PlasmoDraft: a database of Plasmodium falciparum gene function predictions based on postgenomic data

Genome-wide microsatellite characteristics of five human Plasmodium species, focusing on Plasmodium malariae and P. ovale curtisi

Microsatellites can be utilized to explore genotypes, population structure, and other genomic features of eukaryotes. Systematic characterization of microsatellites has not been a focus for several species of Plasmodium, including P. malariae and P. ovale, as the majority of malaria elimination programs are focused on P. falciparum and to a lesser extent P. vivax. Here, five human malaria species (P. falciparum, P. vivax, P. malariae, P. ovale curtisi, and P. knowlesi) were investigated with the aim of conducting in-depth categorization of microsatellites for P. malariae and P. ovale curtisi. Investigation of reference genomes for microsatellites with unit motifs of 1-10 base pairs indicates high diversity among the five Plasmodium species. Plasmodium malariae, with the largest genome size, displays the second highest microsatellite density (1421 No./Mbp; 5% coverage) next to P. falciparum (3634 No./Mbp; 12% coverage). The lowest microsatellite density was observed in P. vivax (773 No./Mbp; 2% coverage). A, AT, and AAT are the most commonly repeated motifs in the Plasmodium species. For P. malariae and P. ovale curtisi, microsatellite-related sequences are observed in approximately 18-29% of coding sequences (CDS). Lysine, asparagine, and glutamic acids are most frequently coded by microsatellite-related CDS. The majority of these CDS could be related to the gene ontology terms "cell parts," "binding," "developmental processes," and "metabolic processes." The present study provides a comprehensive overview of microsatellite distribution and can assist in the planning and development of potentially useful genetic tools for further investigation of P. malariae and P. ovale curtisi epidemiology.

Landscape and Dynamics of Transcription Initiation in the Malaria Parasite Plasmodium falciparum

A comprehensive map of transcription start sites (TSSs) across the highly AT-rich genome of P. falciparum would aid progress toward deciphering the molecular mechanisms that underlie the timely regulation of gene expression in this malaria parasite. Using high-throughput sequencing technologies, we generated a comprehensive atlas of transcription initiation events at single-nucleotide resolution during the parasite intra-erythrocytic developmental cycle. This detailed analysis of TSS usage enabled us to define architectural features of plasmodial promoters. We demonstrate that TSS selection and strength are constrained by local nucleotide composition. Furthermore, we provide evidence for coordinate and stage-specific TSS usage from distinct sites within the same transcription unit, thereby producing transcript isoforms, a subset of which are developmentally regulated. This work offers a framework for further investigations into the interactions between genomic sequences and regulatory factors governing the complex transcriptional program of this major human pathogen.

A chemical proteomics approach for the search of pharmacological targets of the antimalarial clinical candidate albitiazolium in Plasmodium falciparum using photocrosslinking and click chemistry

Plasmodium falciparum is responsible for severe malaria which is one of the most prevalent and deadly infectious diseases in the world. The antimalarial therapeutic arsenal is hampered by the onset of resistance to all known pharmacological classes of compounds, so new drugs with novel mechanisms of action are critically needed. Albitiazolium is a clinical antimalarial candidate from a series of choline analogs designed to inhibit plasmodial phospholipid metabolism. Here we developed an original chemical proteomic approach to identify parasite proteins targeted by albitiazolium during their native interaction in living parasites. We designed a bifunctional albitiazolium-derived compound (photoactivable and clickable) to covalently crosslink drug-interacting parasite proteins in situ followed by their isolation via click chemistry reactions. Mass spectrometry analysis of drug-interacting proteins and subsequent clustering on gene ontology terms revealed parasite proteins involved in lipid metabolic activities and, interestingly, also in lipid binding, transport, and vesicular transport functions. In accordance with this, the albitiazolium-derivative was localized in the endoplasmic reticulum and trans-Golgi network of P. falciparum. Importantly, during competitive assays with albitiazolium, the binding of choline/ethanolamine phosphotransferase (the enzyme involved in the last step of phosphatidylcholine synthesis) was substantially displaced, thus confirming the efficiency of this strategy for searching albitiazolium targets.

Identifying novel cell cycle proteins in Apicomplexa parasites through co-expression decision analysis

Hypothetical proteins comprise roughly half of the predicted gene complement of Toxoplasma gondii and Plasmodium falciparum and represent the largest class of uniquely functioning proteins in these parasites. Following the idea that functional relationships can be informed by the timing of gene expression, we devised a strategy to identify the core set of apicomplexan cell division cycling genes with important roles in parasite division, which includes many uncharacterized proteins. We assembled an expanded list of orthologs from the T. gondii and P. falciparum genome sequences (2781 putative orthologs), compared their mRNA profiles during synchronous replication, and sorted the resulting set of dual cell cycle regulated orthologs (744 total) into protein pairs conserved across many eukaryotic families versus those unique to the Apicomplexa. The analysis identified more than 100 ortholog gene pairs with unknown function in T. gondii and P. falciparum that displayed co-conserved mRNA abundance, dynamics of cyclical expression and similar peak timing that spanned the complete division cycle in each parasite. The unknown cyclical mRNAs encoded a diverse set of proteins with a wide range of mass and showed a remarkable conservation in the internal organization of ordered versus disordered structural domains. A representative sample of cyclical unknown genes (16 total) was epitope tagged in T. gondii tachyzoites yielding the discovery of new protein constituents of the parasite inner membrane complex, key mitotic structures and invasion organelles. These results demonstrate the utility of using gene expression timing and dynamic profile to identify proteins with unique roles in Apicomplexa biology.

Malaria proteomics: insights into the parasite-host interactions in the pathogenic space

Proteomics is improving malaria research by providing global information on relevant protein sets from the parasite and the host in connection with its cellular structures and specific functions. In the last decade, reports have described biologically significant elements in the proteome of Plasmodium, which are selectively targeted and quantified, allowing for sensitive and high-throughput comparisons. The identification of molecules by which the parasite and the host react during the malaria infection is crucial to the understanding of the underlying pathogenic mechanisms. Hence, proteomics is playing a major role by defining the elements within the pathogenic space between both organisms that change across the parasite life cycle in association with the host transformation and response. Proteomics has identified post-translational modifications in the parasite and the host that are discussed in terms of functional interactions in malaria parasitism. Furthermore, the contribution of proteomics to the investigation of immunogens for potential vaccine candidates is summarized. The malaria-specific technological advances in proteomics are particularly suited now for identifying host-parasite interactions that could lead to promising targets for therapy, diagnosis or prevention. In this review, we examine the knowledge gained on the biology, pathogenesis, immunity and diagnosis of Plasmodium infection from recent proteomic studies. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

MaGnET: Malaria Genome Exploration Tool

SUMMARY

The Malaria Genome Exploration Tool (MaGnET) is a software tool enabling intuitive 'exploration-style' visualization of functional genomics data relating to the malaria parasite, Plasmodium falciparum. MaGnET provides innovative integrated graphic displays for different datasets, including genomic location of genes, mRNA expression data, protein-protein interactions and more. Any selection of genes to explore made by the user is easily carried over between the different viewers for different datasets, and can be changed interactively at any point (without returning to a search).

AVAILABILITY AND IMPLEMENTATION

Free online use (Java Web Start) or download (Java application archive and MySQL database; requires local MySQL installation) at http://malariagenomeexplorer.org

CONTACT

joanna.sharman@ed.ac.uk or dgerloff@ffame.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Comparative Genomics and Systems Biology of Malaria Parasites Plasmodium

Malaria is a serious infectious disease that causes over one million deaths yearly. It is caused by a group of protozoan parasites in the genus Plasmodium. No effective vaccine is currently available and the elevated levels of resistance to drugs in use underscore the pressing need for novel antimalarial targets. In this review, we survey omics centered developments in Plasmodium biology, which have set the stage for a quantum leap in our understanding of the fundamental processes of the parasite life cycle and mechanisms of drug resistance and immune evasion.

Determination of protein subcellular localization in apicomplexan parasites

Parasites from the phylum Apicomplexa include causative agents of serious diseases including malaria (Plasmodium spp.) and toxoplasmosis (Toxoplasma gondii). Apicomplexan parasites infect thousands of types of animal cells and send their proteins to an array of compartments within their own cell, as well as exporting proteins into and beyond their host cell. Ascertaining destinations to which individual proteins are delivered allows researchers to better understand parasite biology and to identify potential targets for therapeutic interventions. Our toolkit for establishing subcellular locations of apicomplexan proteins is becoming more extensive and specialized, and here we review developments in this technology.

Genome comparison of human and non-human malaria parasites reveals species subset-specific genes potentially linked to human disease

Genes underlying important phenotypic differences between Plasmodium species, the causative agents of malaria, are frequently found in only a subset of species and cluster at dynamically evolving subtelomeric regions of chromosomes. We hypothesized that chromosome-internal regions of Plasmodium genomes harbour additional species subset-specific genes that underlie differences in human pathogenicity, human-to-human transmissibility, and human virulence. We combined sequence similarity searches with synteny block analyses to identify species subset-specific genes in chromosome-internal regions of six published Plasmodium genomes, including Plasmodium falciparum, Plasmodium vivax, Plasmodium knowlesi, Plasmodium yoelii, Plasmodium berghei, and Plasmodium chabaudi. To improve comparative analysis, we first revised incorrectly annotated gene models using homology-based gene finders and examined putative subset-specific genes within syntenic contexts. Confirmed subset-specific genes were then analyzed for their role in biological pathways and examined for molecular functions using publicly available databases. We identified 16 genes that are well conserved in the three primate parasites but not found in rodent parasites, including three key enzymes of the thiamine (vitamin B1) biosynthesis pathway. Thirteen genes were found to be present in both human parasites but absent in the monkey parasite P. knowlesi, including genes specifically upregulated in sporozoites or gametocytes that could be linked to parasite transmission success between humans. Furthermore, we propose 15 chromosome-internal P. falciparum-specific genes as new candidate genes underlying increased human virulence and detected a currently uncharacterized cluster of P. vivax-specific genes on chromosome 6 likely involved in erythrocyte invasion. In conclusion, Plasmodium species harbour many chromosome-internal differences in the form of protein-coding genes, some of which are potentially linked to human disease and thus promising leads for future laboratory research.

With more than 250 million infections and over a million deaths each year, malaria remains one of the most devastating infectious diseases worldwide. With the availability of complete genome sequences of both human and non-human Plasmodium parasites, the causative agents of malaria, it is now possible to use comparative genomics as a tool to look for genes that are present in some but not all Plasmodium species. Such species subset-specific genes possibly underlie important phenotypic differences between malaria parasites and could provide important clues for the development of new strategies to prevent and treat malaria in humans. In this study, we performed a comprehensive computational comparison of the published genomes of six Plasmodium species, including two human (P. falciparum and P. vivax), one monkey (P. knowlesi), and three rodent malaria parasites (P. berghei, P. yoelii, and P. chabaudi). This comparison revealed many species subset-specific genes that are potentially linked to human pathogenicity, human-to-human transmissibility, and human virulence. These genes can now be examined further by targeted experimental analyses to test predicted phenotypic associations and to elucidate gene function.

Computational prediction of host-parasite protein interactions between P. falciparum and H. sapiens

To obtain candidates of interactions between proteins of the malaria parasite Plasmodium falciparum and the human host, homologous and conserved interactions were inferred from various sources of interaction data. Such candidate interactions were assessed by applying a machine learning approach and further filtered according to expression and molecular characteristics, enabling involved proteins to indeed interact. The analysis of predicted interactions indicated that parasite proteins predominantly target central proteins to take control of a human host cell. Furthermore, parasite proteins utilized their protein repertoire in a combinatorial manner, providing a broad connection to host cellular processes. In particular, several prominent pathways of signaling and regulation proteins were predicted to interact with parasite chaperones. Such a result suggests an important role of remodeling proteins in the interaction interface between the human host and the parasite. Identification of such molecular strategies that allow the parasite to take control of the host has the potential to deepen our understanding of the parasite specific remodeling processes of the host cell and illuminate new avenues of disease intervention.

Shared molecular strategies of the malaria parasite P. falciparum and the human virus HIV-1

We augmented existing computationally predicted and experimentally determined interactions with evolutionarily conserved interactions between proteins of the malaria parasite, P. falciparum, and the human host. In a validation step, we found that conserved interacting host-parasite protein pairs were specifically expressed in host tissues where both the parasite and host proteins are known to be active. We compared host-parasite interactions with experimentally verified interactions between human host proteins and a very different pathogen, HIV-1. Both pathogens were found to use their protein repertoire in a combinatorial manner, providing a broad connection to host cellular processes. Specifically, the two biologically distinct pathogens predominately target central proteins to take control of a human host cell, effectively reaching into diversified cellular host cellular functions. Interacting signaling pathways and a small set of regulatory and signaling proteins were prime targets of both pathogens, suggesting remarkably similar patterns of host-pathogen interactions despite the vast biological differences of both pathogens. Such an identification of shared molecular strategies by the virus HIV-1 and the eukaryotic intracellular pathogen P. falciparum may allow us to illuminate new avenues of disease intervention.

Difference in gene duplicability may explain the difference in overall structure of protein-protein interaction networks among eukaryotes

Background

A protein-protein interaction network (PIN) was suggested to be a disassortative network, in which interactions between high- and low-degree nodes are favored while hub-hub interactions are suppressed. It was postulated that a disassortative structure minimizes unfavorable cross-talks between different hub-centric functional modules and was positively selected in evolution. However, by re-examining yeast PIN data, several researchers reported that the disassortative structure observed in a PIN might be an experimental artifact. Therefore, the existence of a disassortative structure and its possible evolutionary mechanism remains unclear.

Results

In this study, we investigated PINs from the yeast, worm, fly, human, and malaria parasite including four different yeast PIN datasets. The analyses showed that the yeast, worm, fly, and human PINs are disassortative while the malaria parasite PIN is not. By conducting simulation studies on the basis of a duplication-divergence model, we demonstrated that a preferential duplication of low- and high-degree nodes can generate disassortative and non-disassortative networks, respectively. From this observation, we hypothesized that the difference in degree dependence on gene duplications accounts for the difference in assortativity of PINs among species. Comparison of 55 proteomes in eukaryotes revealed that genes with lower degrees showed higher gene duplicabilities in the yeast, worm, and fly, while high-degree genes tend to have high duplicabilities in the malaria parasite, supporting the above hypothesis.

Conclusions

These results suggest that disassortative structures observed in PINs are merely a byproduct of preferential duplications of low-degree genes, which might be caused by an organism's living environment.

Gene function prediction using semantic similarity clustering and enrichment analysis in the malaria parasite Plasmodium falciparum

MOTIVATION

Functional genomics data provides a rich source of information that can be used in the annotation of the thousands of genes of unknown function found in most sequenced genomes. However, previous gene function prediction programs are mostly produced for relatively well-annotated organisms that often have a large amount of functional genomics data. Here, we present a novel method for predicting gene function that uses clustering of genes by semantic similarity, a naïve Bayes classifier and 'enrichment analysis' to predict gene function for a genome that is less well annotated but does has a severe effect on human health, that of the malaria parasite Plasmodium falciparum.

RESULTS

Predictions for the molecular function, biological process and cellular component of P.falciparum genes were created from eight different datasets with a combined prediction also being produced. The high-confidence predictions produced by the combined prediction were compared to those produced by a simple K-nearest neighbour classifier approach and were shown to improve accuracy and coverage. Finally, two case studies are described, which investigate two biological processes in more detail, that of translation initiation and invasion of the host cell.

AVAILABILITY

Predictions produced are available at http://www.bioinformatics.leeds.ac.uk/∼bio5pmrt/PAGODA.

PlasmoPredict: a gene function prediction website for Plasmodium falciparum

The genome sequence of the malaria parasite Plasmodium falciparum was published in 2002 and revealed that approximately 60% of its genes could not be assigned a function. Eight years later the majority of P. falciparum proteins are still of unknown function. We therefore present PlasmoPredict, an easy-to-use online gene function prediction tool that integrates a wide range of functional genomics data for P. falciparum to aid in the annotation of these genes.

Assessing functional annotation transfers with inter-species conserved coexpression: application to Plasmodium falciparum

BACKGROUND

Plasmodium falciparum is the main causative agent of malaria. Of the 5 484 predicted genes of P. falciparum, about 57% do not have sufficient sequence similarity to characterized genes in other species to warrant functional assignments. Non-homology methods are thus needed to obtain functional clues for these uncharacterized genes. Gene expression data have been widely used in the recent years to help functional annotation in an intra-species way via the so-called Guilt By Association (GBA) principle.

RESULTS

We propose a new method that uses gene expression data to assess inter-species annotation transfers. Our approach starts from a set of likely orthologs between a reference species (here S. cerevisiae and D. melanogaster) and a query species (P. falciparum). It aims at identifying clusters of coexpressed genes in the query species whose coexpression has been conserved in the reference species. These conserved clusters of coexpressed genes are then used to assess annotation transfers between genes with low sequence similarity, enabling reliable transfers of annotations from the reference to the query species. The approach was used with transcriptomic data sets of P. falciparum, S. cerevisiae and D. melanogaster, and enabled us to propose with high confidence new/refined annotations for several dozens hypothetical/putative P. falciparum genes. Notably, we revised the annotation of genes involved in ribosomal proteins and ribosome biogenesis and assembly, thus highlighting several potential drug targets.

CONCLUSIONS

Our approach uses both sequence similarity and gene expression data to help inter-species gene annotation transfers. Experiments show that this strategy improves the accuracy achieved when using solely sequence similarity and outperforms the accuracy of the GBA approach. In addition, our experiments with P. falciparum show that it can infer a function for numerous hypothetical genes.

Revisiting the Plasmodium falciparum RIFIN family: from comparative genomics to 3D-model prediction

Background

Subtelomeric RIFIN genes constitute the most abundant multigene family in Plasmodium falciparum. RIFIN products are targets for the human immune response and contribute to the antigenic variability of the parasite. They are transmembrane proteins grouped into two sub-families (RIF_A and RIF_B). Although recent data show that RIF_A and RIF_B have different sub-cellular localisations and possibly different functions, the same structural organisation has been proposed for members of the two sub-families. Despite recent advances, our knowledge of the regulation of RIFIN gene expression is still poor and the biological role of the protein products remain obscure.

Results

Comparative studies on RIFINs in three clones of P. falciparum (3D7, HB3 and Dd2) by Multidimensional scaling (MDS) showed that gene sequences evolve differently in the 5'upstream, coding, and 3'downstream regions, and suggested a possible role of highly conserved 3' downstream sequences. Despite the expected polymorphism, we found that the overall structure of RIFIN repertoires is conserved among clones suggesting a balance between genetic drift and homogenisation mechanisms which guarantees emergence of novel variants but preserves the functionality of genes. Protein sequences from a bona fide set of 3D7 RIFINs were submitted to predictors of secondary structure elements. In contrast with the previously proposed structural organisation, no signal peptide and only one transmembrane helix were predicted for the majority of RIF_As. Finally, we developed a strategy to obtain a reliable 3D-model for RIF_As. We generated 265 possible structures from 53 non-redundant sequences, from which clustering and quality assessments selected two models as the most representative for putative RIFIN protein structures.

Conclusion

First, comparative analyses of RIFIN repertoires in different clones of P. falciparum provide insights on evolutionary mechanisms shaping the multigene family. Secondly, we found that members of the two sub-families RIF_As and RIF_Bs have different structural organization in accordance with recent experimental results. Finally, representative models for RIF_As have an "Armadillo-like" fold which is known to promote protein-protein interactions in diverse contexts.