Sequence-Specific Capture of Oligonucleotide Probes (SCOPE): a Simple and Rapid Microbial rRNA Quantification Method Using a Molecular Weight Cutoff Membrane

ABSTRACT

A method named sequence-specific capture of oligonucleotide probes (SCOPE) was developed for quantification of microbial rRNA molecules in a multiplex manner. In this method, a molecular weight cutoff membrane (MWCOM) was used for the separation of fluorescence-labeled oligonucleotide probes hybridized with rRNA from free unhybridized probes. To demonstrate proof of concept, probes targeting bacteria or archaea at different taxonomic levels were prepared and were hybridized with rRNAs. The hybridization stringency was controlled by adjusting reaction temperature and urea concentration in the mixture. Then, the mixture was filtered through the MWCOM. The rRNA and hybridized probes collected on the MWCOM were recovered and quantified using a spectrophotometer and fluorospectrometer, respectively. The method showed high accuracy in detecting specific microbial rRNA in a defined nucleic acid mixture. Furthermore, the method was capable of simultaneous detection and quantification of multiple target rRNAs in a sample with sensitivity up to a single-base mismatch. The SCOPE method was tested and benchmarked against reverse transcription-quantitative PCR (RT-qPCR) for the quantification of Bacteria, Archaea, and some key methanogens in anaerobic sludge samples. It was observed that the SCOPE method produced more reliable and coherent results. Thus, the SCOPE method allows simple and rapid detection and quantification of target microbial rRNAs for environmental microbial population analysis without any need for enzymatic reactions.

IMPORTANCE Microorganisms play integral roles in the Earth’s ecosystem. Microbial populations and their activities significantly affect the global nutrient cycles. Quantification of key microorganisms provides important information that is required to understand their roles in the environment. Sequence-based analysis of microbial population is a powerful tool, but it provides information only on relative abundance of microorganisms. Hence, the development of a simpler and quick method for the quantification of microorganisms is necessary. To address the shortcomings of a variety of molecular methods reported so far, we developed a simple, rapid, accurate, and multiplexed microbial rRNA quantification method to evaluate the abundance of specific microbial populations in complex ecosystems. This method demonstrated high specificity, reproducibility, and applicability to such samples. The method is useful for quantitative detection of particular microbial members in the environment.

INTRODUCTION

Microorganisms play vital roles in nutrient cycles of the Earth’s ecosystem. Extensive studies have been carried out to understand the roles of microbes in the environment mostly using high-throughput sequencing (HTS) of rRNA gene amplicons (1). These studies have provided a better understanding of microbial ecology in natural and engineered ecosystems. However, HTS of gene amplicons can provide only relative abundance data, and there have been open discussions on whether the amplicon data can provide a quantitative picture of microbial community. For example, Giner et al. (2) reported reasonable estimates of relative abundance of specific picoeukaryotes compared with catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) results. On the other hand, Piwosz et al. (3) concluded that the amplicon data alone are not sufficient for quantification of microbial community after comparing them with CARD-FISH results for Bacteria and Eukarya. It was recommended instead to combine the amplicon data with outcomes of other quantification methods, such as FISH/CARD-FISH, for studying specific microbial groups. However, accuracy of the quantification results obtained via FISH/CARD-FISH could be compromised by low rRNA content, low probe permeability, different probe coverage/specificity, and difficulty in counting aggregated cells by microscopy (4). Furthermore, low throughput of FISH/CARD-FISH restricts the analysis of a large number of samples without an automated counting system (5).

Quantification of nucleic acids extracted from microbial cells is another popular method. DNA is often targeted to assess the presence of microorganisms regardless of their viability, and RNA is suitable for monitoring of active microbial groups in certain environments due to its faster turnover compared to DNA (6–9). A variety of RNA-based molecular methods have been developed and implemented for detection and quantification of specific microorganisms. Some examples are reverse transcription-quantitative PCR (RT-qPCR) (10), RT–loop-mediated isothermal amplification (LAMP) (11), DNAzyme assay (12), RNase H assay (13), SYBR green assay (14), magnetic bead affinity capillary electrophoresis (MB-ACE) assay (15), and bead array direct rRNA capture assay (rCapA) (16). Despite their advantages, these methods sometimes provide inconsistent results due to amplification biases caused by enzymatic reactions and the coverage of primers/probes. Additionally, the specificity and multiplexity of these methods are insufficient for simple and rapid quantitative detection. Therefore, there is a need to develop a quantification tool which is simple, rapid, accurate, and multiplexed to evaluate the abundance and behavior of specific microbial members in complex ecosystems.

In this study, we developed a novel, simple and rapid rRNA quantification method using a molecular weight cutoff membrane (MWCOM). The general workflow of the developed method is presented in Table 1 and Fig. S1. The MWCOM was utilized to separate fluorescence-labeled oligonucleotide probes hybridized with rRNA molecules (large molecules, about 500 kDa, such as 16S rRNA) from free unhybridized probes (small molecules, 6 to 8 kDa). In this method, DNA probes were designed and prepared to target different levels of taxonomy (i.e., domain, phylum, genus, species, etc.). Multiple DNA probes were first mixed and hybridized with rRNA extracted from environmental samples and then filtered through the MWCOM. Free, unhybridized probes pass through the membrane, while probes hybridized with rRNA are trapped on the membrane. The trapped probe-rRNA hybrids are recovered by reverse centrifugation. These are then quantified spectrophotometrically. Fluorescent signals from the trapped probes correspond to the abundance of the targeted rRNA. We named this method sequence-specific capture of oligonucleotide probes (SCOPE). In this study, we first verified the proof of concept and then evaluated the quantitative performance of this method. Furthermore, applicability of the method was also demonstrated for RNA samples extracted from complex microbial communities residing in anaerobic sludge.

TABLE 1.

Workflow of the SCOPE method

Step	Process
Prepn for hybridization mixture and washing buffer
1	Hybridization mixture: 2 μg of extracted RNA and 50 pmol of probe in 200 μl of hybridization buffer (20 mM Tris [pH 8.0], 400 mM NaCl, 0–6 M urea [concn depends on the probe]) in a 0.5-ml tube.
2	Washing buffer: prewarm 400 μl of washing buffer (20 mM Tris [pH 8.0], 400 mM NaCl, 0–6 M urea [the same concn as in the hybridization buffer]) to 60°C.
Hybridization
3	Heat the hybridization mixture at 95°C for 2 min on heat block for denaturation.
4	Incubate the hybridization mixture at 60°C for 15 min on heat block for hybridization.
Separation of probe-rRNA hybrids and unhybridized probes
5	Filter the hybridization mixture through the MWCOM filtration module at −15 kPa.
6	Filter 200 μl of washing buffer through the MWCOM filtration module. Repeat this step.
7	Remove the remaining filtrate on the reverse side of the MWCOM unit: set the MWCOM unit to a Microcon centrifugal tube, and centrifuge using a tabletop centrifuge for a few seconds.
Recovery of probe-rRNA hybrids
8	Set the inverted MWCOM unit inside a fresh Microcon centrifugal tube.
9	Apply 15 μl of TE buffer to the reverse side of the membrane.
10	Centrifuge the recovery tubes at 1,000 × g for 2 min.
11	Rotate the recovery tubes by 180° and centrifuge at 1,000 × g for 2 min again. Obtain >10 μl of solution.
Measurement of fluorescent intensity and absorbance
12	Measure the fluorescence intensity of the recovered solution. The probe concn is calculated by using external standards (0 to 125 fmol/μl).
13	Measure the absorbance at 260 nm (cm−1) of the recovered solution to determine the total RNA concn.
14	Calculate the target concn using the equation C = ([probe]/[RNA])/H, where C is the target rRNA concn (fmol/ng), “[probe]” is the probe concn (fmol/μl; determined in step 12), “[RNA]” is the total RNA concn (ng/μl; determined in step 13), and H is the hybridization efficiency (mol/mol).a

^aSee the supplemental material for determination of hybridization efficiency.

RESULTS AND DISCUSSION

Selection of the MWCOM unit.

Two important properties of a MWCOM unit critical to our application are the ability to recover rRNA (about 1,500 nt for 16S rRNA) and permeability to fluorescently labeled oligonucleotide probes (6 to 10 kDa) for their removal. Initially, several commercially available MWCOM units were evaluated using fluorescent dye-labeled oligonucleotides. Based on the applicability, a Microcon YM-100 membrane unit (nominal molecular weight limit, 100 kDa) was selected (for more details, see the supplemental material). Oligonucleotide probes of various lengths (i.e., 10, 18, 25, 35, and 50 nucleotides [nt]) were used for the MWCOM filtration test to determine the optimum size of the probe for the study. It was determined that the length of oligonucleotide probe should be 25 nt or less to be able to be used in the filter of choice. Most of the published oligonucleotide probes for detecting microbial rRNA satisfy this length criterion (17) and can be used for the SCOPE method.

Next, the ability to recover rRNA was investigated using ca. 1,500-nt in vitro synthesized RNA. The filter provided high recovery efficiency (over 90%) for the rRNA. In addition, high removal efficiency of the oligonucleotide probe was also demonstrated in the presence of RNA molecules. However, the Microcon YM-100 membrane unit was discontinued by the manufacturer during the study. As a result, we selected and used a Microcon DNA Fast Flow membrane unit for the rest of the study. The properties of the Microcon DNA Fast Flow membrane unit are similar to those of the Microcon YM-100 membrane, with an added benefit of a higher filtration rate.

Development of the SCOPE method.

The SCOPE method includes the following 4 steps: (i) hybridization of probe with rRNA, (ii) separation of probe–rRNA hybrids from unhybridized probes using the MWCOM, (iii) recovery of the probe–rRNA hybrids, and (iv) measurement of fluorescent intensity and absorbance. Step-by-step examination and evaluation were carried out for the method development.

First, the parameters affecting the hybridization efficiency of the probes and RNA were investigated. The investigated parameters were probe-to-RNA molar ratio (tested at 10, 25, 50, 100, and 500), NaCl concentrations (tested at 0, 25, 50, 100, 200, 400, and 800 mM) in the hybridization mixture, and hybridization time (tested at 5, 8, 10, 15, and 30 min). Lower fluorescence intensity was obtained when either lower probe-to-RNA molar ratios (≤25), low NaCl concentrations (≤100 mM), or shorter hybridization times (≤5 min) were used. This could be due to insufficient hybridization efficiency. Based on these observations, we selected the following hybridization conditions: probe-to-RNA molar ratio, 50; NaCl concentration, 400 mM; and hybridization time, ≥15 min.

Next, the parameters for sequence-specific RNA detection were investigated. Generally, hybridization temperature and concentrations of the denaturing reagents and NaCl are adjusted to control the stringency of hybridization. For this study, adjustment of NaCl concentration was omitted as a variable because of the inefficient hybridization at low NaCl concentrations, as described above. Therefore, we evaluated only the effects of hybridization temperature and denaturing reagents. We observed a decrease in the fluorescent intensity with an increase in the hybridization temperature (up to 80°C) without any loss of RNA recovery efficiency. Since insufficient specificity for nontarget RNA was observed at low hybridization temperatures (∼40°C), a temperature of 60°C was selected for the study. Hybridization temperatures higher than 60°C were difficult to handle.

For the selection of a denaturing agent, formamide and urea were compared. Formamide is one of the most commonly used denaturing agents. However, the use of formamide resulted in undesirable effects on the spectrophotometric measurements at 260 nm. As a result, we selected urea as a denaturing agent for the SCOPE tests. The effect of urea concentrations on the hybridization buffer was evaluated using 5 probes: EUB338, ARC915m, MX825m, MG1200m, and GAM42a. As shown in Fig. 1, the ratio of fluorescent intensity to absorbance (FI/Abs) for the targeted RNA showed higher values at high urea concentrations. Meanwhile, the FI/Abs values for the nontargeted RNA decreased with an increase in the urea concentration. Hence, higher concentration of urea in the hybridization mixture was effective for the detection of target RNA with sufficient specificity. This specificity was demonstrated for up to 2-base mismatches (e.g., MX825m) (Fig. 1C) but not for a single-base mismatch (e.g., GAM42a) (Fig. 1E). Normally, in the FISH analysis, a single-base mismatch can be identified and excluded using a competitor probe (18). Therefore, 50 pmol of nonlabeled cGAM42a as a competitor probe was used in this study. Figure 1F presents the results obtained after addition of the competitor probe, demonstrating high FI/Abs values for the target RNA and significantly low FI/Abs values for the nontarget RNA. Hence, a single-base discrimination was possible by the use of a competitor probe.

FIG 1.

Dissociation profiles of probes tested in this study. FI/Abs is the fluorescent intensity divided by the absorbance of recovered probe-rRNA hybrid solution. (A) EUB338, specific for the domain Bacteria; (B) ARC915s, specific for the domain Archaea; (C) MX825m, specific for the family Methanosaetaceae; (D) MG1200m, specific for the order Methanomicrobiales; (E) GAM42a, specific for the class Gammaproteobacteria; (F) GAM42a with competitor probe cGAM42a. In all of the experiments, targeted or nontargeted synthesized RNAs were used. For each probe, the probe sequence and the corresponding site of the targeted and nontargeted rRNA are indicated. The double line in the nontargeted RNA indicates complementarity to the probe sequence.

Eventually, the experimental condition for SCOPE was established as follows: a hybridization mixture was prepared using 50 pmol of probes, 1 pmol of RNA (probe-to-RNA molar ratio of 50), 20 mM Tris-HCl, 400 mM NaCl, and an appropriate concentration of urea (0 to 6 M) to maintain probe specificity. Incubation was performed at 60°C for 15 min. To apply SCOPE under this condition, design of the probe is important. Oligonucleotides with a high melting temperature (T_m) were not applicable for SCOPE under this defined condition, as they could not maintain the specificity even under the most stringent denaturing conditions (6 M urea). Thus, the length of the probes used should be shortened to lower the T_m. For example, the ARC915m probe is a shorter version of ARC915 and has lower T_m. Probe design criteria for the SCOPE test were evaluated using 4 probes, namely, EUB338, ARC915m, MX825m, and MG1200m. The T_m of the oligonucleotide probes can be estimated by free energy change of the probe-RNA duplex formation (ΔG°₁) (19). The ΔG°₁ values of the selected probes were −17.6, −17.9, −13.2, and −14.5 kcal/mol, respectively. Therefore, the probes with ΔG°₁ values in the range of −18 and −13 kcal/mol could be better candidates for the SCOPE method.

Quantification by SCOPE.

To evaluate accuracy of quantification by the SCOPE method, we initially evaluated the hybridization efficiency of each probe (20). Hybridization efficiency was calculated by dividing the molar concentration of the probe by the molar concentration of the RNA in the SCOPE recovered solution. Molar concentrations of the probes were determined by using external standards (series dilution of probe). Likewise, molar concentrations of the RNAs were determined by using spectrophotometric method at 260 nm. Following the above-mentioned method, hybridization efficiencies for all of the selected probes were evaluated (Table 2).

TABLE 2.

Probes used in this study

	Fluorescent dye	Target taxonomy	Sequence (5′ to 3′)	ΔG°1 (kcal/mol)a	Hybridization efficiencyb	Urea concn (M)	Reference
EUB338	Alexa Fluor 546	Bacteria	GCT GCC TCC CGT AGG AGT	−17.6	0.81	6	33
ARC915m	Alexa Fluor 488	Archaea	TGC TCC CCC GCC AAT TCCc	−17.9	0.85	6	13
ARC915m	Alexa Fluor 647	Archaea	TGC TCC CCC GCC AAT TCCc	−17.9	0.76	6	13
MX825m	Alexa Fluor 488	Methanosaetaceae	TGG CCG ACA CCT AGC GAG	−13.2	0.72	6	13
MG1200m	Alexa Fluor 488	Methanomicrobiales	CCG GAT AAT TCG GGG CAT GCT G	−14.5	0.42	6	34
MB1175m	Alexa Fluor 488	Methanobacteriaceae	CCG TCG TCC ACT CCT TCC TC	−19.0	0.73	6	34
GAM42a	Alexa Fluor 488	Gammaproteobacteria	GCC TTC CCA CAT CGT TTc	−13.8	0.77	4	18
cGAM42a	None	Competitor for GAM42a	GCC TTC CCA CTT CGT TTc	−14.3	ND	4	18

^aThe value of ΔG°₁ was calculated using mathFISH (19).

^bHybridization efficiency at the indicated urea concentration.

^cModified from the cited source.

Then, the quantitative performance of the SCOPE was evaluated. Two fluorescently labeled probes (ARC915m labeled with Alexa Fluor 488 and EUB338 labeled with Alexa Fluor 546) and RNA mixtures (500 ng) at different proportions (0, 1.25, 2.5, 5, 10, 25, 50, 75, 90, 95, 97.5, 98.75, and 100%) of two synthesized RNA molecules (16S rRNA of Methanosarcina mazei and Escherichia coli) were prepared (e.g., “5%” means the mixture containing 25 ng of M. mazei RNA and 475 ng of E. coli RNA), and the SCOPE analysis was carried out. Quantitative values were corrected using respective hybridization efficiency values (Table 2). There was a linear correlation between the SCOPE-estimated and theoretically calculated abundance values of RNAs for both ARC915m and EUB338 (Fig. 2). This indicated that the SCOPE method can be used for sequence-specific RNA quantification. Nevertheless, quantification of small amounts of RNA was not possible because of false-positive values (Fig. 2). This limitation in quantification is due to the dependency of the SCOPE method on the signal-to-noise ratio of each probe.

FIG 2.

Quantitative detection of archaeal (M. mazei [A]) and bacterial (E. coli [B]) RNA by SCOPE. Two probes, ARC915m and EUB338, were used simultaneously for the artificial mixture of the synthesized rRNA of M. mazei and E. coli at different proportions. Defined abundances of archaeal and bacterial RNA are plotted along the x axis. The quantified values of the target RNA in total RNA (copies/ng) are shown along the y axis.

We then evaluated multiple and simultaneous quantification of RNA by SCOPE using 3 probes: ARC915m labeled with Alexa Fluor 647 for the domain Archaea, MX825m labeled with Alexa Fluor 488 for the family Methanosaetaceae, and EUB338 labeled with Alexa Fluor 546 for the domain Bacteria. A 500-ng batch of the test RNA mixture was prepared, which consisted of equal quantities of synthesized M. mazei, Methanosaeta concilii, and E. coli RNAs. The SCOPE method was applied on the synthesized RNA samples using the mix of 3 probes in a hybridization matrix containing 4 M urea. The relative abundances (average ± standard deviation; n = 3) of Archaea, Methanosaetaceae, and Bacteria were 61.8% ± 7.8%, 30.0% ± 2.9%, and 33.4% ± 2.4%, respectively. The experimental values closely matched the theoretical values, which were 66.7% for Archaea, 33.3% for Methanosaetaceae, and 33.3% for Bacteria. These results demonstrated simultaneous and multiplex quantification of RNA by the SCOPE method. The multiplex detection/quantification capability of the SCOPE method also depends on the variation of fluorescent dyes available for the respective fluorospectrometer used for detection.

Quantification of various microbial groups in complex samples.

To evaluate the applicability of the SCOPE method to complex microbial communities, sludge samples were collected from two anaerobic reactors, an upflow anaerobic sludge blanket (UASB) reactor treating industrial wastewater and an anaerobic sewage sludge digester. Quantification of the 16S rRNA of the collected samples was carried out by both the SCOPE and RT-qPCR methods for benchmarking purposes. Five probes (i.e., EUB338, ARC915m, MX825m, MG1200m for Methanomicrobiales, and MB1175m for Methanobacteriaceae) were used for the quantification in the hybridization buffer containing 6 M urea. The RT-qPCR of the respective five groups was conducted as described previously (21). The results are shown in Table 3. A notable difference between the two methods was the sum of bacterial and archaeal copy numbers in 1 ng of RNA. The sums of bacterial and archaeal copy numbers quantified by SCOPE were 2.96 × 10⁸ copies/ng and 4.85 × 10⁸ copies/ng for the granular sludge and digester sludge samples, respectively. On the other hand, results from the RT-qPCR method showed 2.81 × 10⁷ copies/ng and 1.47 × 10⁸ copies/ng for the granular sludge and digester sludge samples, respectively. Theoretically, the total number of rRNA copies present in the sample was approximately 3 × 10⁸ copies/ng (the detailed calculation is in the supplemental material). Of the two samples evaluated, the quantitative value of the granular sludge sample determined by RT-qPCR was approximately 1 order of magnitude lower than the theoretical value, whereas the SCOPE method showed acceptable values for both the granular sludge and digester sludge samples.

TABLE 3.

Quantification of Bacteria, Archaea, and three methanogenic groups in granular and digester sludge samples by SCOPE and RT-qPCR^a

Target group	Granular sludge			Digester sludge
	Copies/ng (%)		HTS (%)b	Copies/ng (%)		HTS (%)b
	SCOPE	RT-qPCR		SCOPE	RT-qPCR	Without PMA	With PMA
Bacteria	(1.51 ± 0.24) × 108 (50.9 ± 8.3)*	(2.33 ± 0.36) × 107 (83.1 ± 12.9)	60.6	(4.60 ± 0.19) × 108 (94.7 ± 4.0)	(1.46 ± 0.05) × 108 (99.0 ± 3.1)	92.3	95.2
Archaea	(1.45 ± 0.36) × 108 (49.1 ± 12.1)	(4.75 ± 0.37) × 106 (16.9 ± 1.3)	38.7	(2.56 ± 0.38) × 107 (5.3 ± 0.8)	(1.41 ± 0.04) × 106 (1.0 ± 0.0)	7.0	4.0
Methanosaetaceae	(1.21 ± 0.40) × 107 (4.1 ± 1.4)	(6.79 ± 2.69) × 106 (24.2 ± 9.6)	13.5	(1.32 ± 0.14) × 107 (2.7 ± 0.3)	(2.50 ± 0.37) × 105 (1.7 ± 0.3)	5.4	2.4
Methanomicrobiales	(2.15 ± 0.22) × 107 (7.3 ± 0.7)	(1.52 ± 0.10) × 105 (0.5 ± 0.0)	3.5	(1.24 ± 0.40) × 107 (2.5 ± 0.8)	(1.09 ± 0.03) × 104 (0.7 ± 0.0)	1.3	1.3
Methanobacteriaceae	(8.01 ± 1.81) × 107 (27.1 ± 6.1)	(5.43 ± 0.59 )× 106 (19.3 ± 2.1)	21.7	— (—)	— (—)	0.1	0.1
Correlation coefficient (r)c
For all targets	0.916	0.865		0.999	0.999
Without Bacteria	0.941	0.485		0.760 (0.938 [PMA])	0.518 (0.189 [PMA])

^aValues in parentheses indicate the relative abundance against the total 16S rRNA number (the sum of bacterial and archaeal rRNA). The mean value and standard deviation were calculated from three independent experiments. —, not determined.

^bRelative abundance.

^cCorrelation coefficient (r) between HTS and SCOPE or RT-qPCR.

Both SCOPE and RT-qPCR methods showed higher bacterial abundance than archaeal abundance, although their ratios were different. In the case of granular sludge sample, the SCOPE method showed almost equal abundances of bacteria and archaea, whereas RT-qPCR showed approximately 4-fold higher bacterial abundance than archaeal abundance (Table 3). For the digester sludge sample, the ratios of bacterial and archaeal abundances were similar, although the quantitative values were different (Table 3). The ratios of quantitative values determined by SCOPE and RT-qPCR (i.e., RT-qPCR/SCOPE) were 0.15 to 0.32 for Bacteria and 0.03 to 0.05 for Archaea, suggesting a significant underestimation of archaeal quantity by RT-qPCR. In addition, the abundances of Methanosaetaceae, Methanomicrobiales, and Methanobacteriaceae quantified by SCOPE were lower than the total archaeal abundance, whereas those quantified by RT-qPCR surpassed the total archaeal abundance. This could be because of the underestimation of the archaeal population by RT-qPCR owing to the biases associated with the method as discussed above.

The results obtained by the SCOPE and RT-qPCR methods were compared with the results of the microbial community analysis performed with 16S rRNA gene-targeted HTS. The data obtained by HTS show only the relative abundance. Therefore, for comparison, the relative abundances of microbes determined by the SCOPE and RT-qPCR methods were calculated by dividing the numbers of the target microbial group by the sum of the numbers of Bacteria (i.e., EUB338) and Archaea (ARC915m) (Table 3). The correlation coefficients (r) among SCOPE, RT-qPCR, and HTS results were compared. For the anaerobic sludge digester sample, two samples, with and without propidium monoazide (PMA) treatment, were prepared for HTS analysis to see the effects of amplicons derived from dead cells on microbial community structure. This is because PMA-PCR can provide a picture of a living microbial community based on cell membrane integrity (22). The r value was calculated with and without bacterial abundance (i.e., Bacteria plus Archaea and only Archaea). The relative abundances obtained from the SCOPE method were more consistent with the microbial community structures analyzed after 16S rRNA gene-targeted HTS than with that of the RT-qPCR (detailed community structures are shown in Table S1). The r value of the SCOPE versus PMA-PCR was highest for the anaerobic digester sludge sample. These results also indicated that the SCOPE method can capture living and active methanogens in the sample.

Salient features of the SCOPE method.

For microbial community analysis, HTS of 16S rRNA gene amplicons is a widely accepted method. However, it provides data only on relative abundance of microbial populations. The relative abundance data are always affected by the dynamics of other microorganisms, and therefore, it is recommended to combine other quantification methods with HTS (e.g., FISH) for more complete analysis (3). FISH can provide cell-based quantification data, but it is sometimes time-consuming, and the construction of an automated system for high-throughput analysis is not an easy task. Alternatively, rRNA can be a useful molecular marker for quantifying a specific microbial group of interest because it can provide quantitative data based on the phylogenetic information as well as microbial activity in terms of protein synthesis capacity.

Several methods for the detection and quantification of microbial RNA have been extensively developed over the last 2 decades. The most commonly accepted and implemented method is RT-qPCR (23, 24), which includes a PCR amplification step, resulting in high method sensitivity. Any methods with amplification steps have much lower quantification limits than those without amplification. On the other hand, it is well known that the biases introduced during enzymatic reactions, including reverse transcription and PCR amplification, are unavoidable, some of which were also encountered in this study (i.e., overquantification of the lower taxonomic groups compared to the higher taxonomic groups and obtaining the results with lower copy numbers per nanogram of RNA compared to theoretically expected values). In addition to the PCR bias, it is also well known that the reverse transcription reaction is affected by primers, the hairpin structure of rRNA, and sequences of rRNA, thus increasing the potential of introducing additional biases (25, 26). Therefore, it is sometimes difficult to see the quantitative relationship of more than two phylogenetic groups of interest.

To avoid these biases, quantification of rRNA without amplification is an attractive approach. After the publication of the Northern blot method, several quantification methods, such as sequence-specific RNA cleavage with RNase H (13), SYBR green I based assay (14), MB-ACE (15), and rCapA (16), were developed. The method of sequence-specific RNA cleavage employs an oligonucleotide scissor DNA probe and RNase H. This method has been successfully applied for the detection and quantification of specific microbial groups with high specificity that excludes even a single-base mismatch (13). This is a simple and rapid method but is not capable of multiplex detection. On the other hand, the MB-ACE method (15) can quantify several groups at once using several oligonucleotide probes labeled with different dyes. However, the experimental procedure is rather complicated, and single-base discrimination is questionable.

The SCOPE method assessed in this study overcomes the drawbacks of the previously published methods. The SCOPE method is a simple and rapid method that allows multiplex detection and quantification with a single-base mismatch discrimination. With regard to the specificity, optimization of probe design and reaction conditions for the single-base mismatch discrimination is generally a difficult task and is often not possible. The SCOPE method makes it possible to optimize experimental conditions for each probe and further improves specificity by using competitor probes, making the optimization process easier. Although quantification of less abundant RNA (a few percent) by SCOPE is not reliable in some cases, the reliability is most likely dependent on proper selection of the dyes, fluorospectrometer, and probe sequences. Another drawback is that the amount of RNA required for the method is relatively high compared to the methods that use amplification steps. This is true for all methods that do not use amplification. For example, in the current study, approximately 2 μg of extracted RNA per reaction was required for SCOPE. As a result, currently, the application of the SCOPE method is mostly restricted to artificial or natural ecosystems which have a high abundance of microorganisms.

Conclusion.

In this study, we developed a novel, simple and quick RNA quantification method using an MWCOM, named SCOPE. Sequence-specific detection and quantification of a target microbial RNA using specific oligonucleotide probes were achieved with specificity of a single-base mismatch and high reproducibility. Multiplex quantification at different taxonomic levels was also achieved by using different fluorophore-labeled probes. Finally, quantification of RNAs belonging to different microbial groups in sludge samples obtained from various engineered systems was successfully demonstrated. The advantages of this method are as follows: (i) no need for enzymatic reaction, (ii) use of simple and minimal instrumentation (a thermal controller, a vacuum manifold, a UV spectrophotometer and a fluorospectrometer), (iii) simple and rapid experimental procedure, (iv) easy preparation of external standards, and (v) multiplex quantification with single-base mismatch discrimination. In this regard, the SCOPE method has the potential to become a useful method for the quantitative detection of environmental microbial communities.

MATERIALS AND METHODS

Pure cultures, clones, and sludge samples.

Escherichia coli (ATCC 700926), Comamonas testosteroni (NBRC14951), Methanosaeta concilii (JCM10134), and Methanosarcina mazei (JCM9314) were cultivated in their respective media according to institutional instructions. Clones with a nearly full-length 16S rRNA gene of the genus Methanolinea (accession number LC106411) and genus Methanobacterium (accession number LC106391) were prepared in-house from phenol-treating anaerobic sludge (27). Sludge samples were collected from an upflow anaerobic sludge blanket reactor treating wastewater from a food processing industry (granular sludge) and from an anaerobic digester treating sewage sludge (digester sludge) in a municipal sewage treatment plant.

RNA synthesis.

Template DNA with nearly full-length of 16S rRNA gene for RNA synthesis was prepared by PCR using the primers shown in Table 4. The PCR mix contained 1× AmpliTaq Gold PCR master mix (Applied Biosystems), 500 nM (each) forward and reverse primers, and template DNA. The PCR amplification was carried out under the following thermal program: initial heat activation (10 min at 95°C), 40 cycles of amplification (30 s at 95°C, 30 s at 55°C, and 90 s at 72°C), and final extension (7 min at 72°C). After verification of the amplicons by agarose gel electrophoresis, the PCR products were purified using a MinElute PCR purification kit (Qiagen). The RNA transcripts were obtained using a T7 RiboMAX express kit (Promega) and were purified with a DNA-free RNA kit (Zymo Research). The quality of the products was checked with an Agilent 2100 Bioanalyzer with RNA 6000 nanokit (Agilent). Concentrations of RNA transcripts were measured with a NanoDrop 2000 UV spectrophotometer (Thermo Scientific).

TABLE 4.

Primers used in this study

Primer	Target site	Sequence (5′ to 3′)	Reference
Bac8fa	16S rRNA gene of Bacteria	AGA GTT TGA TCC TGG CTC AG	31
Arc109fa	16S rRNA gene of Archaea	ACK GCT CAG TAA CAC GTb	32
Univ1500r	16S rRNA gene of Bacteria and Archaea	GGH TAC CTT GTT ACG ACT T	31
559fa	23S rRNA gene of Bacteria	GCG TAC CTT TTG TAT AAT Gb	35
1623r	23S rRNA gene of Bacteria	CAC CWG TGT CGG TTTb	35

^aT7 promoter sequences (5′-TAA TAC GAC TCA CTA TAG GG-3′) is added at the 5′ end of all forward primers.

^bModified from the cited source.

RNA extraction.

Samples subjected to RNA extraction were immediately washed 2 or 3 times with pH 5.1 buffer (10 mM EDTA, 50 mM sodium acetate) after sampling and stored at −80°C. The RNA extraction was performed as previously described (28) with a slight modification. Briefly, samples (approximately 0.05 to 0.1 g [wet weight]) were transferred to 2.2-ml conical screw-cap tubes together with 0.4 g of baked glass beads (0.1 mm in diameter), 400 μl of pH 5.1 buffer, 500 μl of phenol-chloroform-isoamyl alcohol solution (50:49:1), and 80 μl of 20% sodium dodecyl sulfate. The tubes were subjected to bead-beating in an MS-100R unit (Tomy) under cooling conditions for 120 s. Total nucleic acids were purified using an RNeasy minikit (Qiagen) including a DNA digestion step according to the manufacturer’s protocol. The extracted RNA was concentrated by ethanol precipitation or by using Microcon DNA Fast Flow centrifugal filter unit (Millipore) to make the final concentration greater than 100 ng/μl. Shorter RNA fragments (<500 nucleotides) were removed using a MicroSpin S-400 column (GE Healthcare).

SCOPE.

The overall workflow of the SCOPE method is shown in Table 1. The RNA samples (500 ng of synthesized RNA or 2 μg of extracted RNA) were hybridized with 50 pmol of probes in 200 μl of hybridization buffer (20 mM Tris-HCl [pH 8.0], 400 mM NaCl and 0 to 6 M urea) in a 0.5-ml tube. Urea was used to adjust the stringency of hybridization. The mixture was heated at 95°C for 2 min for denaturation and incubated at 60°C for 15 min for hybridization. The mixture was then subjected to filtration with a MWCOM unit (Microcon YM-100 membrane unit or Microcon DNA Fast Flow membrane unit; Millipore) using an AxyVac vacuum manifold (AxyGen) adjusted at −15 kPa. Subsequently, 200 μl of prewarmed washing buffer (20 mM Tris-HCl [pH 8.0], 400 mM NaCl, and 0 to 6 M urea at 60°C) was passed through the MWCOM unit twice to remove excess probes. The filtration and the following recovery steps were conducted at room temperature. The membrane unit was set in a Microcon centrifugal tube and was centrifuged by a tabletop centrifuge for a few seconds to remove the remaining filtrate on the unit. For the recovery of the probe-rRNA hybrids, the membrane unit was inverted and set inside a fresh Microcon centrifugal tube. Approximately 15 μl of Tris-EDTA (TE) buffer was applied onto the inverted membrane unit. The tube was centrifuged at 1,000 × g for 2 min. To improve the recovery efficiency, the tube was rotated 180° and centrifuged again.

The fluorescent intensity was measured by either a combination of NanoDrop 3300 (fluorospectrometer) and NanoDrop 2000 (spectrophotometer) (Thermo Scientific) or a Tecan Infinite M1000 Pro microplate reader (Tecan). In the case of NanoDrop 3300 instrument, the excitation light source and emission wavelengths for Alexa Fluor 488, Alexa Fluor 546/Alexa Fluor 555, and Alexa Fluor 647 were blue LED and 520 nm, white LED and 570 nm, and white LED and 670 nm, respectively. External standards (0 to 125 fmol/μl) of each probe were prepared for quantification (Fig. S2). In the case of the microplate reader, 10 μl of the recovered solution was applied to a 384-well microplate (384-IQ 100 LV/EB Blk ST/TR; Aurora Microplates), and fluorescent intensity and absorbance (260 nm) were measured. The excitation/emission wavelengths for Alexa Fluor 488, Alexa Fluor 546/Alexa Fluor 555, and Alexa Fluor 647 were 480 ± 5/530 ± 5 nm, 545 ± 5/595 ± 5 nm, and 630 ± 5/690 ± 5 nm, respectively. External standards were also measured with the microplate reader (Fig. S3 for fluorescence and Fig. S4 for absorbance). The total time required for the experimental process from RNA extraction to the measurement was less than 3 h.

RT-qPCR.

RT-qPCR was carried out using a LightCycler 2.0 instrument (Roche Diagnosis). The RT-qPCR mixture was prepared using 2 μl of template RNA, 1 μl each of forward and reverse primers (10 μM), 1 μl of TaqMan probe (4 μM), 10 μl of 2× PrimeScript One Step RT-PCR mix (TaKaRa), 0.8 μl of PrimeScript One Step RT-PCR enzyme mix (TaKaRa), and 4.2 μl of distilled water to make a final volume of 20 μl. The primers and TaqMan probes used are shown in Table 5. The RT-qPCR conditions were as follows: an initial reverse transcription for 30 min at 50°C, followed by an initial activation for 2 min at 94°C and 45 cycles of PCR amplification (10 s at 94°C, 20 s at 60°C, and 15 s at 72°C). All tests were performed in duplicate, and information about the external standards is shown in Table S2.

TABLE 5.

Primers and probes used for RT-qPCR (21)

Target	Primer or probe	Name	Sequence (5′ to 3′)
Bacteria	Forward primer	Bac338f	ACT CCT ACG GGA GGC AG
	Reverse primer	Bac805r	GAC TAC CAG GGT ATC TAA TCC
	TaqMan probe	Bac516fa	TGC CAG CAG CCG CGG TAA KAC
Archaea	Forward primer	Arc787f	ATT AGA TAC CCS BGT AGT CC
	Reverse primer	Arc1059r	GCC ATG CAC CWC CTC T
	TaqMan probe	Arc915f	AGG AAT TGG CGG GGG AGC AC
Methanosaetaceae	Forward primer	Mst702fa	TAA TCC TYG ARG GAC CAC CA
	Reverse primer	Mst862ra	CCT ACG GCR CCV ACM AC
	TaqMan probe	Mst753fa	ACG GY(A) AGG GAC GA(A) ARC TAG Gb
Methanomicrobiales	Forward primer	Mmb282f	ATC GRT ACG GGT TGT GGG
	Reverse primer	Mmb832r	CAC CTA ACG CRC ATH GTT TAC
	TaqMan probe	Mmb749f	TYC GAC AGT GAG GRA CGA AAG CTG
Methanobacteriales	Forward primer	Mbt857f	CGW AGG GAA GCT GTT AAG T
	Reverse primer	Mbt1196r	TAC CGT CGT CCA CTC CTT
	TaqMan probe	Mbt929f	AGC ACC ACA ACG CGT GGA

^aModified from the cited source.

^bNucleotides in parentheses are locked nucleic acid (LNA).

Microbial community analysis.

Microbial community structures were analyzed by amplicon sequencing of 16S rRNA genes according to the method described by Ni et al. (22). Propidium monoazide (PMA) treatment was introduced in case of the digester sludge sample to eliminate dead microbial cells from analysis. DNA extraction was performed using ISOIL for the Beads Beating kit (Nippon Gene). The 341F/806Rmix primer pair was used to amplify the V3-V4 region of the 16S rRNA gene. The Illumina MiSeq system (Illumina) was employed for sequencing. Bioinformatics was carried out by using QIIME software (version 1.8.0) (29) and the silva132 database (30).