Large–scale data–driven network analysis of human–plasmodium falciparum interactome: extracting essential targets and processes for malaria drug discovery

Background: Plasmodium falciparum malaria is an infectious disease considered to have great impact on public health due to its associated high mortality rates especially in sub Saharan Africa. Falciparum drugresistant strains, notably, to chloroquine and sulfadoxine-pyrimethamine in Africa is traced mainly to Southeast Asia where artemisinin resistance rate is increasing. Although careful surveillance to monitor the emergence and spread of artemisinin-resistant parasite strains in Africa is on-going, research into new drugs, particularly, for African populations, is critical since there is no replaceable drug for artemisinin combination therapies (ACTs) yet. Objective: The overall objective of this study is to identify potential protein targets through host–pathogen protein–protein functional interaction network analysis to understand the underlying mechanisms of drug failure and identify those essential targets that can play their role in predicting potential drug candidates specific to the African populations through a protein-based approach of both host and Plasmodium falciparum genomic analysis. Methods: We leveraged malaria-specific genome wide association study summary statistics data obtained from Gambia, Kenya and Malawi populations, Plasmodium falciparum selective pressure variants and functional datasets (protein sequences, interologs, host-pathogen intra-organism and host-pathogen inter-organism protein-protein interactions (PPIs)) from various sources (STRING, Reactome, HPID, Uniprot, IntAct and literature) to construct overlapping functional network for both host and pathogen. Developed algorithms and a large-scale data-driven computational framework were used in this study to analyze the datasets and the constructed networks to identify densely connected subnetworks or hubs essential for network stability and integrity. The host-pathogen network was analyzed to elucidate the influence of parasite candidate key proteins within the network and predict possible resistant pathways due to host-pathogen candidate key protein interactions. We performed biological and pathway enrichment analysis on critical proteins identified to elucidate their functions. In order to leverage disease-target-drug relationships to identify potential repurposable already approved drug candidates that could be used to treat malaria, pharmaceutical datasets from drug bank were explored using semantic similarity approach based of target–associated biological processes Results: About 600,000 significant SNPs (p-value< 0.05) from the summary statistics data were mapped to their associated genes, and we identified 79 human-associated malaria genes. The assembled parasite network comprised of 8 clusters containing 799 functional interactions between 155 reviewed proteins of which 5 clusters contained 43 key proteins (selective variants) and 2 clusters contained 2 candidate key proteins(key proteins characterized by high centrality measure), C6KTB7 and C6KTD2. The human network comprised of 32 clusters containing 4,133,136 interactions between 20,329 unique reviewed proteins of which 7 clusters contained 760 key proteins and 2 clusters contained 6 significant human malaria-associated candidate key proteins or genes P22301 (IL10), P05362 (ICAM1), P01375 (TNF), P30480 (HLA-B), P16284 (PECAM1), O00206 (TLR4). The generated host-pathogen network comprised of 31,512 functional interactions between 8,023 host and pathogen proteins. We also explored the association of pfk13 gene within the host-pathogen. We observed that pfk13 cluster with host kelch–like proteins and other regulatory genes but no direct association with our identified host candidate key malaria targets. We implemented semantic similarity based approach complemented by Kappa and Jaccard statistical measure to identify 115 malaria–similar diseases and 26 potential repurposable drug hits that can be 3 appropriated experimentally for malaria treatment. Conclusion: In this study, we reviewed existing antimalarial drugs and resistance–associated variants contributing to the diminished sensitivity of antimalarials, especially chloroquine, sulfadoxine-pyrimethamine and artemisinin combination therapy within the African population. We also described various computational techniques implemented in predicting drug targets and leads in drug research. In our data analysis, we showed that possible mechanisms of resistance to artemisinin in Africa may arise from the combinatorial effects of many resistant genes to chloroquine and sulfadoxine–pyrimethamine. We investigated the role of pfk13 within the host–pathogen network. We predicted key targets that have been proposed to be essential for malaria drug and vaccine development through structural and functional analysis of host and pathogen function networks. Based on our analysis, we propose these targets as essential co-targets for combinatorial malaria drug discovery

Similarities of Antimalarial Resistance Genes in Plasmodium Falciparum Based on Ontology

The finding of P. falciparum chloroquine resistance (pfcrt) and P. falciparum multidrug resistance 1(pfmdr1) gene in P. falciparum has become an obstacle in treating malaria. The polymorphism between the two genes may result in molecular functions, in cellular components, or in biological processes. The objective of this research is to find similarities between the two genes in 3 components; cellular components, molecular functions and biological processes, based on Gene Ontology. the similarity will be counted semantically by path length approach with Wang method. The range of similarity values is 0-1. After the similarity value examined; in Molecular Function the similarity is 1 due to the same drug transmembrane transporter activity, in Cellular Component is 0,714, the similarity only at the same vacuole food cells, and in Biological Processes is 1 due to the same proces in responding to drug. Therefore, this research proves both genes have similarities based on gene ontology

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

<p>Abstract</p> <p>Background</p> <p>A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance.</p> <p>Results</p> <p>Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, <it>Escherichia coli</it>, <it>Saccharomyces cerevisiae</it>, and <it>Plasmodium falciparum </it>(malaria). The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO) category, <it>i.e. </it>Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the <it>funSim </it>score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the <it>funSim </it>score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted.</p> <p>Conclusion</p> <p>The analyses demonstrate that applying high confidence predictions from PFP can have a significant impact on a researchers' ability to interpret the immense biological data that are being generated today. The newly introduced functional similarity networks of the three organisms show different network properties as compared with the protein-protein interaction networks.</p

Systems analysis and controlled malaria infection in Europeans and Africans elucidate naturally acquired immunity

Controlled human infections provide opportunities to study the interaction between the immune system and malaria parasites, which is essential for vaccine development. Here, we compared immune signatures of malaria-naive Europeans and of Africans with lifelong malaria exposure using mass cytometry, RNA sequencing and data integration, before and 5 and 11 days after venous inoculation with Plasmodium falciparum sporozoites. We observed differences in immune cell populations, antigen-specific responses and gene expression profiles between Europeans and Africans and among Africans with differing degrees of immunity. Before inoculation, an activated/differentiated state of both innate and adaptive cells, including elevated CD161(+)CD4(+) T cells and interferon-gamma production, predicted Africans capable of controlling parasitemia. After inoculation, the rapidity of the transcriptional response and clusters of CD4(+) T cells, plasmacytoid dendritic cells and innate T cells were among the features distinguishing Africans capable of controlling parasitemia from susceptible individuals. These findings can guide the development of a vaccine effective in malaria-endemic regions.Malaria immunity can be acquired through natural infection, but the correlates of protection are still being determined. Yazdanbakhsh and colleagues combine experimental infection of volunteers with Plasmodium falciparum with systems analysis to throw light on the nature of protective immune responses.Radiolog

Ca2+ signals critical for egress and gametogenesis in malaria parasites depend on a multipass membrane protein that interacts with PKG.

Calcium signaling regulated by the cGMP-dependent protein kinase (PKG) controls key life cycle transitions in the malaria parasite. However, how calcium is mobilized from intracellular stores in the absence of canonical calcium channels in Plasmodium is unknown. Here, we identify a multipass membrane protein, ICM1, with homology to transporters and calcium channels that is tightly associated with PKG in both asexual blood stages and transmission stages. Phosphoproteomic analyses reveal multiple ICM1 phosphorylation events dependent on PKG activity. Stage-specific depletion of Plasmodium berghei ICM1 prevents gametogenesis due to a block in intracellular calcium mobilization, while conditional loss of Plasmodium falciparum ICM1 is detrimental for the parasite resulting in severely reduced calcium mobilization, defective egress, and lack of invasion. Our findings suggest that ICM1 is a key missing link in transducing PKG-dependent signals and provide previously unknown insights into atypical calcium homeostasis in malaria parasites essential for pathology and disease transmission

Análises dos mecanismos imunopatológicos e moleculares envolvidos no processo de citoaderência de Plasmodium vivax

Orientadores: Fabio Trindade Maranhão Costa, Letusa AlbrechtTese (doutorado) - Universidade Estadual de Campinas, Instituto de BiologiaResumo: Plasmodium vivax é o parasita causador malária humana mais prevalente, disseminado e negligenciado, colocando todos os anos bilhões de pessoas em risco de infeção, acarretando sérios problemas de saúde e econômicos. A emergência de resistência a antimaláricos e complicações clínicas graves são preocupantes. Pouco se sabe sobre os mecanismos envolvidos nas características patogénicas da biologia do negligenciado P. vivax. A impossibilidade de executar a cultura in vitro de isolados a longo prazo, limita os pesquisadores ao estudo da sua biologia no espaço e tempo, restringindo o trabalho experimental a áreas endêmicas de malária vivax, onde a execução bem-sucedida de aplicações ômicas é desafiadora. A capacidade de P. vivax remodelar a membrana dos reticulócitos do hospedeiro e promover a sua adesividade foi já demostrada, dendo um mecanismo importante de evasão ao sistema imunitário humano. Estudos funcionais têm reportado que a adesão de reticulócitos infectados por P. vivax (RTi-Pv) a células endoteliais do hospedeiro, apesar de em menor número, é forte e estável, como o verificado para eritrócitos infectados por P. falciparum. Também foi observado que a adesão de eritrócitos não infectados a RTi-Pv é forte e resulta na formação estável de rosetas, que apresenta uma maior taxa em malária vivax do que falciparum. Mais recentemente, foi publicado que existe uma correlação entre a formação de rosetas e a deformabilidade de RTi-Pv, na qual RTi-Pv que formam rosetas são significativamente mais rígidos. Estágios maduros de P. vivax (esquizontes) têm elevada capacidade de aderir relativa a outros estágios assexuais do parasita, em ambos fenótipos de citoadesão e roseteamento. A menor proporção de esquizontes na circulação sanguínea periférica de pacientes sugere que os parasitas podem sequestrar no endotélio vascular do hospedeiro. Os RTi-Pv que formam rosetas poderão ser a causa desta baixa taxa de esquizontes circulantes no sangue dos pacientes, contribuindo para o fenómeno de sequestro parasitário na microvasculatura e/ou baço do hospedeiro, e consequentemente contribuindo para características reopatológicas da malária vivax. Autópsias de pacientes com malária vivax mostraram a acumulação de RTi-Pv nos pulmões, baço, fígado e medula óssea. Ainda, foi demonstrado que a parasitemia subestima a biomassa total parasitária, que é elevada em malária vivax severa, portanto, capaz de mediar a inflamação sistémica da patologia. O objetivo deste estudo é a compreensão dos mecanismos moleculares envolvidos nos fenótipos adesivos, identificando proteínas, principalmente ligantes parasitários, que possam ser importantes na capacidade de aderência de P. vivax. Usando RNA-seq em conjunto com o enriquecimento, maturação ex vivo e ensaio funcional de adesão com amostras clínicas de P. vivax, foi sequenciado o transcriptoma de populações de parasitas com características adesivas distintas. Os nossos perfis de expressão mostram a importância de diferentes grupos de proteínas membranares ou associadas a membranas, com propriedades de adesinas, tais como proteínas Plasmodium Interspersed repeats (PIR) e Plasmodium Helical Interspersed SubTelomeric (PHIST), que podem ter um papel importante no fenótipo adesivo de P. vivax. Dentro deste grupo de proteínas diferencialmente expressas foi verificado que muitas são tradicionalmente produzidas por parasitas em fase sexuada, sugerindo a importância da formação de rosetas por gametócitos de P. vivax. Adicionalmente, análise do perfil de expressão gênica humano permitiu a identificação de genes diferencialmente expressos associados a vias de fagocitose. Estes dados sugerem fortemente que o fenótipo de roseteamento pode impedir a fagocitose do parasita por leucócitos como resposta do sistema imune humano à infeção. Os resultados obtidos refletem as características patogénicas de populações brasileiras circulantes de P. vivax, principalmente no que diz respeito à sua capacidade de aderência como principal fonte das manifestações clínicas severas reportadas. Para além disso, esperamos que estes dados abram ainda mais as investigações sobre a biologia deste parasita apicomplexo, ajudando no desenho de vacinas e na descoberta de novos antimaláricos, promovendo o sucesso na eliminação da malária vivax no futuro.Abstract: Plasmodium vivax is the most prevalent, widespread and neglected human malaria parasite, currently placing billions of people at risk of infection, thus imposing major health and economic burdens. Worldwide, anti-malarial drug resistance emergence and severe clinical complications are of great concern. The mechanisms underlying the pathobiology of the neglected P. vivax are still little known. The lack of a reliable in vitro P. vivax long-term culture restricts its biology study in place and time, relegating researchers to work in malaria endemic field conditions, where successful omics applications are very challenging. The capacity of P. vivax to remodel host reticulocyte membrane and promote adhesivity has been demonstrated, which is an important mechanism for host immune evasion. Functional studies have already reported that adhesion of P. vivax infected red blood cells (PvIRBCs) to the host endothelial cells, although in considerably lower rates, is as strong and stable as the verified for P. falciparum infections. Also, it has been reported adhesion of normocytes to the PvIRBCs is strong and results in stable rosette formation, which shows higher rates in vivax compared to falciparum malaria. More recently, it was reported that there is a correlation between rosette formation and altered membrane deformability of PvIRBCs, where the rosette-forming PvIRBCs are significantly more stiff and rigid than their non-rosetting equals. Mature staged parasites (schizonts) show a higher capacity for adherence than other asexual parasite stages both in cytoadherence and rosetting. The lower proportion of schizonts observed on the peripheral blood circulation of patients suggests that parasites could be sequestered on the host vascular endothelium. Rosette-forming PvIRBCs may also be the cause for this lower rate of schizonts in the patients’ blood, contributing for parasite sequestration phenomena in the host microvasculature and/or spleen, and consequently, the rheopathological characteristics present in vivax malaria disease. Vivax malaria patient autopsies have shown accumulation of PvIRBCs in the lungs, spleen, liver and bone marrow. Additionally, it has been demonstrated that parasitemia underestimates total parasite biomass, which is greater in severe vivax malaria patients, and thus, capable of mediating systemic inflammatory pathology. In this study, we aimed to understand the molecular mechanisms behind adherence phenotypes by identifying proteins, especially parasitic ligands, which might be important in P. vivax adhesion capacity. Using RNA-seq coupled with parasite field sample enrichment, ex vivo maturation and cytoadherence assays, we have sequenced the whole transcriptome of parasite populations with distinct adhesive characteristics. Our expression profiles brings out the importance of membrane and membrane-associated proteins, with adhesin or adhesin-like properties, such as Plasmodium Interspersed repeats (PIR) and Plasmodium Helical Interspersed SubTelomeric (PHIST) proteins, which might pay a role in adherence phenotypes. Within those protein groups, we found a percentage of differentially expressed genes that traditionally are more expressed in sexual rather than asexual parasite stages, suggesting the relevance of rosette formation by P. vivax gametocytes. Importantly, we found host immune-related differentially expressed genes, of which several are associated with the human phagocytosis pathways. These data strongly suggest that rosetting can hamper leukocyte phagocytosis host immune response, as an effective mechanism of P. vivax immune evasion adaptation. Our results reflect the pathobiology of circulating Brazilian P. vivax populations, principally concerning its adhesive capacity as a possible source of the severe clinical manifestations reported. Furthermore, we hope that such achievements will further enable the investigations on the biology of P. vivax apicomplexan parasite, impacting considerably in vaccine and drug design, ultimately helping us achieve the future elimination of vivax malaria.DoutoradoImunologiaDoutora em Genética e Biologia Molecular2013/20509-5FAPES

Dissecting the biological content of host and parasite-derived extracellular vesicles in malaria

Plasmodium falciparum causes the deadliest form of malaria, especially in African children under five years. The parasite and its human host secrete small nanoparticles called extracellular vesicles (EVs) into their extracellular milieu. EVs contain bioactive molecules such as RNA and proteins reflecting that in the secreting cells. However, the biological contents of EVs are not well-characterized in the context of falciparum malaria. EVs are attractive sources of non-invasive biomarkers for diseases affecting inaccessible tissues such as the brain. Analysing the biological content of EVs will provide insights into their functions and could illuminate pathophysiological mechanisms of severe malaria syndromes, including cerebral malaria, respiratory distress, and severe malaria anaemia. The first part of this thesis aimed to investigate the biological benefit of EVs to the secreting parasite. To achieve this purpose, I sequenced four-hourly RNA samples obtained from EVs secreted by six P. falciparum isolates and compared them to the RNA within the secreting whole parasites. The data suggest parasite-derived EVs might be part of a post-transcriptional gene regulatory mechanism that maintains RNA homeostasis in P. falciparum. The second part of this thesis aimed to understand the pathophysiology of severe malaria complications. To this purpose, I quantified the protein and RNA content of plasma EVs obtained from acute malaria patients. I developed temporal models of disease progression by applying manifold learning to the cross-sectionally collected EV samples. In a parallel approach, I used plasma EV transcriptomes to develop a pseudo-temporal model of cerebral malaria. I determined that cerebral malaria might feature a progressive decrease in neural gene expression and an increase in glial gene expression, which can be followed using peripheral blood EVs. I conclude that EVs are treasure troves of biomarkers that can be used to eavesdrop on biological mechanisms in P. falciparum and its human host

Computational approaches to discovering differentiation genes in the peripheral nervous system of drosophila melanogaster

In the common fruit fly, Drosophila melanogaster, neural cell fate specification is triggered by a group of conserved transcriptional regulators known as proneural factors. Proneural factors induce neural fate in uncommitted neuroectodermal progenitor cells, in a process that culminates in sensory neuron differentiation. While the role of proneural factors in early fate specification has been described, less is known about the transition between neural specification and neural differentiation. The aim of this thesis is to use computational methods to improve the understanding of terminal neural differentiation in the Peripheral Nervous System (PNS) of Drosophila. To provide an insight into how proneural factors coordinate the developmental programme leading to neural differentiation, expression profiling covering the first 3 hours of PNS development in Drosophila embryos had been previously carried out by Cachero et al. [2011]. The study revealed a time-course of gene expression changes from specification to differentiation and suggested a cascade model, whereby proneural factors regulate a group of intermediate transcriptional regulators which are in turn responsible for the activation of specific differentiation target genes. In this thesis, I propose to select potentially important differentiation genes from the transcriptional data in Cachero et al. [2011] using a novel approach centred on protein interaction network-driven prioritisation. This is based on the insight that biological hypotheses supported by diverse data sources can represent stronger candidates for follow-up studies. Specifically, I propose the usage of protein interaction network data because of documented transcriptome-interactome correlations, which suggest that differentially expressed genes encode products that tend to belong to functionally related protein interaction clusters. Experimental protein interaction data is, however, remarkably sparse. To increase the informative power of protein-level analyses, I develop a novel approach to augment publicly available protein interaction datasets using functional conservation between orthologous proteins across different genomes, to predict interologs (interacting orthologs). I implement this interolog retrieval methodology in a collection of open-source software modules called Bio:: Homology::InterologWalk, the first generalised framework using web-services for “on-the- fly” interolog projection. Bio::Homology::InterologWalk works with homology data for any of the hundreds of genomes in Ensembl and Ensembgenomes Metazoa, and with experimental protein interaction data curated by EBI Intact. It generates putative protein interactions and optionally collates meta-data into a prioritisation index that can be used to help select interologs with high experimental support. The methodology proposed represents a significant advance over existing interolog data sources, which are restricted to specific biological domains with fixed underlying data sources often only accessible through basic web-interfaces. Using Bio::Homology::InterologWalk, I build interolog models in Drosophila sensory neurons and, guided by the transcriptome data, find evidence implicating a small set of genes in a conserved sensory neuronal specialisation dynamic, the assembly of the ciliary dendrite in mechanosensory neurons. Using network community-finding algorithms I obtain functionally enriched communities, which I analyse using an array of novel computational techniques. The ensuing datasets lead to the elucidation of a cluster of interacting proteins encoded by the target genes of one of the intermediate transcriptional regulators of neurogenesis and ciliogenesis, fd3F. These targets are validated in vivo and result in improved knowledge of the important target genes activated by the transcriptional cascade, suggesting a scenario for the mechanisms orchestrating the ordered assembly of the cilium during differentiation