A bioinformatic survey of RNA-binding proteins in Plasmodium
© Reddy et al. 2015
Received: 18 April 2015
Accepted: 15 October 2015
Published: 2 November 2015
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.
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.
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.
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.
Malaria continues to be a major public health and socio-economic problem in developing countries, and in 2013, it still caused 584,000 deaths (http://www.who.int/malaria/publications/world_malaria_report_2014/en/). Multifaceted control efforts are directed towards reducing malaria transmission, including vector control, early diagnosis, and effective treatment. Recently, the introduction of artemisinin combination therapies (ACTs) to deal with continually evolving multidrug resistance is a cornerstone of malaria chemotherapy, but this too is faltering and is spreading at a faster pace than anticipated . As parasites continue to develop resistance to existing antimalarial drugs, continued research on developing new antimalarials remains a high priority . One such approach has used systems biology methods in this postgenomic era of Plasmodium to identify multiple novel pathways in the parasite as potential drug targets [3–5]. Information gleaned from comparative genomic analysis and functional studies has contributed to improving our understanding of the parasite’s biology and our ability to design new control measures, and understanding basic regulatory mechanisms that parasite has evolved may help to guide future decisions in selecting targets.
The Plasmodium life cycle includes multiple stages with drastically different morphologies in a mosquito vector and a vertebrate host. This sophisticated developmental program requires regulation of gene expression and protein synthesis [6, 7]. Even with the discovery of the AP2-domain specific transcriptional factors , the parasite genome is still relatively deficient in identifiable transcriptional regulators , implying that post-transcriptional regulation (PTR) is an important means of regulation of gene expression. Furthermore, comparative studies examining the parasite’s transcriptomes and proteomes revealed significant lags in protein abundance relative to mRNA abundance . During intraerythrocytic development, the half-life of mRNAs is substantially extended at the schizont stage when compared with that at the ring stage . Translational regulation plays particularly critical roles during parasite transmission, when the parasites must remain relatively quiescent for an extended period of time before transmission occurs . In the specific stages (gametocytes and sporozoites) that are transmitted, many mRNAs that are needed for subsequent development are kept in a translationally repressed state. Premature expression of these mRNAs leads to considerable defects in development [12, 13]. Altogether, these studies underscore the importance of post-transcriptional control in the development of the malaria parasite.
From transcription to degradation, every step of mRNA metabolism is subject to extensive regulation. Through mRNA maturation, export, subcellular localization, stability, and degradation, RNAs are accompanied by RNA-binding proteins (RBPs) and are thus found as messenger ribonucleoproteins (mRNPs). RBPs also play crucial roles in processing of stable RNAs such as rRNA, tRNA, snRNA, and snoRNA . The significance of RBPs in translational regulation is underscored by their abundance in diverse eukaryotes. For example, the yeast Saccharomyces cerevisiae encodes ~600 RBPs , whereas in humans the number of RBPs is considerably larger with at least 1000 genes containing the RNA recognition motif (RRM) alone . To date, more than a dozen RNA-binding domains (RBDs) have been identified and the best-characterized domains include RRMs, RNA helicases, zinc-finger domains (C3H1 and C2H2), K Homology (KH), Pumilio and Fem-3 binding factor (Puf), and Acetylation Lowers Binding Affinity (Alba) families. While most of our understanding about RBPs and their functions comes from studies of model organisms, their importance in the development of Plasmodium has recently been more appreciated [7, 11, 12, 17–20]. Given the potential roles of RBPs in virtually every aspect of RNA metabolism and in every part of the life cycle of the malaria parasites, we performed a comprehensive in silico analysis of RBPs in the malaria parasite P. falciparum. Many recent studies have also found that some RNA-interacting proteins may not possess commonly known RBDs , however, in this study we have used commonly known RBDs for the searches to ensure only more robust predictions are made. Using a set of bioinformatic tools, we identified 189 putative RBPs in the malaria parasite genome that contain well-characterized RBDs and provide functional annotation based on homology, domain organization, and expression patterns.
Results and discussion
Using a combination of search strategies, we identified a total of 189 putative RBPs in the P. falciparum genome including 72 with the RRM, 48 putative RNA helicases, 11 with the KH domain, 2 with the Puf domain, 6 with the Alba domain, 31 with zinc fingers (ZnFs), and 19 other minor families of RBPs (Additional file 1). Most of these putative RBPs in Plasmodium lack definitive functional annotations. For functional predictions, each of these RBPs was BLAST searched against the model species by considering the total query sequence coverage against the template and the degree of domain-architecture conservation. This analysis allowed functional predictions for 140 putative RBPs (Additional file 1). While 179 of genes are conserved both in Plasmodium vivax and Plasmodium yoelii with clearly identifiable orthologs, 9 of the genes are lost in either or both P. vivax or P. yoelii (Additional file 1).
RNA-binding domains and RBPs in Plasmodium
RNA-Recognition Motif (RRM)
List of different Pfam- and other profile families used to search RBPs from P. falciparum along with corresponding number of genes found in P. falciparum
RNA-binding domain (number of families)
Pfam id description
Number of corresponding genes in P. falciparum
RRM (8 families)
Nup53/35/40-type RNA recognition motif
Helicase conserved C-terminal domain
Mitochondrial degradasome RNA helicase subunit C terminal
KH_1 (type I)
KH_2 (type II)
Eukaryotic type KH_domain I
Prokaryotic type KH_domain II
Pumilio Homology Domain
C2H2 zinc finger
ZnF_C2H2/ Zinc finger, RING-type
C2H2 type domain
Comparative abundance of RRMs by Pfam class (including isoforms) across evolutionarily diverse species
The frequencies of occurrence of RRM in single, modular and multi-domain organization in P. falciparum
Single RRM (28 genes)
PF3D7_1367100, PF3D7_0923900, PF3D7_0503300, PF3D7_1002400, PF3D7_1224900, PF3D7_0515000, PF3D7_0319500, PF3D7_0415500, PF3D7_0615700
PF3D7_0815600, PF3D7_0933000, PF3D7_1024200, PF3D7_1207500, PF3D7_1320900, PF3D7_1406000, PF3D7_1131000, PF3D7_1360100, PF3D7_0812500, PF3D7_0623400, PF3D7_1310700, PF3D7_1317300, PF3D7_1110400, PF3D7_1330800, PF3D7_0416000, PF3D7_0205700, PF3D7_1445600, PF3D7_1139100, PF3D7_1126800
Two RRM (21)
PF3D7_0414500, PF3D7_0920900, PF3D7_0935000, PF3D7_1306900, PF3D7_0629400, PF3D7_0517300, PF3D7_1004400, PF3D7_1119800, PF3D7_1006800, PF3D7_1022400, PF3D7_0916700, PF3D7_1420000, PF3D7_1020000, PF3D7_0728900, PF3D7_0606100, PF3D7_1107100, PF3D7_1405900, PF3D7_0723900, PF3D7_0929200, PF3D7_1022000, PF3D7_1326300
Three RRM (4)
PF3D7_1468800, PF3D7_1360900, PF3D7_1321700, PF3D7_1405900
Four RRM (2)
Five RRM (1)
RRM + ZnF (2)
Znf + RRM + Znf (3)
PF3D7_1119300, PF3D7_0603100, PF3D7_1353400
RRM + SWAP + RPR (1)
RRM + WW + RRM (2)
Two RRM + WW + RRM (2)
Four RRM+ Poly(A) (1)
RRM + G patch (1)
RRM + RING finger (1)
Prp8 Multidomain (single RRM) (1)
RRM + WD40 (1)
RRM + PWI (1)
The average length of the RRM in P. falciparum is 75 aa (range 65–188 aa) (Additional file 2), which is similar to what has been reported in other species. Comparison of the different RRM families in Plasmodium found that the RRM_4 member Prp8 splicing factor is evolutionarily divergent from the other four families (Fig. 1a). Divergence of RRM_2 and RRM_4 family members from the other three major families is particularly noticeable in the RNA-binding motifs RNP1 and 2 (Fig. 1a). Phylogenetic analysis using only RRM-domain sequences of representatives from RRM_1-6 families failed to resolve evolutionary relationships as expected. For example, all RRM_1, 5 or 6 did not form monophyletic clades (Fig. 1b). Nonetheless, modeling of representative members of the five RRM families showed that the predicted structures conform to the typical organization of RRM and contains four anti-parallel beta strands and two alpha helices arranged as β1α1β2β3α2β4 (canonical RRM domain and RNP motifs are illustrated in Additional files 2 and 3) while showing sufficient diversity in overall 3D structures (Fig. 1c). For example, the RRM_4 family’s (Prp8) predicted 3D structure is highly diversified from the rest of the families.
Phylogeny-based orthology prediction identified one-to-one orthologs from P. vivax and P. yoelii except in two instances (PF3D7_1119800, PF3D7_1131000) where they were lost in P. yoelii. Both genes possess an SR domain and are predicted to participate in pre-mRNA splicing and export (Additional file 1). No recent duplications and species-specific expansion of RRM family genes were identified in a particular Plasmodium species (deficiency in paralogs), suggesting evolutionary constraints on independent evolution of the RRM gene family.
Phylogenetic analysis also identified four CUG-BP Elav-like (CELF) proteins and four potential poly(A)-binding proteins (PABPs) in Plasmodium. All CELF proteins have a similar multidomain organization with RRM domains flanking a variable WW domain, and they might have resulted from two gene duplication events (Table 3). PfCELF1 has recently been found to be a nuclear protein and participate in splicing . Comparative bioinformatic analysis with human, Drosophila and Arabidopsis homologs classified the four Plasmodium PABPs into one nuclear and three cytoplasmic PABPs (Additional file 4). One cytoplasmic PABP (PfPABP1c) is evolutionarily conserved while the other three might have specifically acquired by Plasmodium species.
Because most of the Plasmodium RRM genes have not been characterized, we performed a variety of predictions of their functions. Thirty P. falciparum RRM proteins are predicted to participate in pre-mRNA splicing (13 genes), alternative splicing (10), transport (1), ribosome biogenesis (1), RNA degradation (1), translation (2), and post-transcriptional regulation (2). There are 25 other genes with different cellular functions while 17 genes are Plasmodium-specific with unknown functions (17) (Additional file 1). Functional analysis is needed to verify these predictions.
Helicases are ubiquitous in nature and are considered to have evolved from near the very root of the evolutionary tree. Typically, helicases function in the separation of double-stranded RNA, DNA, and RNA/DNA structures in an energy-dependent manner . Based on sequence similarities and domain conservation, helicases are classified into five superfamilies; superfamily II (SFII) is the most studied and most widely distributed in eukaryotes. Major components of SFII are DExD/H (Asp-Glu-x-Asp/His) helicase family members that primarily function in RNA metabolism including chaperoning snRNAs that participate in pre-mRNA splicing .
A comparative table of helicases from different Phyla
All hits including isoforms
Cryptosporidium parvum Iowa
The frequencies of occurrence of RNA helicases in single, modular and multi-domain organization in P. falciparum
Name of the domain architecture
PF3D7_0521700, PF3D7_0218400, PF3D7_1307300, PF3D7_1332700, PF3D7_0827000, PF3D7_1251500, PF3D7_0422700, PF3D7_1021500, PF3D7_1445900, PF3D7_0504200, PF3D7_0903400, PF3D7_1031500, PF3D7_1241800, PF3D7_0320800, PF3D7_0807100, PF3D7_0810600, PF3D7_1459000, PF3D7_1468700, PF3D7_0321600, PF3D7_0209800, PF3D7_0508700, PF3D7_0518500, PF3D7_0703500, PF3D7_0405000, PF3D7_1202000, PF3D7_0411400, PF3D7_0103600, PF3D7_1445200
HelicaseC + Suv3
Helicase + DUF4217
PF3D7_0721300, PF3D7_1419100, PF3D7_1418900, PF3D7_0630900
Helicase + ZnF
PF3D7_0527900, PF3D7_0909900, PF3D7_1313400
Helicase + UPF_Zn
Helicase + Sec63
Helicase + HA2 + S1
Helicase + HA2 + OB fold
PF3D7_1364300, PF3D7_1231600, PF3D7_0917600, PF3D7_0821300
Helicase + ZnF + DSHCT
Helicase + rRNA proc-arch + DSHCT
Helicase + HA2
With regard to the functions of RNA helicases, generally DEAH helicases are involved in pre-mRNA processing, while DEAD helicases participate in ribosome biogenesis . In P. falciparum, PF3D7_1364300, PF3D7_1231600, PF3D7_0917600 and PF3D7_1030100 all have a conserved DEAH domain and are classified as Prp (pre-mRNA processing) proteins. Similarly, almost all of the proteins classified under ribosome biogenesis (Fig. 2 and Additional file 6) have a conserved DEAD domain, indicative of evolutionary conservation of the protein synthesis apparatus. However, numerous exceptions to these rules have been observed, so these classifications should be experimentally confirmed and manually curated.
We performed a gene enrichment analysis using information on assigned biological processes as well as molecular functional information available from UniProt (http://www.uniprot.org/). From this analysis, 36 and 10 genes were classified as RNA-binding and mRNA processing, respectively, leaving the rest of the members unassigned. However, we could manually assign functions to 70 % of the RNA helicases from P. falciparum to ribosome biogenesis and related (17 genes), pre-mRNA processing (9), RNA degradation (3), mRNA turnover (1), genome repair and maintenance (2), and post-transcriptional regulation (2). Further corroborating the fact that helicases mainly take part in ribosome biogenesis, 30 of the 39 DExD/H helicases have a DExD domain (ribosome biogenesis), while 9 have a DExH domain (Additional file 5). Whereas 10 genes have homologs in model species without known functions, two genes (PF3D7_0103600 and PF3D7_1313400) appeared to be specific for the Plasmodium group. Though helicases are potential targets for drug design , very few of them have been characterized in P. falciparum [32, 33]. One such helicase (DOZI, a homolog of human DDX6 and yeast Dhh1) is essential to the development of the zygote in infected mosquitoes, and traffics a substantial portion of the mRNA pool to storage granules [12, 34, 35]. It would be interesting to see if Plasmodium specific helicases perform unique functions.
The KH domain was first identified in the human heterogeneous nuclear ribonucleoprotein K (hnRNP) or pre-mRNA-binding protein K almost two decades ago . The functional domain is about 70 aa in size, which primarily binds RNA [36–38]. KH domain proteins have a diverse regulatory portfolio, which includes transcription and translational regulation, RNA metabolism, and chromatin remodeling [37, 38].
Functional annotation through BLASTp search showed seven of the eleven KH domain genes have well-defined homologs in model species, allowing better prediction of their potential roles. Two KH domain genes are predicted to function in mRNA processing, three in ribosome biogenesis, one each in poly(A)- (PF3D7_1415300) and poly(rC)-binding (PF3D7_0605100), and in splicing (Fig. 3b). Interestingly, a recent study of a KH domain gene PF3D7_1011800 indicated it as a novel specific transcription factor . This may be possible since some of the KH domains are found to interact with both RNA and ssDNA . Similar to other RBPs, all the KH domain genes have orthologs in P. vivax and P. yoelii. We failed to detect homologs for four KH domain genes except in Plasmodium species, implying genus-specific evolution of KH proteins in malaria parasites.
Puf is named after the two founding members from P umilio in Drosophila protein and FBF (fem-3 binding factor) in Caenorhabditis elegans. They represent an evolutionarily conserved class of translational repressors from a wide range of eukaryotic species, and are known to have diverse functions such as sexual differentiation and development, stem cell maintenance and neurogenesis [42, 43]. The Puf domain typically consists of eight homologous repeat units, each consisting of about 36 amino acids. Puf domains form a modular structure that can interact with eight ribonucleotides, with each repeat recognizing a single base. Two Puf proteins, Puf1 and Puf2 have been identified in all sequenced Plasmodium species (Puf domain-only alignment of PfPuf1, 2 is shown in Additional file 7) . Homology modeling of the two Puf domains in P. falciparum showed a modular structure consistent with the typical Puf domain structure (Additional file 7). Puf1 and Puf2 have been characterized to regulate sexual development and transition from the mosquito vector to vertebrate hosts [11, 44]. Genetic deletion of Puf2 in P. berghei and P. yoelii leads to severe defects in sporozoite morphology and transmissibility, misregulation of mRNA transcript abundances, and in some cases affects male/female gametocyte ratios [12, 19, 45]. Over expression and knockdown of PfPuf2 expression in P. falciparum showed repression and elevation of gametocytogenesis, respectively . A study by Miao et al. show that PfPuf2 regulates translationally repressed transcripts by interacting with Puf-binding elements (PBEs) located in both 3′- and 5′- untranslated regions . For the first time, that study underscores the importance of 5′ UTRs in post-transcriptional regulation by PUF proteins, which now prompts investigations into additional regulation by PfPufs.
The Alba domain has been implicated in transcriptional and translational regulation through its ability to bind both DNA and RNA, and due to its association with Sir2 [49, 50]. Functional annotation of PfAlbas is not possible based on homology searches of genomes of model organisms. Whereas homologs of Alba1-3 were found in Arabidopsis with unknown functions, we did not identify homologs of Alba4-6 in model organisms even after relaxing the search parameters, suggesting a lineage-specific evolution. Similar to the canonical Alba proteins, PfAlba1-4 were reported to bind both DNA and RNA [20, 48]. Several Alba proteins from Apicomplexa (including Plasmodium) were reported to be involved in diverse cellular functions such as binding and regulating their own transcripts, regulating transcription through condensation of chromatin, and post-transcriptional regulation of mRNAs involved in development [49–51]. PfAlba1 is essential for asexual erythrocytic development and binds to ~30 % of the trophozoite transcriptome, regulating the timing of the translation . Yeast two-hybrid data revealed interactions between PfAlba3 and 4. Similar observations were made for Toxoplasma TgAlba2 and TgAlba1, where the former depends on the latter for expression . In P. berghei, PbAlba1-4 were associated with the DOZI and CITH translational repression complexes, confirming their roles in Plasmodium RNA biology .
Zinc finger domain
Zinc Finger (ZnF) domains are small protein domains present in all forms of life and are one of the most studied domains in transcription factors. The functional versatility of the ZnF-containing proteins arises from the modular structure of ZnFs, which can be found in multiple copies and in different forms. At least 46 different types of ZnFs have been identified in mammalian transcriptomes . ZnFs are classified into various groups based on structural similarities, including the number of zinc ligands they bind, and the arrangement and the number of cysteine (C) and histidine (H) residues surrounding one or more zinc atoms . ZnFs can bind DNA, RNA, or protein, and the distance between two ZnF domains on a protein critically influences these interactions. The most characterized forms of RNA-binding ZnF forms are C2H2 and C3H1, which fold to create RNA-binding surfaces composed of α-helices and aromatic side chains .
Using various Pfam and other profile families as seed sequences (Table 1), we retrieved a total of 31 putative RNA-binding ZnF proteins. Of which, 20 and 11 genes belong to the C3H1 and C2H2 forms, respectively. Both C3H1 and C2H2 ZnFs coexist with other protein domains such as the RRM, RING, YTH, and PWI domains (C3H1) and the CactinC and RANB2 domains (C2H2) (Additional file 1). Based on homology searches, functional annotation was possible for eight of the eleven C2H2 genes; five genes may be involved in splicing and two in ribosome biogenesis. For 18 of the 20 C3H1 genes, specific functions could not be ascertained due to lack of orthologs in model species (Additional file 1).
Other potential RBDs
In addition to the major RBDs described above, we identified several minor RBP families including proteins containing the pseudouridine synthase and archaeosine transglycosylase (PUA) domain, YT521-B homology, S-1 motif, SWAP (Suppressor-of-White-APricot domains), PWI, and G-patch motif. All these minor domains have predicted orthologs in P. vivax and P. yoelii genomes.
The PUA is a compact 67–94 aa motif frequently found in RNA modification enzymes and nucleoproteins . The motif is also commonly found in other proteins that have functional roles in translation and ribosome biogenesis . Our analysis revealed five PUA containing genes (Additional file 1). Functional annotation of these genes indicates that they may have potential roles in tRNA and rRNA post-transcriptional modifications and maturation, RNA methylation, and translation initiation. In Plasmodium, the PUA domain is found to coexist with the S-adenosyl methionine domain (important for methylation functions) and the DKCLD domain (a TruB_N/PUA domain variant associated N-terminal domain of Dyskerin-like proteins).
The YTH (YT521-B homology-a part of PUA domain superfamily) constitutes a new class of RBP in eukaryotes , which was first identified and characterized in the YT521-B protein . The domain is typically 100–150 aa in length, and is rich in aromatic residues that are reminiscent of RRM and PUA domains . The domain is found to have functions in alternative splicing and the prevention of untimely meiosis in yeast through the degradation of meiosis-specific transcripts during vegetative growth . Two genes were identified in the P. falciparum genome (PF3D7_0309800 and PF3D7_1419900) that encode this domain and other putative RBDs such as the C3H1 ZnF (Additional file 1). In silico functional annotation suggests that the YTH domain may participate in modulating alternative splicing, mRNA cleavage and polyadenylation in P. falciparum.
The S1 motif was first identified in E. coli ribosomal S1 protein and exhibits an evolutionarily conserved nucleic acid binding OB (oligonucleotide/oligosaccharide binding) structural fold . The S1 motif in P. falciparum was found to co-exist with other RBDs such as KH and RNA helicase domains. These proteins may be involved in pre-mRNA processing, ribosome biogenesis and translation in Plasmodium (Additional file 1).
The SWAP domain was first identified in Drosophila splicing regulators. Pfam searches of the P. falciparum genome revealed the presence of two genes with the SWAP domains, namely PF3D71474500 (splicing factor 3A) and PF3D7_1402700 (pre-mRNA splicing factor). While PF3D7_1474500 has two SWAP domains, the PF3D7_1402700 has one SWAP domain with one RRM (Additional file 1).
The PWI domain is an another RNA-binding domain first reported in splicing factors [60, 61]. Of the three PWI-containing genes in P. falciparum, one (PF3D7_0610200) also has an N-terminal RRM domain. PWI genes may play roles in splicing and alternative splicing in Plasmodium (Additional file 1).
The glycine-rich nucleic acid binding domain called G-patch was first described by Aravind and Koonin . We identified three G-patch genes (PF3D7_1454000, PF3D7_1110300, and PF3D7_0531400) in P. falciparum genome. Only PF3D7_1454000 is associated with an RRM (Additional file 1).
Functional roles of Plasmodium RBPs
RBPs are at the center of RNA metabolism and involved in all aspects of RNA biology. Based mostly on homology with RBPs in model organisms with known functions, we manually annotated the predicted functions of some putative RBPs in Plasmodium and categorized them into various cellular processes.
RBPs in splicing
List of genes and their putative functions involved in splicing mechanism in P. falciparum
Pre-mRNA-splicing factor Cwc2
Splicing factor 3B subunit 6 (SF3B6)
Splicing factor 3B subunit 4 (SF3B4)
U2 snRNP associated small nuclear ribonucleoprotein B
U1 small nuclear ribonucleoprotein 70 kDa
U1 snRNP assocaited small nuclear ribonucleoprotein A
U2 snRNP-associated SURP motif-containing protein
Splicing factor homolog
Splicing factor homolog
Splicing factor U2AF large subunit B
Splicing factor U2AF small subunit B
Splicing factor, CC1 like
Spliceosome RNA helicase DDX39B; alias UAP56
U1 small nuclear ribonucleoprotein C (SNRPC)
Supraspliceosme complex component -alternative splicing
Spliceosome RNA helicase DDX39B; alias UAP56
Pre-mRNA-processing ATP-dependent RNA helicase Prp5
ATP-dependent RNA helicase DDX23 (PRP28)
Mdlc (midlife crisis) or Cwc24p in yeast
Splicing factor 1 (SF1)
Splicing factor 3A subunit 1 (PRP-21)
Splicing factor 3a, subunit 3, 60 kDa (SF3A3)
Putative poly-adenylation factor
mdlc (midlife crisis) or Cwc24p in yeast
Pre-mRNA-splicing factor ATP-dependent RNA helicase PRP16
Pre-mRNA-splicing factor ATP-dependent RNA helicase PRP22
Pre-mRNA-splicing factor ATP-dependent RNA helicase PRP43
Polypyrimidine tract-binding protein 3
RNA binding protein Bruno, putative (HoBo) Bruno
CUG-BP Elav-like family member 3
CUGBP, Elav-like family member 2
Pre-mRNA-splicing factor SF2
Splicing factor 45
Splicing factor, arginine/serine-rich 1
Serine/arginine-rich splicing factor 4
Serine/arginine-rich splicing factor 1
Serine/arginine-rich SC35-like splicing factor SCL28
Transformer-2 protein homolog beta isoform 2 (TRA2B)
Nova2 or BTR1
Alternative splicing creates multiple transcripts from a single gene, thus contributing to the diversity of the cellular proteome without a need for genomic expansion. While 95 % of multi-exon genes have more than one transcript isoform in humans, alternative splicing also occurs in P. falciparum, albeit to a much lesser extent [64, 71–73]. RNA-seq analyses of the P. falciparum transcriptomes found evidence for alternative splicing in about 300 genes [64, 71]. Through bioinformatic analysis, we identified 13 genes in P. falciparum with predicted roles in alternative splicing (Table 6). Most of these genes are from the SR (7 genes) and the CELF (4 genes) families. SR family proteins have RRM domain(s) and arginine-serine repeats. Two SR genes in P. falciparum (PfSrrm1 and PfRSrrm3) were shown to bind to RNA [68, 79], and PfSrrm1 was predicted to regulate alternative splicing . PfSF2, a homolog of serine/arginine-rich splicing factor 1(AF1) or pre-mRNA-splicing factor SF2 (SF2) was predicted to function in alternative splicing in P. falciparum and affected parasite proliferation in erythrocytes . The CELF/Bruno-like family RBPs regulate pre-mRNA splicing/alternative splicing in the nucleus, as well as mRNA deadenylation and translation in the cytoplasm [75–77]. Of the four Plasmodium CELF family genes, PfCELF1 was characterized to function in pre-mRNA processing . The polypyrimidine tract binding proteins (PTBPs), a family of multiple RRM domain containing proteins, regulate alternative splicing by binding to the polypyrimidine regulatory tracts that exist in introns [78, 79]. While at least two PTBPs are found in the human genome, we only identified one PTBP-like protein, PfPTBP1, in the P. falciparum genome (Table 6).
RNA maturation, exon-exon junction complex formation and mRNA shuttling
RNA maturation in eukaryotes includes 5′ methyl capping and 3′ poly (A)-tailing of mRNAs. These processes are predicted to be conserved in malaria parasites. Among them, PF3D7_1419900 is a homolog of the 30 kDa subunit of human cleavage and polyadenylation specificity factor (CPSF), an RNA-binding endonuclease playing a role in 3′ processing of pre-mRNA . Following complete maturation, export of mRNAs to the cytoplasm is achieved by a special mRNP complex termed the exon-exon junction complex (EJC) [81, 82]. It is comprised of a mixture of mRNA export factors—Aly/REF, TAP, Upf3b, UAP56 , and nonsense mediated mRNA surveillance (NMD) components—Y14 and Magoh. Our analysis identified all of the known homologs of both EJC and NMD complexes; however, their predicted functions have yet to be confirmed in P. falciparum except for PfUAP56 which was shown to harbor RNA binding and helicase activities that depend upon glycine 181, isoleucine 182 and arginine 206 .
RBPs in ribosome biogenesis and translation initiation
A list of genes and their putative functions involved in ribosome biogenesis in P. falciparum
Named in P. falciparum
*18S rRNA processing, participates in cleavages at A2, and to a lesser extent, A0 and A1 sites
27S pre-ribosomal rRNA processing (60S ribosomal subunit biogenesis) 
*5.8S/25S pre-ribosomal rRNA processing (60S ribosomal subunit biogenesis)
18S rRNA processing
*27S pre-rRNA processing (60S ribosomal subunit biogenesis)
*60S ribosomal subunit assembly-27S pre-rRNA processing
DBP10 (DBP10) or DDX54 isoform 1
*5.8S/25S rRNA processing
*27S- > 25S rRNA conversion (60S ribosomal subunit biogenesis)
*18S rRNA processing, participates in cleavage at A0, A1 and A2 sites
*18S rRNA processing, participates in cleavage at A1 and A2 sites
*60S ribosome subunit assembly
*18S rRNA processing, participates in cleavage at A0, A1 and A2 sites
DDX17 isoform 1 (Dbp2p)
*60S ribosomal subunit biogenesis
SKIV2L2 or Mtr4p
*5.8S rRNA processing
Maturation of 40S and 60S ribosomal subunits
RNA processing and nucleolar localization
Release of base-paired U3 snoRNA within the pre-ribosomal complex 
It has functional redundancy with yeast proteins Reh1 in cytoplasmic 60S subunit maturation
Helps in shuttling pre-ribosomal 60S complex to cytoplasm; U1-like Zn-finger-containing protein
Splicing factor 3a
Splicing of rRNA genes
40S ribosomal protein S3-1
Multifaceted functional roles; involves in translation, binding to DNA, and regulating transcription of specific set of genes
Synthesis of 18S rRNA (SSU) processome component
Pno1p or Dim2p
Shuttling of Dim1 rRNA from cytoplasm to nucleolus
60S ribosome subunit biogenesis protein NIP7 homolog isoform 1; nucleolar pre-rRNA processing
Pseudouridine synthase NAP57 or H/ACA ribonucleoprotein complex subunit 4 (5e-178), H. sapiens
SUI1 family protein
Eukaryotic translation initiation factor SUI1 family protein isoform 1 (formerly named as ligetin)
May be initiation factor homolog
SAM dependent methyltrasferase
RNA-binding protein NOB1
Biogenesis of 40S rRNA through cleavage of D-site in 20S rRNA
RBPs in genome repair and maintenance
Genome repair and maintenance are crucial for the integrity of the genome. Based on a homology search, we identified two RBPs from the P. falciparum genome that have putative functions in genome maintenance. Human DDX1 is reported to be activated by phosphorylation in response to double-stranded breaks in DNA. DDX1 has RNase activity towards single-stranded RNA as well as ADP-dependent RNA-DNA- and RNA-RNA-unwinding activities [83, 84]. The putative DDX1 homolog from Plasmodium (PF3D7_0521700) is highly conserved with 29 % identity at 93 % total gene coverage. Another gene, PF3D7_0623700 has a C-terminal domain resembling the yeast Suv3p protein, which is associated with mitochondrial genome stability [85, 86].
RBPs in RNA granules, degradation and translational regulation
The inferred contents of exosomes, P -bodies, and stress granules in Plasmodium species. The composition of RNA granules in Plasmodium was inferred by conducting BLASTp queries using the amino acid sequences of components of exosomes, P bodies, and stress granules from model organisms (D. melanogaster, S. cerevisiae, C. elegans) against known and predicted Plasmodium amino acid sequences. Other Plasmodium proteins that traffic to granules, but that cannot be definitively placed in a currently annotated granule type, are listed separately. Gene identifiers for these proteins for three commonly studied malaria species (P. falciparum, P. vivax, P. yoelii) were obtained from PlasmoDB.org
P. falciparum Gene ID
P. vivax Gene ID
P. yoelii Gene ID
P. falciparum Gene ID
P. vivax Gene ID
P. yoelii Gene ID
P. falciparum Gene ID
P. vivax Gene ID
P. yoelii Gene ID
P. falciparum Gene ID
P. vivax Gene ID
P. yoelii Gene ID
RNA degradation is largely initiated through the removal of the poly(A)-tail by the deadenylation complex Caf1-CCR4-Not. In eukaryotes including Drosophila, Saccharomyces, and Homo sapiens, the core Caf1-CCR4-Not complex is conserved . The various subunits of the Caf1-CCR4-Not complex functionally contribute in different ways, including deadenylation of transcripts, RNA processing, nuclear export, translational repression and feeding into the DNA damage response [91, 93, 94]. Through a BLASTp search, we identified 9 potential members of the Plasmodium Caf1-CCR4-Not complex (Table 8). These predicted members include the scaffold protein Not1, the deadenylases Caf1 and a HCCR4-like protein, as well as CNOT4 and CNOT3, which are responsible for ubiquitination and chromatin modifications respectively. Only Caf1 has been genetically characterized in P. falciparum, and genetic disruption of PfCaf1 by the piggyBac transposon resulted in mistimed expression of transcripts, abnormal expression of merozoite invasion proteins and a slight growth defect in blood stage cultures . The Caf1-CCR4-Not complex is important for tasks ranging from deadenylation to ubiquitination, and may be differentially employed by Plasmodium to progress through its complex life cycle.
The eukaryotic exosome consists of multiple subunits and plays an essential role in RNA quality control, turnover and processing. The exosome complex has been shown to be important for 3′-to-5′ mRNA degradation. In Plasmodium we have found eight predicted subunits that align though BLASTP to common eukaryotic exosome components (Table 8). Rrp6 and Rrp44, which are the two active exoribonuclease components of the complex in archaeal and eukaryotic cells, are also present. An RBP (PF3D7_0903400) with putative function in exosome has been identified, which is a homolog of DDX60 in humans or Ski2 in yeast .
Transcriptomic analysis of RBPs
It is noteworthy that of 28 single RRM-containing genes (Table 3), 13 are upregulated at the gametocyte stage. Noticeably, PF3D7_1126800 and PF3D7_0205700 both lack homologs in model species and showed remarkably specific elevated expression in young and mature gametocytes. PF3D7_1320900 encodes a putative peptidyl-prolyl cis-trans isomerase that interconverts cis- and trans-peptide bonds in the amino acid proline, and it was expressed at higher levels in gametocytes. A Plasmodium unique gene, PF3D7_1139100, showed higher expression levels at ring and merozoite stages but was virtually undetectable in other stages. Most of the 21 two-RRM containing genes (Table 3), however, had a uniform pattern of expression across different life stages of parasite development except for two genes [PF3D7_0414500 (musashi homolog 1) and PF3D7_1119800 (AFS-1)], which had notably higher expression during gametocyte stage.
Even though the Plasmodium transcriptome generally shows rigid, just-in-time expression patterns and ribosomal profiling demonstrates that the abundance of mRNAs correlates with their translational efficiency, many mRNAs do not fit within these bounds . Therefore, assessment of RBP candidates, especially those with an enrichment of mRNA levels in a stage-specific manner merit further investigation to determine their downstream roles in gene regulation.
Predicted protein-protein interaction network of RBPs in Plasmodium
Similarly, we have also constructed an interactome network for another important complex that governs post-transcriptional regulation— the PfCaf1-CCR4-NOT deadenylation complex (Fig. 6b). Currently there are no studies that have described the composition of this complex in Plasmodium species. Hence, we utilized published human Caf1-CCR4-NOT complex information to derive corresponding homologs in P. falciparum (Additional file 9). Following this analysis, the interologous network for human genes were extracted and the final gene set was searched against P. falciparum genome using BLASTp search at E-value <0.1. A total of 1090 interactions were studied, of which 774 (59 %) have homologs in P. falciparum, suggesting extensive conservation of interacting partners of this complex. Channeling these hits further into PlasmoDB we extracted and enriched gene ontology terms for biological processes. Most of the 774 predicted proteins of the Pf interactome have been categorized under primary metabolic process (GO: 0044238) that child branches into lipid metabolic process (GO:0006629), protein metabolic process (GO:0019538), carbohydrate metabolic process (GO:0005975), tricarboxylic acid cycle (GO:0 006099), nucleobase-containing compound metabolic process (GO:0006139), and cellular amino acid metabolic process (GO:0006520) suggestive of extensive interactions of the complex (Additional file 9). The entire protein network analyses in performed in this study are purely based on extrapolation of the information found in human or P. berghei, and hence these data presented here should be interpreted with those qualifiers.
Post-transcriptional regulation is a critical way by which malaria parasite controls its developmental processes, and RBPs are basic, underpinning elements in this process. A very few number of PfRBPs have been functionally characterized through experimentation, leaving a large portion without functional assignments. About 80 % of the total retrieved 189 PfRBPs were assigned putative functions using literature search and in silico methods. Most of these genes are predicted to be involved in pre-mRNA processing (42 genes) and ribosome biogenesis (29 genes), and a few have functions in cytosolic granules and as translational regulators. About 50 % (25 genes) of the 42 RBPs involved in pre-mRNA processing belong to the RRM family, while 55 % of 29 RBPs participating in ribosome biogenesis are from the RNA helicase family, suggesting a large fraction of these RBP families are devoted to these two basic functions. Transcriptome analyses of RBPs show both stage-specific enrichment of transcripts and mixed-curve expression profiles suggesting involvement of complex cues in their regulation. Some of the components of pre-mRNA processing and ribosome biogenesis, which are thought to be essential for these basic processes, show stage-specific enrichment of mRNA levels. Because most PfRBPs have no experimentally defined functions, these data may provide a guide to prioritize a subset of genes with an aim to better understand the basic biology of the parasite.
Database search for sequence retrieval
A multipronged search strategy was employed to retrieve putative homologs of RNA-binding proteins (RBP) genes from public domain databases. Initially, a ‘text’ based search was performed against PlasmoDB Version 12.0 (http://plasmodb.org/plasmo/) . For example, to identify RBPs with a zinc-finger (Znf) like domain, “RNA-binding” followed by “Zinc finger” key words were used. Similarly, RRM, RNA helicase, Puf, K homology, Alba, PUA, S-1, YTH, PWI, SWAP, G-patch key words were used in quotes to search for RNA recognition motifs, RNA helicase, Pumilio-Homology Domain, K homology, and Acetylation Lowers Binding Affinity, pseudouridine synthase and archaeosine transglycosylase domain, S-1 motif, YT521-B homology, PWI, Suppressor-of-White-APricot domains, and G-patch motif domain containing genes, respectively. As a second strategy, a hidden Markov model (HMM) for each of the RNA-binding domains was constructed using a reference set of genes annotated from the “text” based search using hmmbuild in package HMMER version 3.0 . Multiple sequence alignments were performed using the MUSCLE program using default parameters . The created HMM profiles were subsequently used to perform hmmsearch (http://hmmer.janelia.org/search/hmmsearch) against the P. falciparum genome. As final strategy, Pfam ID’s of each of the putative RBDs (Additional file 1) were used to search PlasmoDB. The genes retrieved from each of the above analyses were combined and parsed to remove duplicate genes that were retrieved in multiple search strategies to arrive at the final list of putative RBPs.
Domain mapping and confirmation
To define the protein domain organization of the putative RBPs, sequences were subjected to domain profiling using the Simple Modular Architecture Research Tool (SMART)  and Conserved Domain Database (CDD) search tools . While the SMART searches use the underlying SMART database, which consists of manually annotated protein profiles , the NCBI-CDD search hosts multiple databases, including CDD profiles v3.13. In addition, the CDD database uses protein 3D models in conjunction with primary sequences to classify domains into different superfamilies . Where possible, a superfamily of each identified domain was used to predict RBP function in addition to annotations derived from homology searches (see below).
Functional assignment of the genes predicted to encode RBPs was achieved by combining results from existing annotations from PlasmoDB v. 12.0, protein BLAST (search of GenBank , literature searches, and domain superfamily classification from CDD searches. BLASTp was carried out against the reference sequences of five selected model organisms—Saccharomyces cerevisiae (taxid: 4932), Caenorhabditis elegans (6239), Arabidopsis thaliana (3702), Drosophila melanogaster (7227), Homo sapiens (9606) and Trypanosoma cruzi (5693) using the following parameters: word size-3; Blosum 62 substitution matrix, gap opening 11 and extension 1. Because Plasmodium genes are often interspersed with low complexity regions (LCR), BLAST searches were configured to negate the impact of these regions on the outcome by selecting LCR filters in algorithm parameters. To avoid false functional assignment due to partial sequence matching, we employed reciprocal searches against Plasmodium genomes using sequences from model species or Trypanosomes, and more stringent criteria (≥40 % identity of the query protein and covering ≥80 % of the target gene) to assign specific functions to the proteins. In certain cases, the criteria were relaxed if the orthologs from more than one model species had a similar functional assignment, and when protein homology extends beyond the functional unit of the query protein. In the event of lack of homologs in models species, a relaxed modified-search was performed with lowered E-value (e.g. 10) and its use is noted where it is applied in this study.
Multiple sequence alignments and phylogenetic reconstruction
All multiple sequence alignments made in the study were performed using MUSCLE software with default parameters (gap opening and extending penalties as −2.9 and 0) as implemented in MEGA version 6.0 . Similarly, all phylogenetic reconstructions and molecular evolutionary analysis were conducted using MEGA v6. The genetic distances were estimated using Poisson correction and phylogenetic trees were constructed following Neighbor-Joining method . Tree robustness was evaluated using 1000 bootstrapped replicates.
Three dimensional structures and domain folds of proteins are commonly more conserved than the amino acid sequences themselves. Hence, in this study we threaded 3D models for either defining different classes of RBPs, or to locate conserved residues, or to differentiate prokaryotic vs eukaryotic protein structures. A representative homology models for each of the five major RBDs (RRM, RNA helicase, KH, Puf, and Alba) were constructed by structural threading using algorithms implemented in I-TASSER (Iterative Threading ASSEmbly Refinement)  or Swiss-model . The Swiss-model server automates building the homology model by first searching for a suitable template for constructing a reference-based model. Following this, the model was subjected to strained angle correction, and quality control parameters were estimated (e.g. Qmean Z-score, a likelihood of comparable quality of an estimated model to the native structure . Similar to Swiss-model, the I-TASSER server also automates the model building, however, it uses three different conventional 3D model building procedures to do so (homology modeling, sequence threading, and ab initio modeling) [114, 117]. The procedure uses C-score and TM-score as quality parameters to estimate the model quality [114, 118]; where C-score is a confidence score (−5 to −2.25, higher is better) while TM-score (0–1, a higher value translates to increased confidence in the model) measures degree of absolute similarity between the built model to the native structure .
Transcriptome analysis on putative RBPs was performed using curated microarray and RNA-seq  datasets downloaded from PlasmoDB. Heat map and clustering of the RNA-seq data was performed using the MeV software . Average linkage agglomeration rule was applied to cluster genes hierarchically with similar expression patterns. We also combined self-organizing maps data to the hierarchical clustering to derive stage-specific gene expression, which was determined using 2000 iterations at α-0.05.
An interactome analysis for PfCITH and PfDOZI was performed based on published protein-protein interaction (PPI) data for the orthologs of these proteins in the rodent parasite P. berghei . The top six hits that have assigned putative functions in PlasmoDB were further used to search the STRING v9.1 database for identifying interacting partners. The STRING database reposits known and predicted protein-protein interactions. Known interactions are confirmed physical interaction between proteins, while predicted interactions were derived from four sources: genomic contexts, high-throughput experiments, coexpression and literature review . We used a high-confidence score (0.7) to select the most likely interactions for further network construction using Cytoscape (www.cytoscape.org).
We have also constructed an interactome network for the PfCaf1-CCR4::NOT complex associated genes using human homologs. Following this, PPI data for human homologs were retrieved from Interologous Interaction Database (http://220.127.116.11/ophidv2.204/ppi.jsp) and the hits were used to collect P. falciparum homologs using BLASTp search against PlasmoDB with E-value <0.1. Interactions for each of the core components were searched for gene ontology terms in PlasmoDB and enrichment for biological process and primary metabolic processes were done.
This work is supported by the R01AI104946 and U19AI089672 to LC, and NIAID K22 (1K22AI101039-01) and Pennsylvania State University Start-Up Funds to SEL.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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