Differentiating Plasmodium falciparum alleles by transforming Cartesian X,Y data to polar coordinates

<p>Abstract</p> <p>Background</p> <p>Diagnosis of infectious diseases now benefits from advancing technology to perform multiplex analysis of a growing number of variables. These advances enable simultaneous surveillance of markers characterizing species and strain complexity, mutations associated with drug susceptibility, and antigen-based polymorphisms in relation to evaluation of vaccine effectiveness. We have recently developed assays detecting single nucleotide polymorphisms (SNPs) in the <it>P. falciparum </it>genome that take advantage of post-PCR ligation detection reaction and fluorescent microsphere labeling strategies. Data from these assays produce a spectrum of outcomes showing that infections result from single to multiple strains. Traditional methods for distinguishing true positive signal from background can cause false positive diagnoses leading to incorrect interpretation of outcomes associated with disease treatment.</p> <p>Results</p> <p>Following analysis of <it>Plasmodium falciparum </it>dihydrofolate reductase SNPs associated with resistance to a commonly used antimalarial drug, Fansidar (Sulfadoxine/pyrimethamine), and presumably neutral SNPs for parasite strain differentiation, we first evaluated our data after setting a background signal based on the mean plus three standard deviations for known negative control samples. Our analysis of single allelic controls suggested that background for the absent allele increased as the concentration of the target allele increased. To address this problem, we introduced a simple change of variables from customary (<it>X,Y</it>) (Cartesian) coordinates to planar polar coordinates (<it>X </it>= <it>r</it>cos(<it>θ</it>), <it>Y </it>= <it>r</it>sin(<it>θ</it>)). Classification of multidimensional fluorescence signals based on histograms of angular and radial data distributions proved more effective than classification based on Cartesian thresholds. Comparison with known diallelic dilution controls suggests that histogram-based classification is effective for major:minor allele concentration ratios as high as 10:1.</p> <p>Conclusion</p> <p>We have observed that the diallelic SNP data resulting from analysis of <it>P. falciparum </it>mutations is more accurately diagnosed when a simple polar transform of the (<it>X,Y</it>) data into (<it>r,θ</it>) is used. The development of high through-put methods for genotyping <it>P. falciparum </it>SNPs and the refinement of analytical approaches for evaluating these molecular diagnostic results significantly advance the evaluation of parasite population diversity and antimalarial drug resistance.</p

A Multiplex Ligase Detection Reaction-Fluorescent Microsphere Assay for Simultaneous Detection of Single Nucleotide Polymorphisms Associated with Plasmodium falciparum Drug Resistance

Incomplete malaria control efforts have resulted in a worldwide increase in resistance to drugs used to treat the disease. A complex array of mutations underlying antimalarial drug resistance complicates efficient monitoring of parasite populations and limits the success of malaria control efforts in regions of endemicity. To improve the surveillance of Plasmodium falciparum drug resistance, we developed a multiplex ligase detection reaction-fluorescent-microsphere-based assay (LDR-FMA) that identifies single nucleotide polymorphisms (SNPs) in the P. falciparum dhfr (9 alleles), dhps (10 alleles), and pfcrt (3 alleles) genes associated with resistance to Fansidar and chloroquine. We evaluated 1,121 blood samples from study participants in the Wosera region of Papua New Guinea, where malaria is endemic. Results showed that 468 samples were P. falciparum negative and 453 samples were P. falciparum positive by a Plasmodium species assay and all three gene assays (concordance, 82.2%). For P. falciparum infections where the assay for each gene was positive, 2 samples carried resistance alleles for all three genes, 299 carried resistance alleles for dhfr and pfcrt, 131 carried resistance alleles for only one gene (dhfr [n = 40], dhps [n = 1], or pfcrt [n = 90]), and 21 carried only sensitive alleles at all three genes. Mixed-strain infections characterized 100 samples. Overall, 95.4% (432/453) of P. falciparum-infected samples carried at least one allele associated with resistance to Fansidar or chloroquine. In view of the fact that 86.3% (391/453) of P. falciparum-infected samples carried pfcrt mutations, chloroquine is largely ineffective against P. falciparum in Papua New Guinea. Surveillance of additional dhfr and dhps polymorphisms in order to monitor the continued effectiveness of Fansidar is recommended

Treatment with Coartem (Artemether-Lumefantrine) in Papua New Guinea

A recent drug efficacy trial reported Coartem (artemether-lumefantrine) to be highly effective against Plasmodium falciparum in children less than 5 years of age in Papua New Guinea (PNG). In contrast, we have observed high levels of treatment failures in non-trial conditions in a longitudinal cohort study in the same age group in PNG. Recrudescences were confirmed by genotyping of three different marker genes to provide optimal discrimination power between parasite clones. After excluding genetic host factors by genotyping potentially relevant cytochrome P450 loci, the high number of treatment failures in our study is best explained by poor adherence to complex dosing regimens in combination with insufficient fat supplementation, which are both crucial parameters for the outcome of Coartem treatment. In contrast to the situation in classic drug trials with ideal treatment conditions, our field survey highlights potential problems with unsupervised usage of Coartem in routine clinical practice and under program conditions

Microsatellite polymorphism within <it>pfcrt </it>provides evidence of continuing evolution of chloroquine-resistant alleles in Papua New Guinea

<p>Abstract</p> <p>Background</p> <p>Polymorphism in the <it>pfcrt </it>gene underlies <it>Plasmodium falciparum </it>chloroquine resistance (CQR), as sensitive strains consistently carry lysine (K), while CQR strains carry threonine (T) at the codon 76. Previous studies have shown that microsatellite (MS) haplotype variation can be used to study the evolution of CQR polymorphism and to characterize intra- and inter-population dispersal of CQR in Papua New Guinea (PNG).</p> <p>Methods</p> <p>Here, following identification of new polymorphic MS in introns 2 and 3 within the <it>pfcrt </it>gene (msint2 and msint3, respectively), locus-by-locus and haplotype heterozygosity (<it>H</it>) analyses were performed to determine the distribution of this intronic polymorphism among <it>pfcrt </it>chloroquine-sensitive and CQR alleles.</p> <p>Results</p> <p>For MS flanking the <it>pfcrt </it>CQR allele, <it>H </it>ranged from 0.07 (B5M77, -18 kb) to 0.094 (9B12, +2 kb) suggesting that CQ selection pressure was responsible for strong homogenisation of this gene locus. In a survey of 206 <it>pfcrt</it>-SVMNT allele-containing field samples from malaria-endemic regions of PNG, <it>H </it>for msint2 was 0.201. This observation suggests that <it>pfcrt </it>msint2 exhibits a higher level of diversity than what is expected from the analyses of <it>pfcrt </it>flanking MS. Further analyses showed that one of the three haplotypes present in the early 1980's samples has become the predominant haplotype (frequency = 0.901) in CQR parasite populations collected after 1995 from three PNG sites, when CQR had spread throughout malaria-endemic regions of PNG. Apparent localized diversification of <it>pfcrt </it>haplotypes at each site was also observed among samples collected after 1995, where minor CQR-associated haplotypes were found to be unique to each site.</p> <p>Conclusion</p> <p>In this study, a higher level of diversity at MS loci within the <it>pfcrt </it>gene was observed when compared with the level of diversity at <it>pfcrt </it>flanking MS. While <it>pfcrt </it>(K76T) and its immediate flanking region indicate homogenisation in PNG CQR parasite populations, <it>pfcrt </it>intronic MS variation provides evidence that the locus is still evolving. Further studies are needed to determine whether these intronic MS introduce the underlying genetic mechanisms that may generate <it>pfcrt </it>allelic diversity.</p

Mitochondrial Disease Sequence Data Resource (MSeqDR): A global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The “Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium” is a grass-roots effort facilitated by the United Mitochondrial Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondrial disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1,300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial disease