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Applied and Environmental Microbiology, September 2006, p. 5857-5863, Vol. 72, No. 9
0099-2240/06/$08.00+0 doi:10.1128/AEM.00113-06
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Australian Water Quality Centre, South Australia Water Corporation, Private Mail Bag 3, Salisbury, South Australia 5108, Australia
Received 16 January 2006/ Accepted 27 June 2006
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In our laboratory, the density of thermophilic amoebae is estimated by differential plaque counts, with identification of discrete plaque types by biochemical or molecular criteria. Until recently, identification was based on a well-validated data set of isozyme profiles (1, 9, 25). While isozyme analysis has a number of attractions, it is less sensitive than DNA sequence-based methods, requiring 106 to 107 cells for detection of sufficient enzyme activity. In moving toward sequence-based identification, we have several criteria for an effective method. Foremost, the method must be definitive in identifying the pathogenic and potentially pathogenic species. Second, to facilitate multiple identifications of strains to enable quantitation, the method should be simple and reliable to execute, with as few steps and requiring as few specific molecular tools as possible. Finally, it is desirable that the method provide simultaneous identification of as many Naegleria species as possible for the collection of ecologically useful data. The published PCR methods for Naegleria (16, 19, 23, 26, 27) meet these criteria only to a limited extent, as all require end-point analysis using agarose gel electrophoresis and none identifies species other than N. fowleri without additional sequencing.
DNA melting-curve analysis is a relatively new analytical technique that can be applied post-PCR to provide information on the characteristics of the amplification products. To date, this technique has been used principally as an alternative to gel electrophoresis to verify the identity of a desired PCR product (21, 24, 32), or to differentiate the matching or mismatching of particular types of hybridization probes, for example, in fluorescence resonance energy transfer (22, 31). A few publications have explored the potential of melting analysis to differentiate the products of a PCR in which the primers are conservative but the amplified material spans a region of variable sequence (11, 14, 18). The most commonly used dye for DNA melting-curve analysis is SYBR green I; however, melting curves generated using this dye are sensitive to changes in either dye or DNA concentration (17, 24). Recently, two alternative dyes, LCGreen (30) and SYTO9 (17), have been reported to provide melting-curve-analysis performance superior to that of SYBR green I.
Currently, the soundest systematic scheme for Naegleria species is based on the internal transcribed spacer (ITS) region of the ribosomal DNA (rDNA) complex, comprising ITS1-5.8S rDNA-ITS2 within which the sequence of individual species is almost invariant but divergent from other species (6, 8). The consensus primers for this region were originally designed to amplify DNA for sequencing from a range of Naegleria species. The published data suggested to us that the sequence differences in this region might be manifested in distinguishable, species-specific melting curves. In this paper, we report a discriminating and sensitive method for identifying thermophilic Naegleria species, based on real-time PCR coupled with melting-curve analysis of the ITS amplicon using the intercalating dye SYTO9.
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TABLE 1. Positions of diagnostic melting curve peaks for reference strains of Naegleria species and Willaertia magna
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PCR and melting analysis.
Real-time PCR and melting-curve analysis were carried out in a RotorGene 3000 (Corbett Research, Sydney, Australia). An advantageous feature of this instrument for our purpose is that it permits the operator to manipulate key conditions of the melting analysis, including the temperature interval and the holding time before fluorescence data are collected at each step. The 20-µl reaction mixture consisted of 200 µM concentrations of deoxynucleoside triphosphates (Promega, Madison, WI), 200 nM forward and reverse primers (NGITSF, 5'-AACCTGCGTAGGGATCATTT, and NGITSR, 5'-TTTCCTCCCCTTATTAATAT (6), PCR buffer II, 2.5 mM MgCl2 (Applied Biosystems, Branchburg, NJ), 2.0 µM SYTO9 (Molecular Probes, Eugene, OR), 1 U of AmpliTaq Gold (Applied Biosystems), and 2.0 µl of sample DNA in Instagene supernatant or nuclease-free water. A range of conditions for real-time PCR were tested. Unless otherwise stated, the conditions for experiments reported here were 10 min at 95°C to activate Taq polymerase, followed by 50 cycles of 20 s at 94°C, 20 s at 50°C, and 20 s at 72°C. The ramping between the extension and melting steps included a 1-s pause at 80°C for acquisition of fluorescence data (6-carboxyfluorescein channel, excitation at 470 nm, detection at 510 nm, gain set to maximum of 10). Upon completion of amplification, the program continued directly to a melting-curve analysis in which temperature was ramped from 75 to 95°C in steps of 0.5°C. Fluorescence data were collected after pauses of 60 s on the first step and 20 s on subsequent steps to allow the melting DNA structure to stabilize, again using the 6-carboxyfluorescein channel, but with two gain settings, 3 and 5, to allow for variations in the amount of product amplified. For fine-scale resolution of the melting analysis, data were collected in some experiments at 0.2°C intervals, with pauses of 60 s on the first and 10 s on subsequent steps. The method of analysis of the DNA melting-curve data is critical for the resolution of multiple melting domains. The RotorGene software uses bicubic interpolation to estimate fluorescence between data points when graphing the negative of the first derivative of the raw DNA melting data and provides the option of curve smoothing. For all analyses reported here, no smoothing was used in the generation of melting curves (i.e., the digital filter was set to none).
Sensitivity.
To determine the sensitivity of the method, serial dilutions of DNA extracted from a known number of log-phase cells were run in triplicate in the real-time PCR for N. fowleri NG166 (several experiments using separate DNA extracts), N. lovaniensis, and N. carteri. This quantitative PCR was calibrated to cell number because the copy number of rRNA genes is known only for N. gruberi (5) and because it provided the sensitivity measure most useful in assessing the utility of the assay for identifying environmental isolates. The proprietary software of the RotorGene 3000 calculated the best fit of threshold cycle (CT) as a function of cell number by linear regression to produce a standard curve.
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FIG. 1. Melting curves of the 5.8S rDNA/ITS product of seven Naegleria species: N. fowleri (a), N. lovaniensis (b), N. italica (c), N. australiensis (d), N. gruberi (e), N. byersi (f) N. carteri (g), and Willaertia magna (h). Diagnostic features include the number and position of peaks and their relative heights.
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The species specificity of the melting curves is confirmed by their concordance with isozyme- or sequence-based identification for all strains tested (between 3 and 20 per species). The reproducibility among strains is illustrated by plotting Tm1, Tm2, and the ratio of the peak heights in three-dimensional space (Fig. 2): the combination of these key features of the melting curves is clearly discrete for each species. We investigated the small but reproducible difference in the position of peak 1 for N. italica and N. gruberi by running melting analysis at 0.2°C intervals. Each melting curve was resolved into a series of smaller peaks (Fig. 3), which we term cryptic peaks, since they are hidden at the temperature resolution of the usual diagnostic test. In particular, the position of peak 1 at 0.5°C resolution is seen to be determined by the weighted average of several cryptic peaks which have coincident positions but different relative heights in the two species (Fig. 3).
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FIG. 2. Diagnostic features of the melting curves of multiple strains of Naegleria species and Willaertia magna, plotted in three-dimensional space: N. fowleri ( , n = 20), N. lovaniensis ( , n = 20), N. carteri ( , n = 16), N. italica ( , n = 5), N. australiensis (, n = 20), N. gruberi ( , n = 3), N. byersi ( , n = 3), and Willaertia magna ( , n = 6). Note that many of the points are nearly coincident.
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FIG. 3. Melting curves of the 5.8S/ITS product of N. italica NG073 (thin line) and N. gruberi NG008 (thick line) resolved at 0.2°C. The boxed area highlights the cryptic peaks that contribute to the small difference in position of peak 1 at 0.5°C resolution (compare Fig. 1c and e).
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FIG. 4. Sensitivity of real-time PCR and integrity of melting curves for N. fowleri NG166. (a) Relationship of CT to DNA concentration, expressed as the log-equivalent number of cells (r = 0.987); (b) melting curves from the corresponding melting analyses; (c) lack of effect of starting template concentration on the position of melting peaks.
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FIG. 5. Melting curves of amplified DNA from multiple Naegleria plaques from a survey of an industrial cooling system, showing unambiguous identification of N. fowleri and N. lovaniensis (Rotorgene-generated graphic).
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The current expanded taxonomy of Naegleria, which recognizes more than 30 species, is based on sequence divergence in the 5.8S rRNA gene and the flanking noncoding spacers, particularly the longer ITS2 (7, 8). Comparison of large- and small-subunit (LSU and SSU) sequences returns similar relationships among Naegleria species, but these genes have not been sequenced for some of the more recently named species. Since the rRNA genes in Naegleria and related organisms are encoded on an extrachromosomal circular DNA element with a copy number estimated at 3 x 103 to 5 x 103 in N. gruberi (4, 5), these genes make ideal targets for a sensitive, sequence-based identification method.
While the published primers have been used principally to amplify DNA for sequencing, Pélandakis and Pernin (19) developed a multiplex PCR using these consensus primers to identify Naegleria collectively and species-specific primers to identify N. fowleri. In other published sequence-based identification methods for N. fowleri, the PCR targets have been an ATPase 6-subunit homologue (16, 27) or genes from clone libraries which have unknown functions but have been shown by hybridization to be N. fowleri specific (12, 23).
Recently, there has been a move toward direct detection of N. fowleri by extraction of DNA from environmental samples and amplification by N. fowleri-specific PCR (15, 26). Such a method is attractive because it has the potential to be more rapid, since it eliminates the cultivation step, and because it removes the need for microscopists experienced in the generic identification of Naegleria species. Unfortunately, DNA-based detection also presents several difficulties. First, the potential for coconcentration of environmental materials that are inhibitory to PCR makes it necessary to design inhibition controls to interpret negative results correctly (and, if quantitative PCR is attempted, to ensure that the quantity of the product can be reliably related to a standard curve). Second, the stability of genomic DNA and the high copy number of rDNA targets make the detection of nonviable organisms highly likely; this may not be a problem if the analysis has a forensic purpose but is not helpful in prospective investigations of risk or in the monitoring of water treatment processes. All of the methods reviewed here require gel electrophoresis to verify the PCR product and none identifies Naegleria species other than N. fowleri without additional sequencing.
Our approach to identification is based on an idealization that analysis of environmental samples should detect only viable N. fowleri, that it should provide estimates of organism density, that it should be simple, rapid, and inexpensive, and that, if possible, it should identify the other potential pathogens and benign Naegleria species. The requirements for quantitation and identification of other species have an ecological basis. N. fowleri is far more dynamic in aquatic environments than truly parasitic protozoa such as Cryptosporidium or Giardia, with marked spatial and temporal density variations arising from proliferation, mortality, and conversion between amoeboid and flagellate forms. Observation of these patterns and interpretation of their significance for the risk of infection demands a quantitative approach. The occurrence of other Naegleria species, particularly those in the same or adjoining thermal niches, adds another dimension to ecological questions; understanding the seasonal and spatial distribution of this community of organisms can lead to more intelligent design of investigative and monitoring programs.
Melting-curve analysis is growing in precision as thermal cyclers continue to improve in the precision and reproducibility of temperature ramping. In its simplest form, melting analysis employs an intercalating fluorogenic dye specific for double-stranded DNA, most commonly SYBR green I, to monitor the amount of duplex DNA during both the amplification phase of the real-time PCR and the subsequent controlled melting. Melting of a PCR product is predicted to depend on its size and GC content, and melting temperature (Tm) is increasingly being used to verify that a particular target sequence has been amplified, replacing gel electrophoresis and reducing the repeat handling of samples and PCR products in some assays (24). Under carefully controlled conditions, the separate products of a real-time multiplex PCR can be recognized as separate peaks in a more complex melting curve (17). SYBR green I has a number of limitations, including inhibition of PCR at certain concentrations (17), selective attachment to higher-temperature-melting products, and dye redistribution during melting (10). Exploration of the utility of other dyes, including LC Green (30) and SYTO9 (17), is in its early stages.
A few recent studies have reported the discrimination of closely related microorganisms using SYBR green I and melting analysis coupled to PCR with a single set of consensus primers. Where the PCR product spans a region whose sequence has diverged among the organisms of interest, the differences may be sufficient to be manifested as distinguishable curves. Nicolas et al. (18) amplified part of the Leishmania kinetoplast minicircle DNA (kDNA) that varies in length among species from 650 to 750 bp. The amplicons melted at characteristic and distinguishable Tms for Leishmania major and Leishmania donovani, while Leishmania tropica and Leishmania infantum melted at a third Tm but were not distinguishable from each other. The melting profile was simple, comprising only a single peak for each species, and Tms were reproducible (<1% variation between different runs) and not greatly affected by DNA concentration in the case of L. major. Helps et al. (11) reported the differentiation of feline caliciviruses from the Tms of a 76-bp amplicon spanning a variable region. The melting profile for this amplicon resulted in a single peak, and the maximum variation in Tm between replicates for any given isolate was 0.2°C. The authors did not investigate the effect of different starting numbers of virus on Tm and attributed the variation in Tm to sequence variation between isolates. Most recently, Mangold et al. (14) distinguished four Plasmodium species using the Tms of partial SSU rDNA duplexes amplified using consensus primers and labeled with SYBR green I. As with the other reported assays, the melting profile consisted of a single peak. The variation in Tm among replicates was higher than that reported in the two other studies, and the authors observed differences in Tm between plasmid clones and patient specimens for the same amplicon. The effect of DNA concentration on Tm was not investigated and could have been a contributing factor to the variation that they observed. Melting curve analysis has also been used to differentiate Cryptosporidium species that have different host specificities (13, 28).
In the study reported here, we were able to distinguish the pathogenic Naegleria species N. fowleri, potential pathogens N. italica and N. australiensis, four benign Naegleria species, and the related organism Willaertia magna. This assay represents a considerable advance on other published diagnostic applications of melting analysis described above, which we attribute to the information-rich and reproducible melting profiles observed. There is little recognition in published reports that the step-wise, sequence-dependent melting of double-stranded DNA might be manifested in distinguishable melting maxima within a single amplicon. Indeed, the conventional definition of Tm as "the temperature where one-half of the nucleotides are paired and one-half are unpaired" (29) does not encourage the exploration of this possibility. The complexity of DNA melting has long been recognized in physical chemistry; most of the experimental work in this area has been directed at understanding the subtransitions that occur when specific (usually synthetic) sequences melt over narrow temperature intervals (2). The only significant discussion in the diagnostic literature is that of Wittwer et al. (30), who recognize that distinguishable melting domains of 50 to 300 bp may occur within larger amplicons. Here, we treat the reproducible peaks as local maxima in the melting process, with the annotation Tm1, Tm2, etc.
We believe that the melting curves reported here are more informative than any previously published. This has been made possible by the selection of an appropriate intercalating dye, the size and specific sequences of the PCR products, the temperature resolution (i.e., the interval between fluorescence measurements), and the method of graphing the first derivative of the fluorescence data without smoothing. The latter is particularly important because data smoothing, which is often a default setting of the software used to operate real-time PCR platforms, will result in a loss of peak resolution.
Since a number of experimental variables can influence Tm, including choice of dye, Mg2+ concentration, ramping rate, and holding time at each temperature step, the values reported here are not absolute characteristics of the species studied. Nevertheless, the assay is highly reliable and lends itself readily to making multiple identifications in conjunction with a plaque count method to enable species quantitation. Application to environmental samples has resulted in successful identification of a large number of isolates, with a relatively small number showing divergent melting curves. We suspect that these melting curves represent different species and have archived selected isolates for further study.
At present, the melting domains cannot be assigned to specific sequence domains, but we believe that there are real prospects for doing so. For example, the observation that N. fowleri, which has the most AT-rich ITS1 in the genus (6), also has the most significant leftward (low temperature) peak suggests that this peak may correspond to (or incorporate or overlap with) ITS1. We postulate that the currently recognized N. fowleri genotypes that vary in the number of tandem repeats in ITS1 (6, 20, 33) might be distinguishable in this part of the melting curve. We intend to pursue the theoretical interpretation of the melting curves reported here and to explore the identification of the N. fowleri genotypes and additional Naegleria species by similar criteria.
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