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ABSTRACT |
 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Combinations of single nucleotide polymorphisms (SNPs) in the dihydrofolate reductase (dhfr) gene at codons 51, 59, 108 and 164 and the dihydropteroate synthetase (dhps) gene at codons 436, 437, 540, 581, and 613 correlate with P. falciparum resistance to SP in vivo.2–4 Primarily, mutations in codons 51, 59, and 108 of dhfr coupled with codons 437 and 540 of dhps have been associated with a high risk of SP treatment failure.2,3 For CQ, a single key mutation at position 76 of the P. falciparum chloroquine resistance transporter (Pfcrt) gene has been linked to CQ resistance.5–7 Thus, increasing problems with drug resistance are reflected in the frequency of mutations in these genes and longitudinal monitoring of mutations in the parasite population can be used in large-scale surveillance of drug resistance.2,8,9
Currently, the most commonly used method to identify SNPs in dhfr/dhps and Pfcrt is a nested polymerase chain reaction (PCR) followed by restriction fragment length polymorphism (RFLP) analysis.10 This method is reliable, but not suitable for high-throughput screening. Furthermore, the results are constrained to individual analysis of each SNP and interpretation is complicated by the occurrence of multiclonal P. falciparum infections.11
Analyses of haplotypes detecting combinations of SNPs in one gene may be more suitable and biologically sound than measuring the prevalence of SNPs when assessing SP and CQ resistance at a population level,12 and alternatives to the PCR-RFLP method have been developed. Abdel-Muhsin and others described a dot-blot method for the detection of a limited number of SNPs in dhfr using radiolabeled sequence-specific oligonucleotide probes (SSOPs) post-PCR.13 Mehlotra and others developed a similar system for the detection of Pfcrt haplotypes at c72–76 using fluorescein isothiocyanate-labeled SSOPs.14 Pearce and others described a high-throughput PCR SSOP-dot blot method detecting all known SNPs of dhfr and dhps using digoxigenin-labeled probes and high stringency washing with tetra-methyl-ammonium chloride (TMAC), enabling similar stringent washing procedures for almost all the SSOPs, simplifying the methodology significantly.12
Here, we describe a dot blot–based technique where the SNPs are visualized in an enzyme-linked immunosorbent assay (ELISA) system. The technique is simple and allows laboratories with limited laboratory facilities to process a large number of samples. The methodology is applicable regardless of the gene or organism under investigation, and the technique can be applied as a general tool for the detection of SNPs.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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To test the validity of the SSOP-ELISA technique, we compared it to the dot blot method described by Pearce and others12 and the PCR-RFLP method described by Duraisingh and others10 using 84 samples collected on filter paper at the Tanganyika Planting Company (TPC) sugarcane plantation in Moshi, Tanzania. All samples were collected after informed consent was obtained from the patients by trained clinicians at the TPC sugar plantation hospital. Ethical permission for the study was obtained from the Tanzanian National Institute of Medical Research ethics committee and the London School of Hygiene and Tropical Medicine. The samples were for comparison and validation of the methods and the details of the patients will be described elsewhere (Drakeley C and others, unpublished data).
Extraction of DNA from parasites in culture and from blood samples on filter paper. Parasite isolates were grown in vitro and approximately 2.5 x 108 parasites were purified by magnetic activated cell sorting.15 The purified parasite cultures were extracted with phenol/chloroform and precipitated with ethanol as described by Sambrook and others.16 The resulting DNA pellet was resuspended in 30 µL of water. The 3D7 isolate was used to determine the sensitivity of the SSOP-ELISA. DNA was extracted from 250,000 3D7 parasites and resuspended in 50 µL of water. The sample was diluted 10-fold to a concentration corresponding to one parasite genome/µL. Extraction of DNA from bloodspots on filter paper was carried out by the Chelex-100 method described by Wooden and others17 with some modifications described by Pearce and others.12
Polymerase chain reactions for dhfr/dhps and Pfcrt. A nested PCR described by Pearce and others12 was used to amplify fragments of the dhfr and dhps genes. A nested PCR described by Djimde and others18 (described in detail at http://medschool.umaryland.edu/CVD/nejm2001djimde.htm) was used to amplify fragments of the Pfcrt gene. The only modification in our procedures was that the M9, R/, and TCRD2 primers for the dhfr, dhps, and Pfcrt nested PCRs were biotinylated at the 5'-end by the supplier (MWG Biotech, Riskov, Denmark). The 20-µL dhfr/dhps outer PCR mixture consisted of 0.3 mM of each dNTP, 0.25 µM of either primer set M1/M7 (dhfr) or N1/N2 (dhps), one unit of DNA HotStart polymerase (Qiagen, Albertslund, Denmark), buffer containing 1.5 mM MgCl2, as recommended by the manufacturer (Qiagen), and 1 µL of extracted DNA.
Prior to use of the outer dhfr PCR products for the nested reactions, the products were diluted 1:20 in distilled water in a PCR plate and 1 µL of these dilutions or the outer dhps PCR products were used in the nested PCRs. The nested dhfr and dhps PCR reaction mixture was the same as the outer PCR mixture using primer sets M3b/M9 and R2/R/ for the dhfr and dhps PCR, respectively. The outer and nested dhfr/dhps PCR conditions were as previously described.12
The 20-µL Pfcrt outer PCR mixture consisted of 0.2 mM of each dNTP, 1 µM of the primer set TCRP1/TCRP2, 1.25 units of DNA Qiagen HotStart polymerase, buffer containing 2.5 mM MgCl2, and 1 µL of extracted DNA. The reaction mixture of the nested Pfcrt PCR was identical to that of the outer PCR and the primer set TCRD1/TCRD2 was used. The conditions of the outer and nested Pfcrt PCR were as previously described.18
Amplifications were performed in 96-well PCR plates and the reaction mixture was overlaid with one drop of mineral oil. The nested PCR products were confirmed by electrophoresis on a 1.5% agarose gel along with a set of controls.
SSOP-ELISA. The ELISA plates (Maxisorp; Nunc, Roskilde, Denmark) were coated with streptavidin in phosphate-buffered saline (PBS) (1 µg/mL), covered,and left overnight at 4°C. The plates could be kept for at least two weeks at 4°C without loss of reactivity. Prior to use, the plates were washed three times in washing buffer (1x PBS containing 0.05% Tween 20).
The nested PCR products were diluted 1:10 in water in a 96-well PCR plate, denatured at 95°C for 5 minutes, and immediately thereafter cooled to 4°C until use. One hundred microliters of cold dilution buffer (1x PBS with 0.05% Tween 20) and 2 µL of the diluted PCR products was then added to each well of the ELISA plate. Replicate ELISA plates were made to enable simultaneous probing with SSOPs targeting the full panel of dhfr, dhps, and Pfcrt SNP/haplotypes. The plates were incubated at room temperature for one hour and washed three times in washing buffer. The 3'-end digoxigenin-conjugated SSOPs (MWG Biotech) were diluted in tetra-methyl ammonium chloride (TMAC; Sigma Aldrich Chemie, Seelze, Germany) solution (3 M TMAC, 50 mM Tris, pH 8.0, 0.1% sodium dodecyl sulfate, 2 mM EDTA, pH 8.0), heated to 53°C, and 100 µL was then added to each well at the concentrations indicated in Table 1
. The plates were then incubated in a hybridization oven (AH Diagnostics, Aarhus, Denmark) at 53°C on a shaking device for one hour and washed three times in washing buffer. This was followed by two rounds of washing and incubation (10 minutes per round) in TMAC solution at the temperatures indicated in Table 1. To remove TMAC, the plates were then washed three times in washing buffer and peroxidase-conjugated anti-digoxigenin antibody in dilution buffer (1:1,000) (Roche Diagnostics, Mannheim, Germany) was added to each well. After incubation for one hour at room temperature, the plates were washed three times in washing buffer and an o-phenylenediamine solution of 1.5 mg/mL of 1,2-phenyldiamine dihydrochloride (Dako, Glostrup, Denmark) dissolved in water containing 0.015% H2O2 was added to the plates. After 30 minutes, the reaction was stopped by adding 1.25 M H2SO4 and the optical density (OD) at 492 nm was measured in an ELISA reader. A flow chart of the method is shown in Figure 1.
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PCR-RFLP assay. The outer dhfr and dhps PCR products produced as described earlier were used in the nested dhfr and dhps PCR-RFLP assays; otherwise, the nested primers and conditions described by Duraisingh and others10 was used. The RFLP was performed using restriction enzymes and buffers obtained from New England Biolabs (Medinova, Glostrup, Denmark). The digested products were visualized by electrophoresis on 2–2.5% Metaphor agarose gels (Medinova) and analyzed using Kodak (Rochester, NY) 1D software version 3.5.3.
Scoring of ELISA and dot-blot data. The OD values of positive and negative controls varied between experiments, although only rarely compromising specificity. The variation was possibly due to marginal differences in the strength of the probe binding and washing force during the high-stringency washes. Thus, no fixed threshold value could be specified and for each SNP test, a simple analysis of the positive and negative control samples was performed to set a threshold for positivity. For each SNP analyses, parasite samples were categorized into single, mixed but with one SNP in majority or mixed infections as follows: Infections were considered to be of single genotype when only one SNP was present at OD values above the threshold of positivity. Samples were considered to be mixed but containing a majority SNP genotype when the OD value of the weakly reacting SSOP was less than half the OD value of the strongly reacting SSOP. Conversely, if the OD value of the weakly reacting SSOP was higher than half the OD value of the strongly reacting SSOP, the infection was categorized as mixed with no dominant genotype. For samples that contained infections categorized as single or mixed with a dominant SNP type at all analyzed codons, results were combined to construct haplotypes.
The manual scoring of the dot-blot results was performed on a light table. The definition of single, majority, or mixed infections for each SNP and combined as haplotypes was performed with a similar methodology as described earlier.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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show that the assay correctly identified the SNPs of the different isolates using SSOPs for 50/51CN, 50/51CI, 59C, 59R, 108S, 108N, and 108T. The OD values of the positive reactions obtained with specific probes were markedly higher than the OD values obtained when using unspecific probes. The difference in OD value between the threshold of positivity and the positive reactions (
OD) was always greater than 1. To assess the specificity for most of the SSOPs in the dhps SSOP-ELISA, the four laboratory isolates and three additional parasite isolates from malaria patients were tested using SSOPs for 436/437AA, 436/437AG, 436/437SA, 436/437SG, 436/437FG and for 540K, 540E, 581A, 581G, 613A, and 613S (Figure 3). The assay correctly identified the SNPs of the different isolates. The threshold of positivity and the OD vary between SNPs and between consecutive experiments; however, the ODs for the different SNPs were at least 1. Testing of the remaining SNPs of dhfr (variants at c50/51 and 164L) and dhps (436/437CA, 436/437FA, and 613T) were done, but are not shown since positive controls for these SNPs were unavailable.
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show that the assay correctly identified the c72–76 haplotypes of the different isolates using SSOPs for CVMNK, CVIET, and SVMNK. The OD was at least 1. Finally, the sensitivity of the SSOP-ELISA was determined using a 10-fold dilution series of 3D7 with the dhfr c108 SSOP-ELISA as standard. The results indicated that the SSOP-ELISA was capable of detecting DNA from one parasite genome.
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) and identical positive results were obtained for 74 of 80 samples (92.5%). The dhps haplotypes were constructed based on analysis of SNPs at 436/437 and c540. The two methods gave identical positive results for 65 of 69 samples (94.2%) (Table 2). One sample was found to be AAK by dot blot, but SGE by SSOP-ELISA; however, this sample had the SGE haplotype as a minority infection by dot-blot.
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). One sample was found to be CIRN by RFLP but CNRN by SSOP-ELISA; however, the SSOP-ELISA analysis showed that CIRN was present as a minority haplotype. For the dhps haplotypes (Table 3), identical positive results were obtained in 49 of 54 samples (90.7%). However, some differences were encountered. Seventeen samples were found to be negative at one or more codons by RFLP and positive by SSOP-ELISA, while nine samples were negative at one or more codons by SSOP-ELISA and positive by RFLP. The detailed dhfr and dhps genotype distribution by SSOP-ELISA of the patient samples is available as Appendix 1 at http://www.cmp.dk/SSOP-ELISA/TPC.pdf
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The methodology uses an outer and nested PCR for dhfr and dhps amplification step almost identical to that described previously,12 except for the inclusion of one biotinylated primer in each nested PCR. The nested PCRs are performed as single nested PCRs for each gene in contrast to several needed for the PCR-RFLP method, simplifying the procedure and reducing the cost. This is because the PCR-RFLP method is sometimes hampered by the dependency of recognizable restriction sites in the sequence surrounding a SNP in question. Thus for this method, it is often necessary to design additional PCRs with modifications into one of the primers to provide a suitable restriction site. For the PCR-ELISAs, SSOP probes were either based on published probe sequences12 or simply designed by targeting 18 basepairs surrounding the SNP in question, and it was generally not complicated to optimize the performance of the probes in the assay.
The high-throughput of the SSOP-ELISA method compared with the RFLP method is an important advantage. We used a panel of P. falciparum isolates with known SNPs to test the specificity of SSOP-ELISA system. For all the tested SNPs in dhfr, dhps, and Pfcrt genes, the signal-to-noise difference (OD) was greater than 1. The resulting OD values varied markedly between experiments. This might be due to probe hybridization efficiency, the TMAC stringency washing step, and marginal differences in the extremely sensitive nested PCR. However, we seldomly observed that the OD was less than 1 and in that case, the experiment was repeated. The high stringency TMAC washing involved three different temperatures for the dhfr SNPs. It was possible to perform the stringency washing at 60°C for all the codons, although lower ODs were encountered for the c108 SNPs and the c50/51 SNPs.
A high degree of concordance was observed when comparing the new SSOP-ELISA with the existing PCR-RFLP method, probably the most widely used of current methodologies. The SSOP-ELISA haplotyping has the advantage that it identifies the most abundant SNPs through its exact measures of OD, rather than detecting the more general mixed genotype infections alone. The samples used to compare the methods were mainly single genotype infections due to low malaria transmission in the area (Drakeley C, unpublished data). Thus, this advantage was not seen frequently. However, to detect alleles in mixed infections that are present in very low quantities, none of these methods may be suitable. However, an alternative method used by Hastings and others has the capacity to detect these.20
As expected, the detection of SNPs in dhfr and dhps by dot blotting and SSOP-ELISA gave generally similar results and both methods can be applied for high-throughput haplotyping of dhfr and dhps. However, there are several advantages of the SSOP-ELISA. In general, the full haplotyping post-PCR of 88 samples in dhfr, dhps, or Pfcrt can be done within five hours. The results can be assessed visually or analyzed on an ELISA reader and can be exported into a computer spreadsheet format, providing a quick and objective analysis of the data. In contrast, dot blotting take two days and demands an expensive imager or manual analysis of the resulting dots. Finally, only half of the TMAC solution, which is a health hazard, is required per ELISA plate compared with dot blot membranes, thus reducing the amount of hazardous waste.
The most promising practical application of the analyses for molecular markers of antimalarial drug resistance is determining the frequency of the relevant haplotypes in large-scale longitudinal studies as an adjunct to the laborious in vivo surveillance of drug resistance. This might provide data on the initial development and spread of antimalarial drug resistance prior to potential change of first-line treatment. Conversely, it may facilitate the surveillance of the possible restoration of drug susceptibility once drug pressure has ceased. As excellent examples of the latter, two recent studies performed in Malawi have shown that the prevalence of the codon 76 mutation in the Pfcrt gene and thus, the level of P. falciparum resistance to CQ has decreased markedly since the country abandoned the use of CQ as a first-line drug in 1993,21,22 raising the intriguing possibility of reintroducing discarded drugs such as CQ.8 However, it is still controversial whether mutations in the Pfcrt gene are the sole mediator of CQ resistance and other alleles or loci may be involved.22 Furthermore, the prevalence of the wild-type dhfr allele has been shown to increase as a result of installation of bed nets, possibly through decreased malaria transmission followed by less SP use.23
Monitoring molecular markers of drug resistance on a large scale in malaria-endemic areas demands a wide collection of samples collected routinely, as well as a simple method to perform high-throughput detection of the markers. Networks such as the East African Network for Monitoring Antimalarial Treatment (EANMAT) (www.eanmat.org) monitors annual sensitivity of P. falciparum to various antimalarial drugs at multiple sentinel sites in Kenya, Rwanda, Tanzania, Uganda, and Burundi. Thus, the network provides a unique basis for the measurement of molecular markers longitudinally that could be correlated with SP and CQ resistance and possibly other antimalarial drugs in the future. The SSOP-ELISA described here represents a suitable method to perform an analysis of such large numbers of samples within the countries involved.
The SSOP-ELISA may be extended to identify SNPs at other positions in dhfr, dhps, or Pfcrt simply by designing new probes/primers. Furthermore, the technology can be modified into SNP analyses for other P. falciparum genes or in other disease-causing organisms.
Received July 14, 2004. Accepted for publication October 9, 2004.
Acknowledgments: We thank the staff of TPC Hospital, particularly Dr. H. Mwerinde for sample collection, and Jimmy Weng for excellent technical assistance in performing the PCR-ELISA and dot blotting. We also thank David Wallikers (University of Edinburgh, Edinburgh, United Kingdom) for providing P. falciparum isolates K1, 7G8, and DD2, and Trine Staalsoe and Kirsten Pihl (Centre for Medical Parasitology) for providing isolates 3D7 and FCR3.
Financial support: This study was supported by the Danish International Development Agency Research Council (RUF, grant no. 91106) and the Wellcome Trust (GR063516) and conducted as part of the Joint Malaria Programme, a collaboration between the National Institute for Medical Research, Kilimanjaro Christian Medical College, the London School of Hygiene and Tropical Medicine, and the Centre for Medical Parasitology, University of Copenhagen.
Authors’ addresses: Michael Alifrangis, Insaf F Khalil, Anita M. Rønn, and Ib C. Bygbjerg, Centre for Medical Parasitology, Institute of Medical Microbiology and Immunology and Institute of Public Health, University of Copenhagen, Copenhagen, Denmark and Department of Infectious Diseases, Copenhagen University Hospital, Copenhagen, Denmark, E-mails: Alifrangis{at}cmp.dk, Insafk{at}immu.ku.dk, ARN{at}euro-alarm.dk, and I.Bygbjerg{at}pubhealth.ku.dk. Sonia Enosse, Centre for Medical Parasitology, Institute of Medical Microbiology and Immunology and Institute of Public Health, University of Copenhagen, Copenhagen, Denmark and Instituto Nacional de Saúde, Ministério de Saúde, Maputo, Mozambique, E-mail: Senosse{at}hotmail.com. Richard Pearce and Cally Roper, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom, E-mails: Richard.Pearce{at}lshtm.ac.uk and Cally.Roper{at}lshtm.ac.uk. Chris Drakeley, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom and The Joint Malaria Programme, Moshi, Tanzania, E-mail: Chris.Drakely{at}lshtm.ac.uk. Watoky M. M. M. Nkya, Kilimanjaro Christian Medical Centre, Moshi, Tanzania and The Joint Malaria Programme, Moshi, Tanzania, E-mail: Nkya10{at}hotmail.com. Thor G. Theander, The Joint Malaria Programme, Moshi, Tanzania, E-mail: Theander{at}cmp.dk.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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