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New insights into the genetic regulation of Plasmodium falciparum obtained by Bayesian modeling.

ABSTRACT: The most fatal and prevalent form of malaria is caused by the bloodborne pathogen Plasmodium falciparum (henceforth P.f). Annually, approximately three million people died of malaria. Despite P.f devastating effect globally, the vast majority of its proteins have not been characterized experimentally. In this work, we provide computational insight that explore the modalities of the regulation for some important group of genes of P.f, namely components of the glycolytic pathway, and those involved in apicoplast metabolism. Glycolysis is a crucial pathway in the maintenance of the parasite while the recently discovered apicoplast contains a range of metabolic pathways and housekeeping processes that differ radically to those of the host, which makes it ideal for drug therapy.We have been able to validate some of our findings from available literature and therefore provide a basis to give theoretical insight for some genes regulations, which has not been characterized experimentally.

SUBMITTER: Bulashevska S

PROVIDER: S-EPMC2759121 | biostudies-literature | 2007 Nov

REPOSITORIES: biostudies-literature

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New insights into the genetic regulation of Plasmodium falciparum obtained by Bayesian modeling.

Bulashevska Svetlana S Adebiyi Ezekiel E Brors Benedikt B Eils Roland R

Gene regulation and systems biology 20071129

The most fatal and prevalent form of malaria is caused by the bloodborne pathogen Plasmodium falciparum (henceforth P.f). Annually, approximately three million people died of malaria. Despite P.f devastating effect globally, the vast majority of its proteins have not been characterized experimentally. In this work, we provide computational insight that explore the modalities of the regulation for some important group of genes of P.f, namely components of the glycolytic pathway, and those involve ...[more]

PMID: 19936084

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Project description:Hispaniola, comprising Haiti and the Dominican Republic, has been identified as a candidate for malaria elimination. However, incomplete surveillance data in Haiti hamper efforts to assess the impact of ongoing malaria control interventions. Characteristics of the genetic diversity of Plasmodium falciparum populations can be used to assess parasite transmission, which is information vital to evaluating malaria elimination efforts. Here we characterize the genetic diversity of P. falciparum samples collected from patients at seven sites in Haiti using 12 microsatellite markers previously employed in population genetic analyses of global P. falciparum populations. We measured multiplicity of infections, level of genetic diversity, degree of population geographic substructure, and linkage disequilibrium (defined as non-random association of alleles from different loci). For low transmission populations like Haiti, we expect to see few multiple infections, low levels of genetic diversity, high degree of population structure, and high linkage disequilibrium. In Haiti, we found low levels of multiple infections (12.9%), moderate to high levels of genetic diversity (mean number of alleles per locus = 4.9, heterozygosity = 0.61), low levels of population structure (highest pairwise Fst = 0.09 and no clustering in principal components analysis), and moderate linkage disequilibrium (ISA = 0.05, P<0.0001). In addition, population bottleneck analysis revealed no evidence for a reduction in the P. falciparum population size in Haiti. We conclude that the high level of genetic diversity and lack of evidence for a population bottleneck may suggest that Haiti's P. falciparum population has been stable and discuss the implications of our results for understanding the impact of malaria control interventions. We also discuss the relevance of parasite population history and other host and vector factors when assessing transmission intensity from genetic diversity data.

Dataset Information

New insights into the genetic regulation of Plasmodium falciparum obtained by Bayesian modeling.

Publications

New insights into the genetic regulation of Plasmodium falciparum obtained by Bayesian modeling.

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