Article pubs.acs.org/est
Bioreactor Function under Perturbation Scenarios Is Affected by Interactions between Bacteria and Protozoa Ameet J. Pinto and Nancy G. Love* Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, United States S Supporting Information *
ABSTRACT: This study investigated the impact of transient cadmium perturbations on the structure and function of the microbial community in an activated sludge system. The impact of cadmium perturbation on the bioreactor performance, bacterial activity, bacterial community structure, and bacteria-protozoa interactions was examined. The bacterial community exhibited a short-term inhibition following a pulse perturbation of cadmium. Process recovery was associated with an increase in bacterial abundance above the unperturbed control reactor, followed by high biomass activity after the washout of cadmium. This trend was seen for multiple experiments at both laboratory- and pilot-scale. The increase in biomass activity could not be explained by changes in bacterial community structure. Independent experiments showed that the increase in bacterial abundance, and by association biomass activity, was caused by the decrease in the protozoal grazing due to the higher inhibition of ciliated protozoa as compared to bacteria when exposed to cadmium. This paper highlights the importance of expanding the investigative boundaries of the microbial ecology of bioengineered systems to include protozoal grazing, especially under perturbation scenarios.
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INTRODUCTION The activated sludge wastewater treatment process represents an engineered ecosystem with well-defined functional demands. Consistent with the vulnerabilities exhibited by any ecosystem, activated sludge processes experience upsets due to an array of unpredictable environmental changes, including chemical perturbations.1−4 In an effort to assist operators with the development of corrective action strategies that they can use when faced with a process upset event, we have evaluated the mechanistic basis between various chemical stressors and the type of process upset they cause.5,6 This paper reflects a continuation of that work. Though toxin-related process upsets are relatively common,7 many studies about the microbial ecology of bioreactors have primarily focused on steady state systems (e.g., refs 8−10), whereas a few have looked at chemically perturbed systems.11,12 Most of these studies are focused on bacteria and archaea, despite the fact that eukaryotes such as protozoa influence the community dynamics of bacteria in the activated sludge matrix.13 The abundance of protozoa in activated sludge systems can vary between 103−106 per mL.14−16 Although these concentrations represent a small percent of activated sludge biomass, protozoa have a significant impact on the bacterial community within the activated sludge matrix17−19 and can affect bioreactor performance under normal operating conditions, for example, ensuring low effluent turbidity in gravity clarified systems.17 Despite previous studies demonstrating the role of protozoal grazing in activated sludge processes,20,21 there are no studies that investigate how © 2012 American Chemical Society
chemical perturbations affect protozoa−bacteria interactions and the resulting impact on process upset and recovery. Specifically, it is important to understand how the bacterial community responds to perturbations that minimize or eliminate predator grazing over a short-term, pulsed perturbation resulting from a contaminant spill upstream of a wastewater treatment plant (WWTP) from a process control perspective, as it may inform corrective action strategies that operators can employ to minimize the impact of an ongoing upset event. In this paper, we evaluate the impact of a transient perturbation with a model toxin, cadmium, on the process upset and recovery of a nitrifying activated sludge system. Cadmium is an industrially important chemical22 and its impact on bacteria23,24,27 and protozoa14,25 has been investigated separately, making it a reasonably well characterized industrial pollutant. We assess the treatment process performance patterns in response to cadmium perturbations and the probable roles that protozoa, all bacteria (GenBac) and ammonia oxidizing bacteria (AOB) play during the recovery from the perturbation. We use a range of reactor configurations, scales (laboratory to pilot) and perturbation levels during this study, and demonstrate a consistent phenomenon; that bacterial activity increases well above control levels during the Received: Revised: Accepted: Published: 7558
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Table 1. Summary of Cadmium Perturbation Experiments Conducted for All Reactor Configurationsa reactor configuration
experiment type
operational scale
continuous flow
single perturbation
sequencing batch reactor
repeat perturbation single perturbation
laboratory pilot laboratory laboratory
first cadmium perturbation load (mg/g VSS) PR1 = 96 PR1 = 37.5 ± 5b PR1 = 96 SBR-PRlow = 9.5
PR2 = 120 PR2 = 54 ± 6b PR2 = 120 SBR-PRhigh = 19
second cadmium perturbation load (mg/g VSS) N/A N/A PR1 = 101 N/A
N/A N/A PR2 = 138 N/A
replication 2 2 1 2
Perturbations were simulated as an acute shock load of cadmium. Each replicate continuous flow experiment consisted of two perturbed (PR1, PR2) and one unperturbed control reactor. The second perturbation for the Repeat Perturbation experiment was applied after complete recover of PR1 and PR2 to the control levels following the first perturbation (t = 13 days). Each replicate SBR experiment consisted of two perturbed conditions (SBR-PRlow, SBR-PRhigh), two unperturbed control reactors and two positive control salt stressed reactors. bCadmium loads are presented as the average of replicate experiments ± absolute difference between replicate experiments. N/A: Not applicable. a
recovery phase from cadmium shock. Our results collected across the range of reactor systems suggest that the phenomenon with bacterial activity (both GenBac and AOB) correlates with a loss of surface feeding protozoa and an increase in overall bacterial abundance, but does not correlate with a change in community composition.
treatment plant. The pSBR was operated with a six hour cycle including a 15 min fill period, five hour react time, 30 min settling time, and 15 min decant period. The HRT and SRT were maintained at 8 hours and 10 days as was done for the continuous flow experimental systems. After acclimating the biomass and stabilizing the reactor performance over one SRT, the biomass from the parent SBR was distributed into eight 800 mL SBRs which were operated identical to the pSBR. The eight smaller SBRs were subjected to four different treatments (two reactors per treatment): (1) control, (2) SBR-PRlow, (3) SBRPRhigh, and (4) 5 g/L salt spike (in addition to the 1 g/L added to the influent to mimic conditions at the full-scale CMNAS) to selectively inhibit protozoal grazers.18,26 The SBR-PRlow and SBR-PRhigh doses are given in Table 1. Chemical Analyses. For the continuous flow systems, all analyses were conducted three times a day for the first day immediately after the cadmium perturbation, twice each day from the second through fourth day, and once every day until the end of the experiment. For the SBR experiments, samples were collected every 24 h. Influent was characterized daily for soluble (sCOD) and total chemical oxygen demand (COD) and ammonium (NH4+) concentrations. Effluent samples were characterized multiple times each day for sCOD, NH4+, nitrite (NO2−), nitrate (NO3−), alkalinity, total (TSS) and volatile suspended solids (VSS), and total and soluble cadmium concentrations according to Standard Methods,28 with a few exceptions. For the pilot scale experiments, effluent total organic carbon (TOC) (measured instead of COD) and NO3− were estimated by measuring light absorption in the UV-visible spectrum using a STIP:Scan probe (Endress+Hauser Inc.). STIP:Scan-based NO3− estimates were corrected for NO2− interference (SI Figure S2). Biomass samples were analyzed for mixed liquor (MLSS) and mixed liquid volatile suspended solids (MLVSS) according to Standard Methods.28 Biomass Activity Analyses. The intrinsic biomass activity assays29 were conducted in batch mode with high substrate concentrations to determine the maximum rates possible at any given sampling point. Biomass samples were collected from each reactor and aerated for 5−6 minutes to increase the dissolved oxygen (DO) concentration to 6−8 mg/L and transferred to 80 mL bottles. Aliquots of biomass (80 mL) were spiked with 100 mg/L of sCOD solution which was composed of an equivalent blend of carbohydrates, proteins and organic acids, as described previously.1 The rate of oxygen depletion (mg O2/l-hr) was divided by the biomass MLVSS (mg VSS/l) to obtain intrinsic specific oxygen uptake rate (sOURI − mg O2/gVSS-hr). The rate of NO2− generation by AOB was determined by estimating intrinsic specific nitrite generation rate (sNGRI). The sNGRI assays were conducted by transferring 100 mL of freshly collected biomass into a well-mixed
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MATERIALS AND METHODS Bioreactor Setup and Experimental Design. Continuous flow reactor experiments were conducted at both laboratory- and pilot-scales. Both operational scales consisted of three identical reactor trains operated in parallel with an 8 hour hydraulic retention time (HRT) and ten day solids retention time (SRT) which were seeded with inoculum from a full-scale complete mixed nitrifying activated sludge (CMNAS) facility located in Charleston, South Carolina and fed raw wastewater. In order to mimic the hydraulics of toxin flow through the full-scale CMNAS system, each reactor train consisted of a primary clarifier, aeration basin, and secondary clarifier with a total volume of 30 and 260 L (per reactor train) for the laboratory- and pilot-scale systems, respectively (Supporting Information (SI) Figure S1). The pilot-scale experiments were conducted at the full-scale CMNAS system in Charleston, SC allowing access to the same wastewater stream as the full-scale facility. The laboratory-scale experiments were conducted at a research shed in Blacksburg, Virginia and required the addition of 1 g/L NaCl to the influent to simulate saline influent conditions similar to the full-scale facility. Of the three identical reactor trains, one was treated as an unperturbed control (control), whereas the other two reactor trains (PR1 and PR2) were perturbed with cadmium. Two singleperturbation experiments were conducted at each operational scale, that is, four experiments in total. A fifth experiment was conducted at the laboratory-scale and involved the application of a repeat cadmium perturbation. The repeat cadmium perturbation was applied after complete recovery of PR1 and PR2 following complete recovery from the first perturbation event. Recovery was determined by comparing effluent quality and biomass activity in PR1 and PR2 to the unperturbed control reactor. Table 1 summarizes the experimental schedule and the cadmium loads applied to the continuous flow perturbed reactors. A second set of experiments was conducted using sequencing batch reactor (SBR) systems to quantitatively measure the protozoal and bacterial response to cadmium perturbation. A 20 L parent sequencing batch reactor (pSBR) system was seeded with inoculum from the same CMNAS system in Charleston, SC and fed fresh primary effluent (supplemented with 1 g/L NaCl) collected daily from a local wastewater 7559
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Figure 1. Impact of cadmium perturbation on the AOB (A, B, C) and GenBac (D, E, F) communities on the perturbed reactors PR1 and PR2 in comparison to the unperturbed control for one laboratory-scale continuous flow cadmium perturbation event. The cadmium perturbation resulted in increased (A) effluent NH4+ and (D) sCOD concentrations, an increase in (B) AOB and GenBac (E) abundance, and inhibited (C) sNGRI and (F) sOURI levels.
DNA Extraction. Four milliliters of biomass were collected and centrifuged at 8000g for 2 min. The supernatant was discarded and the biomass pellets were stored at −80 °C until further analyses. DNA was extracted using the UltraClean Soil DNA extraction kit (MoBio Inc., Carlsbad, CA) according to the manufacturer’s instructions, with previously recommended modifications to improve DNA yield.31,32 Extracted DNA was aliqouted into several DNAase-free sterile tubes and stored at −80 °C until further processing. DNA quantity and purity was determined spectrophotometrically by measuring absorbance at 260 nm/280 nm using Nanodrop ND1000 (Nanodrop
and aerated batch reactor. Biomass samples were spiked with sodium azide to selectively inhibit the nitrite oxidizing bacteria (NOB) and 30 mg/L NH4+ (as N) as substrate for AOB. The optimum sodium azide dose30 to selectively inhibit NOB was determined prior to each experiment and was consistently found to be 9.8 mg/L for the biomass used in this study. Nitrite accumulation in the sNGRI vessels was monitored at 10 minute intervals for a period of 50 min. The rate of NO2− (mg NO2− as N/l-hr) accumulation was normalized to the biomass MLVSS to obtain sNGRI (mg NO2− as N/gVSS-hr). 7560
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ments as follows. Freshly collected activated sludge samples were thoroughly mixed and a 100 μL sample was spotted on a glass slide and mounted with a glass coverslip. The protozoal community was monitored qualitatively on an AxioSkop 2 (Carl Ziess Microimaging Inc., Thornwood, NY) and visualized at 40× magnification. The ciliated bacterivorous protozoa were further categorized into free swimming, crawling, and stalked ciliates and were manually counted.19,41 Protozoal quantification was conducted in duplicate for each sample.
Technologies, Wilmington, DE). The average mass of DNA extracted from four milliliters of activated sludge for all samples was approximately 16.2 ± 5.6 μg. Quantitative PCR. Quantitative PCR (Q-PCR) was conducted by targeting the 16S rRNA gene. Primer sets Eub338f/Univ518r33 and CTO189F/RT1r34 were used to quantify the 16S rRNA copies per mL of activated sludge for GenBac and AOB 16S rRNA genes, respectively. Q-PCR assays were conducted using a 25 μL reaction volume and Power SYBR Green Chemistry (Applied Biosystems, Foster City, CA) on an Eppendorf Realplex2 thermocycler (Eppendorf, North America). A stock solution of plasmid containing an insert from the 16S rRNA gene of Nitrosomonas europaea ATCC 19718 was serially diluted over a range of 108−102 copies per μL and used to generate a standard curve. Samples were serially diluted thrice and each dilution was analyzed independently. To ensure no contamination of PCR reagents, each Q-PCR assay included triplicate blank reactions, where sterile nanopure water was added into the Q-PCR reaction mix instead of the DNA extract. Each Q-PCR cycle was followed by a melting curve analysis to ensure the absence of unspecific PCR products. Q-PCR efficiency for the AOB-specific and GenBac 16S rRNA targets was 94 ± 1.7% and 98 ± 3.0%, respectively. In order to determine if ammonia-oxidizing archaea (AOA) were present in the system, DNA extracts from inocula for all experiments were tested with the archaeal amoA primers.35 Archaeal amoA gene was not detected in any of the tested samples; hence AOA were excluded from any further analyses. Terminal Restriction Fragment Length Polymorphism (T-RFLP) Analyses. T-RFLP was used to generate fingerprints for the AOB community35 using primer set Eub338f/ Nso1225r.36 For T-RFLP, The forward primer Eub338f was labeled with fluorescent marker 6-FAM at the 5′ primer end. PCR reactions for T-RFLP were conducted in duplicate in a 25 μL reaction volume. The duplicate PCR products were combined and purified using a PCR purification kit (Qiagen, Valencia, CA). The purified products were digested in duplicate, according to manufacturer’s instructions. Each digestion reaction consisted of 7 μL of purified PCR product and 10 units of the Taq1 enzyme.36 Digested products were purified and analyzed on an ABI 3730 XL DNA sequencer at the University of Michigan DNA sequencing core (Ann Arbor, MI). T-RFLP Data Analysis. Fragment data were analyzed using Peak Scanner V1.0 (Applied Biosystems, Foster City, CA) using a threshold of 50 fluorescence units. Replicate profiles were standardized using the constant baseline thresholding method37 and consensus profiles were derived and aligned from standardized replicate profiles using T-Align.38 Drifts in fragment sizes were corrected by comparing sample electropherograms to synthetic controls that consisted of a mix of fragments of known sizes. T-RFLP fragments retained in the final profiles were checked for AOB specificity by using TAPTRFLP analysis.39 T-RFs that were unambiguously associated with non-AOB sequences were eliminated from further analysis. T-RFLP profile similarities/dissimilarities were determined along the sampling time-series using the Bray−Curtis index. Relevant statistical analyses were conducted using Paleontological Statistics (PAST) software40 and Microsoft Excel. Microscopic Analyses. Ciliated protozoa were qualitatively monitored for the continuous flow experiments by observing under a microscope at 40× magnification. Quantitative protozoal measurements were conducted for the SBR experi-
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RESULTS AND DISCUSSION Cadmium Perturbations Increase Bacterial Abundance and Biomass Activity during Recovery. In both pilot- (SI Figure S3) and laboratory-scale (Figure 1) continuous flow activated sludge systems, cadmium perturbations caused complete inhibition for a short time period but quickly recovered. Figure 1A and D show a typical response to a cadmium perturbation to the lab scale system, which temporarily caused treatment to cease as demonstrated by increases in effluent NH4+ and sCOD concentrations to levels found in the influent. However, the effluent quality recovered to unperturbed control levels within a week. During the recovery phase, AOB and GenBac abundance (Figure 1B and E) increased substantially during the recovery phase. The abundance peaked between 7 and 9 days for both AOB and GenBac before declining toward abundance levels in the unperturbed control. Abundance numbers did not recover before the end of the experiment, which lasted just over one SRT. In addition to increased cell abundance, overall biomass and AOB activity (measured via sOURI and sNGRI) increased during the recovery phase and exceeded levels in the control (Figure 1C and F). The sOURI and sNGRI values for the perturbed reactors increased significantly above the unperturbed control reactor (p < 0.05) only after the soluble cadmium concentrations in the bioreactor fell below 1 mg/L (Figure S4). The increase in bacterial abundance, coupled with the increase in both total biomass and AOB activity levels after washout of cadmium, was highly reproducible since it was observed for all 10, independent laboratory- and pilot-scale continuous flow system perturbation experiments (Table 1, more examples in SI Figures S3 and S5). During the process recovery phase (i.e., sNGRIminimum < sNGRI < sNGRIcontrol), the AOB abundance correlated positively with the sNGRI values for the three laboratory-scale experiments (Pearson’s R = 0.7, p < 0.001) and two pilot-scale experiments (Pearson’s R = 0.8, p < 0.05) (SI Figure S6). The sOURI and sNGRI rates returned to levels observed in the unperturbed control approximately one SRT after the cadmium perturbation was applied. We also conducted a qualitative microscopic assessment of the biomass over the course of the laboratory perturbation experiments, and observed a loss of bacterivorous protozoa levels followed by recovery by the end of the experiment (data not shown). Unfortunately, microscopic evaluation was not done in a quantitative way over the course of the continuous flow experiments. The persistent “over-correction” in biomass activity was interesting and we did not find this behavior reported elsewhere. Therefore, we focused on possible reasons for the phenomenon. One possibility was that the cadmium perturbation provided a selective pressure for a subset of bacteria with inherently higher maximum specific growth rates to dominate. To check for this possibility, we evaluated if there were changes in relative dominance among the AOBs. We 7561
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Figure 2. AOB specific T-RFLP profiles for the (A) control reactor, (B) perturbed reactor 1, and (C) perturbed reactor 2 for the repeat perturbation experiment conducted using the laboratory scale continuous flow experimental setup. Cadmium perturbation was applied at t = 0 and t = 13 days. The relative abundance for each T-RF is indicated as a % of the total AOB specific T-RFLP signal.
sOURI relative to the control. Furthermore, the strongest community dynamic observed in all the reactors (including the unperturbed control) was the long-term increase in abundance of TRF1 at the expense of the other three T-RF’s (Figure 2). Therefore, we conclude that the increase in AOB activity relative to the unperturbed control was not due to changes in the community structure of the AOBs. Cadmium Perturbations Resulted in Reduced Protozoal Abundance and a Concomitant Increase in Bacterial Abundance. Since increases in biomass activity and bacterial abundance levels could not be correlated with changes in community structure, we subsequently performed an experiment using SBRs to quantitatively assess whether loss and
focused on the AOB community rather than all bacteria since AOB have a constrained phylogeny,42 limited diversity in bioreactors,43 and a well-defined niche in bioreactor systems, which makes them a manageable target for microbial ecology studies.44,45 Four dominant AOB associated T-RF’s (TRF1 = 106 bp, TRF2 = 382 bp, TRF3 = 485 bp, and TRF4 = 679 bp) were observed in this study.36,39 When the dominant clusters were tracked over time prior to and following cadmium perturbation (Figure 2), a significant but temporary decrease in the relative abundance of TRF3 and TRF4 were observed in the perturbed reactors (Figure 2B and C) and unperturbed control (Figure 2A) reactors. The decrease in abundance of TRF3 and TRF4 occurred 1−2 days before the measured increase in sNGRI and 7562
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Figure 3. Changes in (A) protozoal abundance, (B) GenBac 16S rRNA copy number, and (C) AOB 16S rRNA copy number normalized to the values measured for the control reactor at each time point. All results are from SBR experiments. Changes are reported for the unperturbed control, SBR-PRlow, SBR-PRhigh, and salt stress reactors over time after the perturbation was imposed. Sample at t = 0 is identical for all four reactors. * indicates significant differences from the control at each time point (α = 0.05).
Figure 4. Impact of cadmium stress on the eukaryotic community observed in the SBR experiments. Photos highlight stalked ciliates from unstressed (A, C) and stressed (B, D) bioreactor communities. Heavy metal stress results in (B) decapitation and (D) morphological damage to ciliated heads.
perturbation. The GenBac abundance in SBR-PRhigh and SBRPRlow treatments remained significantly higher than the unperturbed control for 3 and 2 days after their respective treatments (t test, p < 0.05). A salt stressed positive control that causes selective loss of protozoa also had higher GenBac abundance relative to the unperturbed control for 2 days after treatment. In contrast, the AOB abundance in each of the three aforementioned treatments was significantly higher than the unperturbed control for only one day. These results are consistent with changes in bacterial abundance seen with the continuous flow experiment, although bacterial abundance changes were seen within one day in the SBR experiment and within 2 days in the continuous flow experiments. The span of
subsequent recovery of bacterivorous protozoal grazers correlated with patterns of changing AOB and GenBac abundance numbers. The SBRs were perturbed with sublethal concentrations of cadmium that ranged from partial to near complete inhibition of nitrification and caused temporary deterioration in effluent quality followed by a recovery (SI Figure S7), as observed previously with the continuous flow reactors. Concomitant with the performance recovery and as observed with the continuous flow systems, we observed an increase in the bacterial 16S rRNA copy numbers for both the GenBac and AOB communities normalized to the unperturbed control (Figure 3A, B, C, and SI Figure S8) following the cadmium 7563
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bacterial interactions. Predator abundance played a significant role in regulating the GenBac and AOB abundance during cadmium perturbations in the SBR experiments. We observed that despite the presence of cadmium, bacterial abundance increased significantly during the upset and recovery phase (Figure 1 and SI Figures S3, and S5) and that this increase was due to a reduction in predator abundance as observed qualitatively in continuous flow experiments and confirmed by the SBR experiments (Figure 3). The increase in bacterial abundance resulted in increased biomass activities in the continuous flow experiments during process recovery (Figure 1 and SI Figures S3, and S5). Bacteria in activated sludge systems experience constant protozoal grazing pressures and this may result in the constitutive expression of predator-resistance responses, which have been discussed previously.49 For example, genetic pathways may be up-regulated to increase or begin the production of toxins and toxin secretion systems once predatory organisms are detected.50 Additionally, protozoa may also compete with bacteria for soluble organic material.17 The reduction in protozoal abundance may not only free the bacterial community from the burden of investing energy into predator-resistance, but also increase the availability of substrates thus favoring the proliferation of bacterial biomass and activity. For example, we observed similar levels of increase in AOB and GenBac abundance following cadmium perturbation in the SBR experiments; 2.3 ± 0.7 and 2.2 ± 0.6 fold in the SBR-PRhigh reactor for AOB and GenBac on day 1, respectively. This would not be expected based on typically estimated growth rates in activated sludge systems.51 However, Monod growth rate kinetics are typically derived for steady state systems which do not account for changes in bacterial physiology52 and disruptions in protozoa−bacteria interactions under perturbation conditions. Though our discussion of this possibility is speculative, the notion that bacteria use a potential energy allocation strategy merits further investigation, especially in complex ecosystem such as the activated sludge system.
time over which higher abundances were seen in the perturbed reactors were much longer in the continuous flow systems (over a week versus up to 3 days in the SBRs). These differences could be either due to the higher cadmium doses used in the continuous flow system relative to the SBR or differences in biomass physiology and environmental conditions in the different reactor configurations. Nevertheless, the patterns of increased abundance during the recovery before returning to unperturbed control levels are consistent. Both quantitative and qualitative assessments were performed on the protozoal community in the SBRs from all four treatments. The impact of cadmium perturbation on protozoal cells is apparent from microscope images (Figure 4). The cadmium perturbation caused significant morphological changes in several members of the protozoal community, which could be a result of oxidative stress-mediated cell membrane damage46 or metal bioaccumulation.47 Protozoal abundance showed a significant decrease (t test. p < 0.05) in both cadmium-stressed treatments as compared to the unperturbed control (Figure 3C). Their abundance remained lower than the unperturbed control for 3 and 2 day(s) after the SBR-PRhigh and SBR-PRlow treatments, respectively. The positive control salt stressed treatment showed a modest but significant decrease in protozoal abundance relative to the unperturbed control for one day, demonstrating its utility as a positive control. The concentrations of stalked, crawling, and free swimming protozoal populations under each treatment are shown in SI Figure S9. The increase in GenBac and AOB 16s rRNA copy numbers correspond with the decrease in the abundance of ciliated protozoal abundance. The faster return of AOB abundance in the perturbed reactors to the unperturbed control level may indicate that protozoal−AOB interactions are weaker than protozoa−GenBac interactions. Indeed, this is consistent with the stronger correlation observed between protozoa abundance and GenBac 16S rRNA copy number (Pearson’s R = −0.66, p < 0.001), as compared to AOB 16S rRNA copy number (Pearson’s R = −0.49, p = 0.04) (SI Figure S10). This is likely due to the fact that AOB tend to exist primarily as part of the floc structure and in tightly packed microcolonies.43 Therefore, predatory pressures on AOB originating from ciliated protozoa may be relatively dampened due to protection within the floc structure and/or microcolonies. Moreno et al.21 showed that surface feeders are primary consumers of nitrifiers. Consistent with previous observations, AOB abundance was much more sensitive to surface feeders, that is, crawling ciliates (Pearson’s R = −0.5, p = 0.03) and stalked ciliates (Pearson’s R = −0.5, p = 0.02), as compared to free swimming ciliates (Pearson’s R = −0.2, p = 0.4), which exclusively feed on dispersed floc material (SI Figure S11). This is also consistent with observations by Madoni,48 who reported a greater abundance of floc feeders such as crawling and stalked ciliates in nitrifying WWTPs, as compared to free-swimming ciliates. These results show that protozoa play a role in defining the abundance of important functional bacterial groups in activated sludge systems that are recovering from cadmium perturbations. Bacteria−Protozoa Dynamics under Perturbation Scenarios May Indicate an Important Ecological Strategy. Protozoal populations have been long known as excellent indicators of sludge health.41 Further, our study shows that solely focusing on bacterial community structure will not elucidate the functionally relevant dynamics of perturbed bioreactors because of the existence of important protozoal−
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ASSOCIATED CONTENT
S Supporting Information *
Additional information as noted in the text. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*Phone (734) 763-9664; fax: (734) 764-4292; e-mail: nglove@ umich.edu. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This research was supported by funding from the Water Environment Research Foundation and the Department of Civil and Environmental Engineering at the University of Michigan. We thank S. M. Cook, S. Ghosh, S. C. Hardin and L. Raskin for helpful discussions and technical review of this study.
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REFERENCES
(1) Henriques, I. D. S.; Kelly, R. T.; Dalphinais, J. L.; Love, N. G. Activated sludge inhibition by chemical stressorsA comprehensive study. Water Environ. Res. 2007, 79, 940−951. (2) Juliastuti, S. R.; Baeyens, J.; Creemers, C.; Bixio, D.; Lodewyckx, E. The inhibitory effects of heavy metals and organic compounds on
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oxidizing activated sludge by RNA stable isotope probing. Appl. Environ. Microbiol. 2010, 76, 2203−2211. (22) Morrow, H. Cadmium electroplating. Met. Finish. 2000, 98, 210−214. (23) Chandran, K.; Love, N. G. Physiological state, growth mode and oxidative stress play a role in Cd(II) mediated inhibition of Nitrosomonas europaea 19718. Appl. Environ. Microbiol. 2008, 74, 2447−2453. (24) Zarnovsky, L.; Derco, J.; Kuffa, R.; Drtil, M. The influence of cadmium on activated-sludge activity. Water Sci. Technol. 1994, 30, 235−242. (25) Madoni, P.; Davoli, D.; Guglielmi, L. Response of sOUR and AUR to heavy metal contamination in activated sludge. Water Res. 1999, 33, 2459−2464. (26) Salvado, H.; Mas, M.; Menendez, S.; Gracia, M. P. Effects of shock loads of salt on protozoan communities of activated sludge. Acta Protozool. 2001, 40, 177−185. (27) Henriques, I. D. S.; Holbrook, R. D.; Kelly, R. T.; Love, N. G. The impact of floc size on respiration inhibition by soluble toxicants A comparative investigation. Water Res. 2005, 39, 2559−2568. (28) APHA. Standard Methods for the Examination of Water and Wastewater; American Public Health Association/American Water Works Association/Water Environment Federation: Washington, DC, 1998. (29) Grady, C. P. L.; Smets, B. F.; Barbeau, D. S. Variability in kinetic parameter estimates: A review of possible causes and a proposed terminology. Water Res. 1996, 30, 742−748. (30) Ginestet, P.; Audic, J.-M.; Urbain, V.; Block, J.-C. Estimation of nitrifying bacterial activities by measuring oxygen uptake in the presence of the metabolic inhibitors Allylthiourea and Azide. Appl. Environ. Microbiol. 1998, 64, 2266−2268. (31) Chan, J.; Goodwin, P. H. Extraction of genomic DNA from extracellular polysaccharide-synthesizing Gram negative bacteria. Biotechniques 1995, 18, 418−422. (32) Regan, J. M.; Harrington, G. W.; Baribeau, H.; Leon, R. D.; Noguera, D. R. Diversity of nitrifying bacteria in full-scale chloraminated distribution systems. Water Res. 2003, 37, 197−205. (33) Ovreas, L.; Jensen, S.; Daae, F. L.; Torsvik, V. Microbial community changes in a perturbed agricultural soil investigated by molecular and physiological approaches. Appl. Environ. Microbiol. 1998, 64, 2739−2742. (34) Hermansson, A.; Lindgren, P. E. Quantification of ammoniaoxidizing bacteria in arable soil by real-time PCR. Appl. Environ. Microbiol. 2001, 67, 972−976. (35) Francis, C. A.; Roberts, K. J.; Beman, J. M.; Santoro, A. E.; Oakley, B. B. Ubiquity and diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 14683−14688. (36) Siripong, S.; Rittmann, B. E. Diversity study of nitrifying bacteria in full-scale municipal wastewater treatment plants. Water Res. 2007, 41, 1110−1120. (37) Dunbar, J.; Ticknor, L. O.; Kuske, C. R. Phylogenetic specificity and reproducibility and new method for analysis of terminal restriction fragment profiles of 16S rRNA genes from bacterial communities. Appl. Environ. Microbiol. 2001, 67, 190−197. (38) Smith, C. J.; Danilowicz, B. S.; Clear, A. K.; Costello, F. J.; Wilson, B.; Meijer, W. G. T-Align, a web-based tool for comparison of multiple terminal restriction fragment length polymorphism profiles. FEMS Microbiol. Ecol. 2005, 54, 375−380. (39) Marsh, T.; Saxman, P.; Cole, J.; Tiedje, J. Terminal restriction fragment length polymorphism analysis program, a web-based research tool for microbial community analysis. Appl. Environ. Microbiol. 2000, 66, 3616−3620. (40) Hammer, O.; Harper, A.; Ryan, P. PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron. 2001, 4, 4−9. (41) Madoni, P. A sludge biotic index (SBI) for the evaluation of the biological performance on activated sludge plants based on the microfauna analysis. Water Res. 1994, 28, 67−75.
the net maximum specific growth rate of the autotrophic biomass in activated sludge. J Hazard. Mater. 2003, 100, 271−283. (3) You, S.; Tsai, Y.; Huang, R. Effect of heavy metals on nitrification performance in different activated sludge processes. J Hazard. Mater. 2009, 165, 987−94. (4) Buitron, G.; Schoeb, M. E.; Moreno-Andrade, L.; Moreno, J. A. Evaluation of two control strategies for a sequencing batch reactor degrading high concentration peaks of 4-chlorophenol. Water Res. 2005, 39, 1015−1024. (5) Love, N. G.; Pinto, A. J.; Hardin, S. C.; Guest, J. S. Determining and Assessing Corrective Action Strategies for Treatment Plants Exposed to Chemical Toxins, Report No. 04-CTS-11S; Water Environment Research Foundation: Alexandria, VA, 2009 (6) Love, N. G.; Henriques, I. D. S.; Kelly, R. T. Upset Early Warning Systems for Biological Treatment Processes: Source and Effect Relationships, Report No. 01-CTS-2; Water Environment Research Foundation: Alexandria, VA, 2005 (7) Love, N. G.; Bott, C. B. a Review and Needs Survey of Upset Early Warning Devices, Report No. 99-WWF-2; Water Environment Research Foundation: Alexandria, VA, 2000 (8) Ayala-del-Rio, H. L.; Callister, S. J.; Criddle, C. S.; Tiedje, J. M. Correspondence between community structure and function during succession in phenol- and phenol-plus-trichloroethene-fed sequencing batch reactors. Appl. Environ. Microbiol. 2004, 70, 4950−4960. (9) Fernandez, A. S.; Hashsham, S. A.; Dollhopf, S. L.; Raskin, L.; Glagoleva, O.; Dazzo, F. B.; Hickey, R. F.; Criddle, C. S.; Tiedje, J. M. Flexible community structure correlates with stable community function in methanogenic bioreactor communities perturbed by glucose. Appl. Environ. Microbiol. 2000, 66, 4058−4067. (10) Hashsham, S. A.; Fernandez, A. S.; Dollhopf, S. L.; Dazzo, F. B.; Hickey, R. F.; Tiedje, J. M.; Criddle, C. S. Parallel processing of substrate correlates with greater functional stability in methanogenic bioreactor communities perturbed by glucose. Appl. Environ. Microbiol. 2000, 66, 4050−4057. (11) Principi, P.; Villa, F.; Bernasconi, M.; Zanardini, E. Metal toxicity in municipal wastewater activated sludge investigated by multivariate analysis and in situ hybridization. Water Res. 2006, 40, 99−106. (12) Principi, P.; Villa, F.; Giussani, B.; Zanardini, E.; Cappitelli, F.; Sorlini, C. The effect of copper on the structure of the ammoniaoxidizing microbial community in an activated sludge wastewater treatment plant. Microbial Ecol. 2009, 57, 215−220. (13) Konopka, A. What is microbial community ecology? ISM. J 2009, 1223−1230. (14) Hoffman, R.; Atlas, R. Measurement of the effects of cadmium stress on protozoan grazing of bacteria (bacterivory) in activated sludge by fluorescence microscopy. Appl. Environ. Microbiol. 1987, 53, 2440−4. (15) Hao, X.; Wang, Q.; Cao, Y.; van Loosdrecht, M. C. M. Measuring the activities of higher organisms in activated sludge by means of mechanical shearing pretreatment and oxygen uptake rate. Water Res. 2010, 44, 3993−4001. (16) Madoni, P.; Davoli, D.; Chierici, E. Comparative-analysis of the activated sludge microfauna in several sewage treatment works. Water Res. 1993, 27, 1485−1491. (17) Curds, C. The ecology and role of protozoa in aerobic sewage treatment processes. Annu. Rev. Microbiol. 1982, 36, 27−46. (18) Moussa, M.; Hooijmanas, C.; Lubberding, H.; Gijzen, H.; van Loosdrecht, M. Modelling nitrification, heterotrophic growth and predation in activated sludge. Water Res. 2005, 39, 5080−5098. (19) Lee, Y.; Oleszkiewicz, J. A. Effects of predation and ORP conditions on the performance of nitrifiers in activated sludge systems. Water Res. 2003, 37, 4202−4210. (20) Moussa, M.; Fuentes, O.; Lubberding, H.; Hooijmans, C.; van Loosdrecht, M.; Gijzen, H. Nitrification activities in full-scale treatment plants with varying salt loads. Environ. Technol. 2006, 27, 635−43. (21) Moreno, A. M.; Matz, C.; Kjelleberg, S.; Manefield, M. Identification of ciliate grazers of autotrophic bacteria in ammonia7565
dx.doi.org/10.1021/es301220f | Environ. Sci. Technol. 2012, 46, 7558−7566
Environmental Science & Technology
Article
(42) Purkhold, U.; Pommerening-Roser, A.; Juretschko, S.; Schmid, M. C.; Koops, H.-P.; Wagner, M. Phylogeny of all recognized species of ammonia oxidizers based on comparative 16S rRNA and amoA sequence analysis: Implications for molecular diversity surveys. Appl. Environ. Microbiol. 2000, 66, 5368−5382. (43) Juretschko, S.; Timmermann, G.; Schmid, M.; Schleifer, K. H.; Pommerening-Roser, A.; Koops, H. P.; Wagner, M. Combined molecular and conventional analyses of nitrifying bacterium diversity in activated sludge: Nitrosococcus mobilis and Nitrospira-like bacteria as dominant populations. Appl. Environ. Microbiol. 1998, 64, 3042−3051. (44) Coskuner, G.; Curtis, T. P. In situ characterization of nitrifiers in an activated sludge plant: Detection of Nitrobacter spp. J. Appl. Microbiol. 2002, 93, 431−437. (45) Wittebolle, L.; Vervaeren, H.; Verstraete, W.; Boon, N. Quantifying community dynamics of nitrifiers in functionally stable reactors. Appl. Environ. Microbiol. 2008, 74, 286−293. (46) Rico, D.; Martín-González, A.; Díaz, S.; de Lucas, P.; Gutiérrez, J.-C. Heavy metals generate reactive oxygen species in terrestrial and aquatic ciliated protozoa. Comp. Biochem. Physiol., C: Comp. Pharmacol. 2009, 149, 90−96. (47) Díaz, S.; Martín-González, A.; Carlos Gutiérrez, J. Evaluation of heavy metal acute toxicity and bioaccumulation in soil ciliated protozoa. Environ. Int. 2006, 32, 711−717. (48) Madoni, P. Estimates of ciliated protozoa biomass in activated sludge and biofilm. Bioresour. Technol. 1994, 48, 245−249. (49) Matz, C.; Kjelleberg, S. Off the hook - how bacteria survive protozoan grazing. Trends Microbiol. 2005, 13, 302−307. (50) Matz, C.; Moreno, A.; Alhede, M.; Manefield, M.; Hauser, A.; Givskov, M.; Kjelleberg, S. Pseudomonas aeruginosa uses type III secretion system to kill biofilm-associated amoebae. ISME J. 2008, 2 (8), 843−52. (51) Grady, C. P. L.; Daigger, G. T.; Love, N. G., Filipe, C., Biological Wastewater Treatment, 3rd ed.; CRC Press: Boca Raton, FL: 2011. (52) Radniecki, T. S.; Ely, R. L. Transcriptional and physiological responses of Nitrosococcus mobilis to copper exposure. J Environ. Eng. 2011, 137, 307−314.
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