Inferring malaria parasite population structure from serological networks.
Ontology highlight
ABSTRACT:
SUBMITTER: Buckee CO
PROVIDER: S-EPMC2581777 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Malaria cases caused by the zoonotic parasite Plasmodium knowlesi are being increasingly reported throughout Southeast Asia and in travelers returning from the region. To test for evidence of signatures of selection or unusual population structure in this parasite, we surveyed genome sequence diversity in 48 clinical isolates recently sampled from Malaysian Borneo and in five lines maintained in laboratory rhesus macaques after isolation in the 1960s from Peninsular Malaysia and the Philippines. Overall genomewide nucleotide diversity (π = 6.03 × 10(-3)) was much higher than has been seen in worldwide samples of either of the major endemic malaria parasite species Plasmodium falciparum and Plasmodium vivax. A remarkable substructure is revealed within P. knowlesi, consisting of two major sympatric clusters of the clinical isolates and a third cluster comprising the laboratory isolates. There was deep differentiation between the two clusters of clinical isolates [mean genomewide fixation index (FST) = 0.21, with 9,293 SNPs having fixed differences of FST = 1.0]. This differentiation showed marked heterogeneity across the genome, with mean FST values of different chromosomes ranging from 0.08 to 0.34 and with further significant variation across regions within several chromosomes. Analysis of the largest cluster (cluster 1, 38 isolates) indicated long-term population growth, with negatively skewed allele frequency distributions (genomewide average Tajima's D = -1.35). Against this background there was evidence of balancing selection on particular genes, including the circumsporozoite protein (csp) gene, which had the top Tajima's D value (1.57), and scans of haplotype homozygosity implicate several genomic regions as being under recent positive selection.
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Project description:If copy number variants (CNVs) are predominantly deleterious, we would expect them to be more efficiently purged from populations with a large effective population size (Ne) than from populations with a small Ne. Malaria parasites (Plasmodium falciparum) provide an excellent organism to examine this prediction, because this protozoan shows a broad spectrum of population structures within a single species, with large, stable, outbred populations in Africa, small unstable inbred populations in South America and with intermediate population characteristics in South East Asia. We characterized 122 single-clone parasites, without prior laboratory culture, from malaria-infected patients in 7 countries in Africa, SE Asia and S. America using a high density SNP/CNV microarray. We scored 134 high-confidence CNVs across the parasite exome, including 33 deletions and 102 amplifications, which ranged in size from <500bp to 59kb, as well as 10,107 flanking, biallelic SNPs. Overall, CNVs were rare, small and skewed towards low frequency variants, consistent with the deleterious model. Relative to African and SE Asian populations, CNVs were significantly more common in S. America, showed significantly less skew in allele frequencies, and were significantly larger. On this background of low frequency CNV, we also identified several high-frequency CNVs under putative positive selection using an FST outlier analysis. These included known adaptive CNVs containing rh2b and pfmdr1, and several other CNVs (e.g. DNA helicase, and 3 conserved proteins) that require further investigation. Our data are consistent with a significant impact of genetic structure on CNV burden in an important human pathogen. SNP/CGH hybridisation of 175 malaria parasite samples
2015-11-19 | E-GEOD-75137 | biostudies-arrayexpress
Project description:A novel form of acto-myosin regulation has been proposed in which polymerization of new actin filaments regulates motility of parasites of the apicomplexan class of protozoa. In vivo and in vitro parasite F-actin is very short and unstable, but the structural basis and details of filament dynamics remain unknown. Here, we show that long actin filaments can be obtained by polymerizing unlabeled rabbit skeletal actin (RS-actin) onto both ends of the short rhodamine-phalloidin-stabilized Plasmodium falciparum actin I (Pf-actin) filaments. Following annealing, hybrid filaments of micron length and "zebra-striped" appearance are observed by fluorescence microscopy that are stable enough to move over myosin class II motors in a gliding filament assay. Using negative stain electron microscopy we find that pure Pf-actin stabilized by jasplakinolide (JAS) also forms long filaments, indistinguishable in length from RS-actin filaments, and long enough to be characterized structurally. To compare structures in near physiological conditions in aqueous solution we imaged Pf-actin and RS-actin filaments by atomic force microscopy (AFM). We found the monomer stacking to be distinctly different for Pf-actin compared with RS-actin, such that the pitch of the double helix of Pf-actin filaments was 10% larger. Our results can be explained by a rotational angle between subunits that is larger in the parasite compared with RS-actin. Modeling of the AFM data using high-resolution actin filament models supports our interpretation of the data. The structural differences reported here may be a consequence of weaker inter- and intra-strand contacts, and may be critical for differences in filament dynamics and for regulation of parasite motility.
| S-EPMC2978586 | biostudies-literature
Project description:BackgroundMalaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species 123, providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum.ResultsWe investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database 4, and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system 5, blood stage microarray experiments 678, proteomics 9101112, literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle progression, transcriptional regulation, and signal transduction networks.ConclusionsOur network analysis of proteases from P. falciparum uses a so-called guilt-by-association approach to extract sets of proteins from the proteome that are candidates for further study. Novel protease targets and previously unrecognized members of the protease-associated sub-systems provide new insights into the mechanisms underlying parasitism, pathogenesis and virulence.
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Project description:If copy number variants (CNVs) are predominantly deleterious, we would expect them to be more efficiently purged from populations with a large effective population size (Ne) than from populations with a small Ne. Malaria parasites (Plasmodium falciparum) provide an excellent organism to examine this prediction, because this protozoan shows a broad spectrum of population structures within a single species, with large, stable, outbred populations in Africa, small unstable inbred populations in South America and with intermediate population characteristics in South East Asia. We characterized 122 single-clone parasites, without prior laboratory culture, from malaria-infected patients in 7 countries in Africa, SE Asia and S. America using a high density SNP/CNV microarray. We scored 134 high-confidence CNVs across the parasite exome, including 33 deletions and 102 amplifications, which ranged in size from <500bp to 59kb, as well as 10,107 flanking, biallelic SNPs. Overall, CNVs were rare, small and skewed towards low frequency variants, consistent with the deleterious model. Relative to African and SE Asian populations, CNVs were significantly more common in S. America, showed significantly less skew in allele frequencies, and were significantly larger. On this background of low frequency CNV, we also identified several high-frequency CNVs under putative positive selection using an FST outlier analysis. These included known adaptive CNVs containing rh2b and pfmdr1, and several other CNVs (e.g. DNA helicase, and 3 conserved proteins) that require further investigation. Our data are consistent with a significant impact of genetic structure on CNV burden in an important human pathogen.
2015-11-19 | GSE75137 | GEO
Project description:Constructing gene regulatory networks is crucial to unraveling the genetic architecture of complex traits and to understanding the mechanisms of diseases. On the basis of gene expression and single nucleotide polymorphism data in the yeast, Saccharomyces cerevisiae, we constructed gene regulatory networks using a two-stage penalized least squares method. A large system of structural equations via optimal prediction of a set of surrogate variables was established at the first stage, followed by consistent selection of regulatory effects at the second stage. Using this approach, we identified subnetworks that were enriched in gene ontology categories, revealing directional regulatory mechanisms controlling these biological pathways. Our mapping and analysis of expression-based quantitative trait loci uncovered a known alteration of gene expression within a biological pathway that results in regulatory effects on companion pathway genes in the phosphocholine network. In addition, we identify nodes in these gene ontology-enriched subnetworks that are coordinately controlled by transcription factors driven by trans-acting expression quantitative trait loci. Altogether, the integration of documented transcription factor regulatory associations with subnetworks defined by a system of structural equations using quantitative trait loci data is an effective means to delineate the transcriptional control of biological pathways.
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