-7210; Fax (513) 569-7879; Email [email protected] ¥

Abstract With the inclusion of engineered nanomaterials in industrial processes and consumer products, wastewater treatment plants (WWTPs) could serve as a major sink for these emerging contaminants. Previous research has demonstrated that nanomaterials are potentially toxic to microbial communities utilized in biological wastewater treatment (BWT). Copper-based nanoparticles (CuNPs) are of particular interest based on their increasing use in wood treatment, paints, household products, coatings, and byproducts of semiconductor manufacturing. A critical step in BWT is nutrient removal through nitrification. This study examined the potential toxicity of uncoated and polyvinylpyrrolidone (PVP) coated CuO, and Cu2O nanoparticles, as well as Cu ions to microbial communities responsible for nitrification in BWT. Inhibition was inferred from changes to the specific oxygen uptake rate (sOUR) in the absence and presence of Cu ions and CuNPs. X-ray Absorption Fine Structure spectroscopy, with Linear Combination Fitting (LCF), was utilized to track changes to Cu speciation throughout exposure. Results indicate that the dissolution of Cu ions from CuNPs drive microbial inhibition. The presence of a PVP coating on CuNPs has little effect on inhibition. LCF analysis of the biomass combined with metal partitioning analysis supports the current hypothesis that Cu-induced cytotoxicity is primarily caused by reactive oxygen species formed from ionic Cu in solution via catalytic reaction intermediated by reduced Cu(I) species.

Introduction Over the last two decades, the inclusion of engineered nanomaterials (ENMs) in

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consumer products has continued to increase. Currently, nano-enabled products are available in a

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large variety of areas including, but not limited to, textiles, food packaging, consumer

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electronics, and composites.1 While the variety of ENMs used in consumer products continues to

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grow, copper-based nanoparticles (CuNPs) are of particular interest based on their increasing use

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as preservatives in pressure treated lumber, paints, anti-microbials (in fabrics, coatings, and

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plastics), conductive inks, household products, nanometal lubricants, and coatings.2-6 CuNPs in

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these products have potential to enter wastewater treatment plants (WWTP) throughout product Page 1 of 23 ACS Paragon Plus Environment


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lifetime through non-point release to the environment during product use and inappropriate

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disposal. The non-source release of CuNPs in urban environments represents a potential pathway

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for the introduction of CuNPs into WWPTs through Combined Sewer Systems (wastewater

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collection systems that treat both sanitary sewage and stormwater runoff). In 2004 the EPA

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estimated that a total of 772 cities (including New York City and Philadelphia) in 32 states still

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employed combined sewer treatment systems that serviced close to 40 million people.7

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As with many emerging contaminants, an understanding of CuNP behavior in WWTPs is

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an important component in predicting their fate, transport, and potential ecological impact once

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released to the environment. Accordingly, previous work has investigated the mobility of ENMs

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in WWTPs with specific attention paid to how these materials partition between the water

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column and biosolids during conventional treatment.6,

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attempted to understand how the presence of ENMs in these systems may inhibit the microbial

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communities used in biological treatment.12-15 Previously published work has focusing on CuNPs

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in these systems, have lacked a detailed examination of how Cu speciation affects the observed

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inhibition.6, 16-21

8-11

Additionally, researchers have also

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A critical step in biological wastewater treatment is nutrient removal via nitrification-

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denitrification. It is well understood that wastewaters containing copper, and/or other metals,

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entering municipal treatment plants may affect nitrogen removal in conventional activated sludge

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treatment processes.22-24 Ammonia oxidation is the first step in nitrification and as a result,

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instrumental to nitrogen removal. The aerobic nitrification process involves two genera of

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bacteria: Nitrosomonas and Nitrobacter, which are aerobic autotrophic bacteria that convert

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ammonia to nitrite and nitrite to nitrate, respectively. While this is a two-step process, the

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conversion of ammonia to nitrite is the rate limiting step.25, 26 One species of Nitrosomonas, N.

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europaea, an obligate chemolithoautotrophic aerobe uses ammonia as its sole natural energy

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source in oxidizing ammonia to nitrite via ammonia monooxygenase (AMO).27 Nitrosomonas

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populations grow slowly and are sensitive to growing conditions (e.g., pH, temperature, oxygen).

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In addition, nitrifying bacteria are widely identified as one of the most vulnerable organisms

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present in biological wastewater treatment, making them a critical screening species to monitor

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upon exposure to emerging contaminants such as CuNPs.28, 29 A better understanding of specific

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nitrification inhibition during exposure to CuNPs will improve our ability to predict the

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resiliency of these microbial systems. Page 2 of 23 ACS Paragon Plus Environment

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In this work, we aim to achieve a mechanistic understanding of how the nature, (ionic

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versus particle) and speciation, (Cu(I) versus Cu(II)), of copper affects the nitrifying bacterial

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communities typically present in biological wastewater treatment. This is accomplished through

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detailed tracking of the mobility, solubility, and fate of uncoated and polyvinylpyrrolidone (PVP)

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coated CuNPs throughout the exposure process using X-Ray Absorption Fine Structure (XAFS)

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Spectroscopy.

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Materials and Methods

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powders were purchased from U.S. Research Nanomaterials (Houston, TX) and used without

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further purification. The primary particle size listed by the manufacturer is 40 nm and 18 nm for

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CuO and Cu2O, respectively. CuNP suspensions were prepared by adding the appropriate mass

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of powder to Milli-Q water (> 18.2 MΩ·cm) at a pH of 7.5 to minimize Cu dissolution.30 To

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investigate the effect of capping agents on CuNP behavior in these systems, pristine powders

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were also added to solutions of 1 wt % polyvinylpyrrolidone (PVP). PVP was chosen as an

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additional dispersion medium due to its wide use as a capping agent for other metal and metal

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oxide NPs, as well as its lack of toxicity to a wide range of test organisms used in biological

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assays.31-34 All stock solution concentrations were approximately 500 mg/L Cu. Cu2O

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suspensions were prepared in low DO Milli-Q water (Milli-Q water kept under anaerobic

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conditions) to promote stability of the Cu(I) species before biomass exposure. CuNP dispersion

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was achieved through 30 min bath sonication at 25°C. (Branson Ultrasonics, Danbury CT,

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Model 1510). Release of ionic Cu during suspension preparation was minimal. (< 1 %). After

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sonication, aliquots of CuNP suspensions were diluted with Milli-Q water in a 10:1 ratio by

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volume for characterization of hydrodynamic diameter (HDD), size, and morphology. (See SI for

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details). Finally, stock suspension of ionic copper (10 g/L) were prepared by dissolution of

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CuSO4 in Milli-Q water or 1 wt % PVP solution.

Nanoparticle Characterization and Suspension Preparation: CuO and Cu2O nanoparticle

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Nitrifying Enrichment Cultivation: The nitrifying bacteria enrichment used in this study was

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cultivated following the protocols from Hu and coworkers with minor modifications.35 A 7-L

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reactor containing a nitrifying enrichment media was inoculated with return activated sludge

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from the Cincinnati Metropolitan Sewer District (MSD) when operating in nitrification mode.

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Reactor pH was maintained automatically at 7.5 ± 0.1 with 1 M sodium bicarbonate, operating Page 3 of 23 ACS Paragon Plus Environment


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with a solids retention time (SRT) of 35 d and a hydraulic retention time (HRT) of 1 d. The

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enriched media was withdrawn from the reactor for use in batch studies after attainment of

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steady state, characterized as 99% ammonia removal. Additional details of nitrogen enrichment

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cultivation and maintenance are described in the SI.

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Metal Partitioning Analysis: Aliquots of the enriched media were withdrawn from the reactor

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and the biomass was allowed to settle. After separation, supernatant was removed and replaced

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with 250 mL of Milli-Q water. This washing step was completed three times to remove residual

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salts and extra polymeric substance from samples that may complex metals of interests, as well

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as simplify the matrix for this mechanistic study. The washed biomass was re-suspended in

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Milli-Q water to a final volume of 50 mL. After dilution, samples were buffered with MOPS ((3-

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(N-morpholino)propanesulfonic acid), to a final concentration of 20 mM. When necessary, the

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sample pH was adjusted to 7.5 with 1 M NaOH and HCl. MOPS complexation with Cu has

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proven to be insignificant.35, 36 After re-suspension, the resulting biomass concentration was 683

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± 28 mg/L. Aliquots of CuNPs or ionic solutions were added to the biomass samples to create a

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Cu concentration range of 0–40 mg/L for ionic Cu, and 0-20 mg/L for CuNPs. These

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concentration ranges were selected to represent the highest possible pulses of both ionic Cu and

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CuNPs potentially found in wastewater influent.37,

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equilibrated for 1 h as initial test showed no significant changes in partitioning behavior at

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extended exposure times. (Figure S3) Alternatively, samples exposed to CuNPs were allowed to

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rotary mix for 3 h to reach steady state.9,

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additional equilibration time of the NPs as well as being representative of typical retention times

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for conventional activated sludge WWTPs.39 In all systems, Cu partitioning and dissolution was

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tracked through careful analysis of both sample supernatant and biomass. After settling and

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removal of the supernatant, the collected biomass was washed twice with Milli-Q Water to

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remove any weakly adsorbed Cu from the biomass surface. Any Cu unaccounted for is assumed

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lost during this washing procedure. Additionally, 12 mL aliquots of supernatant were placed in

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10 kDa (nominal 3 nm) Amicon Ultrafiltration filters (Millipore, Billerica MA) and filtrates

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analyzed for ionic Cu concentration. Both sample supernatants and solids were digested using

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established protocols (EPA Methods 3015A and 3051A) and analyzed for Cu concentration by

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inductively coupled plasma-optical emission spectrometry (ICP-OES, Thermo Fisher iCAP 6000

10

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Samples exposed to ionic Cu were

The mixing period was extended to allow for

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Series). Statistical significance of the differences in partitioning behavior between treatments

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was determined by t-Test. Additional details of sample preparation are outlined in the SI.

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Nitrification Activity Assay: Nitrification activity of biomass was evaluated in duplicate using

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batch respirometric vessels following established protocols.40, 41 Enriched media extracted from

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the reactor and washed three times with Milli-Q water. Washed biomass was resuspended to a

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final volume of 100 mL with a TSS concentration of 683 ± 28 mg/L. This TSS concertation is

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much lower than typically found in BWT, but was a necessity to accurately measure oxygen

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uptake. Prior to nitrification activity assays, biomass samples were exposed to ionic Cu and

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CuNPs for 1 or 3 h respectively. After exposure, biomass suspensions and controls were

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saturated with pure oxygen prior to addition of 20 mg/L of NH4-N as (NH4)2SO4. The

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suspensions were then transferred into separate 95 mL water-jacket respirometric vessel free of

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headspace, and held at 22 ± 0.1 °C using a circulating water bath. Dissolved oxygen (DO)

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concentrations in the vessel were measured with a biological oxygen monitor system (Model

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5300A, YSI, Yellow Springs, OH) and continuously recorded at 4 Hz via computer. Inhibition of

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biological activity was inferred from the difference between the measured maximum specific

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oxygen uptake rate (sOUR) in the control (sOURcontrol) and Cu exposed samples (sOURsample)

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running in parallel. Statistical significance between treatments was determined by t-Test. % inhibition = (sOURcontrol-sOURsample)/sOURcontrol × 100%

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(1)

X-ray Absorption Spectroscopy Analysis: XAFS samples were prepared identically to those

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used in the metal partitioning analysis with one exception. After washing the biomass,

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supernatant was carefully removed, and the remaining biomass freeze-dried. (Millrock

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Technologies, Kingston NY, BT48) Freeze-dried biomass samples containing ionic Cu and

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CuNP were homogenized through grinding into a fine powder. Sub-samples of ground powder

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were pressed into 13 mm diameter self-supported pellets, diluted when necessary with PVP

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powder, and sealed by Kapton polyimide tape. Additionally, filters from 10 kDa Amicon

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Ultrafiltration units were extracted and sealed in Kapton tape to elucidate the Cu speciation

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remaining in sample supernatant after exposure to biomass. XAFS analyses were conducted at

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Sector 10BM (MRCAT) and 20BM (PNC XOR) at the Advanced Photon Source at Argonne

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National Laboratory, Argonne, IL. Details of the XAFS analysis, data processing, standard

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spectra, and representative Linear Combination Fits (LCF) are provided in the SI. Page 5 of 23 ACS Paragon Plus Environment


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Results & Discussion Nanoparticle Characterization: A summary of the CuNP properties used in this study are listed

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in the SI, Table S1. According to the manufacturer, CuO particles are roughly twice the size of

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their Cu2O counterparts, listed at 40 nm and 18 nm respectively. However imaging analysis

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indicates that the particles are similar in size, at approximately 46 nm. Individual particles and

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larger aggregates appear in both CuO and Cu2O samples shown in Figure S1. Critically, the large

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variation observed in the Cu2O images includes a significant amount of smaller particles in the

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range reported by the manufacturer and shown in our imaging analysis (Table S1, Figure S1).

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However, larger aggregates of a plate like morphology shift the particle size distribution to larger

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values. Histograms developed from particle size analysis are presented in Figure S2. Once

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dispersed in aqueous solution the measured HDD of the particles shows considerable aggregation

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compared to their listed primary particle size in agreement with previously published studies of

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CuNPs.30,

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suspension give a consistent HDD of approximately 720 nm. These large HDD values may be

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explained by particle aggregation as well as the sintered nature of the initial material, highlighted

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in Figure S1. These sintered sections are a result of the manufacturing method and are difficult to

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disperse, even with the aid of extended sonication. Clearly, the addition of PVP as a stabilizing

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agent has an effect on the size of CuNPs dispersed in solution. In the case of CuO, the addition

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of PVP decreased the observed HDD by over 60% to approximately 588 nm. Alternatively, PVP

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only decreased the Cu2O particle size to roughly 20% to 575 nm.

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Copper Partitioning & Nanoparticle Persistence: Results of ionic Cu (CuSO4) partitioning

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studies as well as the adsorption isotherm are presented in Figure 1. The relative abundance of

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adsorbed Cu decreases as initial total Cu concentration increases, suggesting that the biomass

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adsorption sites are saturated with respect to Cu at approximately 10-12 mg/g (Figure 1b). In all,

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ionic Cu showed a stronger affinity for partitioning with the biomass relative to the supernatant,

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and represented the highest fraction until reaching a steady state at approximately 20 mg/L total

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Cu.

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CuO particles in Milli-Q water were measured at ~1,600 nm while the Cu2O


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Previous research on the interaction of NP with activated sludge has demonstrated that

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the identity of the NP as well as the presence of a coating play a critical role on the extent of

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removal.9-11, 43 These findings are again evident in this study even when using a highly select

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group of organisms typically found in activated sludge biomass shown in Figure 2. In the case of

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biomass samples exposed to uncoated CuO, the vast majority of Cu remains in the aqueous

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phase, with roughly 14 % of the copper adsorbing onto or internalized by the biomass across the

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exposure range. Additionally, further analysis of the aqueous phase showed little evidence of

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ionic Cu as triplicate analysis of 10 kDa filtrates gave Cu values under the method detection

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limit. (MDL,4 µg/L) The lack of Cu ions in these samples is likely due to the slightly basic pH

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used during exposure (pH = 7.5). Previous work has demonstrated that CuO nanoparticles do not

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readily dissolve in this pH range.30 While ionic Cu concentrations were below the method

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detection limit this does not imply that there is zero dissolution of CuO particles in solution.

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However, the disolved factor will be insignificant in comparison to the particulate copper phase.

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The addition of PVP as a stabilizing agent significantly (α = 0.05) decreases the amount of total

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aqueous Cu remaining in the aqueous phase after the 3 h incubation period. However, the

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overall trend remains the same, with the vast majority of Cu (approx. 80%) remaining in solution

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throughout the exposure range. Previous studies evaluating the interaction of CuNPs with

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activated sludge have reported 95% of injected Cu partitioning to the biomass over a 20 h

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incubation period.17 The reduced interaction between the CuNPs and biomass in this study is

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likely a result of the lower incubation time, decreased TSS level, and use of a small subset of

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microorganisms typically found in activated sludge. Although the presence of the PVP coatings

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has an important effect on NP behavior.

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Partitioning results for Cu2O samples are also outlined in Figure 2. For uncoated samples,

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roughly 65% of all injected Cu remains in the aqueous phase, while with the remaining 35%

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becomes associated with the biomass. The addition of PVP to Cu2O samples also significantly

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alters (α = 0.05) the partitioning behavior. The amount of Cu associated with the aqueous phases

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decreases (~ 40%) coupled with an increase in the Cu associated with the biomass (~50%).

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Unlike CuO samples, additional analysis of sample supernatants identified significant amounts of

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ionic Cu when dosed with Cu2O. In some cases, as high as 10% of the total injected Cu2O was

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released into solution as ionic Cu during exposure. This increase in ionic Cu in Cu2O samples is

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logical as the oxidation of Cu2O to CuO in aqueous solution will release Cu ions. Page 7 of 23 ACS Paragon Plus Environment


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There was significant aggregation of the CuNPs once dispersed in solution, (Table S1))

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with very little dissolution during the 3 h exposure time. Visual inspection of the 10 kDa

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membrane filters show extensive retention of both CuO and Cu2O NPs. (See Supporting

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Information, Figure S7). Furthermore, SEM images show the presence of particulate matter

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remaining on the 10 kDa filtration unit shown in Figure S8. XAFS analysis of these filters

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confirmed a significant amount of the material retained on the filter were CuNPs. In the case of

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samples exposed to Cu2O, a portion of the initial material has been oxidized to CuO, but still

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remains in the solid phase. (Figure S9) The elevated pH of the system (pH = 7.5) and the short

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equilibration time are likely responsible for the lack of appreciable dissolution of the CuNPs.

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Previous research has shown minimal dissolution of CuO NPs at pH values above 7 in the

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presence of DOC over short time periods (less than 24 h) similar to the results reported here.42, 44

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In contrast, Wang et al. reported substantial dissolution of CuO NPs in the presence of

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complexing ligands at pH 7.4 over a 70 minute time period.45 Further research is needed to

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determine the factors that influence CuNP and other NP removal/dissolution active sludge

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systems including detailed characterization of the sludge and degradation of the NPs throughout

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testing.

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sOUR Inhibition Assays: The results of the sOUR inhibition assays for ionic Cu, and CuNPs,

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are summarized in Figure 3. Immediately apparent is the non-linear relationship between

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inhibition and total Cu concentration. There is a distinct reduction in the inhibitory response

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produced in the biomass with increasing Cu concentration, suggesting that the specific enzyme

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activity sites affected by Cu are limited and increasing concentrations of Cu do not have as

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dramatic of an impact on oxygen uptake. Clearly, there are distinct changes in the observed

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inhibition depending on the identity of the initial Cu species. The introduction of ionic Cu to the

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system results in the greatest inhibition (Figure 3). The sOUR decreased rapidly as the ionic Cu

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dose to nitrifying biomass increased from 2 to 10 mg/L. At concentrations above 10 mg/L ionic

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Cu, only limited increases in inhibition were observed reaching an apparent plateau at

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approximately 55 % reduction. Preliminary testing (not shown) indicated that the presence of

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PVP in systems exposed to ionic Cu had no effect on the observed inhibition. Low inhibition was

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observed for both uncoated and PVP coated CuO suspensions. In fact, increases to the oxygen

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uptake rate were observed at doses of CuO below 5 mg/L. The highest dose of CuO and PVPPage 8 of 23 ACS Paragon Plus Environment

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CuO (20 mg/L) resulted in reduction of oxygen uptake rate of between 10 and 17 % respectively.

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However, differences in inhibition between CuO and PVP-CuO at concentration > 5 mg/L are

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not statistically significant (α = 0.05).

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Exposure to both coated and uncoated Cu2O suspensions resulted in additional inhibition,

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compared to the CuO NP, as high as 40 % at the maximum exposure concentration (20 mg/L),

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again with no statistical differences between uncoated and PVP coated Cu2O samples (α = 0.05).

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It is critical to note that biomass exposed to CuNPs resulted in considerably less inhibition, even

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with the increased incubation times (3 h), compared to ionic Cu (1 h) treatments. Considering

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the differences in exposure times, the ability of ionic Cu to inhibit biological activity is much

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more pronounced than CuNPs when compared with the two Cu NPs used in the current study.

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Ionic Driven Inhibition: It is clear from the data presented in Figure 3 that the nature of the

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initial Cu species, (i.e. ionic or CuNP) has a substantial effect on the observed inhibition. Even at

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extended exposure times, CuNPs do not result in extensive biological inhibition as inferred from

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the sOUR assays. Studies using Cu2O show a maximum inhibition of 40%, but only at the

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highest dose under investigation. (20 mg/L) Alternatively, the results of the ionic Cu studies fit a

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traditional model of biological response. At low exposure concentrations, a rapid increase in

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inhibition is observed (2-5 mg/L), followed by a plateau at increasing dose (10-40 mg/L).

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Previous studies have indicated that the slow release of toxic metals from ENM surfaces

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is the mechanism of their observed toxicity.46,

47

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ENM itself does not explain the biological response, but rather a traditional understanding of the

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metals intrinsic toxicity. In order to investigate this phenomenon on this system, the observed

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inhibition was plotted against the ionic Cu concentration remaining in solution after incubation

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with the nitrifying biomass. Samples using both CuO and PVP-CuO are not included as triplicate

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analysis resulted in ionic Cu concentrations was just below the method detection limit (4 µg/L).

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The results of this analysis shows a clear connection between the concentration of ionic Cu

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remaining in solution and the observed inhibition (Figure 4). Cu2O doses result in ionic Cu

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concentrations between 0.2 and 0.5 mg/L. This region is typical of large increase in inhibition

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with small changes in ionic Cu concentration. Furthermore, the limited inhibition observed

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during exposure to both uncoated and PVP coated CuO is likely driven by the low levels of Cu

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dissolution at the slightly basic pH used in the assay. While some inhibition was observed at the

In other words, the particulate nature of the



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highest dose (10-17%), any ionic Cu released to solution has likely been complexed by the

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biomass, explaining the lack of ionic Cu remaining in the sample supernatants and corresponding

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increase in the Cu concentration in the dried biomass. Furthermore, simple incubation studies of

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uncoated Cu2O and PVP-Cu2O samples in Milli-Q water, buffered to the same pH as biomass

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test samples, show an increase of 2.25 times the concentration of ionic Cu remaining in solution

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when compared to samples incubated with the biomass liquor (See Table S5). It is therefore

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likely that significant portions of the Cu ions released from Cu2O NPs are complexed by the

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biomass, causing the observed inhibition. This is compelling evidence that CuNPs themselves

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are not the driver of the observed inhibition. While it is possible that extended contact times (> 3

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h) of CuNPs with test organisms could increase observed inhibition, the continued release of Cu

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ions would be fundamentally limited by the system pH.30 A better understanding of the CuNP

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transformations in these systems is needed to fully understand their potential to effect treatment

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processes in an activated sludge system.

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Cu Speciation through X-Ray Absorption Spectroscopy: XAFS spectra of standard

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references, including a biomass control (no additional Cu exposure) and a Cu-exposed biomass

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sample are shown in Supporting Information (Figure S5). The edge positions for Cu(II) and

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Cu(I) are represented by CuO and Cu2O standards, respectively. Initial analysis of blank biomass

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sample obtained from the reactors indicated a background Cu concentration of 1.47 mg/g of

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biomass. This concentration is not unexpected as Cu is a trace nutrient used in feedstock for this

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system (Table S2). Visual examination of the biomass XAFS spectra prior to exposure to ionic or

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CuNPs indicate that both Cu(I) and Cu(II) oxidation states are present. Distinguishing features

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between the spectra are clearer when the raw spectra are transformed to their first derivatives

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highlighting the presence of Cu(I) (Figure S5). Linear Combination Fitting (LCF) results for the

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untreated biomass indicated that the Cu speciation was distributed between the three Cu-organic

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species used as reference complexes in the current study, Cu-Cysteine (47%), Cu-Acetate (35%)

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and Cu-Histidine (18%). It is generally accepted that results of LCF analysis carry and error of

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approximately +/- 5-10%.48 A representative example of the results of LCF results for this

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system are presented in Figure S5.

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Samples exposed to ionic Cu also exhibit features of both the Cu(I) and Cu(II) oxidation

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increasing ionic Cu concentrations a biomass control sample (no Cu added), Cu-Acetate, and Cu-

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Histidine standards were used in LCF analysis. Complete summaries of LCF results for all

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samples exposed to ionic Cu using both normalized and first derivate spectra are presented in

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Table S3. No significant deviation was observed between the fitting results based on normalized

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and the first derivative spectra. Therefore, results based on first derivative spectra were adopted

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and presented in Figure 5. To highlight changes in Cu speciation upon the addition of ionic Cu

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compared to the control sample, the results of the LCF analysis were normalized against the Cu

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distribution in control samples (Figure 5). It is critical to note that the percentages depicted in

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Figure 5 are not indicative of the raw Cu distribution in the analyzed samples, but rather relative

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changes compared to unexposed control samples. For example, if the abundance of specific

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complex increased with the addition of ionic copper compared to its relative abundance in the

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control (no added copper) there would an increase shown in Figure 5. With increasing dosses of

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ionic Cu, the relative contribution of Cu-Histidine complexes, relative to control samples,

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increases reaching a pseudo-steady state at 20 mg/L. Histidine, an α–amino acid, exists in a wide

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range of proteins with its imidazole side-chain serving as a coordinating ligand. Histidine is as an

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essential component in metalloproteins and enzymes, particularly, AMO.49, 50 As discussed in the

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introduction, AMO catalyzes the oxidation of ammonia and its intracellular level reflects the

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degree of nitrifying activity.51-54 In our nitrifying enrichment system, nitrification is vigorously

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active and therefore AMO and histidine concentrations would be high under these conditions, in

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turn explaining the high portion of Cu-Histidine bonds in the biomass at increased ionic Cu dose.

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A similar analysis strategy was used to evaluate changes in the Cu speciation in samples

344

exposed to increasing concentrations of CuNPs. CuO and Cu2O nanoparticle standards were

345

included in LCF analysis of CuNP exposed biomass along with the suite of standards used for

346

fitting ionic exposed samples. Detailed breakdowns of LCF analysis on samples exposed to

347

CuNPs are presented in Tables S3 and S4. Normalized LCF results from first derivate spectra

348

were adopted and presented in Figure 6. It is critical to note that as with Figure 5, the percentages

349

depicted in Figure 6 are not indicative of the raw Cu distribution in the analyzed samples, but

350

rather relative changes compared to unexposed control samples. Analysis of biomass samples

351

exposed to uncoated CuO shows an interesting trend (Figure 6a). As the initial dose increases,

352

the LCF results become dominated by the CuO standard. This strong signal from CuO is

353

consistent with the minimal Cu dissolution observed during Cu partitioning experiments. This Page 11 of 23 ACS Paragon Plus Environment


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does not imply a complete lack of CuO dissolution in these systems. The XAFS signal from CuO

355

particulates dominates the spectra obscuring ionic Cu spectral features. PVP-CuO exposed

356

samples show similar trends (Figure 6b), although the reduction of Cu-Histidine complexes is

357

less pronounced. This change in the speciation is likely attributed to interactions between Cu and

358

PVP, as PVP also contains a significant amount of cyclic amide functional groups. LCF results

359

of samples exposed to both Cu2O and PVP-Cu2O required the use of CuO and Cu2O standards to

360

describe the Cu distribution. (Figures 6c and 6d). Significant portions of the pristine Cu2O was

361

oxidized to CuO during incubation with the biomass. This chemical transformation is not

362

unexpected, as Cu2O will readily oxidize in Milli-Q water.

363 364

Cu(I) Mediated Inhibition: Previously published research has suggested that Cu-induced

365

cytotoxicity may involve Cu(I)-intermediated redox reactions forming Reactive Oxygen Species

366

(ROS), which subsequently damage significant macromolecules, including lipoproteins, DNA,

367

and thiol-containing enzymes and membranes.55-59 Letelier and coworkers proposed that at low

368

concentrations of Cu, specialized proteins enriched in thiol groups (e.g., cysteine-enriched

369

proteins) mitigate Cu toxicity by transporting and storing copper ions.60 Simultaneously, Cu(II)

370

is reduced by proteins containing thiol groups in cells, forming reduced copper phases, for

371

example Cu-Cysteine. However, when Cu concentrations exceed the adsorption capacity of these

372

specialized proteins, additional thiol-enriched groups will bind Cu indiscriminately.60 At this

373

stage, the resulting Cu(I) may produce excessive ROS such as hydroxyl (OH·) and superoxide

374

anion (O2·-) radicals, which will lead to cellular toxicity.56

375

In order to understand the potential for this proposed inhibition mechanism, an in depth

376

analysis of the LCF results is necessary. The Cu partitioning behavior and sOUR inhibition

377

assays indicate that the presence of ionic Cu, introduced as aqueous CuSO4 or released from the

378

surface of CuNPs, is responsible for the observed inhibition (see Figures 3 and 4), and therefore

379

biomass samples exposed to ionic Cu are the most critical to analyze for a mechanistic

380

understanding of the observed inhibition. LCF analysis of samples exposed to ionic Cu were fit

381

with three standards, an untreated biomass sample, Cu-Acetate, and Cu-Histidine (Figure 5) as

382

previously discussed. As the ionic Cu concentration increases, changes in the Cu distribution

383

relative to the control are evident, namely an increase in the relative percentages of Cu-Acetate

384

complexes and decreases in the Cu-Histidine and Cu-Cysteine complexes. This seems to suggest Page 12 of 23 ACS Paragon Plus Environment

Page 13 of 23


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a lack of Cu(I) species in samples treated with ionic Cu. However, it is critical to note that the

386

untreated biomass sample contains approximately 47% Cu-Cysteine based on LCF analysis.

387

Therefore, to derive an estimate of the amount of Cu(I) (as Cu-Cysteine), in treated samples, the

388

relative abundance of each fitting component must be converted to mg of Cu per gram of

389

biomass using the concentrations of Cu found in biomass samples during the metal partitioning

390

analysis shown in Figure 7. These conversions show that the mass of Cu affiliated with the thiol

391

groups reaches a steady state near initial Cu concentrations of 10 mg L-1. Reaching steady state

392

at this specific concentration coincides with the observed bacterial inhibition inferred from the

393

sOUR assays at the same Cu concentration (Figure 3). This suggests that a limited number of

394

sites for Cu complexation exist, as addition of Cu above this critical concentration will result in

395

minimal increases to inhibition. This convergence of saturation of Cu-Cysteine concentrations

396

and observed inhibition is supports the mechanisms of Cu(I) mediated bacterial inhibition,

397

especially the involvement of Cu-thiol complexes, proposed by Letelier and coworkers.60

398 399

Implications: Increased use of CuNPs in a variety of consumer products makes them an

400

important model nanoparticle for environmental fate and transport studies. Combined WWTPs

401

may serve as a major sink for CuNPs released from consumer products through both direct and

402

indirect release of CuNPs into the environment. Therefore, the ability to track the mobility and

403

transformation of CuNPs after entering WWTPs is an important area of study. Cu partitioning

404

analysis as well as SEM imaging highlighted the stability of CuNPs under nitrification inhibition

405

conditions, highlighting the low levels of dissolution, specifically for CuO particles, at the

406

slightly basic pH used in this study. (7.5) Furthermore, it was determined that the main driver of

407

inhibition for microorganisms responsible for nitrogen removal in biological wastewater

408

treatment was the release of Cu ions from injected CuNPs. While the presence of a PVP coating

409

on CuNPs resulted in significant changes to their biomass partitioning, these changes did not

410

result in significant effects to the sOUR inhibition assay. XAFS analysis, in combination with

411

LCF, Cu partitioning and nitrification inhibition, support the operating hypothesis of Cu(I)

412

mediated microbial inhibition. However, the specific mechanisms of these processes need to

413

further exploration in order to better understand how different Cu species may interact under

414

more complex wastewater treatment conditions.

415

Acknowledgements Page 13 of 23 ACS Paragon Plus Environment


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Any opinions expressed in this paper are those of the authors(s) and do not, necessarily, reflect

417

the official positions and policies of the U.S. EPA. Any mention of products of trade name does

418

not constitute recommendation for use by the U.S. EPA. Thanks to Deborah Roose, Samantha

419

Smith, William Wright, Maria Maurer, Nicholas Sylvest, and Vikram Kapoor for their laboratory

420

expertise. Thanks to Kit Daniels for his engineering support on building the reactor. Use of the

421

Advanced Photon Source (APS), a U.S Department of Energy (DOE) Office of Science User

422

Facility operated for the DOC Office of Science by Argonne National Laboratory under contract

423

No. DE-AC0206CH1357. PNC/XSD facilities (Sector 20) at APS are supported by the U.S.

424

Department of Energy, Basic Energy Sciences, the Canadian Light Source and its funding

425

partners, the University of Washington. MRCAT operations (Sector 10) are supported by the

426

Department of Energy and the MRCAT member institutions. The authors extend their deepest

427

appreciation to the staff of PNC/XSD, Dr. Chenguin Sun and Dr. Zou Finfrock. Finally, authors

428

Clar and Li greatly acknowledge support from the Oak Ridge Institute for Science Education

429

(ORISE).

430 431 432

Supporting Information

433

maintenance, characterization of CuNPs, model XAFS spectra, examples of LCF analysis,

434

images of 10 kDa filters used in particle separation, and results of XAFS, LCF for all samples.

435

This material is available free of charge via the Internet at http://pubs.acs.org.

Additional text, five tables, and nine figures showing details of enriched media cultivation and

436


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437

Tables and Figures

438 439 440 441 442

Figure 1: Results of ionic copper (CuSO4) partitioning after 1 h incubation with enriched media. a) Partitioning analysis showing the distribution of injected Cu between the aqueous phase and tightly bound to biomass after 1 h incubation. b) Isotherm showing saturation of Cu adsorption sites at approximately 10-12 mg/g.



443 444 445 446 447 448

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Figure 2: Partitioning analysis showing the distribution of injected Cu between the aqueous phase and biomass after 3 h incubation with uncoated CuNPs and CuNPs suspended in 1 wt % PVP. Ionic Cu concentrations in CuO samples were below the MDL.


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449 450 451 452 453 454

455 456 457 458 459 460 461


Figure 3: Biological inhibition inferred from decreases to specific oxygen uptake rate (sOUR) in untreated samples, and those treated with increasing concentrations of both ionic Cu and CuNPs. Data are presented as a percent decrease from blank samples and completed in duplicate.

Figure 4: Biological inhibition inferred from decreases to specific oxygen uptake rate in untreated samples, and those treated with increasing concentrations of both ionic Cu and CuNPs. Data is plotted as the observed inhibition, versus ionic Cu concentration remaining in solution after incubation with either ionic Cu or CuNPs. Inset is an expanded view of data points between 0 and 0.4 mg/L ionic Cu. Data from tests using CuO as a toxicant are not included as triplicate analysis resulted in ionic Cu concentrations below the method detection limit. Page 17 of 23 ACS Paragon Plus Environment


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463 464 465 466 467 468 469

Figure 5: Normalized results of linear combination fitting (LCF) of biomass samples after incubation with increasing concentrations of ionic Cu (CuSO4) for 1 h. LCF studies were completed on first derivate of normalized spectra as they highlight spectral differences between samples. The percentages are not representative of the raw Cu Distribution in analyzed samples but are relative changes in speciation compared to unexposed control samples. (Black dotted line) A complete speciation breakdown is available in the Supporting Information Table S3


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470 471 472 473 474 475 476 477 478


Figure 6: Normalized results of linear combination fitting (LCF) of biomass samples after incubation with increasing concentrations of both uncoated and PVP coated CuO and Cu2O nanoparticles for 3 h. LCF studies were completed on first derivative spectra as they highlight spectral differences between samples. The percentages are not representative of the raw Cu Distribution in analyzed samples but are relative changes in speciation compared to unexposed control samples. (Black dotted line) A complete speciation breakdown is available in the Supporting Information Tables S3 and S4. Page 19 of 23 ACS Paragon Plus Environment


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Figure 7: Distribution of Cu found in biomass samples after 1 h exposure to ionic Cu as CuSO4. Mass conversions calculated by multiplying the total concentration of Cu (mg/g) by the distribution results developed in LCF fitting throughout the exposure range. A clear plateau for Cu-Cysteine complexes develops at a Cu dose of 10 mg/L.

484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507

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Table of Contents Figure

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Copper Nanoparticle Induced Cytotoxicity to Nitrifying Bacteria in

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