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Keywords:

  • activated sludge;
  • carbon nanotubes;
  • microbial community structure;
  • wastewater treatment

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Aims:  Single-walled carbon nanotubes (SWNTs) are likely to become increasingly widespread and yet their environmental impact is not well understood. The purpose of the current study was to evaluate the impact of SWNTs on microbial communities in a ‘sentinel’ environmental system, activated sludge batch-scale reactors.

Methods and Results:  Triplicate batch reactors were exposed to SWNTs and compared to control reactors exposed to impurities associated with SWNTs. Automated ribosomal intergenic spacer analysis (ARISA) was used to assess bacterial community structure in each reactor. SWNT exposure was found to impact microbial community structure, while SWNT-associated impurities had no effect, compared to controls. 16S rRNA gene sequence analysis indicated that dominant phylotypes detected by ARISA included members of the families Sphingomonadaceae and Cytophagacaceae and the genus Zoogloea. ARISA results indicated an adverse impact of SWNTs on the sphingomonad relative to other community members. Changes in community structure also occurred in both SWNT-exposed and control reactors over the experimental time period and with the date on which activated sludge was obtained from a wastewater treatment facility.

Conclusions:  These results indicate that SWNTs differentially impact members of the activated sludge reactor bacterial community.

Significance and Impact of the Study:  The finding that community structure was affected by SWNTs indicates that this emerging contaminant differentially impacted members of the activated sludge bacterial community and raises the concern that SWNTs may also affect the services it provides.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Carbon nanotubes (CNTs) are known for their unique mechanical, electronic and biological properties and have far-reaching potential applications (Masciangioli and Zhang 2003; Boczkowski and Lanone 2007; Chen 2007; Erdem 2007; Rivas et al. 2007; Kislyuk and Dimitriev 2008; Prato et al. 2008; Theron et al. 2008). However, concerns have been raised about the potential toxicity and environmental impacts of CNTs. Several studies have shown that carbon nanomaterials have antimicrobial properties under pure culture conditions (e.g. Kang et al. 2007; Ghafari et al. 2008; Kang et al. 2009). However, the conditions found in complex environmental systems, such as soil, anaerobic sludge and wastewater effluent, may mitigate carbon nanomaterial toxicity to varying degrees (Tong et al. 2007; Kang et al. 2009).

Microbial communities responsible for the treatment of wastewater have been referred to as ‘sentinels’ of environmental impacts of emerging contaminants such as CNTs (Nyberg et al. 2008). These communities serve as the primary receptacles of contaminants in wastewater, and they are likely to be exposed to high levels of contaminants compared to other environmental systems. Although they are engineered systems, they typically represent the first complex microbial community to encounter waterborne contaminants. Any toxicity to micro-organisms exhibited by CNTs has the potential to reduce the efficacy of the biological wastewater treatment processes, which would result in the release of untreated sewage, pathogenic microbes and CNTs into the environment. In addition, the ability of CNTs to strongly adsorb organic matter can reduce the bioavailability and, therefore, microbial degradation of organic pollutants (Farréet al. 2009), which would then effectively bypass the treatment process. In the current study, we assessed the impact of single-walled carbon nanotubes (SWNTs) on the structure of microbial communities from activated sludge, using triplicate batch-scale bioreactors exposed to SWNTs (Yin et al. 2009).

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Experimental set-up

Fresh activated sludge was collected from an aeration basin at the Lowell Regional Wastewater Treatment Facility, Lowell, MA, on 28 June 2007 and 19 July 2007. This facility is designed to treat primarily municipal wastewater through conventional primary and secondary treatment processes. The sludge was transported immediately to the laboratory and aerated for 2 h prior to the experiment to ensure proper dissolved oxygen concentration.

Experimental conditions for batch-scale reactor studies were previously described by Yin et al. (2009). Briefly, six 2·5- l batch-scale reactors placed on a Phipps & Bird, PB-700 Jartester were used to simulate the activated sludge process (Phipps & Bird, Richmond, VA). Each reactor was filled with 2 l of fresh activated sludge with an initial soluble chemical oxygen demand of 20 mg l−1. The sludge was fed with peptone (c. 350 mg l−1) and aerated with an aeration stone (0·6′ diameter × 1′ length) at an air supply rate of c. 0·53 l min−1 and mixed at 60 rev min−1. To distinguish between effects of SWNTs and potential toxic effects of impurities associated with them (such as amorphous carbon and metal catalysts), triplicate SWNT-exposed reactors were compared to triplicate reactors exposed to impurities alone. Because there are virtually no data on realistic SWNT concentrations in wastewater treatment plants, we chose to expose reactor communities to a SWNT concentration that reasonably approximates shock-loading with contaminants such as cadmium and octanol used in other studies (e.g. Henriques and Love 2007). This first experiment (E1) was conducted using fresh sludge collected on 28 June 2007. Three reactors were shock-loaded with presonicated SWNTs at a concentration of 219 mg l−1. The three control reactors were fed with fresh activated sludge, a peptone solution of 350 mg l−1, and the impurities based on the manufacturer’s provided property information of the SWNTs used: amorphous carbon 10·94 mg l−1, magnesium 2·62 mg l−1, cobalt 1·31 mg l−1, molybdenum 0·22 mg l−1 and calcium silicates 0·22 mg l−1. The reaction time in each reactor lasted over 5 h. In addition, the effects of impurities alone were analysed by comparing triplicate reactors exposed to impurities to triplicate control reactors receiving only synthetic feed in a second experiment (E2) using fresh sludge collected on 19 July 2007. SWNTs used in this study consisted of >90% pure CNTs (Sigma-Aldrich, Inc., St Louis, MO, USA) characterized by Raman spectroscopy (Table 1).

Table 1.   Characteristics of single-walled carbon nanotubes (CNTs) used in this study
Purity
 CNTs>90%
 Single-walled nanotubes>50%
Impurities (%)
 Amorphous carbon<5
 Co0·6
 Mg1·2
 Mo0·1
 Silicates0·1
Average outside diameter1–2 nm
Density1·7–2·1
Length5–15 um
Specific surface area>400 m2 g−1

Subsamples for microbial community analysis were taken aseptically immediately after adding SWNTs or impurities (T0), at 1·25 h (T1) after initial exposure and at 5 h (T4). The samples were placed in cryovials and stored at −80°C until further processing.

DNA extraction, PCR and ARISA

Genomic DNA was extracted and purified from 400 μl subsamples of sludge using the FastDNA Spin kit for Soil (MP Biomedicals Inc., Solon, OH, USA). Automated ribosomal intergenic spacer analysis (ARISA)-PCR was performed as previously described (Fisher and Triplett 1999), with minor modifications. Reaction mixtures contained 1× AmpliTaq PCR buffer (Applied Biosystems, Inc., Carlsbad, CA, USA), 2·5 mmol l−1 MgCl2, 400 ng μl−1 bovine serum albumin, 200 μmol l−1 each dNTP, 400 nmol l−1 each primer, 2·5 U of Taq DNA polymerase and 1, 5, 10 or 20 ng of genomic DNA in a final volume of 50 μl. The primers used were 1392F (5′-G [C/A] ACACACCGCCCGT-3′) and 23SR (5′GGGTT[C/G/T] CCCCATTC[A/G]G-3′). The 5′end of primer 1392F was labelled with 6-carboxyfluorescein (6-FAM). The following thermal profile was used for PCR: denaturation at 94°C for 3 min, followed by 30 cycles of amplification at 94°C for 30 s, 56°C for 30 s and 72°C for 45 s, followed by a final extension of 72°C for 7 min. PCR products were analysed by electrophoresis in 1% agarose gels (Ausubel et al. 1997) and were purified using QiaQuick PCR Purification Kits (Qiagen, Inc., Valencia, CA, USA).

Twenty nanograms of each purified PCR product was lyophilized and subjected to automated capillary electrophoresis (CE) analysis in conjunction with a 50- to 1200 -bp size standard labelled with LIZ™ (Applied Biosystems, Inc.) at the Center for AIDS Research, UMass Medical School, Worcester, MA. ARISA conditions were optimized by comparing profiles generated from multiple DNA template amounts (1, 5, 10 or 20 ng per 50 μl PCR) and PCR product amounts (5, 10 or 20 ng PCR product per well). Comparison of these conditions indicated that the highest diversity (species richness and evenness) and signal to noise ratios were achieved using 1 ng DNA template for PCR and 20 ng PCR product for CE analyses, which were used in subsequent analyses.

ARISA profiles were analysed using PeakScanner software (Applied Biosystems Inc.) and processed as described by Brown et al. (2005). The programs Interactive and Automatic Binner were used to bin peaks, with a window size of 3 bp and a shift value (Sh) of 0·1 (Ramette 2009). Peak areas were normalized to total peak area per sample, and peaks representing <1% total peak area for a given sample were considered indistinguishable from background and removed from the analysis. In subsequent analyses, each ARISA peak was considered as an ‘operational taxonomic unit’ (OTU).

Data visualization and ordination analyses were conducted using the packages Ecodist and Vegan (http://vegan.r-forge.r-project.org/) in the R statistical programming environment (Goslee and Urban 2007). Pairwise Bray–Curtis distances between samples were calculated using the Ecodist package, and a hierarchical clustering algorithm with average linkage clustering was used to construct a dendrogram depicting relationships among the samples’ ARISA profiles. Correspondence analysis (CA), which assumes a unimodal relationship between relative abundance (i.e. normalized peak area) and ordination axes, was used to analyse relationships between samples. The R package Vegan was used to determine whether CA ordination axes were correlated with environmental variables. The latter included the experiment from which samples were analysed (E1 for the experiment comparing SWNTs to SWNT-associated impurities, conducted on 28 June 2007; E2 for the experiment comparing SWNT-associated impurities to a control conducted on 19 July 2007); time elapsed from the initiation of the experiment to sampling (0, 1·25, or 5 h); and treatment (SWNTs, associated impurities or feed alone). Categorical variables were set to 0 or 1 depending on the presence of a given variable (e.g. presence or absence of SWNTs or impurities). The ‘envfit’ goodness of fit test with 1000 permutations was used to assess the fit of environmental variables to ordination axes.

Cloning and sequence analysis

To determine the phylogenetic identity of dominant community members, as detected by ARISA, phylogenetic analysis of 16S rRNA genes contiguous with fragments analysed in ARISA was used (Brown et al. 2005). DNA amplicons containing partial 16S rRNA genes and associated intergenic spacer regions were generated from selected activated sludge genomic DNA samples using primers 338F and 23SR (5′-GGGTT[C/G/T] CCCCATTC[A/G]G-3′) (Amann et al. 1990; Brown et al. 2005). The resulting amplicons were cloned using the TOPO TA cloning kit for sequencing with One Shot® TOP10 chemically competent Escherichia coli, as described by the manufacturer (Invitrogen Corp., Carlsbad, CA, USA). Ninety cloned inserts were analysed using ARISA, as described earlier, except that the template DNA for PCR consisted of E. coli cloned cell lysates (obtained by suspending individual colonies in 0·1 mol l−1 Tris–Cl, pH 8·0 and incubating them at 99˚ C for 2 min). ARISA peaks from cloned inserts were considered to match OTUs from environmental community ARISA patterns if their peak size was placed within the same 3- bp bin as a given OTU from environmental samples.

At least one cloned insert representative of each ARISA OTU was sequenced in both directions by Beckman Coulter Genomics Inc. (Danvers, MA, USA) with M13 primers. Vector and primer sequences were trimmed, trimmed sequences were aligned to the Silva database, and phylogenetic relationships among aligned sequences and their 40 nearest neighbours in the Silva database were analysed using arb (Ludwig et al. 2004; Pruesse et al. 2007). Trimmed sequences were deposited in GenBank under accession numbers HM205112HM205114.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Effects of SWNTs and their associated impurities

Analysis of ARISA profiles revealed several differences between bacterial community structure in batch reactors exposed to SWNTs for 5 h when compared to those exposed to associated impurities alone. For example, the relative peak areas of dominant OTUs represented by peaks 419, 794 and 839 bp were significantly different in communities exposed to SWNTs vs those exposed to SWNT-associated impurities (Fig. 1). Similarly, a chi-square goodness-of-fit test of CA axes revealed that the effect of SWNTs on community structure was significant (P = 0·043), while exposure to impurities alone was not (P = 0·604). To assess the effect of SWNTs without interference from the strong effects of time and experiment, CA ordination was repeated with only the time T4 samples from the experiment comparing SWNTs to impurities alone (E1). A statistically significant effect of SWNTs was observed (< 0·001), while a similar analysis of the effects of impurities alone (CA with experiment E2, time T4 samples) revealed no effect (P = 0·316), as was also evident from direct inspection of ARISA profiles (Fig. 1). Samples taken after only 1·25-h exposure (time T1) revealed no clear differences in ARISA profiles between either SWNT- and impurities-exposed reactors or between reactors exposed to impurities and control reactors), indicating that exposure for 1·25 h was insufficient for SWNT effects to be detected via the approach used here.

image

Figure 1.  Automated ribosomal intergenic spacer analysis profiles of activated sludge bacterial communities exposed to single-walled carbon nanotubes (SWNTs), their associated impurities or synthetic feed alone at the end of the experiments (T4). Comparisons were made between SWN0 and impurities-exposed (IM) reactors during one experiment (designated E1; panel a) and between impurities-exposed and control reactors receiving feed alone (F) in a second experiment (E2; panel b). Means and standard deviations of relative peak areas from triplicate batch reactors are shown. (a) (inline image) E1_T4_IM and (inline image) E1_T4_SWNT. (b) (inline image) E2_T4_IM and (inline image) E2_T4_F.

Download figure to PowerPoint

Both hierarchical clustering and CA of all samples revealed strong effects of the amount of time elapsed prior to sampling (0, 1·25, or 5 h) and the date of the experiment (Fig. 2). Baseline (T0) communities for E1 and E2 were fairly similar. However, these communities diverged substantially over the short experimental time period of 5 h, with the resulting communities sharing only 14/29 total OTUs and 4/9 total ‘dominant’ (considered here to be those with average relative peak areas >5%) OTUs.

image

Figure 2.  Hierarchical clustering analysis and heatmap of Bray–Curtis distances among samples taken from the first and second experiments (E1 and E2, respectively), at times 0, 1·25 and 5 h (T0, T1 and T4, respectively), and exposed to single-walled carbon nanotubes (SWNTs), impurities or feed alone (SWNT, IM or F, respectively).

Download figure to PowerPoint

Three of the OTUs found in environmental samples were identified among the 90 cloned inserts analysed here. These included peaks corresponding to 419, 740 and 812 bp (Fig. 1). Phylogenetic analysis placed these OTUs within the families Sphingomonadaceae (419 bp) and Cytophagaceae (740 bp) and the genus Zoogloea (812 bp) (Table 2). Two representative of OTU 812 were sequenced and found to be identical. The closest relatives of the sequences representing OTUs 419, 740 and 812 were as follows: an uncultivated Sphingomonadaceae bacterium from snow (97·1% similarity); an uncultivated Cytophagaceae bacterium from activated sludge (89·5% similarity); and Zoogloea resiniphila, a denitrifier isolated from activated sludge (99·8% similarity).

Table 2.   Closest relatives and similarity values for cloned 16S rRNA genes matched to given ARISA operational taxonomic units (OTUs)
ARISA OTU matched to sequence (bp)Closest relativeSequence similarity to closest relative (%)
  1. ARISA, automated ribosomal intergenic spacer analysis.

419Sphingomonadaceae bacterium N DQ49724197·07
740Uncultured bacterium from activated sludge (EU283373)89·52
812Zoogloea resiniphila isolated from activated sludge (AJ505854)99·75

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

While SWNTs have the potential to be highly toxic to microbial cells, their impact under the complex abiotic and biological conditions found in environmental microbial communities remains poorly understood. This study revealed changes in microbial community structure in activated sludge batch reactors exposed to SWNTs, while no effects of SWNT-associated impurities were detected. Yin et al. (2009) analysed bulk parameters and performance from the SWNT-exposed batch reactors described here and similarly found that SWNTs, but not their associated impurities, had several effects on sludge performance. These effects included increased organic carbon removal primarily through organic carbon adsorption, less negative surface charges of activated sludge flocs and improved sludge settleability (Yin et al. 2009). Other parameters such as pH, dissolved oxygen, specific resistance to filtration and relative hydrophobicity were not significantly impacted (Yin et al. 2009). These findings suggest that SWNTs impacted community structure through toxicity to some community members, by reducing organic carbon bioavailability and/or by altering floc properties.

The fact that SWNT effects on microbial community structure were detected was especially interesting given that, unlike some previous studies, the experimental conditions used did not maximize SWNT-cell interactions. For example, an assay for cytotoxicity developed by Kang et al. (2007) relies on drawing planktonic cells onto a filter that is coated with nanoparticles and observing the resulting effects on cellular membrane integrity over time. Under these conditions, direct cell-nanoparticle contact is artificially induced and CNTs demonstrated high levels of toxicity to Gram-negative (E. coli and Pseudomonas aeruginosa) and, to a lesser extent, Gram-positive (Staphylococcus epidermis and Bacillus subtilis) cells (Kang et al. 2009). In contrast, here, SWNTs were added to activated sludge bioreactors in suspension, making SWNT-cell contact much less likely. In addition, the presence of extracellular polymeric substances (EPS) and high concentrations of DOC (dissolved organic carbon) in the batch reactors used here may have mitigated SWNT toxicity to some extent, as CNTs are likely to become embedded in EPS and thereby prevented from coming in direct contact with cell membranes (Neal 2008; Luongo and Zhang 2010). Lastly, the exposure time was kept short to avoid confounding effects of starvation and/or accumulation of waste products in closed-system batch reactors. Despite the use of short incubation times, changes in community structure with both SWNT exposure and time over the course of the experiment were found (Figs 1 and 2). Previous studies have shown that cellular inactivation increased with time of exposure (Kang et al. 2009), indicating that use of longer incubation times in continuous reactors may increase effects of SWNTs on community structure.

Phylogenetic analysis of cloned inserts that were matched to ARISA peaks revealed the presence of three phylogenetic groups that are responsible for important functions in activated sludge communities, including the members of the families Sphingomonadaceae (OTU 419) and Cytophagaceae (OTU 740) and the genus Zoogloea (OTU 812) (Manz et al. 1996; Neef et al. 1999; Juretschko et al. 2002; Wagner et al. 2002; Li et al. 2008). Of these, the sphingomonad (OTU 419) showed a trend of decreased relative peak intensity with exposure to SWNTs (Fig. 1), indicating an adverse impact of SWNTs on this group compared to other community members. Within wastewater treatment, microbial communities, sphingomonads are thought to have wide metabolic diversity, are capable of degrading some xenobiotics and contribute to the formation of flocs (Neef et al. 1999; Wagner et al. 2002). Although directly measuring these parameters was beyond the scope of this study, the potential for negative impacts on SWNTs on these microbial functions deserves further attention.

Differences in the ‘baseline’ (T0) community structure from one sampling date to another corroborate results obtained by Wittebolle et al. (2005), who observed that large community shifts occurred over a period as short as a few days in a given wastewater treatment plant and that community structure was related to performance of biological treatment. These findings underscore the need to analyse microbial community structure when assessing the effects of emerging contaminants on environmental systems, as differences in the starting community composition may alter the observed impacts on community performance. Initial differences in community structure may also be amplified over the course of a given experiment as population growth, decline and response to contaminants lead to population shifts over time. Together, these results suggest that routine monitoring of the microbial community may be necessary to predict outcomes of contaminant exposure.

In conclusion, our results indicate that the structure of activated sludge microbial communities is impacted by exposure to SWNTs, even when such exposure is limited to a short time period, and that these effects were not because of impurities associated with SWNTs. Community shifts found here indicated that SWNTs differentially affect microbial species, as has been found under pure culture conditions (Kang et al. 2009). These results raise the concern of SWNT impact on biological functions carried out by the activated sludge process.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

This work was supported by grant NUE-0532551 from the National Science Foundation, a grant from the Massachusetts Water Resources Research Center, and grant from the UMass Lowell Committee of Federated Centers and Institutes. We also thank Yexin Yin and Lauren Luongo for technical assistance, Dr E. Kittler for capillary electrophoresis analysis of ARISA PCR products and Dr S. Nguyen for assistance in optimizing ARISA methods.

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  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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