Philip J. Shaw

Inhibition of Plasmepsin V Activity Demonstrates Its Essential Role in Protein Export, PfEMP1 Display, and Survival of Malaria Parasites

A small molecule inhibitor of the malarial protease Plasmepsin V impairs protein export and cellular remodeling, reducing parasite survival in human erythrocytes.

Inducible knockdown of Plasmodium gene expression using the glmS ribozyme.

Conventional reverse genetic approaches for study of Plasmodium malaria parasite gene function are limited, or not applicable. Hence, new inducible systems are needed. Here we describe a method to control P. falciparum gene expression in which target genes bearing a glmS ribozyme in the 3′ untranslated region are efficiently knocked down in transgenic P. falciparum parasites in response to glucosamine inducer. Using reporter genes, we show that the glmS ribozyme cleaves reporter mRNA in vivo leading to reduction in mRNA expression following glucosamine treatment. Glucosamine-induced ribozyme activation led to efficient reduction of reporter protein, which could be rapidly reversed by removing the inducer. The glmS ribozyme was validated as a reverse-genetic tool by integration into the essential gene and antifolate drug target dihydrofolate reductase-thymidylate synthase (PfDHFR-TS). Glucosamine treatment of transgenic parasites led to rapid and efficient knockdown of PfDHFR-TS mRNA and protein. PfDHFR-TS knockdown led to a growth/arrest mutant phenotype and hypersensitivity to pyrimethamine. The glmS ribozyme may thus be a tool for study of essential genes in P. falciparum and other parasite species amenable to transfection.

PanSNPdb: The Pan-Asian SNP Genotyping Database

The HUGO Pan-Asian SNP consortium conducted the largest survey to date of human genetic diversity among Asians by sampling 1,719 unrelated individuals among 71 populations from China, India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, and Thailand. We have constructed a database (PanSNPdb), which contains these data and various new analyses of them. PanSNPdb is a research resource in the analysis of the population structure of Asian peoples, including linkage disequilibrium patterns, haplotype distributions, and copy number variations. Furthermore, PanSNPdb provides an interactive comparison with other SNP and CNV databases, including HapMap3, JSNP, dbSNP and DGV and thus provides a comprehensive resource of human genetic diversity. The information is accessible via a widely accepted graphical interface used in many genetic variation databases. Unrestricted access to PanSNPdb and any associated files is available at: http://www4a.biotec.or.th/PASNP.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

BackgroundGenome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD).ResultsIn this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles.ConclusioniLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci.

Iterative pruning PCA improves resolution of highly structured populations.

BackgroundNon-random patterns of genetic variation exist among individuals in a population owing to a variety of evolutionary factors. Therefore, populations are structured into genetically distinct subpopulations. As genotypic datasets become ever larger, it is increasingly difficult to correctly estimate the number of subpopulations and assign individuals to them. The computationally efficient non-parametric, chiefly Principal Components Analysis (PCA)-based methods are thus becoming increasingly relied upon for population structure analysis. Current PCA-based methods can accurately detect structure; however, the accuracy in resolving subpopulations and assigning individuals to them is wanting. When subpopulations are closely related to one another, they overlap in PCA space and appear as a conglomerate. This problem is exacerbated when some subpopulations in the dataset are genetically far removed from others. We propose a novel PCA-based framework which addresses this shortcoming.ResultsA novel population structure analysis algorithm called iterative pruning PCA (ipPCA) was developed which assigns individuals to subpopulations and infers the total number of subpopulations present. Genotypic data from simulated and real population datasets with different degrees of structure were analyzed. For datasets with simple structures, the subpopulation assignments of individuals made by ipPCA were largely consistent with the STRUCTURE, BAPS and AWclust algorithms. On the other hand, highly structured populations containing many closely related subpopulations could be accurately resolved only by ipPCA, and not by other methods.ConclusionThe algorithm is computationally efficient and not constrained by the dataset complexity. This systematic subpopulation assignment approach removes the need for prior population labels, which could be advantageous when cryptic stratification is encountered in datasets containing individuals otherwise assumed to belong to a homogenous population.

Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure.

BackgroundThe ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis.ResultsA new heuristic called EigenDev for detecting population structure is presented. When tested on simulated data, this heuristic is robust to sample size. In contrast, the TW statistic was found to be susceptible to type I error, especially for large population samples. EigenDev is thus better-suited for analysis of large datasets containing many individuals, in which spurious patterns are likely to exist and could be incorrectly interpreted as population stratification. EigenDev was applied to the iterative pruning PCA (ipPCA) method, which resolves the underlying subpopulations. This subpopulation information was used to supervise STRUCTURE analysis to infer patterns of ancestry at an unprecedented level of resolution. To validate the new approach, a bovine and a large human genetic dataset (3945 individuals) were analyzed. We found new ancestry patterns consistent with the subpopulations resolved by ipPCA.ConclusionsThe EigenDev heuristic is robust to sampling and is thus superior for detecting structure in large datasets. The application of EigenDev to the ipPCA algorithm improves the estimation of the number of subpopulations and the individual assignment accuracy, especially for very large and complex datasets. Furthermore, we have demonstrated that the structure resolved by this approach complements parametric analysis, allowing a much more comprehensive account of population structure. The new version of the ipPCA software with EigenDev incorporated can be downloaded from http://www4a.biotec.or.th/GI/tools/ippca.

Prediction of avian influenza A binding preference to human receptor using conformational analysis of receptor bound to hemagglutinin

BackgroundIt is known that the highly pathogenic avian influenza A virus H5N1 binds strongly and with high specificity to the avian-type receptor by its hemagglutinin surface protein. This specificity is normally a barrier to viral transmission from birds to humans. However, strains may emerge with mutated hemagglutinin, potentially changing the receptor binding preference from avian to human-type. This hypothesis has been proven correct, since viral isolates from Vietnam and Thailand have been found which have increased selectivity toward the human cell receptor. The change in binding preference is due to mutation, which can be computationally modelled. The aim of this study is to further explore whether computational simulation could be used as a prediction tool for host type selectivity in emerging variants.ResultsMolecular dynamics simulation was employed to study the interactions between receptor models and hemagglutinin proteins from H5N1 strains A/Duck/Singapore/3/97, mutated A/Duck/Singapore/3/97 (Q222L, G224S, Q222L/G224S), A/Thailand/1(KAN-1)/2004, and mutated A/Thailand/1(KAN-1)/2004 (L129V/A134V). The avian receptor was represented by Siaα(2,3)Gal substructure and human receptor by Siaα(2,6)Gal. The glycoside binding conformation was monitored throughout the simulations since high selectivity toward a particular host occurs when the sialoside bound with the near-optimized conformation.ConclusionThe simulation results showed all hemagglutinin proteins used the same set of amino acid residues to bind with the glycoside; however, some mutations alter linkage preferences. Preference toward human-type receptors is associated with a positive torsion angle, while avian-type receptor preference is associated with a negative torsion angle. According to the conformation analysis of the bound receptors, we could predict the relative selectivity in accordance with in vitro experimental data when disaccharides receptor analogs were used.

Insight into the Peopling of Mainland Southeast Asia from Thai Population Genetic Structure

There is considerable ethno-linguistic and genetic variation among human populations in Asia, although tracing the origins of this diversity is complicated by migration events. Thailand is at the center of Mainland Southeast Asia (MSEA), a region within Asia that has not been extensively studied. Genetic substructure may exist in the Thai population, since waves of migration from southern China throughout its recent history may have contributed to substantial gene flow. Autosomal SNP data were collated for 438,503 markers from 992 Thai individuals. Using the available self-reported regional origin, four Thai subpopulations genetically distinct from each other and from other Asian populations were resolved by Neighbor-Joining analysis using a 41,569 marker subset. Using an independent Principal Components-based unsupervised clustering approach, four major MSEA subpopulations were resolved in which regional bias was apparent. A major ancestry component was common to these MSEA subpopulations and distinguishes them from other Asian subpopulations. On the other hand, these MSEA subpopulations were admixed with other ancestries, in particular one shared with Chinese. Subpopulation clustering using only Thai individuals and the complete marker set resolved four subpopulations, which are distributed differently across Thailand. A Sino-Thai subpopulation was concentrated in the Central region of Thailand, although this constituted a minority in an otherwise diverse region. Among the most highly differentiated markers which distinguish the Thai subpopulations, several map to regions known to affect phenotypic traits such as skin pigmentation and susceptibility to common diseases. The subpopulation patterns elucidated have important implications for evolutionary and medical genetics. The subpopulation structure within Thailand may reflect the contributions of different migrants throughout the history of MSEA. The information will also be important for genetic association studies to account for population-structure confounding effects.

Global gene expression profiling of Plasmodium falciparum in response to the anti-malarial drug pyronaridine

BackgroundPyronaridine (PN) and chloroquine (CQ) are structurally related anti-malarial drugs with primarily the same mode of action. However, PN is effective against several multidrug-resistant lines of Plasmodium falciparum, including CQ resistant lines, suggestive of important operational differences between the two drugs.MethodsSynchronized trophozoite stage cultures of P. falciparum strain K1 (CQ resistant) were exposed to 50% inhibitory concentrations (IC50) of PN and CQ, and parasites were harvested from culture after 4 and 24 hours exposure. Global transcriptional changes effected by drug treatment were investigated using DNA microarrays.ResultsAfter a 4 h drug exposure, PN induced a greater degree of transcriptional perturbation (61 differentially expressed features) than CQ (10 features). More genes were found to respond to 24 h treatments with both drugs, and 461 features were found to be significantly responsive to one or both drugs across all treatment conditions.Filtering was employed to remove features unrelated to primary drug action, specifically features representing genes developmentally regulated, secondary stress/death related processes and sexual stage development. The only significant gene ontologies represented among the 46 remaining features after filtering relate to host exported proteins from multi-gene families.ConclusionsThe malaria parasites molecular responses to PN and CQ treatment are similar in terms of the genes and pathways affected. However, PN appears to exert a more rapid response than CQ. The faster action of PN may explain why PN is more efficacious than CQ, particularly against CQ resistant isolates. In agreement with several other microarray studies of drug action on the parasite, it is not possible, however, to discern mechanism of drug action from the drug-responsive genes.

5′ and 3′ end modifications of spliceosomal RNAs in Plasmodium falciparum

Abstract5′ caps provide recognition sequences for the nuclear import of snRNAs. The 5′ and 3′ ends of snRNAs were studied in Plasmodium falciparum with a modified adapter ligation method, which showed that 5′ ends of U1, U2, U4, U5 and U6 snRNAs are capped. In P. falciparum, the 3′ ends of U1, U2, U4 and U5 snRNAs have free hydroxyl groups whereas U6 snRNA has a blocked 3′ end. An immunoprecipitation assay for trimethyl guanosine caps shows that the cap structures of parasite U1-U5 snRNAs are hypermethylated while U6 snRNA may be γ-mono-methylated. Bioinformatics analysis of proteins involved in hypermethylation and trafficking of snRNAs indicates that the methyltransferase TGS1 is present in the P. falciparum genome. PfTGS1 is larger than its orthologs and may have transmembrane domains in the C-terminus. Surprisingly, the snRNA trafficking protein Snurportin is absent from the P. falciparum genome suggesting that reminiscent of yeast, parasite snRNAs may be retained in the nucleus.