A comprehensive Plasmodium falciparum protein interaction map reveals a distinct architecture of a core interactome

Network-driven analysis of human-Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets

BACKGROUND

The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery.

METHODS

This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein-protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis.

RESULTS

This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host-pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways subverted by P. falciparum to increase its within-host survival.

CONCLUSIONS

Host-pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies.

Reconstruction and Application of Protein-Protein Interaction Network

The protein-protein interaction network (PIN) is a useful tool for systematic investigation of the complex biological activities in the cell. With the increasing interests on the proteome-wide interaction networks, PINs have been reconstructed for many species, including virus, bacteria, plants, animals, and humans. With the development of biological techniques, the reconstruction methods of PIN are further improved. PIN has gradually penetrated many fields in biological research. In this work we systematically reviewed the development of PIN in the past fifteen years, with respect to its reconstruction and application of function annotation, subsystem investigation, evolution analysis, hub protein analysis, and regulation mechanism analysis. Due to the significant role of PIN in the in-depth exploration of biological process mechanisms, PIN will be preferred by more and more researchers for the systematic study of the protein systems in various kinds of organisms.

A bioinformatic survey of RNA-binding proteins in Plasmodium

Background

The malaria parasites in the genus Plasmodium have a very complicated life cycle involving an invertebrate vector and a vertebrate host. RNA-binding proteins (RBPs) are critical factors involved in every aspect of the development of these parasites. However, very few RBPs have been functionally characterized to date in the human parasite Plasmodium falciparum.

Methods

Using different bioinformatic methods and tools we searched P. falciparum genome to list and annotate RBPs. A representative 3D models for each of the RBD domain identified in P. falciparum was created using I-TESSAR and SWISS-MODEL. Microarray and RNAseq data analysis pertaining PfRBPs was performed using MeV software. Finally, Cytoscape was used to create protein-protein interaction network for CITH-Dozi and Caf1-CCR4-Not complexes.

Results

We report the identification of 189 putative RBP genes belonging to 13 different families in Plasmodium, which comprise 3.5 % of all annotated genes. Almost 90 % (169/189) of these genes belong to six prominent RBP classes, namely RNA recognition motifs, DEAD/H-box RNA helicases, K homology, Zinc finger, Puf and Alba gene families. Interestingly, almost all of the identified RNA-binding helicases and KH genes have cognate homologs in model species, suggesting their evolutionary conservation. Exploration of the existing P. falciparum blood-stage transcriptomes revealed that most RBPs have peak mRNA expression levels early during the intraerythrocytic development cycle, which taper off in later stages. Nearly 27 % of RBPs have elevated expression in gametocytes, while 47 and 24 % have elevated mRNA expression in ookinete and asexual stages. Comparative interactome analyses using human and Plasmodium protein-protein interaction datasets suggest extensive conservation of the PfCITH/PfDOZI and PfCaf1-CCR4-NOT complexes.

Conclusions

The Plasmodium parasites possess a large number of putative RBPs belonging to most of RBP families identified so far, suggesting the presence of extensive post-transcriptional regulation in these parasites. Taken together, in silico identification of these putative RBPs provides a foundation for future functional studies aimed at defining a unique network of post-transcriptional regulation in P. falciparum.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2092-1) contains supplementary material, which is available to authorized users.

Computational analysis of protein interaction networks for infectious diseases

Infectious diseases caused by pathogens, including viruses, bacteria and parasites, pose a serious threat to human health worldwide. Frequent changes in the pattern of infection mechanisms and the emergence of multidrug-resistant strains among pathogens have weakened the current treatment regimen. This necessitates the development of new therapeutic interventions to prevent and control such diseases. To cater to the need, analysis of protein interaction networks (PINs) has gained importance as one of the promising strategies. The present review aims to discuss various computational approaches to analyse the PINs in context to infectious diseases. Topology and modularity analysis of the network with their biological relevance, and the scenario till date about host–pathogen and intra-pathogenic protein interaction studies were delineated. This would provide useful insights to the research community, thereby enabling them to design novel biomedicine against such infectious diseases.

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.

Harnessing genomics and genome biology to understand malaria biology

Malaria is an important human disease and is the target of a global eradication campaign. New technological and informatics advancements in population genomics are being leveraged to identify genetic loci under selection in the malaria parasite and to find variants that are associated with key clinical phenotypes, such as drug resistance. This article provides a timely Review of how population-genetics-based strategies are being applied to Plasmodium falciparum both to identify genetic loci as key targets of interventions and to develop monitoring and surveillance tools that are crucial for the successful elimination and eradication of malaria.

Application of genomics to field investigations of malaria by the international centers of excellence for malaria research

Success of the global research agenda toward eradication of malaria will depend on development of new tools, including drugs, vaccines, insecticides and diagnostics. Genomic information, now available for the malaria parasites, their mosquito vectors, and human host, can be leveraged to both develop these tools and monitor their effectiveness. Although knowledge of genomic sequences for the malaria parasites, Plasmodium falciparum and Plasmodium vivax, have helped advance our understanding of malaria biology, simply knowing this sequence information has not yielded a plethora of new interventions to reduce the burden of malaria. Here we review and provide specific examples of how genomic information has increased our knowledge of parasite biology, focusing on P. falciparum malaria. We then discuss how population genetics can be applied toward the epidemiological and transmission-related goals outlined by the International Centers of Excellence for Malaria Research groups recently established by the National Institutes of Health. Finally, we propose genomics is a research area that can promote coordination and collaboration between various ICEMR groups, and that working together as a community can significantly advance the value of this information toward reduction of the global malaria burden.

Defining the protein interaction network of human malaria parasite Plasmodium falciparum

Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225 million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network.

A genetic screen for attenuated growth identifies genes crucial for intraerythrocytic development of Plasmodium falciparum

A majority of the Plasmodium falciparum genome codes for genes with unknown functions, which presents a major challenge to understanding the parasite's biology. Large-scale functional analysis of the parasite genome is essential to pave the way for novel therapeutic intervention strategies against the disease and yet difficulties in genetic manipulation of this deadly human malaria parasite have been a major hindrance for functional analysis of its genome. Here, we used a forward functional genomic approach to study P. falciparum and identify genes important for optimal parasite development in the disease-causing, intraerythrocytic stages. We analyzed 123 piggyBac insertion mutants of P. falciparum for proliferation efficiency in the intraerythrocytic stages, in vitro. Almost 50% of the analyzed mutants showed significant reduction in proliferation efficiency, with 20% displaying severe defects. Functional categorization of genes in the severely attenuated mutants revealed significant enrichment for RNA binding proteins, suggesting the significance of post-transcriptional gene regulation in parasite development and emphasizing its importance as an antimalarial target. This study demonstrates the feasibility of much needed forward genetics approaches for P. falciparum to better characterize its genome and accelerate drug and vaccine development.

Caenorhabditis elegans proteomics comes of age

Caenorhabditis elegans, a free-living soil nematode, is an ideal model system for studying various physiological problems relevant to human diseases. Despite its short history, C. elegans proteomics is receiving great attention in multiple research areas, including the genome annotation, major signaling pathways (e.g. TGF-beta and insulin/IGF-1 signaling), verification of RNA interference-mediated gene targeting, aging, disease models, as well as peptidomic analysis of neuropeptides involved in behavior and locomotion. For example, a proteome-wide profiling of developmental and aging processes not only provides basic information necessary for constructing a molecular network, but also identifies important target proteins for chemical modulation. Although C. elegans has a simple body system and neural circuitry, it exhibits very complicated functions ranging from feeding to locomotion. Investigation of these functions through proteomic analysis of various C. elegans neuropeptides, some of which are not found in the predicted genome sequence, would open a new field of peptidomics. Given the importance of nematode infection in plants and mammalian pathogenesis pathways, proteomics could be applied to investigate the molecular mechanisms underlying plant- or animal-nematode pathogenesis and to identify novel antinematodal drugs. Thus, C. elegans proteomics, in combination of other molecular, biological and genetic techniques, would provide a versatile new tool box for the systematic analysis of gene functions throughout the entire life cycle of this nematode.