Development of a TaqMan Allelic Discrimination Assay for detection of Single Nucleotides Polymorphisms associated with anti-malarial drug resistance

Background Anti-malarial drug resistance poses a threat to current global efforts towards control and elimination of malaria. Several methods are used in monitoring anti-malarial drug resistance. Molecular markers such as single nucleotide polymorphism (SNP) for example are increasingly being used to identify genetic mutations related to anti-malarial drug resistance. Several methods are currently being used in analysis of SNP associated with anti-malarial drug resistance and although each one of these methods has unique strengths and shortcoming, there is still need to improve and/or develop new methods that will close the gap found in the current methods. Methods TaqMan Allelic Discrimination assays for detection of SNPs associated with anti-malarial drug resistance were designed for analysis on Applied Biosystems PCR platform. These assays were designed by submitting SNP sequences associated with anti-malarial drug resistance to Applied Biosystems website. Eleven SNPs associated with resistance to anti-malarial drugs were selected and tested. The performance of each SNP assay was tested by creating plasmid DNAs carrying codons of interests and analysing them for analysis. To test the sensitivity and specificity of each SNP assay, 12 clinical samples were sequenced at codons of interest and used in the analysis. Plasmid DNAs were used to establish the Limit of Detection (LoD) for each assay. Results Data from genetic profiles of the Plasmodium falciparum laboratory strains and sequence data from 12 clinical samples was used as the reference method with which the performance of the SNP assays were compared to. The sensitivity and specificity of each SNP assay was establish at 100%. LoD for each assay was established at 2 GE, equivalent to less than 1 parasite/μL. SNP assays performed well in detecting mixed infection and analysis of clinical samples. Conclusion TaqMan Allelic Discrimination assay provides a good alternative tool in detection of SNPs associated with anti-malarial drug.


Background
Spread and emergence of old and new drug resistant parasites is threatening malaria control programmes in most malaria endemic regions [1,2]. Advances that have been made thus far will only be sustained if monitoring and reporting of anti-malarial drug resistance becomes an integral part of malaria control efforts [3]. Anti-malarial drug resistance and drug efficacy can be monitored by performing therapeutic efficacy studies, measurement of drug concentrations in blood, in vitro tests that monitor parasite phenotypic changes and analysis of molecular markers that monitor genetic changes. Although therapeutic efficacy studies are considered the gold standard method for determining anti-malarial drug efficacy, each of these methods presents unique strengths and weaknesses [3][4][5][6]. Recent advances in molecular information and technology in particular has positioned analysis and monitoring of genetic markers as an important alternative method for detection of drug resistance [7,8].
Most of the methods used for detection of drug resistance SNPs are polymerase chain reaction (PCR) based. Once amplicons are obtained, the presence of SNPs can be detected by restriction fragment length polymorphisms (RFLP), DNA sequencing, or single-stranded conformation polymorphisms [19]. Other methods used for SNP analysis include single-nucleotide primer extension (SNPE) [20], melting curve analysis-fluorescence resonance energy transfer (FRET-MCA) [21], molecular beacons [22], melting probe hybridization [23], real-time PCR [24] and microarray [25]. Each of these methods presents unique advantages and disadvantages. While there is a need to develop new SNP analysis methods it is important that next generation SNP analysis improves on the existing methods. Some desirable qualities for next generation SNP analysis methods should include improved accuracy and sensitivity, reduced cost, fast turn-around time, high through-put capability, and field deployable to mention a few.
Here, development of TaqMan Allelic Discrimination assays (SNP assays) for genotyping SNPs associated with P. falciparum drug resistance performed on Applied Biosystems 7500 Fast Real-Time PCR System is described. The performance of each SNP assay was assessed using plasmid DNAs which contained PCR fragment carrying codons of interest from P. falciparum laboratory strains with known genetic profile. The specificity of the SNP assays was assessed by comparing SNP assay data to sequence data of clinical samples.

SNP selection and assay design
Thirty SNP sequences (~100 nucleotides on the left frank and~100 nucleotides on the right frank of the allele of interest) associated with anti-malarial drug resistance were submitted to Applied Biosystems (AB) website for analysis of their suitability to be used in SNP assays. After submitting sequences to the custom TaqMan assay design tool on the AB website, twenty five sequences returned SNP assays that were considered to be good candidate designs. The following SNP assays were selected for further analysis: pfdhfr codons A16V, S22N, N51I, C59R, S108N, and I164L; pfmdr1 codons N86Y, Y184F, S1034C and N1042D; and pfdhps codon A581G. TaqMan-MGB genotyping assay mix for each of these assays was ordered from AB. Each of these TaqMan-MGB genotyping assay mix contained a forward and reverse primer, one probe that perfectly matched to the wild-type sequence variant labeled with VIC and the second probe matched to the mutant (SNP) sequence variant labeled with 6-carboxyfluorescein (FAM) ( Table 1). Probes contained a nonfluorescent quencher and a minor groove binder moiety (MGB) which allows for shorter probe sequences to be designed. TaqMan-MGB genotyping assay mixes were supplied at 40X concentration.

SNP assay
A working master mix was prepared that contained 0.25 μL of TaqMan-MGB genotyping assay mix (20X), 2.5 μL Taq-Man Genotyping Master Mix (Applied Biosystems, Carlsbad CA, USA) and 2.25 μL of water or 1.25 μL water and 1 μL of human genomic DNA at 50 ng. Human genomic DNA was added in reactions which were ran with plasmid DNAs as the template. Each reaction contained 5 μL of working master mix and up to 2 μL of template DNA.
Template DNA used in these experiments was either plasmid DNA or genomic DNA. In some experiments, two different plasmid DNAs were used. In such instances, 0.5 μL or 1 μL of each plasmid DNA was added to the 5 μL of the working master mix bringing the final volume of the reaction to 6 or 7 μL. Extensive experiments (to be reported elsewhere) have been done which show that such differences in volume and concentration of real-time PCR reactions do not alter assay performance. Plates were loaded into Applied Biosystems 7500 Fast Real-Time PCR System and AB 7500 v 2.0.5 software was used to run the genotyping assay experiment following the default standard Allelic Discrimination genotyping assay protocol. The initial step of this protocol includes pre-reading of the plate where the background florescence is recorded followed by AB standard PCR protocol of 95°C for 10 min, 95°C for 15 sec and 60°C for 1 min, repeating steps 2-3 for 40 cycles. The postread step follows after completion of the PCR step where a post-read is performed. The software analysed the before and after florescence level and calculates normalized dye fluorescence (ΔRn) as a function of cycle number for Allele1 (wild-type) or Allele2 (mutant). Based on this number (which is a relative number of the possible outcomes), the software makes an automatic call of either Allele1 (homozygous1/1), Allele2 (homozygous2/2) or heterozygous (1/2). In some instances however, the software does not make automatic calls and returns a call of undetermined which can be due to low or no change of fluorescence. Also, the system requires large enough sample number in order to make automatic calls (from communicating with AB technical help line,~fifteen or more samples are required for the software to make automatic call). However, in some instances there is no clear explanation why the software does not make automatic calls but with proper controls in place, calls can be made manually by assessing the calculated normalized dye fluorescence (ΔRn) as a function of cycle number and the cycle threshold (CT) values.

DNA amplification and cloning PCR fragments into TOPO TA vector
Primers were designed (using Primer Express 3.0 software) that amplified amplicons of interest (

SNP assays performance
To analyse the performance of the selected SNP assays, three P. falciparum strains, 3D7, 7G8 and K1 that differ in some of their genetic profiles at selected codons ( To obtain the initial analytical sensitivity and specificity, each plasmid DNA was diluted to an initial final concentration of 32, 000 copies. SNP assays were performed as described in methods section. SNP assay names were based on the codon being analysed. For example, to analyse codon pfdhfr N51I, the SNP Assay name is referenced as DHFR51 ( Table 1). Performance of each SNP assay was assessed based on the known genetic profile of each strain at each codon and sequence data. Assessment of each SNP assay was based on automatic calls, normalized dye fluorescence (ΔRn) as a function of cycle number for Allele1 (wild-type) or Allele2 (mutant), and the CT values. All the calls made (11 of 11) for each SNP assay were correct, establishing the initial analytical sensitivity and specificity at 100%. To establish the Limit of Detection (LoD) for each assay, each plasmid DNA was serially diluted 5-fold and the initial tentative LoD for each assay was set as the lowest concentration of DNA that yielded positive results in duplicate experiments (Figure 1: shows LoD for pfdhfr 51 and 108, pfmdr1 86 and 184, pfmdr1 1034 and 1042, pfdhps 581). The LoD was confirmed by testing the LoD concentration in replicates of two or more. All the assays had LoD of 2 GE.

Mixed infections
To test the ability of each assay to discriminate mixed infections, plasmid DNAs carrying alternate genetic profiles at each codon were mixed at different ratios and the ability of each assay to make the correct call was assessed. SNP assays analysed for mixed infection were DHFR51 and 108 (using plasmid DNA 16-3D7 and 16-7G8), MDR86 and 184 (using plasmid DNA 86-K1 and 86-7G8), MDR1034 and 1042 (using plasmid DNA 1034-K1 and 1034-7G8), and DHPS581 (using plasmid DNA 581-K1 Genetic profile of P. falciparum laboratory strains used in this study based on PlasmoDB website www.plasmodb.org and/or sequence data. Bold indicates the mutant allele and N indicates there is no information available on the profile of the indicated allele on PlasmoDB website. and 581-7G8). Analysis for mixed infection was performed as follows; one plasmid DNA concentration was kept constant while the other was serially diluted 5-fold or both plasmid DNAs were serially diluted 5-fold and mixed at equal concentrations. As shown in Figure 2 (DHFR108 SNP assay, MDR1034 SNP assay and DHPS581 SNP assay), when one plasmid DNA concentration was kept constant (high) while the other was serially diluted, the presence of heterozygous alleles was only detected when both plasmid DNAs were at high concentration. The presence of the allele in the serially diluted plasmid DNA was not detected beyond when the plasmid DNAs were at equal concentrations. However, for MDR1034 SNP assay, both alleles were detected when one plasmid DNA was diluted to 6400 GE (Figure 2, MDR1034 SNP assay) while the other was at kept at 32000 GE. Curiously, the software did not make automatic calls for the DNA mixtures that contained serially diluted plasmid DNA at 1:5 (6400 GE) and undiluted plasmid DNA (32000 GE) for DHFR51, MDR1042 and DHPS581 SNP assays, rendering these six assays undetermined. There is no clear explanation why such results were obtained (undetermined) at these plasmid DNA mixture ratios since the software made automatic calls for the consequent plasmid DNA mixtures. Note that the software did not make automatic calls for all MDR86 and MDR184 SNP assays. Notwithstanding, Allele1 and Allele2 ΔRn in these SNP assays were clearly separated but yet the software could not make automatic calls (Figure 3). Manual calls were made based on ΔRn values of the Allele1 and Allele2. It was determined the performance of these two SNP assays, MDR86 and MDR184 were similar to those of the other SNP assays. Interestingly, in all the SNP assays, when both plasmid DNAs were serially diluted, the presence of both alleles was detected at or near LoD as established using single plasmid DNA.

Assay specificity
Twelve samples from the clinical trial were randomly selected and sequenced directly or by cloning PCR Figure 1 LoD for DHFR51 and DHFR108, MDR86 and MDR184, MDR1034 and MDR1042, DHPS581 SNP assays. Data showing LoD for allele1 and allele2 for each SNP assay where plasmid DNA carrying either allele1 or allele2 was used as a template. LoD for all the SNP assays was established at 2 GE. Data is shown indicating the SNP assay and the strain which the PCR fragment in the plasmid DNA was cloned from. Example 51-3D7 is data obtained from SNP assay DHFR51 using 16-3D7 plasmid DNA. fragment that contains codons of interest into TOPO TA vector. Primers used for cloning and/or sequencing are described in Table 2. Here, similar scheme was used as that described in the results section, SNP assay performance. PCR fragments were amplified using different primer sets and amplicons were either cloned into TOPO TA vector and then sequenced or were directly sequenced as described in the methods section. SNP assays were performed in replicates of two or more for each sample using either cloned plasmid DNA and/or Figure 3 Manually called SNP assays. Data showing the manual call of MDR86 and MDR184 SNP assays. The automatic call for these SNP assays during these runs were undetermined however as the data shows, Allele1 and Allele2 ΔRn in these SNP assays were clearly separated. This data shows manual calls can be made with great confidence regardless of whether automatic calls are made or not. In addition, CT values showed a clear and distinct difference between the two alleles.  (Table  3). SNP assays were performed as described in the methods section. Figure 4 shows an Allelic Discrimination plots for DHPS581 and MDR86 SNP assays ran using clinical samples and plasmid DNA controls. The plot shows a clear and distinct separation between the two alleles. In these experiments unlike those initially ran, automatic calls were made for MDR86 and 184 SNPs assays since large number of samples and controls were used, emphasizing the need of analyzing a large number of samples for the software to make automatic call. To assess the analytical specificity of the SNP assays, calls made using SNP assay data were compared to the sequence data of the samples. All calls made using SNP assays were in 100% agreement with sequence data. Sequence analysis is considered a gold standard method for SNP analysis. Eleven SNP assays were analysed in 12 clinical samples, representing a total of 132 SNP assays that were correctly called. This analysis, in addition to that initially performed using 3D7, 7G8 and K1 strains represent 100% specificity of all the SNP assays analysed.

Clinical samples analysis
Sixty clinical samples with known parasite density based on microscopy and real-time PCR data [27] were analysed using all the eleven SNP assays. All the SNP assays performed as expected with distinct and clear calls regardless of the parasite density in each sample. In additional, 10 clinical samples that were negative by microscopy and real-time PCR data were ran for further analysis of the analytical specificity of the SNP assays. There were no false positives; all the CT values were undetermined. Figure 4 Allelic Discrimination plots for MDR86 and DHPS581 SNP assays. Two representative plots showing performance of two assays in analysis of clinical samples. These assays show clear separation between the signals derived from allele1 or allele2. Allele1 is shown in red and allele2 is shown in blue. Lime green represents a mixture of the two alleles (which was a positive control allele1/allele2 derived using a mixture of two plasmid DNAs).

Discussion
A TaqMan Allelic Discrimination assays for detection of SNPs associated with anti-malarial drug resistance has been described. The assay was developed for use on Applied Biosystems 7500 Fast Real-Time PCR System. The performance of each of the SNP assays was analysed and control plasmid DNAs developed. Each SNP assay performed well with 100% sensitivity and specificity. Data from genetic profiles of the P. falciparum laboratory strains and sequence data from 12 clinical samples was used as the reference method with which the SNP assays were compared to. All the SNP assays had LoD of 2 copies, which is equivalent to less than 1 parasite/μL (based on unpublished data to be reported elsewhere). The performance of the SNP assays was further validated when each SNP assays was used to assess SNP genetic profile of additional 60 clinical samples with known parasite density based on microscopy and real-time PCR assay which amplifies 18s RNA. Based on microscopy, the density of the parasite ranged from less than a 100 parasites/ μL to more than 10E6 parasites/μL [27]. All SNP assays performed well regardless of parasite density. Using realtime PCR 18s RNA parasite density data, SNP assays successfully genotyped samples containing parasites densities of 10 parasites/μL or less. All clinical samples that were negative by real-time PCR 18s RNA assay were also negative in all SNP assays. Detection of SNPs associated with anti-malarial drugs using real-time PCR based assay has been extensively reported [28]. However, until recently [29], there has not been any published work towards developing SNP detection assays using the TaqMan Allelic Discrimination assay method on Applied Biosystems PCR platform for genotyping SNPs present in the Plasmodium genome. In the study by Daniel et al., [29], TaqMan Allelic Discrimination assay was developed for identification and tracking P. falciparum. Here, the authors selected a panel of twenty-four SNPs that were identified to exhibit a high minor allele frequency for which robust TaqMan genotyping assays were constructed. A variety of samples including P. falciparum laboratory strains, frozen whole blood, or whole blood spotted onto filter paper were used in the assay with a success rate > 99%. The performance of the assay was validated using nested PCR. By making calls using ΔRn, TaqMan Allelic Discrimination assays simplifies and increases accuracy in call making by eliminating subjective decision which can be made by use of CT values. In most of the mixed infections, data present here show that if only CT values were used, wrong calls would have been made. For example in Figure 3 where 1034-K1 plasmid DNA at 32000 GE was mixed with 1034-7G8 plasmid at 6400 GE, the MDR1034 SNP assay had CT values of 17.53 and 19.25 for Allele1 and Allele2 respectively and ΔRn values of 2.23 and 2.27 for Allele1 and Allele2 respectively. Here, heterozygous1/2 automatic call was made but if this decision was based on CT values, probably subjective call would have been Allele1. Automatic calls are less subjective since they are based on the software's algorithm. It is important to have positive and negative controls in place and a large number of samples must be analysed for the software to make automatic calls.
Currently, there are many methods that are being used for molecular analysis of anti-malarial drug resistance. Methods chosen by different studies will be based on many factors including technology capabilities and availability, the availability of intellectual and financial resources to mention a few. Some of the factors that should be important in decision making regarding what assay to use in SNP analysis should include accuracy of the assay, sensitivity, robustness, reproducibility, cost, and reliability. Here, we are adding one more tool that can be used in genotyping anti-malarial drug resistance.
TaqMan Allelic Discrimination assays can be custom designed for detection of SNPs of interest. When designing these assays however, just like any other PCR assay, not all SNP sequences will be good candidate designs. And once good candidate designs are identified, it is important that extensive analysis of each assay is performed before its utilization. It is important that a SNP detection assay is capable of detecting mixed alleles (mixed infection). Here, just like previously reported [29], data shows that TaqMan Allelic Discrimination assay is capable of detecting mixed alleles. However, it is important to note that this is a PCR based assay which discriminates the presence of either allele based on affinity of one probe to the SNP sequences of the allele present as opposed to the one not present. Some SNP assays might detect mixed infections better than others; it all depends on chemistry of each set of probes. Data presented here show that SNP assays can detect mixed infections when DNA of both alleles is present in high to very low concentrations as long as DNAs carrying both alleles are at or near equal concentration.

Conclusion
The SNP assay described here for detection of antimalarial drug resistance is accurate, sensitive, robust, inexpensive, highly reproducible and reliable. And since it is a real-time PCR based assay, it has great potential of being utilized in high-throughput studies such as surveillance and epidemiological studies. TaqMan Allelic Discrimination assays have been widely developed and used for genotyping SNPs in applications such as SNP typing in forensic genetics, pharmacokinetics and bacterial strain typing [30]. However, it is not until recently that Daniels et al [29] showed utilization of this technology in allele discrimination in Plasmodium genome. It is important to note however that all real-time PCR based assays will poorly detect mixed infections where one allele is at much higher concentration than the other. If there is need to resolve mixed infection that might have large differences in DNA concentration between the two alleles, other technologies such as nested PCR must be utilized. To alleviate limitation associated with detecting mixed infection, TaqMan Allelic Discrimination assay can be modified by performing nested PCR where flanking primers can be used in first round to improve the likely hood of detecting mixed infections during the real-time PCR second (nested) round.