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Applied and Environmental Microbiology, December 2005, p. 8481-8490, Vol. 71, No. 12
0099-2240/05/$08.00+0 doi:10.1128/AEM.71.12.8481-8490.2005
Copyright © 2005, American Society for Microbiology. All Rights Reserved.
School of Civil Engineering and Geosciences, University of Newcastle, Newcastle upon Tyne NE1 7RU,1 Brixham Environmental Laboratory, AstraZeneca Global SHE, Brixham, Devon TQ5 8BA,2 Yorkshire Water Services, Western House, Halifax Road, Bradford, West Yorkshire BD6 2LZ,3 Department of Microbiology and Immunology, University of Leicester, Leicester LE1 7RH, United Kingdom4
Received 3 June 2005/ Accepted 8 September 2005
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Each of these methods has particular advantages and disadvantages. For example, FISH allows direct identification and quantification of microorganisms in environmental samples and, because of its ability to measure individuals accurately, represents the "gold standard." However, FISH has a low sample throughput and is thus too slow for routine analysis. In contrast, PCR-based methods allow high sample throughput, which may be required for statistically valid spatial and temporal analysis. However, PCR-based methods are prone to biases (typically introduced during nucleic acid extraction and amplification) that may make quantification of natural bacterial populations difficult (see, e.g., references 20, 39, 39a, and 43). In addition, relatively pure preparations of DNA are required to avoid problems of inhibition of DNA polymerases. Quantitative dot blots and microarrays, on the other hand, often require the use of radioactive isotopes or expensive equipment and consumables.
An alternative sensitive and specific method is a sandwich hybridization assay for the detection of rRNA, developed by Wicks and coworkers (46). The RNA assay is based on hybridization of a target rRNA with differentially labeled capture and detector probes. It allows quantification of specific rRNA species from crude preparations of RNA. Furthermore the RNA assay is amenable to a 96-well plate format, opening the opportunity for automated analysis of large numbers of samples, which would allow rapid quantitative high-throughput analyses. Such analyses are required for generating the long time series needed for understanding the ecology and population dynamics of organisms that mediate many important biological processes, such as nitrification in wastewater treatment plants (WWTPs).
Nitrification is a two-stage process in which ammonia, derived from degraded organic nitrogenous compounds, is oxidized into nitrite and then into nitrate. It is an essential component of the nitrogen cycle and occurs in many environments, including soils, estuaries, and WWTPs. The process is largely mediated by two groups of microorganisms, the autotrophic betaproteobacterial ammonia-oxidizing bacteria (AOB) and the autotrophic nitrite-oxidizing bacteria, where the AOB are responsible for the rate-limiting step of ammonia oxidation.
In the present study, the primary format of the RNA assay developed by Wicks et al. was retained (46), but the assay was extensively modified, developed, and optimized for the specific detection and quantification of betaproteobacterial AOB. Autotrophic AOB are ideal candidates for such an approach, because they form a coherent phylogenetic group that performs a distinct metabolic and process function. To demonstrate the utility of the assay, it was used to measure the relative amounts of AOB 16S rRNA in two WWTPs, one exhibiting good nitrification performance and the other exhibiting poor nitrification.
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Wastewater treatment plant samples.
Samples of activated sludge were collected from two wastewater treatment plants in the United Kingdom. One of the reactors was known to be nitrifying effectively at the time of sampling (average 99.7% ammonia removal), whereas the other reactor was suffering from poor nitrification (average 23% ammonia removal). Activated-sludge samples were taken from each reactor, preserved immediately in 50% ethanol, and stored at 20°C (26). FISH was performed on these samples as previously described to independently validate the relative abundance of AOB in these samples (11).
RNA extraction.
Total RNA was extracted from cultures and activated-sludge samples using a FastRNA extraction kit (blue matrix; Q-biogene, Fisher Scientific UK) and a Ribolyser (Hybaid Ltd., Middlesex, United Kingdom) according to the manufacturers' instructions. Six or more extracts were pooled, and the concentration and purity of RNA were determined by measuring the absorbances at 260 nm and 280 nm. The amount of RNA was expressed as the number of 16S rRNA molecules. The percentage of 16S rRNA in RNA extracts (5S, 16S, and 23S rRNA, tRNA, and mRNA) was estimated to be 27% (31). In preparations of purified 16S-plus-23S rRNA from Escherichia coli MRE600 (Roche Diagnostics, United Kingdom), the 16S rRNA was estimated to account for 34% of the total RNA (31). All the usual precautions were utilized to prevent degradation of RNA (46).
RNA assay.
The RNA assay is a three-step sandwich hybridization assay (hybridization, capture, and detection) that uses a pair of labeled oligonucleotide probes, one to capture the rRNA and another to detect the captured target rRNA (Fig. 1). Helper probes were included in certain assays to improve the accessibility of some target sites on the rRNA. The assay was extensively modified from the procedure developed by Wicks and coworkers (46). Two main modifications were made to adapt the assay for use with AOB and environmental samples. Solid-phase capture of the probe-target hybrids on streptavidin-coated 96-well plates was employed in the original assay to capture target rRNA (45, 46). In the modified assay, capture using suspensions of paramagnetic beads was used to improve the kinetics of the reaction and reduce hybridization time. Furthermore, the detection method employed by Wicks et al. (46), which required extensive purification of the reporter substrate needed for the final detection step, was changed from a direct to an indirect detection method. In the original assay, the probe was conjugated to an enzyme that directly catalyzed the detection reaction, while in the modified method, a digoxigenin (DIG)-labeled probe was indirectly detected using an anti-digoxigenin antibody conjugated to an enzyme that catalyzed the final detection reaction. Furthermore, the assay was optimized extensively, the specificity of the assay was more rigorously tested, and its utility for measuring the abundance of a specific bacterial populations in complex environmental samples was demonstrated.
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FIG. 1. Schematic diagram of the sandwich hybridization assay. DIG, digoxigenin; B, biotin, AP, alkaline phosphatase-conjugated anti-digoxigenin; RNA, extracted RNA; CDP STAR, chemiluminescent substrate.
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TABLE 1. Oligonucleotide probes used in this study
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Capture.
Following hybridization, the reaction products were chilled on ice. Hybridization reaction products were transferred to 96-well plates containing the strepavidin-coated magnetic beads and incubated with gentle mixing on an orbital shaker at room temperature for 90 min (Fig. 1, Capture). The beads were captured using the magnet, the supernatant was removed, and the beads were washed twice with 100 µl of AB with gentle mixing using an orbital shaker. The beads were recaptured, using the magnet, and the supernatant was removed. AB (100 µl) was added to the beads while they were on the magnet, and the beads were incubated for 3 min. The AB was removed, and the beads were resuspended in 100 µl of blocking reagent 2 (2x Denhardt's reagent prepared in AB) and mixed gently for 5 min.
Detection.
The beads were recaptured, and the blocking reagent was replaced with 100 µl anti-DIG antibody labeled with alkaline phosphatase (1/500 dilution; Roche Diagnostics, Germany). The samples were incubated, with gentle mixing, for 30 min. After incubation, the beads were recaptured and washed three times with 100 µl of AB (two washes on the magnet, i.e., without mixing, and one wash with mixing). The beads were captured and resuspended in 50 µl of AB and 100 µl of 0.4 mM CDP-Star Chemiluminescent Substrate with Sapphire-II Enhancer (Applied Biosystems, United Kingdom). The 96-well plate containing the assay reaction mixtures was placed in a luminometer [MicroLumat LB 96 P; Berthold Technologies (U.K.) Ltd.], and the light produced per second per well was measured every 3 min for a total of 1 h. Data were reported as relative light units (RLU) for the total integrated light output (Fig. 1, Detection). The entire procedure takes about 1 day to complete.
Wastewater treatment samples (approximately 4 to 6 ml) and culture preparations were analyzed in triplicate; positive and negative controls were always included. The concentration of RNA in extracts from these samples was determined spectrophotometrically, and the number of 16S rRNA molecules was calculated. The same number of 16S rRNA molecules from each sample was used for the assay. Furthermore, a parallel assay was always conducted using a probe set targeting the 16S rRNA of most bacteria to ensure that equivalent amounts of bacterial 16S rRNA were present in all assays. Purified 16S and 23S rRNA from Escherichia coli MRE600 (Roche Diagnostics, United Kingdom) was used as a positive control. A range of negative controls was included in the assay. These controls were used to test for different sources of error. A magnetic-bead-only control (BO) (no probes or RNA, only magnetic beads treated in the same way as the samples) was used to test for background signal; a probe-only control (PO) (probes and magnetic beads treated in the same way as the samples), a nonbacterial probe (NonBact338 or NONEUB [26]) control (sample hybridized with a NonBact338 detector probe), and a yeast (Saccharomyces cerevisiae) RNA control (i.e., yeast RNA instead of sample RNA) were used to test for nonspecific binding.
During optimization of the assay, slight modifications of the procedure described above were made. These are detailed in Results and Discussion.
Probe design.
Probes targeting 16S rRNA from the majority of bacteria were designed (Table 1) and checked for self-complementarity using PRIMROSE v. 1.1.7 (4) and the RDP database (10). Many of the probes used in this study were modifications of existing probes and primers designed to target all bacteria.
Statistical analysis.
All quantitative data were checked for normality and, where appropriate, transformed using values determined by the Box-Cox transformation (7). Analysis of variance (Tukey's pairwise comparisons) and comparison of means (parametric [t test] or nonparametric [Mann-Whitney test]) were carried out using Minitab v. 11 (Minitab Inc.).
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Optimization of sensitivity. (i) Reduction of background (noise).
Background noise is produced by nonspecific hybridization, or binding of the probes, RNA, and/or anti-DIG antibody to other components in the assay (e.g., the magnetic beads, or the wells of the 96-well plate) (30). To reduce nonspecific hybridization, the washing, blocking, and hybridization steps were optimized.
(ii) Washing.
Other researchers have found that increasing the number and length of hybridization washes leads to a reduction in signal intensity without improvement in specificity (see, e.g., references 8 and 24). Indeed, we found that increasing the washing steps (length and number of washes) appeared to have no effect on the background signal. However, an increase in the frequency of washes resulted in a greater variation in the signal intensity (e.g., coefficients of variation were 7.4% for 5 washes and 47% for 15 washes), most likely due to a loss of magnetic beads.
(iii) Blocking.
The utilization of blocking agents during hybridizations is commonplace (see, e.g., references 3 and 46). Blocking is employed to reduce nonspecific binding by the addition of a mixture of polymeric molecules. These "sticky" polymeric molecules block potential sites for nonspecific binding by, for example, occupying the site through electrostatic interactions prior to the addition of the assay components. A blocking reagent was added in the hybridization reaction to reduce nonspecific probe binding. Optimal blocking of the beads was achieved using salmon testis DNA and Denhardt's solution prior to the capture step. Additionally, in a modification of the method of Wicks et al. (46), we blocked with Denhardt's solution alone after the capture step. Subsequently, salmon testis DNA and Denhardt's solution were also included in the hybridization step, which is normal practice in many hybridization protocols (see, e.g., references 3 and 46). The signals from the bead-only and probe-only controls were reduced by the addition of a blocking reagent to the hybridization reaction (signal from PO without blocking, 2.11 x 109 ± 0.021 x 109 RLU; signal from PO with blocking, 1.9 x 109 ± 0.032 x 109 RLU [P << 0.05]).
(iv) Negative controls.
In contrast to similar studies, we used a broad range of negative controls to ensure that the signal obtained during the assay was due to the specific interaction of the probes with the target rRNA. The negative controls included an oligonucleotide probe that should not hybridize to the target rRNA (NonBact338, commonly used in FISH [26]), BO (mentioned above), PO (mentioned above), and broad-specificity negative-control RNA (e.g., yeast RNA). The different negative-control procedures gave different levels of background signal (Fig. 2). The highest background was generally observed for the probe-only control and for control hybridizations containing nontarget rRNA (S. cerevisiae). The capture and detector probes were examined for complementarity, and a maximum match of 4 bp was observed (in the middles of the probe sequences). Hence, the probes are unlikely to hybridize with each other under the assay conditions. Nevertheless, the signal from probe-only controls was frequently higher than the signal from reaction mixtures containing low concentrations of target rRNA (108 to 109 molecules), which otherwise showed a smooth decrease in signal toward background with the bead-only control (see, e.g., Fig. 4A). The presence of any RNA (whether target or nontarget) in the reaction mixture apparently blocked nonspecific binding of the probe to the paramagnetic beads, leading to a lower background signal. However, it must be noted that the PO control signal was inconsistent and highly variable, and the assay would never be used with samples that contain no RNA. Nucleic acid preparations may also contain trace amounts of naturally occurring biotin, or there may be nonspecific interactions between the biotin-labeled capture probe and the DIG-labeled detection probe, or between the DIG-labeled detection probe and the magnetic beads, when RNA is not present. This could give rise to the background signal seen in the PO negative control. However, the probe-only control may be inappropriate for the actual conditions in the RNA assay reaction, since any biological sample analyzed is likely to contain at least some RNA. It is interesting, however, that even with salmon testis DNA in the assay mix, some form of nonspecific binding of the detector probe to the beads occurred. This is all the more surprising given that the presence of nontarget RNA (yeast RNA in this case) markedly reduced the nonspecific binding of the detector probe (Fig. 2). This suggests that the blocking properties of RNA are quite different from those of DNA.
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FIG. 2. Background signal from a range of controls relative to signal produced with low concentrations of rRNA. NB, NonBact probe control (nonsense probe used with all other reagents); Yeast, broad-specificity control. BO and PO are described in Materials and Methods. Relative light units represent the total integrated light output (light produced per second per well measured every 3 min for 1 h). Error bars, 95% confidence intervals.
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FIG. 4. Response from a twofold dilution series of target 16S rRNA molecules from E. coli (A) and nitrifying activated sludge (B) using the RNA assay with a probe set consisting of probes S-D-Bact-0343-b-S-17-B, S-D-Bact-0518-a-S-18-D, and S-D-Bact-0320-b-S-18-H. Open diamonds, BO (see Materials and Methods). Relative light units represent the total integrated light output (light produced per second per well measured every 3 min for 1 h). Error bars, 95% confidence intervals.
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(v) Enhancement of the signal.
To increase the intensity of the signal, the concentrations of the assay components (e.g., beads, probes, anti-DIG, and CDP-Star) and the combinations of probes used were optimized. The optimized concentrations for each of the reagents were the equivalent of 500 AU (A600) for the magnetic beads, 1 x 1012 molecules of each probe, 1/500 dilution of the anti-digoxigenin-alkaline phosphatase preparation (Roche Diagnostics, Germany), and 100 µl of CDP-Star Chemiluminescent Substrate with Sapphire-II Enhancer (0.4 mM; Applied Biosystems, United Kingdom). The lengths of the hybridization, capture, and detection stages in the assay have been optimized previously (45, 46), and the optimal conditions were confirmed in this study (optimized times, 30 min, 90 min, and 30 min for hybridization, capture, and detection, respectively). However, the most significant factor in increasing signal intensity was a change in the combination of probes used (Fig. 3). The probes initially employed were those used by Wicks et al. (46). The target sites for these probes were distant from each other on the rRNA molecule (capture probe S-D-Bact-0320-a-S-40-B [target region, bases 320 to 359 by E. coli numbering] and detector probe S-D-Bact-1524-a-S-17-D [target region, bases 1525 to 1541 by E. coli numbering] [Table 1]). Indeed, the target site for probe S-D-Bact-1524-a-S-17-D is at the very end of the rRNA molecule, making the target region more prone to degradation by exoribonucleases. Additionally, the target sequences for probes S-D-Bact-0320-a-S-40-B and S-D-Bact-1524-a-S-17-D are not universally conserved. Furthermore, it has been reported previously that an important factor for achieving positive hybridization in microarrays using two probes is the proximity of the oligonucleotide probe target sites on the rRNA molecule (38). Therefore, capture, detector, and helper probes that targeted all bacteria were designed: some targeted adjacent locations on the 16S rRNA molecule, and others targeted regions distant from each other. Different combinations of these probes were examined (Table 1).
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FIG. 3. Response from a twofold dilution series of target 16S rRNA molecules (E. coli 16S and 23S rRNA) using the RNA assay with two different probe sets. Open squares, capture probe S-D-Bact-0320-a-S-40-B and detector probe S-D-Bact-1524-a-S-17-D (1,221 bases apart; probes developed by Wicks [45]). Closed squares, capture probe S-D-Bact-0343-b-S-17-B and detector probe S-D-Bact-0518-a-S-18-D (159 bases apart), with unlabeled helper probe S-D-Bact-0320-b-S-18-H (probes developed in this study). Yeast, broad-specificity control. For BO and PO, see Materials and Methods. Relative light units represent the total integrated light output (light produced per second per well measured every 3 min for 1 h). Error bars, 95% confidence intervals.
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In a previous study using microarrays to analyze rRNA sequences, Small and coworkers (38) found that probes in close proximity (1 to 3 bp) produced a more specific and reliable signal. These workers suggested that this was due to secondary-structure interactions. Probes in close proximity are thought to open up the region of hybridization on the rRNA molecule, thus increasing the accessibility of the target site. Small et al. (38) suggested the inclusion of chaperone probes (cf. helper probes [16]) to prevent "incorrect" secondary structure. Helper probes should be designed to anneal at a similar or higher temperature than the capture and detector probes and to have similar or broader specificity than the capture and detector probes (42). However, in a similar study it was found that probes located in immediate proximity to one another resulted in a high degree of binding of probes to nontarget RNA sequences (9). This phenomenon was thought to be due to "base-stacking effects" (9). To reduce base-stacking effects, these workers used probes separated by 10 to 14 bp. In this study, we obtained similar signals with probes in close proximity (5-bp separation) and probes that were distant from each other (>100-bp separation), with no apparent increase in nonspecific binding to nontarget RNA. However, due to the close proximity of the set of adjacent probes used in this study, the S-D-Bact-0343-b-S-17-B capture probe and S-D-Bact-0320-b-S-18-D detector probe were labeled at opposite ends (the 5' and 3' ends, respectively) to minimize any steric effects between the label molecules.
Optimization of hybridization conditions.
To achieve optimal specificity and reduce the background signal, the hybridization conditions were optimized using probes targeting the majority of bacterial 16S rRNA sequences. This optimization procedure included the use of different temperatures, different formamide concentrations, and different temperature-ramping profiles. Hybridization was conducted at a range of temperatures (4 to 60°C) and formamide concentrations (0 to 60%), and the signal intensities were comparable under all conditions tested (approximately 7 x 109 RLU for 5 x 1011 molecules of RNA under all conditions), with little or no effect on specificity or background. Standard probe optimization curves (see, e.g., reference 40), analogous to nucleic acid temperature melting curves, were not observed under these conditions. However, ramping of the temperature from 95°C (denaturation temperature) to the hybridization temperature (50°C) appeared to improve sensitivity, producing a significantly higher signal (P < 0.05), significantly lower background (P < 0.05), and increased specificity (Table 2). Other researchers have also found, when quantifying RNA, that different temperatures and formamide concentrations have little or no effect on the hybridization signal. For example, Small et al. (38) found that the presence of formamide had no effect on signal enhancement in microarray assays but was crucial for specific hybridization. In contrast, Peplies and coworkers (32) found that the inclusion of formamide in microarray analyses led to fewer true-positive signals (due to lower signal in the presence of formamide) and more false-negative signals (target molecules which should produce signal but are prevented due to highly stringent conditions). Furthermore, in some studies optimal hybridization was achieved at room temperature (25°C) (8, 38).
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TABLE 2. Effects of temperature ramping on the sensitivity and broad specificity of the assay
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Assay sensitivity.
The sensitivity of the assay was determined using the optimized conditions with bacterial probes (capture probe S-D-Bact-0343-b-S-17-B, detector probe S-D-Bact-0518-a-S-18-D, and helper probe S-D-Bact-0320-b-S-18-H [Table 1]) and dilutions of E. coli rRNA (Roche; twofold dilutions, ranging from approximately 1011 to 107 16S rRNA molecules) (Fig. 4A) or activated-sludge RNA (twofold dilutions, ranging from approximately 1012 to 109 16S rRNA molecules) (Fig. 4B). The detection limit for the assay was defined as the minimum number of target molecules required to produce a mean signal significantly greater than background control signals. The detection limit with purified E. coli rRNA was lower than that with RNA from activated-sludge samples. For the standard E. coli rRNA, 5 x 108 molecules of 16S rRNA were detected above background; for the activated-sludge sample, 1 x 109 16S rRNA molecules were detected. These values correspond to approximately 103 to 104 E. coli cells and 104 to 105 bacterial cells, respectively, based on the assumptions that an actively growing bacterium contains 104 to 105 ribosomes (31) and that the rRNA was released with high efficiency during extraction. This level of sensitivity of the assay is similar to, or higher than, that with other quantification methods (for microarrays, 109 to 1010 16S rRNA molecules [38]; for FISH, approximately 103 cells ml1 in activated sludge [13, 41]). Furthermore, this level of detection is within the range of the average concentration of AOB cells in wastewater treatment plants (106 to 108 cells ml1 [11, 19, 36]). Hence, the assay technique should be suitable for quantification of ammonia-oxidizing bacteria in WWTPs. However, the measured sensitivity of the assay was half an order of magnitude lower for the activated-sludge samples than for purified E. coli rRNA. The reason for this may be the more complex nature of the activated-sludge samples, which may lead to problems with probe binding and RNA extraction. RNA extracted from activated-sludge samples was obtained using a crude extraction procedure with little purification. A more intensive cleanup procedure of the extracted RNA may lower the detection limit. However, extensive purification may also lead to a loss of target RNA molecules. Moreover, the RNA extracted from the activated-sludge samples contains RNA from bacteria, archaea, and eukaryotes. Therefore, the concentrations of bacterial RNA, determined spectrophotometrically, for the activated-sludge samples were probably conservative overestimates, which would otherwise lead to detection limits lower than those determined above.
Specificity of the assay.
The specificity of the bacterial probes with respect to distantly related organisms was initially examined by hybridization with excess yeast rRNA (according to reference 46). The yeast rRNA background control was within the range of other background controls (Fig. 2).
The potential of the assay to differentiate between rRNA molecules with very similar sequences at the probe target sites was examined by comparing the results obtained, using an AOB-specific detector probe set (detector probe S-F-bAOB-1224-a-S-20-D, competitor probe S-S-Ral-1224-a-S-20-C, capture probe S-D-Bact-0343-b-S-17-B, and helper probe S-D-Bact-0320-b-S-18-H [Table 1]), with RNAs extracted from cultures of Nitrosomonas europaea NCIMB 11850T (AOB; positive control) and Ralstonia eutropha DSM 17697T (non-AOB: negative control with 2 mismatches at the probe target site). No non-AOB cultured isolates that have a 1-bp mismatch at the probe target site were available. Hence, R. eutropha, which has 2 mismatches at the probe target site (C instead of A at position 1232 and U instead of C at position 1243), was used as a negative control.
To ensure that the amounts of 16S rRNA for the positive- and negative-control assays were comparable, the signal from the 16S rRNA was measured using the general bacterial probe set (capture probe S-D-Bact-0343-b-S-17-B and detector probe S-D-Bact-0320-b-S-18-D). This control measured the total concentration of bacterial 16S rRNA in the cultures, assuming that the probes hybridized with equal efficiency to the different rRNA species. The same concentration of RNA (3.5 x 1011 molecules, determined spectrophotometrically) in the positive- and negative-control samples gave similar signals by using the bacterial probe set in the RNA assay (e.g., N. europaea bacterial-probe signal, 9.9 x 108 ± 0.46 x 108 RLU; R. eutropha bacterial-probe signal, 1.42 x 109 ± 0.654 x 109 RLU). However, the AOB-specific detector probe set produced a statistically greater signal in the assay with RNA extracted from the N. europaea culture (3.56 x 108 ± 0.3 x 108 RLU) than in that with RNA from the R. eutropha culture (2.24 x 108 ± 0.17 x 108 RLU [Fig. 5] [P << 0.001]). The signal intensity of the negative-control assay containing yeast RNA was similar to that for the nontarget rRNA that had only 2 mismatches with the specific detector probe. This indicates that the assay has a good level of specificity in the presence of nontarget RNA (Fig. 5 and 6).
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FIG. 5. Specificity of the RNA assay with RNAs from positive and negative controls. AOB, Nitrosomonas europaea NCIMB 11850T (positive control; 5 x 1012 molecules); NonAOB, Ralstonia eutropha DSM 17697T (negative-control culture; 5 x 1012 molecules); Yeast, negative control containing yeast RNA. Probes used were S-F-bAOB-1224-a-S-20-D, S-S-Ral-1224-a-S-20-C, S-D-Bact-0343-b-S-17-B, and S-D-Bact-0320-b-S-18-H. Relative light units represent the total integrated light output (light produced per second per well measured every 3 min for 1 h). Error bars, 95% confidence intervals.
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FIG. 6. Specificity of the RNA assay with RNA from nitrifying and nonnitrifying activated-sludge samples and a negative control. WWTP A, nitrifying wastewater treatment sample; WWTP B, nonnitrifying wastewater treatment sample; Yeast, negative control containing yeast RNA. Probes used were S-F-bAOB-1224-a-S-20-D, S-S-Ral-1224-a-S-20-C, S-D-Bact-0343-b-S-17-B, and S-D-Bact-0320-b-S-18-H. Relative light units represent the total integrated light output (light produced per second per well measured every 3 min for 1 h). Error bars, 95% confidence intervals.
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The AOB-specific probes employed in this study have been used successfully in numerous FISH-based studies (see, e.g., references 11, 12, 17, and 37). No difference in signal has been reported between AOB-specific probes and bacterial probes in previous studies, although quantitative comparative analysis of the signal intensities produced from bacterial and AOB-specific probes of the same cells was not undertaken in these studies. It is also possible that rRNA may behave differently in ex situ versus in situ (e.g., FISH) hybridization with respect to the relationship between secondary structure and accessibility to probes.
The specificity of the assay could be further increased by using both capture and detector probes that target AOB rRNA sequences. When two AOB-specific probes (capture probe S-F-bAOB-0190-a-S-22-B and detector probe S-F-bAOB-1224-a-S-20-D, with competitor probe S-S-Ral-1224-a-S-20-C [Table 1]) were used with rRNA from pure cultures, a more intense signal was obtained than in an analysis using a probe set where only the detector probe was specific for the target sequence (detector probe S-F-bAOB-1224-a-S-20-D, competitor probe S-S-Ral-1224-a-S-20-C, capture probe S-D-Bact-0343-b-S-17-B, and helper probe S-D-Bact-0320-b-S-18-H [Table 1]), but the results were more variable (data not shown).
Use of the assay to discriminate between the abundances of AOB in WWTPs with different levels of nitrification.
To determine the effectiveness of the assay for quantitative discrimination of AOB populations in WWTPs exhibiting differences in nitrification, RNA extracts from activated sludge (approximately 4 to 6 ml) from two different WWTPs were analyzed using the assay. The same total number of rRNA molecules was used for both samples in the assay. WWTP A exhibited 99.7% ammonia removal, and the second plant, WWTP B, had poor nitrification performance (average 23% ammonia removal). A slightly, but statistically significantly, higher signal was obtained with RNA extracted from the actively nitrifying wastewater treatment reactor (WWTP A) than with RNA from the nonnitrifying reactor (WWTP B) when the bacterium-specific capture and AOB-specific detector probe set was used (Fig. 6) (P < 0.1). The signal from WWTP B was comparable to that of the negative-control assay containing yeast RNA. FISH analysis of the same samples revealed that WWTP A contained an abundant population of AOB, whereas AOB could not be detected in WWTP B by using FISH.
The RNA assay that we have developed was able to clearly discriminate between the sizes of AOB populations in nitrifying and nonnitrifying activated sludge; however, there are limitations associated with any assay based on the detection of RNA. These relate to the efficiency of RNA extraction (e.g., RNA purification, cell lysis, and stability of RNA), sensitivity and probe specificity issues, and/or target site accessibility. However, perhaps the most important limitation of RNA assays is the potential difficulty in correlating rRNA abundance with cell numbers, since the number of ribosomes may differ between different bacterial species and may also differ with the growth rate or physiological status of an organism (22, 23, 31). Therefore, measurements of rRNA may reflect the activity of the organisms rather than the numbers of organisms. Nonetheless, high cellular ribosome levels (measured as fluorescence by FISH) have been observed in AOB cells that were not actively nitrifying (37), were metabolically inhibited (6, 40), or were starved (29). Furthermore, there is evidence to suggest that the abundance of AOB as measured by dot blot hybridization of extracted RNA (35) and FISH (11) correlates with process- and model-based predictions of the sizes of AOB populations (35). Therefore, for AOB, at least under some circumstances, the rRNA content may accurately reflect cell numbers.
Conclusions.
To accurately monitor microbial populations, especially those involved in nutrient removal processes such as nitrification, a rapid and simple quantification method is required. Current cultivation-independent methods for quantifying bacteria are generally slow (FISH), technically complex (PCR, microarrays, FISH), and often expensive (PCR, microarrays, FISH). Thus, the development of simpler and faster technologies, such as real-time PCR (see, e.g., reference 15) or, alternatively, RNA hybridization assays, is welcome. These methods, perhaps calibrated against FISH, will be essential if quantitative analysis of specific bacteria in activated sludge or other environments is to be adopted by routine analytical laboratories, or for generating very long time series, which will be essential if we are to determine natural variation in the sizes of crucial bacterial populations. Situations outside this normal variation may signal impending process failure. In this study we have developed, to proof of principle, a moderately sensitive, specific, and rapid (about 1 day) assay for determining the relative abundance of ammonia-oxidizing bacteria in WWTPs in order to assess nitrification performance. The general trends in populations that could be provided by the assay for relative abundance measurements may suffice for this type of monitoring. The format of the assay is applicable to quantification of other microorganisms in many environments and has the potential to be automated.
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