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Journal of Clinical Microbiology, January 2004, p. 299-306, Vol. 42, No. 1
0095-1137/04/$08.00+0 DOI: 10.1128/JCM.42.1.299-306.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.
Rabies Section, Centers for Disease Control and Prevention, Atlanta, Georgia 30033
Received 30 June 2003/ Returned for modification 25 September 2003/ Accepted 17 October 2003
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The rabies virus (RV) is the type member of the Lyssavirus genus that includes Lagos bat virus, Mokola virus, Duvenhage virus, European bat lyssavirus 1, European bat lyssavirus 2, and Australian bat lyssavirus. Recently, a new lyssavirus discovered in central Asia has been proposed as a new genotype (2). Isolates of RV in the United States exhibit considerable sequence heterogeneity in nature (18), making problematic the designing of oligonucleotide primers for RNA detection. RNA virus heterogeneity may affect the performance of TaqMan PCR assays (16), but there are few data available on the tolerance of TaqMan technology to sequence variation. A TaqMan PCR assay to differentiate lyssaviruses by genotype has been developed (3), but there has been no formal assessment of the impact of RNA sequence diversity on this assay.
The direct fluorescent antibody test (25) is the current laboratory test of choice for detecting RV antigen in tissue samples and has adequate levels of sensitivity and specificity when it is performed correctly (22, 23). The advantages of RNA detection methods are in the transferability of the technology to a wide variety of other sample types that may be unsuitable for the direct fluorescent antibody test, such as saliva and cerebrospinal fluid (5). PCR has been used for the confirmatory diagnosis of human rabies when other tests could not be readily applied (4). For experimental studies, PCR-based techniques have been utilized for the detection of RV RNA from oral swabs (15). RNA can be buffered adequately at room temperature for considerable periods by using commercially available products such as RNAlater (Ambion) and TRIzol (Life Technologies).
In addition to its application to qualitative detection-based assays, TaqMan technology has been used to quantify viral loads from tissue samples (1). At present, methods for estimating the levels of RV in clinical samples are limited to titration in animals or tissue culture. The classic mouse inoculation test (10) can lead to a considerable delay in the estimation of an end point, requires facilities for the use of experimental animals, and is labor intensive. Cell culture isolation methods (26) are problematical due to the inability of certain RV variants to propagate easily in specific cell lines. The TaqMan PCR provides a potential means to accurately quantify levels of RV RNA in a wide variety of sample types. Such information is vital for investigating RV pathogenesis.
In this study, we assessed a TaqMan PCR for the detection of RV RNA in clinical samples. We also assessed the kinetics of the TaqMan reaction for application to quantitative virology and analyzed the effects of sequence divergence on the efficiency of this reaction.
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Following homogenization in phosphate-buffered saline, salivary gland (SG) samples were titrated in mice (10), and 250 µl of homogenate was added directly to TRIzol LS reagent (Invitrogen Life Technologies, Carlsbad, Calif.) for RNA extraction. A 3-mm3 sample of frozen brain tissue (BR) was homogenized directly in 750 µl of TRIzol reagent according to the manufacturer's instructions. All samples were stored at -80°C prior to processing.
Historical samples. A selection of historical samples was used to test the effects of sequence variation on the kinetics of the TaqMan reaction. Four RV variants associated with the infection of terrestrial mammals (11) were selected for this study: California skunk (CASK), north central skunk (NCSK), raccoon (RAC), and south central skunk (SCSK). A total of 63 isolates, which were previously typed by molecular techniques, were selected from those available at the CDC where sequence data for the nucleoprotein (N) gene were available (Table 1 and Fig. 1). These samples are not representative of all circulating lineages of RV in the United States, but they provide a means to study the effect of sequence diversity on the TaqMan PCR. RNA extracted prior to November 1994 had been extracted by a method described elsewhere (19). After November 1994, RNA was extracted by using TRIzol according to the manufacturer's instructions.
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TABLE 1. List of historical samples used for variant-specific TaqMan PCRs
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FIG. 1. Maximum likelihood phylogenetic tree depicting the relationships of the 62 historical rabies virus isolates. The tree is rooted at the midpoint for purposes of clarity. The tree is based on 164 nucleotides of the N gene, corresponding to positions 1123 to 1287 of the Pasteur RV N gene (GenBank accession no. A492968) and generated with the PAUP* program (20). Samples within the clear box are those NCSK samples typed by the TaqMan PCR assay as CASK. Samples within the gray boxes are those that were weakly positive or negative by TaqMan PCR.
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Reverse transcription (RT) of all RNA samples (experimental and historical) was undertaken by using a reverse transcription system (Promega) according to the manufacturer's instructions with 0.5 µg of the supplied random primers. RT was performed with 1 µl of RNA from experimental samples (to avoid saturation) and 5 µl of RNA from historical samples.
Design of TaqMan primer and probe sets. All TaqMan primers and probes were designed by the Primer Express computer program (Applied Biosystems, Foster City, Calif.). For the two isolates used for the experimental infection of the skunks, nucleotide sequences from the N gene of each variant (AZ-SK and AZ-EF with GenBank accession numbers AF483524 and AY170413, respectively) were inputted into the program, and the optimal primer and probe sequences were obtained by using the default settings of the program.
For historical samples, a consensus sequence was generated for the sets of sequences comprising each RV variant (Fig. 1) from a sequence alignment generated with the BioEdit computer program (7). From this alignment, areas of relative conservation were selected as target regions for placement of the TaqMan primers and probes. These regions were used as input for Primer Express to generate the optimal primer and probe sequences according to the default settings.
TaqMan primer and probe details are shown in Table 2. All TaqMan probes were labeled at the 5' end with a fluorescent reporter dye (6-carboxy-fluorescein) and at the 3' end with a quencher. The AZ-EF and AZ-SK probes were quenched with a minor groove binder-nonfluorescent quencher (Applied Biosystems), while the CASK, NCSK, RAC and SCSK probes were quenched with Black Hole Quencher (Biosearch Technologies, Novato, Calif.). Primer and probe concentrations were optimized according to the manufacturer's recommendations.
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TABLE 2. Oligonucleotide sequences for TaqMan primers and probes
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TaqMan runs of experimental samples contained at least four replicates each of a known positive control (from RV-positive BR), an RV-negative control cDNA, and nuclease-free water. Each historical sample was run in triplicate with each of the four variant-specific TaqMan primer and probe sets alongside a positive control cDNA for each variant (from RV-positive BR), negative control cDNA (from BR infected with a big brown bat RV variant), and nuclease-free water (3 wells). Previous testing showed that all four terrestrial TaqMan primer and probe sets did not amplify the big brown bat RV variant used for the control reactions with no amplification. All sample replicates were run on the same plate, thus measuring variability only within the run. In addition, a number of samples were run on separate plates to assess variability between runs.
For each PCR, a threshold cycle number (Ct) was obtained corresponding to the PCR cycle number during which the fluorescence of the reaction rose above a threshold value statistically determined by the computer software. The Ct values are inversely proportional to the log10 of the amount of template in the PCR. A difference of 1 Ct corresponds to a twofold difference in template amounts. A Ct value less than the mean plus two standard deviations of the negative control wells was considered positive. A Ct value of 40 corresponds to no amplification.
Levels of ß-actin, determined by TaqMan PCR, were used to normalize levels of all samples (both experimental and historic). For amplification of ß-actin mRNA, the PCR assay was performed with a ß-actin detection kit (Applied Biosystems) according to the manufacturer's instructions. The adjustment according to the levels of ß-actin was performed by subtracting the highest mean ß-actin Ct value (i.e., the lowest levels of ß-actin) from the mean ß-actin Ct of each sample. This difference was subtracted from the mean Ct value obtained from the RV-specific TaqMan PCR. This provided a method to account for differences in the levels of viral RNA due to sample heterogeneity. Data were adjusted in sets according to tissue type because the suitability of endogenous controls can be tissue specific (14). Standard curves were not generated for quantification experiments as all total RNA levels were within the linear and equal amplification range of the assay and thus applicable to quantification through normalization with ß-actin mRNA.
Conventional PCR and sensitivity assay. A conventional, heminested PCR was used to compare the sensitivity of the TaqMan assay and was performed as described elsewhere (15). Briefly, fivefold serial dilutions of a known RV-positive RNA sample were made in nuclease-free water, and RT was carried out by using a reverse transcription system with random primers. The same cDNA sample was used for heminested (10 µl) and TaqMan (1 µl/replicate) PCRs. Products of conventional PCRs (15 µl) were visualized on a 2% agarose gel stained with ethidium bromide (0.5 µg/ml).
Statistical analysis. Differences in the RNA yields were assessed by means of the Mann-Whitney U test. Associations between variables were determined according to Spearman's rank correlation coefficient (rs) or by linear regression analysis. For parametric tests, data were checked for normality by using the Kolmogorov-Smirnov test. All analyses were performed with SPSS version 11.0 (SPSS Inc., Chicago, Ill.).
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0.1 µg/µl). For experimental samples for which accurate measurement was possible, there were no significant differences in RNA yields from BR and SG samples (P = 0.805).
To test for potential saturation of the RT reaction, fourfold serial dilutions of total RNA from SG and BR samples were made in nuclease-free water and used for RT. The RNA quantities ranged from 1 µg to
17 pg. The linear ranges of the assay were comparable for RNA from both SG and BR (Fig. 2). Over this range, and for both tissue types, there was no evidence that amplification of ß-actin mRNA was nonlinear (results not shown). There were no differences in the linear ranges of the assay between TaqMan primer and probe sets or between samples of the same tissue but from different animals (results not shown). For both sample types, a departure from linearity was observed with the addition of between 15 and 63 ng of total RNA. In all cases this increase required the addition of more than 1 µl of stock RNA. Within the linear range (<63 ng for SG; <15 ng for BR), there was a strongly significant inverse correlation between the amount of total RNA and corresponding Ct (for both, rs = 1.000, P < 0.0001). The amplification efficiencies of the RV-specific target sequence and ß-actin mRNA were assessed by subtracting the ß-actin Ct from the RV Ct over this dilution series and assessing the stability of this new value with various amounts of RNA. Stable amplification efficiencies were evident for both SG and BR samples when <15 ng of total RNA was added (results not shown).
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FIG. 2. Linearity of the TaqMan reaction for RNA extracted from SG homogenates (A) and BR homogenates (B) from an experimentally infected rabid skunk. Error bars show 95% CL of the mean of three replicate TaqMan PCRs.
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Correlation with concentration of infectious virus. The SG homogenates from experimentally infected skunks were inoculated intracerebrally into mice, and a titer was calculated according to the Karber method (9). The MICLD50 correlated significantly (P < 0.01) with the corresponding TaqMan PCR quantity for samples from experimental animals (Fig. 3).
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FIG. 3. Correlation between infectious concentration of RV (mouse inoculation test) and TaqMan PCR quantity for SG tissues obtained from experimentally infected rabid skunks (rs = -1.00, n = 5, P < 0.01). For ease of interpretation, TaqMan quantities are given as 40 minus the mean Ct.
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FIG. 4. Comparative sensitivity of a conventional heminested PCR and TaqMan PCR for detection of RV RNA. (A) Products of conventional PCR. The upper band shows the 397-bp product from the first-round reaction; the lower band shows the 376-bp product from the heminested reaction. (B) Results of TaqMan PCR. A Ct value of 40 indicates a negative reaction. Error bars show 95% CL of the mean of three replicate TaqMan PCRs.
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Detection of rabies virus RNA from historical samples. Of the 62 historical isolates tested, 44 (71%) were typed correctly by this assay. That is, cDNA was successfully amplified by the TaqMan primers and probe designed to detect the variant to which the isolate was placed (Fig. 1). Only three samples (5%) were negative against all TaqMan primer and probe sets (Table 1).
There was considerable cross-reaction between the NCSK and CASK TaqMan assays: 11 samples were positive in the assays using both NCSK and CASK primer and probe sets, but in each case the lowest Ct (i.e., the highest PCR quantity) corresponded to the phylogenetic placement of the isolate (Fig. 1). Additionally, four samples designated NCSK by phylogeny were negative with the NCSK primer and probe set but positive with the CASK TaqMan primer and probe set (sample numbers 2865, 2572, 4374, and 4375).
Three samples were negative in assays that used all four sets of TaqMan primers and probes. Additionally, two samples had a mean Ct of >35. These five samples were all SCSK variants with a high number of mismatches between the viral sequence and that of the TaqMan primer and probe set (4, 5, 6, 5, and 5 mismatches for sample numbers 488, 744, 749, 912, and 3604, respectively). Furthermore, all of these samples contained a mismatch close to the center of the probe.
To assess the effect on Ct values of time since RNA extraction, samples with no differences in sequences from the sequences of the TaqMan primer and probe sets were selected. A correlation analysis showed that the age of the sample significantly reduced the unadjusted Ct value (rs = 0.549, n = 22, P = 0.008) but not the ß-actin-adjusted values (rs = 0.339, n = 22, P = 0.123). The method of RNA extraction did not significantly alter the results of the TaqMan PCRs (results not shown).
Influence of sequence mismatches on amplification. The results of TaqMan PCR assays using historical samples were normalized according to the levels of ß-actin mRNA. For each sample, adjusted values correlated significantly with raw values (rs = 0.851, n = 62, P < 0.001). Mean and adjusted data showed no significant departure from normality (P < 0.05). The total number of mismatches between the target sequences and those of the TaqMan primer and probe sets showed a significant positive association with Ct values (Fig. 5).
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FIG. 5. Association of TaqMan PCR values and sequence mismatches between the TaqMan primer and probe sets and the viral target sequences. The two variables are significantly associated in terms of ß-actin-adjusted data (F1,60 = 57.86, P < 0.001) and raw data (values not shown; F1,60 = 61.27, P < 0.001).
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The use of a large number of historical samples allowed an assessment of the effect of sequence mismatches between the TaqMan primers and probes and the viral target sequences. The primers and probes designed for this study were not intended to be optimal for the detection of the variants of interest but were chosen to allow a thorough, quantitative study of the effect of sequence mismatches on sensitivity and specificity. The genomic region from which the oligonucleotides were designed was limited to that where sufficient sequence data were available.
Mismatches between TaqMan primer and probe sequences and the target sequence are clearly detrimental to amplification. The number of mismatches reduces the efficiency of the reaction such that more than four differences can result in a weakly positive or negative result. A point mutation at the center of the probe (the site used for single nucleotide polymorphism detection) can prevent generation of a fluorescent signal although the PCR itself proceeds normally (results not shown).
For these reasons, which are based on existing sequence data, it seems unlikely that sufficient homology exists to generate TaqMan primer and probe sets capable of detecting a wide range of RV variants. For over 250 bat RV variants from the United States (where sequence data were available over a 300-nucleotide region of the N gene), based on the results of this study,
20 sets of TaqMan primers and probes would be required to detect every isolate (results not shown). An alignment of bat RV sequence data for the region covered by the TaqMan primer and probe set recently described to detect genotype 1 lyssaviruses (3) suggests that a number of these samples would not be detectable by existing TaqMan methodology (results not shown). The level of microdiversity within clades of RV may prove highly problematic in applying TaqMan technology to RV surveillance. Current PCR methods that utilize degenerate primers with a reduced annealing temperature allow amplification despite reduced sequence homology (15), although such methods do generate nonspecific products, requiring confirmation of the PCR results by nucleotide sequencing.
The possibility remains, however, of using TaqMan technology as an adjunct to existing detection methods. If the epidemiology of rabies is well defined within a geographical region, then screening with RV variant-specific TaqMan primer and probe sets could serve as a substitute for nucleotide sequencing. Multiplex assays have been developed that can simultaneously detect different variants and/or viruses (12, 24). Our TaqMan assay used random primers for cDNA generation and identical thermocycling conditions for each TaqMan primer and probe set, ensuring that the same cDNA sample can be used for multiple reactions on the same TaqMan plate, irrespective of the TaqMan primers and probes.
We propose that this TaqMan assay can be readily applied to quantitative studies of RV infection. Over a range of RNA levels there was little distortion of relative values when RNA concentrations that occur with clinical samples were used. In fact, these results suggest that samples for which high levels of total RNA are expected (e.g., tissues) should be suspended in >100 µl of water. The repeatability of the assay (as determined on the basis of different cDNA samples) was excellent in all cases. However, the variability due to repeat RNA extraction was not tested. Importantly, the quantity of RV determined by the TaqMan PCR assay correlated significantly with that estimated through virus isolation by the mouse inoculation test. Such an association is crucial when this technology is applied to pathogenesis studies, such as those used for foot-and-mouth disease virus infection of pigs (1). Although we have only assessed relative quantities of RV RNA, there is no evidence to suggest that absolute quantitation (according to quantitative standards) could not be developed if desired.
Crucial to the success of quantitative PCR is the ability to adjust the levels of RV determined by the TaqMan PCR according to levels of an endogenous control to account for variation in tissue samples and RNA extraction efficiency. Here we have shown that the levels of RV RNA determined by TaqMan PCR can be adjusted according to those of ß-actin mRNA. The amplification of both ß-actin mRNA and RV RNA had acceptable linear ranges and amplification efficiencies over the levels of total RNA used in this study and those likely to be used from biological samples. Normalization was successfully applied to correct for the effects of RNA degradation over time.
G.J.H. was funded by an American Society for Microbiology and National Centers for Infectious Disease postdoctoral fellowship.
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