Introduction

Schistosomiasis is a neglected tropical disease caused by blood-dwelling trematodes of the genus Schistosoma (Phylum Platyhelminthes, Class Trematoda). It has a high prevalence in subtropical regions of Africa, the Americas, and Asia (Gryseels 2012). This helminthiasis has been ranked second only to malaria among parasitic diseases, affects about 200 million people and causes about 41,000 deaths annually worldwide (Gryseels et al. 2006; WHO 2008). Out of the 21 currently recognized Schistosoma species, Schistosoma japonicum (China and Southeast Asia; dwells in peri-intestinal venules), Schistosoma mansoni (Africa, Arabia, and South America; dwells in peri-intestinal venules), and Schistosoma haematobium (Africa and Arabia; dwells in the perivesical plexus) are the main species responsible for human infections and are hence have public health significance as well as imposing an economic burden (Clerinx and Van Gompel 2011). Additionally, Schistosoma mekongi (dwells in peri-intestinal venules) is found in communities along the Mekong River in Cambodia and Lao People’s Democratic Republic. Although primarily of local importance, it is associated with high mortality rates (Muth et al. 2010; Meltzer and Schwartz 2013). Two of these species, S. japonicum and S. mekongi, can also infect some wild and domesticated animals as their reservoir hosts. Their zoonotic nature complicates control efforts (Hotez et al. 2007; Clerinx and Van Gompel 2011).

Nowadays, people are moving around the world more than ever before, responding to the need for social and economic development. Travel to a variety of tropical destinations by expatriates from nonendemic areas exposes them to risk of infection by several Schistosoma species (Li et al. 2015). The specific diagnosis of schistosomiasis in humans is central to control of this disease and to understand the intricacies of its epidemiology. Traditionally, microscopic, biochemical, and serological techniques have been applied for diagnosis of Schistosoma infections, but most of them have limitations in the specific identification, especially in the case of mixed infections and hybrids (Huyse et al. 2009; Zhao et al. 2012a). Increasing evidence from experimental and human studies has shown that polymerase chain reaction (PCR) and PCR-coupled methods improve the diagnosis of Schistosoma infection as well as the identification of Schistosoma species (Gobert et al. 2005; Sandoval et al. 2006; Kato-Hayashi et al. 2010; Lv et al. 2015). Although these techniques are useful and effective, the electrophoresis or sequencing analysis can be, in some cases, quite time consuming and expensive, rendering such tools impracticable for large-scale molecular epidemiological studies (Lymbery and Thompson 2012).

The high-resolution melt (HRM) technique uses a single closed tube in which PCR is followed by precise dissociation (melting) behavior determination of double-stranded DNA amplicons. The accuracy of the melting curve is maximized by acquiring fluorescence data over small temperature increments (as low as 0.02 °C) (Price et al. 2007). Samples can be discriminated according to sequence, length, GC content, or strand complementarity, down to single base-pair changes. The intercalating double-stranded DNA-binding dyes used do not inhibit PCR reactions at the concentrations necessary for them to fully saturate the target DNA duplexes and ensures the accuracy of experimental results. Such a probe-free assay is easier and more cost-effective and, unlike conventional methods, it has no manual post-PCR processing, thus avoiding the risk of contamination with PCR products. This method greatly simplifies the operation and reduces the analysis time, making it suitable for broad application. In the area of parasitology, it has been adapted recently for the genotyping of apicomplexan parasites (Al-Mohammed 2011; Costa et al. 2011; Ngui et al. 2012; Zhang et al. 2012; Higuera et al. 2013; Salim et al. 2013).

In the present study, we established a simple and effective real-time PCR assay coupled with HRM analysis, using the 18S ribosomal DNA (rDNA) region as the genetic marker, for the detection and differentiation of the four main Schistosoma spp. infecting humans, and discuss the value of such a tool in rapid screening and detection of closely related species in a laboratory.

Materials and methods

Parasites and isolation of genomic DNA

Twenty-five worm samples were originated from endemic areas in Puerto Rico, Cameroon, Egypt, China, Philippines, Japan, and Cambodia (Table 1). No specific permission was required for the collection of intermediate host snails of Schistosoma spp. Field studies did not involve any endangered or protected species. No ethical approval was required for the present study because all the parasite samples used in the present study had been prepared and used in previous studies (Sugiyama et al. 1997; Li et al. 2011; Zhao et al. 2010; 2012b). All S. japonicum worms in China were collected from rabbits exposed to cercariae from infected snails (Oncomelania hupensis) in our laboratory (Li et al. 2011; Zhao et al. 2010; 2012b), while S. japonicum from the Philippines and Japan were isolated from experimentally infected mice (Sugiyama et al. 1997). For S. mekongi, S. mansoni, and S. haematobium, worms were collected from rabbits or mice experimentally infected with cercariae from the relevant intermediate snail hosts (Neotricula aperta, Biomphalaria glabrata, and Bulinus spp., respectively). These worms were provided by Dr. Hiroshi Ohmae, Department of Parasitology, National Institute of Infectious Diseases, and by Dr. Mona S. Mahmoud in the Department of Parasitology and Animal Diseases, National Research Center, Dokki, Giza, Egypt. All the Schistosoma specimens were fixed in 70 % molecular grade ethanol and stored at −20 °C until used for DNA extraction. Additionally, some adults of common zoonotic parasites, namely Fasciola hepatica, F. gigantica, Clonorchis sinensis, and Opisthorchis viverrini were used as “controls” for the evaluation of the specificity of the specific PCR-coupled HRM assay.

Table 1 Schistosoma samples used in the present study
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Total genomic DNA (gDNA) of each parasite was extracted using SDS/proteinase K treatment, column-purified (Wizard® SV Genomic DNA Purification System, Promega) and eluted into 60 μL H2O according to the manufacturer’s recommendations. An RNAase treatment step was also used. Then, the quality of parasite gDNA was confirmed by amplification of the first internal transcribed spacer of ribosomal DNA (van Herwerden et al. 1998).

Primers, Real-time PCR, and HRM analysis

18S rDNA sequence has been identified as good genetic marker for identification and phylogenetic studies of Schistosoma members (Johnston et al. 1993; Attwood et al. 2002; Webster et al. 2006). The 18S rDNA sequence is also quite conserved within a Schistosoma species (Yu et al. 2000; Li et al. 2008). Our recent study also demonstrated that 35 S. japonicum isolates from mainland China, the Philippines, and Japan have almost identical 18S rDNA sequences, with only one nucleotide variation (Chen et al. 2011). Therefore, a portion of the 18S rDNA of four Schistosoma species was chosen as the genetic marker. A pair of primers for real-time PCR coupled with HRM analysis was designed specific for the V4 region (∼280 bp) of the nuclear 18S rDNA of four Schistosoma species (based on GenBankTM accession numbers AY157226, AY157228, SMU65657, Z11976). Primer names and sequences are as follows: M182U (5′-GGTAACTCCAGCTCCAAAAGCGTAT-3′) and M182D (5′-TTGTTCAAAGTAAAGATGCCGTCCG-3′). The real-time PCR conditions were optimized empirically. Finally, each PCR reaction (20 mL in volume) was performed in 10 μL 2× HRM PCR master mix (QIAGEN), 0.7 μM of each primer, and 1–50 pg genomic DNA in a Rotor-Gene 6000 (HRM)™ (QIAGEN) under the following thermocycling conditions: 5 min at 95 °C to activate HotStarTaq Plus DNA Polymerase, then 40 cycles of three steps: 10 s denaturation at 95 °C, 30 s annealing at 55 °C, and 10 s extension at 72 °C. After amplification, a melt step in the range 78 to 89 °C in 0.2 °C increments, pausing for 2 s per step, was initiated. The increase in Evagreen fluorescence was monitored in real time during the PCR, and the subsequent decrease during the melt phase was measured by acquiring each step to the green channel (470-nm excitation and 510-nm emission) of the Rotor-Gene 6000. Genotypes were then determined by examining normalized and difference melt plots using the Corbett Rotor-Gene 6000 software (Rotor-Gene Q Series Software 2.0.2) with a confidence limit specified as 80 % (a score above this signifying that a sample can be confidently assigned to a particular genotype, and a score below this indicating a sequence variation).

Cycle threshold (Ct) values and amplification efficiency were assessed to identify outliers (samples of poor quality) that were then filtered out of subsequent HRM analysis. Ct values would be ideally similar for samples and reference. Therefore, amplicons from randomly chosen S. japonicum, S. mansoni, S. haematobium, and S. mekongi individuals were purified and built into recombinant plasmids to establish standard references (namely Sjap-B, Sman-B, Shae-B, Smek-B, respectively, Table 1). Each plasmid stock was diluted so as to give a reaction Ct value between 10 and 20 when used as a standard. To examine their consistency, all standard references of each Schistosoma species were tested in triplicate and repeated on several different days using similar reagents and DNA concentrations. After determining the optimized reaction system and conditions, all samples under test were diluted (ddH2O dilution) or concentrated (DNAmate, TaKaRa, D605A) to match the Ct value of the standards. Any DNA with a Ct ≥ 30 was removed, because it indicated too little starting template or sample degradation. Reactions with amplification efficiency different from the standards or with efficiency less than 1.4 were omitted from evaluation as outliers (Poláková et al. 2008).

The identity of each amplicon was further confirmed by sequencing (Sangong Biotech, China). The acquired sequences were aligned with those of published Schistosoma species from GenBankTM, and phylogenetic analyses (MEGA5.2) (Tamura et al. 2011) were conducted subsequently to verify the accuracy of the genotype results obtained by the established HRM analysis.

Assessment of specificity and sensitivity of the detection assay

To evaluate the specificity of the designed HRM assay, some of the common zoonotic trematodes which are genetically closely related to Schistosoma and used in previous studies (Zhao et al. 2010, 2012b), namely, Fasciola hepatica, F. gigantica, Clonorchis sinensis, and Opisthorchis viverrini, were chosen as “controls.” For the sensitivity analysis, the concentration of DNA in each Schistosoma sample was determined using a spectrophotometer, and then tested in tenfold serial dilutions. The detection limit was determined as the smallest genomic DNA amount at which Ct value <30.

Validation of the HRM assay for identification and differentiation of isolates belongs to the four Schistosoma species

After optimization, 21 representative specimens representing four Schistosoma species from 15 geographical localities in seven endemic countries were randomly chosen to assess the capacity of the real-time PCR coupled with HRM assay (Table 1).

Results and discussion

Alignment of sequences from Schistosoma spp. showed that the ribosomal 18S gene is highly conserved within a species but exhibits some consistent interspecific differences (Johnston et al. 1993). One pair of primers (M182U and M182D), based on conserved portions of the sequences of the V4 region of the 18S rDNA, generated an amplicon from all tested Schistosoma species that could be used for detection and specific identification of these. The primers did not amplify host DNA. Samples representing four Schistosoma species were randomly chosen to establish the standard reaction. All samples amplified a product of about 280 bp with a good Ct value around 10 to 20. Unique HRM profiles were produced for each of the four Schistosoma species (Fig. 1). Nucleotide sequence analyses and phylogenetic analysis of the amplicons confirmed the identity of each species (not shown).

Fig. 1
figure 1

Real-time PCR amplification curve (upper panel) and agarose gel electrophoresis (lower panel) of a portion of the 18S rDNA from four Schistosoma species. Sjap S. japonicum, Smek S. mekongi, Sman S. mansoni, Shae S. haematobium, NC negative control; M DL2000 marker

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The specificity of the detection assay was examined by comparison with some other common zoonotic trematodes. Amplicons could be produced from all worm species using these primers, but visual assessment of the conventional and normalized curves could distinguish all species, with the genotypes of other trematodes represented as “variation” after analysis of the melt curve by the software (Fig. 2, Table 2). The assay sensitivity was assessed by using tenfold serial dilutions of predefined Schistosoma genomic DNA (recombinant plasmids). Besides, there was a good linear correlation coefficient (R 2 = 0.992) between the log concentrations of purified DNA (1–10-6 ng) and the Ct value (Fig. 3). The lower limit of detection was 10-5 ng (Fig. 3), which was four orders of magnitude more sensitive than conventional agarose electrophoresis (Li et al. 2011; Zhao et al. 2012b) and three orders of magnitude higher than polyacrylamide gel detection (Zhao et al. 2010). Our detection assay displayed a high degree of sensitivity and reproducibility.

Fig. 2
figure 2

Specificity of HRM analysis of normalized and temperature-shifted melting curves of Schistosoma spp. and other common zoonotic trematodes. Sjap S. japonicum, Smek S. mekongi, Sman S. mansoni, Shae S. haematobium, NC negative control. Melting peaks of trematodes, Bin A includes S. japonicum and S. mekongi, Tm, 83.65 °C; Bin B represents S. mansoni, Tm, 85.65 °C; Bin C represents S. haematobium, Tm, 85.85 °C; Bin D includes C. sinensis and O. viverrini, Tm, 85.78; and Bin E includes Fasciola hepatica and Fasciola gigantica, Tm, 86.30 °C

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Table 2 Melting points for the peaks and HRM curve profiles of 18S rDNA PCR products from species of Schistosoma
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Fig. 3
figure 3

Assessment of sensitivity of the HRM assay for detection of Schistosoma spp. a Lanes 1–7 represent serial dilutions of genomic DNA of S. japonicum, 1–7: dilutions 1 to 10-6 ng, respectively. b A linear correlation is shown between the Ct and the tenfold diluted DNA of Schistosoma spp. NC negative control

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To assess the capacity of HRM curve analysis for the detection and identification of specimens of different species, 21 individual specimens of Schistosoma from different endemic regions were analyzed: S. mansoni (n = 3), S. haematobium (n = 3), S. mekongi (n = 4), and S. japonicum (n = 11). Visual assessment of the conventional and normalized curves could distinguish all species (Fig. 4, Table 2) with high confidence values. No signal was detected in the negative controls. The melting curves were characterized by peaks of 83.65 °C for S. japonicum and S. mekongi, 85.65 °C for S. mansoni, and 85.85 °C for S. haematobium (Fig. 4). Although S. japonicum and S. mekongi melting peaks were identical to each other, their melting profiles are significantly different. In S. mekongi, a minor peak on the left shoulder of the major peak is a distinctive feature (Fig. 4). These are known to be closely related species from Asia (Chen et al. 2011, 2015), so the similarity is not surprising. S. mansoni and S. haematobium are both from Africa and rather distantly related to the Asian species (Chen et al. 2011; Zhao et al. 2012c).

Fig. 4
figure 4

Real-time PCR and HRM analyses for all Schistosoma spp. samples. a Normalized melting curves for Schistosoma spp. isolates. b Melting peaks of Schistosoma spp. Bin A includes S. japonicum and S. mekongi, Tm, 83.65 °C; Bin B includes S. mansoni, Tm, 85.65 °C; and Bin C includes S. haematobium, Tm, 85.85 °C. Sjap S. japonicum, Smek S. mekongi, Sman S. mansoni, Shae S. haematobium, NC negative control

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Detection of characteristic eggs of parasitic worms, including Schistosoma species, is the “gold standard” for diagnosis. However, direct detection of eggs is not possible in prepatent infections, and difficult in low-endemicity areas, hence rendering specific diagnosis difficult especially in travelers and expatriates with mixed infections (Meltzer and Schwartz 2013).

In recent years, with the increased numbers of travelers and expatriates worldwide, the potential risk of Schistosoma spp. coinfection in endemic areas or discovery of infection in returning travelers and immigrants has attracted broad attention. Development of a rapid and easy screening method for identification and differentiation of species of blood flukes is a problem to be solved. Many PCR and real-time PCR methods (Kato-Hayashi et al. 2010; Cnops et al. 2012; Ten et al. 2008) have been previously reported but showed limitations for rapid interspecies identification. Marx et al. (2000) used a genome-wide melting curve scanning method to distinguish between S. mansoni, S. japonicum, and S. haematobium. Then, Kongklieng et al. (2013) made real-time PCR with high-resolution melting analysis to differentiate S. japonicum and S. mekongi. Compared with traditional melting curve analysis of Marx et al. (2000), the HRM detection assay established in the present study provides more information than just the calculated melting temperature (Tm), permitting differentiation on the basis of curve shape, even when they define the same Tm values (Jin et al. 2012). In addition, the detection method for two schistosoma species established by Kongklieng et al. (2013) showed limited detecting scale compared with the present study which made rapid detection and identification of four major Schistosoma species. Furthermore, the entire process from PCR to HRM curve analysis can be completed within 3 h, which is a great time saving.

In conclusion, the present study developed a real-time PCR coupled with HRM analysis assay for detection and differential identification of S. mansoni, S. haematobium, S. japonicum, and S. mekongi. This method has the advantage of being rapid, sensitive, and inexpensive. It has important implications for epidemiological studies and could be applicable to diagnosis of a wide range of microorganism species, especially when these are closely related.