Module-based subnetwork alignments reveal novel transcriptional regulators in malaria parasite Plasmodium falciparum

Background Malaria causes over one million deaths annually, posing an enormous health and economic burden in endemic regions. The completion of genome sequencing of the causative agents, a group of parasites in the genus Plasmodium, revealed potential drug and vaccine candidates. However, genomics-driven target discovery has been significantly hampered by our limited knowledge of the cellular networks associated with parasite development and pathogenesis. In this paper, we propose an approach based on aligning neighborhood PPI subnetworks across species to identify network components in the malaria parasite P. falciparum. Results Instead of only relying on sequence similarities to detect functional orthologs, our approach measures the conservation between the neighborhood subnetworks in protein-protein interaction (PPI) networks in two species, P. falciparum and E. coli. 1,082 P. falciparum proteins were predicted as functional orthologs of known transcriptional regulators in the E. coli network, including general transcriptional regulators, parasite-specific transcriptional regulators in the ApiAP2 protein family, and other potential regulatory proteins. They are implicated in a variety of cellular processes involving chromatin remodeling, genome integrity, secretion, invasion, protein processing, and metabolism. Conclusions In this proof-of-concept study, we demonstrate that a subnetwork alignment approach can reveal previously uncharacterized members of the subnetworks, which opens new opportunities to identify potential therapeutic targets and provide new insights into parasite biology, pathogenesis and virulence. This approach can be extended to other systems, especially those with poor genome annotation and a paucity of knowledge about cellular networks

A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum

Background According to the World Health organization, half the world\u27s population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum. Results Our novel subnetwork alignment approach was used to compare networks in Escherichia coli and P. falciparum. Some 574 P. falciparum proteins were revealed as functional orthologs of known cell cycle proteins in E. coli. Over one third of these predicted functional orthologs were annotated as conserved Plasmodium proteins or putative uncharacterized proteins of unknown function. The predicted functionalities included cyclins, kinases, surface antigens, transcriptional regulators and various functions related to DNA replication, repair and cell division. Conclusions The results of our analysis demonstrate the power of our subnetwork alignment approach to assign functionality to previously unannotated proteins. Here, the focus was on proteins involved in cell cycle regulation. These proteins are involved in the control of diverse aspects of the parasite lifecycle and of important aspects of pathogenesis

Predicting and exploring network components involved in pathogenesis in the malaria parasite via novel subnetwork alignments

Background Malaria is a major health threat, affecting over 40% of the world\u27s population. The latest report released by the World Health Organization estimated about 207 million cases of malaria infection, and about 627,000 deaths in 2012 alone. During the past decade, new therapeutic targets have been identified and are at various stages of characterization, thanks to the emerging omics-based technologies. However, the mechanism of malaria pathogenesis remains largely unknown. In this paper, we employ a novel neighborhood subnetwork alignment approach to identify network components that are potentially involved in pathogenesis. Results Our module-based subnetwork alignment approach identified 24 functional homologs of pathogenesis-related proteins in the malaria parasite P. falciparum, using the protein-protein interaction networks in Escherichia coli as references. Eighteen out of these 24 proteins are associated with 418 other proteins that are related to DNA replication, transcriptional regulation, translation, signaling, metabolism, cell cycle regulation, as well as cytoadherence and entry to the host. Conclusions The subnetwork alignments and subsequent protein-protein association network mining predicted a group of malarial proteins that may be involved in parasite development and parasite-host interaction, opening a new systems-level view of parasite pathogenesis and virulence

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

Protease-associated cellular networks in malaria parasite Plasmodium falciparum

Abstract Background Malaria 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. Results We 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. Conclusions Our 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.</p

The Schistosoma mansoni genome encodes thousands of long non-coding RNAs predicted to be functional at different parasite life-cycle stages

Next Generation Sequencing (NGS) strategies, like RNA-Seq, have revealed the transcription of a wide variety of long non-coding RNAs (lncRNAs) in the genomes of several organisms. In the present work we assessed the lncRNAs complement of Schistosoma mansoni, the blood fluke that causes schistosomiasis, ranked among the most prevalent parasitic diseases worldwide. We focused on the long intergenic/intervening ncRNAs (lincRNAs), hidden within the large amount of information obtained through RNA-Seq in S. mansoni (88 libraries). Our computational pipeline identified 7029 canonically-spliced putative lincRNA genes on 2596 genomic loci (at an average 2.7 isoforms per lincRNA locus), as well as 402 spliced lncRNAs that are antisense to protein-coding (PC) genes. Hundreds of lincRNAs showed traits for being functional, such as the presence of epigenetic marks at their transcription start sites, evolutionary conservation among other schistosome species and differential expression across five different life-cycle stages of the parasite. Real-time qPCR has confirmed the differential life-cycle stage expression of a set of selected lincRNAs. We have built PC gene and lincRNA co-expression networks, unraveling key biological processes where lincRNAs might be involved during parasite development. This is the first report of a large-scale identification and structural annotation of lncRNAs in the S. mansoni genome

Comparative analysis of gene expression associations between mammalian hosts and Plasmodium

Artenübergreifende Interaktionen helfen uns, Krankheitsmechanismen zu verstehen und Targets für Therapien zu finden. Die Koexpression von Genen, gemessen an der mRNA-Häufigkeit, kann Interaktionen zwischen Wirt und Pathogen aufzeigen. Die RNA-Sequenzierung von Wirt und Pathogen wird als "duale RNA-Sequenzierung" bezeichnet. Malaria ist eine der am besten untersuchten parasitären Krankheiten, so dass eine Fülle von RNA-seq-Datensätzen öffentlich zugänglich ist. Die Autoren führen entweder duale RNA-seq durch, um den Wirt und den Parasiten gleichzeitig zu untersuchen, oder sie erhalten kontaminierende Sequenzierungs-Reads aus dem Nicht-Zielorganismus. Ich habe eine Meta-Analyse durchgeführt, bei diese beiden Arten von RNA-seq-Studien verwendet wurden, um über korrelierte Genexpression auf Wirt-Parasit-Interaktionen zu schließen. Ich habe Studien mit Homo sapiens, Mus musculus und Macaca mulatta als Wirte und ihre Plasmodium-Parasiten einbezogen. Ich benutzte orthologe Einzelkopien von Genen, um ein Repertoire von Interaktionen bei Malaria und in diesen Modellsystemen zu erstellen. Ich verknüpfte die Daten von 63 Plasmodium-Phasen-spezifischen Studien und reduzierte die Zahl der Interaktionen von potenziell 56 Millionen auf eine kleinere, relevantere Menge. Die Zentralität in den Netzwerken der Blutphasen konnte die Essentialität der Plasmodium-Gene erklären. Das aus den verketteten Daten sagte die Genessenzialität besser vor als die einzelnen Studien - ein Vorteil der Meta-Analyse. Neutrophile und Monozyten Immunmarkergene waren überrepräsentiert, was auf eine Fülle von phagozytären und respiratorischen Reaktionen hindeutet. Die Analyse der Leberphase ergab Wirts- und Parasitenprozesse in frühen und späten Entwicklungsphasen. Ich fand bekannte Wirt-Parasit-Interaktionen, die für beide Phasen gleich sind, sowie bisher unbekannte Interaktionen. Dieses Prinzip lässt sich auch auf andere Krankheiten anwenden, um Mechanismen und therapeutische Ziele zu verstehen.Cross-species interactions help us understand disease mechanisms and find targets for therapy. Gene co-expression, measured by mRNA abundance, can identify host-pathogen interactions. The RNA-sequencing of host and pathogen is termed “dual RNA-sequencing”. Malaria is one of the most studied eukayotic parasitic diseases, making an abundance of RNA-seq data sets publicly available. Authors either perform dual RNA-seq to study the host and parasite simultaneously or acquire contaminant sequencing reads from the non-target organism. I performed a meta-analysis using these two kinds of RNA-seq studies to infer host-parasite interactions using correlated gene expression. I included studies of Homo sapiens, Mus musculus and Macaca mulatta as hosts and their corresponding Plasmodium parasites. I used single-copy orthologous genes to generate a repertoire of interactions in human malaria and in these model systems. I found 63 malaria RNA-seq studies. I concatenated sequencing runs from Plasmodium stage-specific studies and reduced the number of interactions from a potential 56 million to a smaller, more relevant set. Centrality in the blood stage networks was able to explain Plasmodium gene essentiality. The network from the concatenated data predicted gene essentiality better than the individual studies, indicating a benefit of the meta-analysis. Immune marker genes for neutrophils and monocytes were over-represented, suggesting an abundance of phagocytic and respiratory burst-related responses. The liver stage analysis revealed linked host and parasite processes at early stages until late developmental stages. I found linked host and parasite processes that are common to the two stages, e.g. parasite cell gliding and invasion and host response to hypoxia and immune response. I showed that existing data can be explored for new information. This principle can be applied to other diseases to understand mechanisms and therapeutic targets

Uncovering interactions between exported Plasmodium falciparum and human erythrocyte cytoskeleton proteins in the process of host cell remodeling

The protozoan parasite Plasmodium falciparum causes the most severe form of human malaria, an infectious tropical disease of global public health importance. Despite efforts and means to prevent or treat this disease, there are still over 200 million cases and almost half a million deaths annually attributed to P. falciparum. Transmitted to the human host by female Anopheles mosquitos serving as vector, the parasite eventually invades erythrocytes and starts asexual replication. This stage causes the clinical symptoms of malaria. The red blood cell is an interesting choice of a host cell for the intracellular parasite P. falciparum as it lacks a nucleus, protein transport machinery, and its nutrient channels are inactive. To survive within this host environment, the parasite therefore has to remodel its host cell. The extensive host cell remodelling of human erythrocytes during the course of P. falciparum infection is facilitated by a large number of proteins which the parasite exports into its host cell cytoplasm. The function of the majority of these proteins remains elusive. Existing data suggests that some of these exported parasite proteins target the host cytoskeleton and modulate its properties, as apparent in changed mechanical properties of the host cell. The aim of this project was to identify interactions between host cytoskeleton and exported parasite proteins and to create a protein interaction network of the remodeled cytoskeleton. Identifying the key players and essential interactions in the process of host cell remodelling will lead to the identification of new targets in the fight against the malaria parasite. To this end, a number of exported proteins belonging to the PHIST family were selected. All selected PHIST proteins were exported into the host cell with most of them localizing in proximity to the erythrocyte cytoskeleton or membrane. The promiscuous biotin ligase BirA* (BioID) was fused to these proteins and upon addition of biotin proteins in the proximity were labelled with biotin. This allowed the pull-down using streptavidin-beads and identification of potential interaction partners of these transgenic, exported proteins by mass spectrometry. Based on the results from this study and additional data from previous projects, I generated a network of potential protein-protein interactions at the erythrocyte cytoskeleton. A standard approach to verify potential protein interactions is to perform reverse protein pull-downs. Because erythrocytes lack a nucleus, the classical transgenic approach to add molecular tags to erythrocyte proteins or to modify them in any way is not possible. To circumvent this holdback and to facilitate immunoprecipitations with erythrocyte proteins as bait, I generated parasite lines which expressed and exported different tagged human cytoskeleton proteins. These transgenic human proteins were designed to be exported and to be soluble within the cytosol of the infected erythrocyte. It was expected that these proteins would bind to their putative endogenous parasite binding partners while these are transported to their final destination within the host cell. These transgenic human proteins can then be used for immunoprecipitations to identify these binding partners. I tested several export sequences and showed that each of them resulted in efficient export of the intracellular loop of band 3 (residues 1-379) and the full-length band 4.1. In both of these cell lines, the majority of the protein was soluble in the host cytosol. Due to time constraints, these cell lines could not be further analyzed in detail. While little is known about the function and role of exported proteins in host cell remodeling during asexual developmental stages, even less is known about these proteins and their functions during gametocyte development of P. falciparum. Until recently, it was difficult to obtain high numbers of gametocytes, making it difficult to study host cell remodeling in these stages. The availability of a transgenic cell line from the Voss lab at Swiss TPH, in which high sexual conversion rates can be induced, provides a great opportunity to study these interactions in gametocytes. Taking advantage of this cell line we characterized GEXP02, a member of the PHIST protein family which is expressed and exported in gametocytes. We confirmed the expression pattern and localized GEXP02 at the periphery of the gametocyte-infected erythrocyte. By immuno-precipitation and mass spectrometry we could identify cytoskeleton proteins as well as other exported proteins as potential interaction partners. Based on co-labelling of GEXP02 with PFI1780w and PF3D7_0424600, two other PHIST proteins, we could confirm these as likely interaction partners. In GEXP02 knock-out parasites, no obvious detrimental effect or phenotype could be observed in asexual parasites or during gametocyte development nor throughout the mosquito stages or in liver hepatocyte infectivity. Although no function could be assigned to this protein, our study is one of the first to characterize in great detail an exported protein in gametocytes and shows that the erythrocyte cytoskeleton is targeted by exported parasite proteins also during gametocyte development. Furthermore, within the context of this present study, I conducted two extensive literature reviews. In one review I collected information on the functionally elusive PHIST family in the genus Plasmodium. The review on the PHIST protein family presents an in-depth overview on this protein family. It acts as a reference work for quick, but detailed information on these proteins that are thought to be involved in cytoskeleton remodelling. The other review concerned protein-protein interactions involved in host cytoskeleton remodeling of P. falciparum. By combining pieces of existing information, new insights were gained in this review. I could show that each stage of the intraerythrocytic life cycle presents different challenges to the intracellular survival of the parasite. Consequently, P. falciparum remodels its host cell differently in the various stages to meet the specific needs. In summary, this thesis provides new insight into host cell remodeling by the malaria parasite, shows the importance of exported proteins in this process, and offers a new tool in the study of interactions between erythrocyte cytoskeleton and exported parasite proteins

A Systems Biology Approach to Investigating Host-Pathogen Interactions in Infection with Burkholderia pseudomallei

This thesis applies systems approaches in order better to understand host-pathogen interactions in infectious diseases; it focuses on the intracellular bacterium Burkholderia pseudomallei, the causative agent of the human disease melioidosis. Little is known about the epigenetic changes in host cells during infection. This study assesses genome-wide patterns of the epigenetic marker DNA methylation in host cells following infection with B. pseudomallei. The studies of this thesis concern the infection of human macrophage-like U937 cells with B. pseudomallei and the DNA methylation levels were measured during the early stages of infection. Analyses reveal significant changes in infected cells (compared to uninfected controls) at multiple locations in the host DNA. Most of the methylation changes in infected cells are losses rather than gains in methylation. Five different differential methylation patterns (constant, early, late, transient, and oscillatory) are identified. Differentially methylated sites mapped to genes that may affect virulence, e.g. genes involved in actin regulation, immune response, inflammatory response, and nitric oxide generation. The thesis also measures whole blood DNA methylation profiles of patients diagnosed with melioidosis in order to test the potential role of host DNA methylation in melioidosis. The results demonstrate that patients with melioidosis are separated from healthy subjects by their distinct methylation profiles. The differentially methylated regions reported here can potentially be used as biomarkers for classification and prognostication of infectious diseases. In addition to exploring the changes to the host, a comprehensive understanding of the pathogen interference and the search for countermeasures requires a framework that assesses how the host changes the pathogen metabolically. In this thesis, to understand the role of trehalose pathway in virulence, computational models were constructed by integrating kinetic information, genomics data and literature surveys. Existing kinetic models of the trehalose pathway were implemented and extended allowing for the in silico investigation of the trehalose mutant. Further, metabolic networks of B. pseudomallei were analysed at the genome scale to identify molecular links between trehalose and metabolic pathways such as glycolysis. The genome- scale reconstruction of the B. pseudomallei metabolic network was used to simulate growth under different conditions and predict the effects of gene knockouts. This thesis not only expands the existing knowledge about B. pseudomallei infection, the novel approaches employed here will stimulate a wider understanding of the applications of systems biology to host-pathogen research and defence needs