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Responses of bacterial communities to CuO nanoparticles in activated sludge system Xiaohui Wang, Jing Li, Rui Liu, Reti Hai, Dexun Zou, Xiaobiao Zhu, and Nan Luo Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b06137 • Publication Date (Web): 14 Apr 2017 Downloaded from http://pubs.acs.org on April 21, 2017

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Environmental Science & Technology

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Responses of bacterial communities to CuO nanoparticles in activated sludge

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system

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Xiaohui Wang1, Jing Li1, Rui Liu1, Reti Hai1*, Dexun Zou1, Xiaobiao Zhu1, Nan Luo2

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1. Beijing Engineering Research Center of Environmental Material for Water

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Purification, College of Chemical Engineering, Beijing University of Chemical

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Technology, Beijing 100029, China

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2. China Sciences MapUniverse Technology Co., Ltd. (MAPUNI), Beijing, 100101, China

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Corresponding author:

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Reti Hai, Department of Environmental Science and Engineering, Beijing University

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of Chemical Technology, Beijing 100029, China.

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E-mail: [email protected]

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Tel: +86-10-64444924

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Fax: +86-10-64413170

ACS Paragon Plus Environment


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ABSTRACT

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The main objectives of this study were to investigate the influence of copper oxide

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nanoparticles (CuO NPs) on wastewater nutrient removal, bacterial community and

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molecular ecological network in activated sludge. The results showed that long-term

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exposure to 1 mg/L CuO NPs induced an increase of effluent concentrations of

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ammonia and total phosphorus, which was consistent with the inhibition of enzyme

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activities of ammonia monooxygenase, nitrite oxidoreductase, exopolyphosphatase

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and polyphosphate in the presence of CuO NPs. MiSeq sequencing data indicated that

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CuO NPs significantly decreased the bacterial diversity and altered the overall

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bacterial community structure in activated sludge. Some genera involved in nitrogen

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and phosphorus removal, such as Nitrosomonas, Acinetobacter and Pseudomonas

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decreased significantly. Molecular ecological network analysis showed that network

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interactions among different phylogenetic populations were markedly changed by

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CuO NPs. For example, β-Proteobacteria, playing an important role in nutrients

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removal, had less complex interactions in the presence of CuO NPs. These shifts of

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the abundance of related genera, together with the network interactions may be

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associated with the deterioration of ammonia and phosphorus removal. This study

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provides insights into our understanding of shifts in the bacteria community and their

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molecular ecological network under CuO NPs in activated sludge systems.

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Keywords: Copper oxide nanoparticles, Activated sludge, Bacterial community,

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Molecular Ecological Network


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INTRODUCTION

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Metal oxide nanoparticles (NPs) have been receiving a lot of attention for their

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potential applications in optoelectronics, nanodevices, nanoelectronics, nanosensors,

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information storage, and catalysis1. Among various metal oxide NPs, CuO has

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attracted particular attention because of its useful physical properties such as high

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temperature superconductivity, electron correlation effects, and spin dynamics2. CuO

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NPs are increasingly used in various applications such as in catalysis, pigments,

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chemical sensors, and bactericidal applications 3. It was reported that the global

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production of CuO NPs was 570 tons in 2014, and the estimated production would be

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1600 tons by the year 2025 4. The large production and utilization of CuO NPs

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inevitably lead to their environmental releases, and their potential health and

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environmental risks have attracted increasing concerns.

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Previous studies have showed that CuO were highly toxic to some model organisms

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such as mammalia cells5, aquatic organisms 6, bacteria and algae 7-9. The main reason

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was attributed to the generation of reactive oxygen species (ROS) 10, which might

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lead to the DNA lesion or gene regulation 5, 11. Although the toxicities of CuO NPs to

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paradigm organisms have already been studied, the evaluation of CuO NPs-induced

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toxicities to microbes in activated sludge was rare 12.

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Since some NPs were observed to enter into wastewater treatment plants (WWTPs) 12,

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researchers began to consider their possible effects on pollutant removal efficiency



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and microbial communities in WWTPs. Previous results indicated that different types

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of NPs such as, Ag 13, Cu 14, ZnO 15, TiO2 16 and SiO2 17, showed different influences

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on the performance of the activated sludge systems. Some preliminary studies have

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evaluated the effect of CuO NPs on activated sludge process

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bioreactors 3, 21. However, most of the studies mainly focus on the effects of CuO NPs

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on various pollutant removal efficiencies, and how microbial communities respond to

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CuO nanoparticles in activated sludge system is still not clear.

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and on anaerobic

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Activated sludge system is a complex ecosystem in which various species interact

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with each other to form complicated networks 22, 23. Through such network

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interactions, the activated sludge system is capable of accomplishing system level

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functions (e.g., removal of oxygen-depleting organics and nutrients) which could not

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be achieved by individual population 24. It is expected that the entering of

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nanoparticles could alter the network interactions among activated sludge bacterial

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populations. However, the effects of CuO NPs on the network interactions of

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activated sludge bacterial populations are mainly unknown.

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The major objectives of this study were to: (i) investigate the influence of CuO NPs

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on wastewater nutrient removal, (ii) examine the effects of CuO NPs on the diversity

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and structure of bacterial communities and (iii) elucidate how molecular ecological

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network of bacterial community respond to CuO nanoparticles in activated sludge

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system. For these purposes, we operated three lab-scale sequencing batch reactors


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(SBRs) subjected to 1mg/L CuO NPs and three control SBRs over an extended period

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(180 d).

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MATERIALS AND METHODS

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Nanoparticles

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The CuO NPs ( 99%) used in this study were purchased from

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Sigma-Aldrich (Shanghai, China) as a dry powder. CuO stock solution was prepared

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by adding 100 mg CuO to 1.0 L Milli-Q (Molsheim, France) water, followed by 1 h of

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ultrasonication (25℃, 120 W, 40 kHz). Based on the literatures review 3, 12, 1 mg/L

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was chosen as the environmentally relevant concentration of CuO NPs .

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The stability of the CuO NPs was evaluated by determining the particle size

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distribution (PSD) and zeta potential in two different liquid media, including

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deionized water and the influent wastewater of SBR. Samples of CuO NPs (10 mg/L)

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were dispersed in the appropriate liquid medium and then sonicated (25℃, 120 W, 40

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kHz) for 60 min and shaken for 2 h to increase their dispersion. The PSD were

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determined by dynamic light scattering (DLS) using a Zetasizer Nano ZS (Malvern

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Instruments, USA). The zeta potential of NPs dispersions was measured with the

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same instrument using laser Doppler velocimetry.

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Activated sludge bioreactors

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Three SBRs subjected to 1 mg/L CuO NPs (CuO SBRs) and three controls were



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operated in parallel. Each SBR has a 4 L working volume, with 1 L of inoculated

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sludge obtained from a municipal WWTP in Beijing, China. All SBRs were operated

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on three 8 h cycles every day, and each cycle consisted of a 1.5 h anaerobic and a 3 h

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aeration period, followed by 1.5 h of settling, then 10 min of decanting, and finally, a

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110 min idle period. After the settling phase, 2 L of the supernatant was discharged

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from each SBR, and was replaced with 2 L synthetic wastewater containing 0 (control

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SBRs) or 1 mg/L CuO (CuO SBRs) during the initial 10 min of a new cycle. The

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hydraulic retention time (HRT) was 16 h, and the sludge retention time (SRT) was

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maintained at approximately 20 days by sludge discharging. During the aeration

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period, DO concentrations in SBRs were maintain between 1.5 and 2.5 mg/L (Fig. S1),

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while in anaerobic period, DO concentrations were maintain lower than 0.5 mg/L.

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The initial concentrations of chemical oxygen demand (COD), ammonia (NH4+-N)

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and total phosphorus (TP) in the influent synthetic wastewater were maintained at

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approximately 500, 30, and 5 mg/L, respectively. The influent pH was maintained

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between 7.2 and 7.6. The composition of the synthetic wastewater was described in

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our previous literature 25.

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Analytical methods

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The determinations of COD, NH4+-N, nitrate (NO3--N) and TP were conducted in

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accordance with the Standard Methods 26. CuO in liquid samples was analyzed by

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inductively coupled plasma-optical emission spectroscopy ICP-OES7700 (Agilent

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Technologies, USA). CuO in biosolids was determined after microwave-assisted acid


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digestion of sludge samples according to previous literature 3. For enzyme activity

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analysis, the activated sludge samples were collected at the end of the aeration stage

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during the final week of the study period. The measurements of the activities of

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ammonia monooxygenase (AMO), nitrite oxidoreductase (NOR), nitrate reductase

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(NAR), nitrite reductase (NIR), exopolyphosphatase (PPX) and polyphosphate kinase

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(PPK) were according to the methods of Zheng, et al. 16.

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DNA extraction and PCR amplification

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Activated sludge samples were weekly collected from each SBR at the aerobic stage

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during the final three weeks of the study period. Totally, 18 activated sludge samples

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were collected, and 9 from CuO SBRs and 9 from control SBRs. DNA extraction was

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performed using a FastDNA SPIN Kit for Soil Kit (MP Biotechnology, USA)

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according to the manufacturer’s protocol.

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Before sequencing, the extracted DNA samples were amplified with a set of primers

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targeting the hypervariable V4 region of the 16S rRNA gene. The forward primer is

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515F (5′-GTGCCAGCMGCCGCGG-3′) and the reverse primer is 806R

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(5′-GGACTACHVGGGTWTCTAAT-3′). PCR was performed according to the

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protocol of Hai et al. 25. PCR products were purified using QIAquick PCR

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Purification Kit (Qiagen, Germany).

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MiSeq sequencing



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About 500 ng of purified PCR product for each sample was mixed and sent to a

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commercial company (Majorbio, China) for Illumina MiSeq sequencing. After

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sequencing, Python scripts were written to perform quality filtering of the raw reads

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as follows: (1) to sort sequences exactly matching the specific barcodes into different

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samples, (2) to check sequencing quality by filtering out the reads with any uncalled

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bases or two-paired end reads with less than 80 bases overlapping, (3) to trim off the

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barcodes and primers. Taxonomic classifications of the effective sequences were

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carried out using the RDP Classifier (Version 2.4) with a set confidence threshold of

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80% to assign the sequences to different taxonomy levels. The raw reads have been

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deposited into the NCBI short-reads archive database (Accession Number:

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SRR1174196).

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Statistical analysis

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The indices of Shannon-Wiener and Pielou evenness were calculated to assess the

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bacterial diversity. Detrended correspondence analysis (DCA) was performed to

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examine the overall variation among bacterial communities of these 18 samples. All

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the statistical analyses were performed using the VEGAN package in R (v.2.15.1;

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http://www.r-project.org/).

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Two molecular ecological network (MENs) were constructed using the online MENA

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pipeline by following these steps 23, 27. First, the MiSeq sequencing data were used to

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construct MENs. The relative proportions of sequence numbers of individual OTUs


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were used for subsequent Pearson correlation analysis. Second, the correlation matrix

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was then converted to a similarity matrix, which measures the degree of concordance

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between the abundance profiles of OTUs across different samples by taking the

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absolute values of the correlation matrix 28. Third, an adjacency matrix encoding the

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connection strength between each pair of nodes was derived from the similarity

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matrix by applying an appropriate threshold, st, which was defined using the random

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matrix theory (RMT)-based network approach 29, 30. Fourth, the modules were

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detected by the fast greedy modularity optimization 31, 32. Then the modularity value

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of each network (M) was calculated as previously described 32, which is used to

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describe how well the modules are separated.

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For network comparison, random networks corresponding to all MENs were

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constructed using the Maslov-Sneppen procedure 33. For each network, a total of 100

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randomly rewired networks were constructed and all of the network indexes were

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calculated individually. Then, the average and standard deviation for each index of all

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of the random networks were obtained. A standard Z or t test was employed to

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determine the significance of network indexes between the MENs and random

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networks and across different experimental conditions. The Cytoscape 3.2.1 software

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was used to visualize the network graphs.

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RESULTS AND DISCUSSION

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The stability of CuO NPs



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The hydrodynamic particle size distribution in deionized water and wastewater was

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showed in Fig. S2. A significant aggregation of the CuO NPs was found in both two

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liquid media and the average sizes were 284 (deionized water) and 336 nm

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(wastewater), respectively, indicating the aggregation in wastewater was little higher

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than in deionized water. Additionally, the average zeta potential values of the

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dispersions were -25.8 mV and -24.6 mV. These values are the typical threshold range

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that separates unstable dispersions with low charged surfaces from stable dispersions

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with highly charged surfaces 3.

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Effects of CuO NPs on nutrient removal from wastewater

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During the study period, the average influent and eluent CuO concentrations were

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0.99 and 0.31 mg/L, respectively, indicating that an average retention of 69% inside

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the reactors (Fig. S3). Analysis of acid-digested samples showed that the

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accumulation of CuO NPs in biosolids increased from 0.21 to 11.3 mg CuO/g volatile

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suspended solids (VSS) during the operating period.

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As shown in Fig. S4, the effluent COD and NO3−-N concentrations in the presence of 1

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mg/L CuO NPs were relatively stable, similar to those of the control over a period of

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180 days. However, the effluent concentrations of NH4+-N and TP in CuO SBR

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obviously changed with increasing exposure time. The effluent NH4+-N increased

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abruptly on day 22 and reached the maxim of 7.5 mg/L on day 31. After day 31,

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NH4+-N fluctuated between 5.3 and 7.5 mg/L. The average effluent concentration of


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NH4+-N during the last 30 days was 6.8 mg/L, remarkably higher than that in the

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control (0.3 mg/L). After day 40, the effluent TP concentration showed a clear

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increasing trend and reached 2.8 mg/L at day 70. After day 70, the TP concentrations

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fluctuated between 0.9 and 2.6 mg/L. The average TP removal efficiency during the

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last 30 days was 63%, remarkably lower than that in the control (91%). This indicated

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that long-term exposure to CuO NPs had adverse effects on phosphorus removal in

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activated sludge system.

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Previous studies have showed that some metallic nanoparticles exposure had adverse

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impacts on a biochemical process. In a lab-scale anaerobic bioreactor, Otero-Gozalez

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et al. 3 found that long-term exposure to 1.4 mg/L CuO NPs caused severe toxicity

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and reduced the acetoclastic methanogenic activity by more than 85%. ZnO NPs has

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also been demonstrated to inhibit nitrogen and phosphorus removal in activated

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sludge system 15. In the coming text the reasons of the effect of CuO NPs on

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biological nitrogen and phosphorus removal were further investigated.

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Long-term effects of CuO NPs on the activity of key enzymes

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Biological nitrogen removal from wastewater depends on the successful nitrification

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and denitrification, and these processes are relevant to the activities of some key

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enzymes. Usually, autotrophic AOB uses AMO to catalyze ammonia oxidation, and

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the subsequent oxidation of nitrite to nitrate is carried out with NOR by nitrite

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oxidizing bacteria (NOB) 34, 35. Denitrification is mainly catalyzed by NAR and NIR



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polyphosphate-accumulating organisms (PAOs), which are able to use PPX and PPK

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to perform the anaerobic hydrolysis of polyphosphate and subsequent aerobic uptake

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of phosphorus, respectively 37. Six key enzymes of activated sludge were investigated

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after long-term exposure to CuO NP (Fig. 1). The results showed that long-term

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exposure to 1 mg/L CuO NPs significantly inhibited the activities of AMO and

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NOR(P

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