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Abstract
Transmission-blocking (TB) vaccines are considered an important tool for malaria control and elimination. Among all the antigens characterized as TB vaccines against Plasmodium vivax, the ookinete surface proteins Pvs28 and Pvs25 are leading candidates. These proteins likely originated by a gene duplication event that took place before the radiation of the known Plasmodium species to primates. We report an evolutionary genetic analysis of a worldwide sample of pvs28 and pvs25 alleles. Our results show that both genes display low levels of genetic polymorphism when compared to the merozoite surface antigens AMA-1 and MSP-1; however, both ookinete antigens can be as polymorphic as other merozoite antigens such as MSP-8 and MSP-10. We found that parasite populations in Asia and the Americas are geographically differentiated with comparable levels of genetic diversity and specific amino acid replacements found only in the Americas. Furthermore, the observed variation was mainly accumulated in the EGF2- and EGF3-like domains for P. vivax in both proteins. This pattern was shared by other closely related non-human primate parasites such as Plasmodium cynomolgi, suggesting that it could be functionally important. In addition, examination with a suite of evolutionary genetic analyses indicated that the observed patterns are consistent with positive natural selection acting on Pvs28 and Pvs25 polymorphisms. The geographic pattern of genetic differentiation and the evidence for positive selection strongly suggest that the functional consequences of the observed polymorphism should be evaluated during development of TBVs that include Pvs25 and Pvs28.
Author Summary
Plasmodium vivax is the most prevalent human malarial parasite outside Africa. The fact that patients can relapse due to the parasite dormant liver stages, among other biologic and epidemiologic characteristics of vivax malaria, facilitates the persistence of the disease in many endemic areas. These challenges have fueled the search for new control tools, including transmission blocking (TB) vaccines targeting the parasite sexual stages. Here we study the genetic diversity of two major TB vaccine antigens, Pvs25 and Pvs28. We show that these genes are relatively conserved worldwide but still harbor diversity that is not evenly distributed across the genes. These patterns are shared by the same proteins in closely related parasite species suggesting their functional importance. We also identify strong geographic differentiation between the circulating variants found in Asia and the Americas. Finally, evolutionary genetic analyses indicate that the observed variation in both genes could be maintained by natural selection. Thus, these polymorphisms may confer an adaptive advantage to the parasite. These results indicate that the genetic variation found in these genes and their geographic distribution should be considered by vaccine developers.
Citation: Chaurio RA, Pacheco MA, Cornejo OE, Durrego E, Stanley CE Jr, Castillo AI, et al. (2016) Evolution of the Transmission-Blocking Vaccine Candidates Pvs28 and Pvs25 in Plasmodium vivax: Geographic Differentiation and Evidence of Positive Selection. PLoS Negl Trop Dis 10(6): e0004786. https://doi.org/10.1371/journal.pntd.0004786
Editor: Photini Sinnis, Johns Hopkins Bloomberg School of Public Health, UNITED STATES
Received: March 1, 2016; Accepted: May 28, 2016; Published: June 27, 2016
Copyright: © 2016 Chaurio et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All the sequences reported in this investigation are deposited in the GenBank under the accession numbers KU285229 to KU285332.
Funding: This work was supported by the grant NIH 1U19AI089702 from the National Institute for Health and by the grant S12000000537 from the Fondo Nacional de Tecnología e Innovación, Venezuela. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Transmission-blocking (TB) vaccines are considered an important tool for malaria control and elimination [1]. TB vaccines aim to disrupt malaria transmission by eliciting antibody mediated responses against antigens expressed during sexual or sporogonic stages of the parasite thereby inhibiting its development inside Anopheles mosquitoes. Thus far, the search of suitable targets for TB vaccines has yielded promising results. In particular, antibodies against some of the multiple parasite proteins have shown excellent TB activities [1]. Among those antigens, the ookinete surface proteins Pvs28 and Pvs25 have been considered candidates to be incorporated in TB vaccines against Plasmodium vivax. These proteins may have originated as result of a duplication event and their orthologous genes (referred to as p28 and p25) have been described in many Plasmodium species [2,3]. P28 and P25 are the two most abundant membrane proteins expressed on the zygote and ookinete surfaces; indeed, they might represent as much as 25% of the total ookinete surface proteins [4]. Their structure has been characterized as a triangular prism of EGF-like domains tethered on the cell by a glycosylphosphatidylinositol (GPI) anchor at the C-terminus [5,6]. Although their specific functions are still not clear, it is known that they are essential for the survival of ookinetes in the mosquito midgut [4]. In particular, studies in P. berghei strongly suggest that P28/P25 proteins have multiple, and partially redundant functions during ookinete and oocyst development [4].
Although they share a common origin and their functions appear to overlap, preliminary studies indicate that P25 proteins are expressed earlier than P28. Specifically, P25 is expressed prior to fertilization, achieving peak synthesis in the initial hours soon after, and then most abundantly expressed on the surface of the developing zygotes and ookinetes [7]. In contrast, P28 proteins are expressed slightly later on the ookinete surface until the young oocyst stage [7]. In the context of developing TB vaccines, antibodies against these proteins interfere both with ookinete maturation and oocyst formation [8]. In particular, mice antisera against recombinant Pvs28 and Pvs25 recognized both antigens in short term cultures of parasite sexual-stages derived from patients with P. vivax malaria, and significantly suppressed oocyst development in four Anopheles species fed with blood infected with P. vivax Salvador I strain [8]. In addition, in a preclinical trial conducted in Aotus monkeys, animal immunization with recombinant Pvs25 elicited specific antibodies able to fully block parasite infection in membrane feeding assays (MFAs) [9]. Furthermore, in a phase I clinical trial conducted with Pvs25 sera obtained from the vaccinated volunteers induced significant inhibition of P. vivax transmission in Anopheles dirus mosquitoes using an ex-vivo MFA [1,10]. Moreover, TB immunity elicited with orthologous proteins in P. falciparum and other malaria parasites has been shown as well [8,11,12]. Unlike the extensive polymorphism commonly observed in several Plasmodium blood stage surface antigens, these proteins are considered to be conserved [13–17]. Therefore, the immunogenicity, TB potential, and limited polymorphism support the use of Pvs28 and Pvs25 as suitable targets for TB vaccines.
Here, we study a worldwide sample of pvs28 and pvs25 coding alleles. We detected strong geographic differentiation between populations in Asia and the Americas with replacements at specific amino acid residues novel in the Americas. We also found that these genes can be as polymorphic as some merozoite antigens such as MSP-8 and MSP-10, with most of their variation accumulating in the EGF2 and EGF3 like domains of both proteins. Finally, our analysis indicates that positive selection may be acting on the accumulation of pvs28 and pvs25 polymorphisms.
Methods
Parasite strains and field isolates
We report pvs28 and pvs25 complete CDS sequences from geographically and temporally diverse laboratory strains provided by William Collins at the Centers for Disease Control and Prevention (CDC). We obtained pvs28 gene sequences from the following laboratory strains grouped by their geographic origin: Africa (Mauritania I), Central America (El Salvador II, Honduras III, Nicaragua, and Panama), South America (Río Meta from Colombia), Asia (Vietnam II, India VII, Thailand and Malaysia), and Oceania (Sumatra from Indonesia, Indonesia XIX, Chesson, and Harris from Papua New Guinea). We also obtained 11 pvs28 and 15 pvs25 sequences from Venezuelan archived samples [18]. In addition, we included 259 pvs28 (total of 284 in the global alignment) and 310 pvs25 (total of 325 in the final alignment) sequences available at the GenBank (release 208, June 2015). Those included data of pvs25 from Venezuelan and laboratory strains [19] and sequences from pvs28 and pvs25 from China (Yunnan Province) [13], India (Delhi, Chennai, Kamrup, Nadiad and Panna) [16], Iran [17], Korea (ROK) [15], Southern Mexico [14], Thailand (Tak Province) [12] and, Bangladesh [20].
Additionally, we report 58 sequences for p28 and p25 orthologous genes from the following species of nonhuman primate parasites (NHPPs): Plasmodium cynomolgi (p28 from: Berok, B, BX-20, Cambodian, ceylonensis, PT1, PT2, RO, Smithsonian, Gombak, and Mulligan strains; p25 from: Berok, B, BX-20, Cambodian, ceylonensis, PT1, PT2, RO, and Smithsonian strains), Plasmodium inui (p28 from: Celebes I and II, Leaf Monkey II, N34, OS, Philippine, Leucosphyrus, Perak, Taiwan I and II, and Perlis; p25 from Celebes II, Hawking, Leaf Monkey I, Leucosphyrus, Mulligan, and Perlis), Plasmodium knowlesi (p28 from: H, Hackeri, Malayan from Malaysia, Nuri from India, and the Philippine strain; p25 from: Philippine, Hackeri, and Malayan), Plasmodium coatneyi, Plasmodium fieldi (p28: Hackeri and N-3; p25: ABI and N-3 from Malaysia), Plasmodium hylobati, Plasmodium simiovale (Sri Lanka), and a parasite from African primates, Plasmodium gonderi. Information about these species and strains can be found in Coatney et al. [21].
In order to estimate the phylogenetic relationships for the genes encoding pvs28 and pvs25 and their NHPPs orthologs, we also included the published sequences in PlasmoDB, version 24 [22] and NCBI for the Asian species P. cynomolgi (PCYB_062530, PCYB_062520) and P. inui (San Antonio 1, GCA_000524495.1 and; AY639974); the Laverania group that includes P. falciparum (3D7_1030900 and 3D7_10310003), Plasmodium gaboni (Pgk strain, GCA_000576715.1), and Plasmodium reichenowi (PRCDC_1030200 and PRCDC_1030300); the human parasite Plasmodium ovale (AB051632 and AB051631); and the rodent parasites Plasmodium bergei (strain Anka, AF232051 and XM_670232), Plasmodium chabaudi (AF232048 and XM_739934), and Plasmodium yoelii (AF232055 and XM_720005). The phylogenies were rooted with the avian parasite Plasmodium gallinaceum (M96886 and J04008). In the specific case of P. cynomolgi (strain B), in addition to the p28 orthologous PCYB-062530, the two other paralogous genes were also retrieved (PCYB-062510/PCYB-007100) from PlasmoDB. To the best of our knowledge, only P. ovale [23] and P. cynomolgi [24] have one and two paralogs to p28 respectively. In the specific case of P. ovale, we only included the pos28-1 (AB051632) sequence in our phylogenetic analyses.
PCR amplification, cloning, and sequencing
For all the samples processed in this study, DNA was extracted from whole blood by using QIAamp DNA Blood Mini Kit (Qiagen GmbH, Hilden, Germany). All the p28 and p25 genes reported in this study were amplified by polymerase chain reaction (PCR). PCR reactions were carried out in 50 μl volume that included 1.5 mM MgCl2, 1 X PCR buffer, 1.25 mM of each deoxynucleosidetriphosphate, 0.4 mM of each primer, and 0.03 U/μM of AmpliTaqDNA polymerase (Applied Biosystems, Roche-USA). For the pvs28 gene, we used the primers 5’-TTTGTTCATTTTTGACATACTCACTT-3’ and 5’-ATGCGCGGTGTGTTATTTGGAG-3’ with an annealing temperature (Ta) of 50°C. For P. cynomolgi, P. fieldi, P. fragile, P. inui and P. simiovale, we used the primers 5’-CCAACTGCATTATACAAAAAC-3’ and 5’-ATCTTCTTCGGCGAAAAAA-3’ (Ta: 47°C). For P. knowlesi and P. hylobati, we used 5’-TGCCACCCCTTGTTCAAAATG-3’ and 5’-GWACTGACTCTGYGADACC-3’ (Ta: 54°C). In some cases, a nested PCR was required by using the primer sets 5’-ACTTGCTCACTCGACTTAACC-3’ and 5’-CGTTTTTCTTGTCCCTTTGTCAC-3’ (Ta: 53°C) for P. vivax and 5’-ATACAAAAACGACTCCCCCTTT-3’ and 5’-CGTATGACTTGAACTGACTC-3’ (Ta: 47°C) for NHPPs.
The pvs25 gene and its orthologs were amplified with the primers 5’-CTGACTTTCGTTTCACAGCA-3’ and 5’-ACATCACAAGTCCGTAAGTT-3’ (Ta: 53°C). In the case of nested PCRs, we combined the external primers 5’-CTGACTTTCGTTTCACAGCA-3’ and 5’-CATCACAAGTCGGTAAGT-3’ (Ta: 53°C) with the internal 5’-TTCGACCGCTCAATTCGCC-3’ and 5’-CAAGTCGGTAAGTTCAGTAAAG-3’ (Ta: 55°C). The amplification conditions for both genes were as follow: 5 min at 95°C, followed by 35 cycles with 1 min of denaturation at 94°C, 1 min at the specific Ta and elongation at 72°C for 2 min. After 35 cycles, a final elongation step at 72°C for 10 min was carried out. Amplified products from the two independents PCRs were either directly purified or gel extracted and cloned in pGEM-T easy Vector Systems I following the manufactory protocol (Promega, USA). For at least two clones, both strands were sequenced using an Applied Biosystems 3730 capillary sequencer. All the sequences reported in this investigation are deposited in the GenBank under the accession numbers KU285229 to KU285332.
Genetic diversity and natural selection of pvs28 and pvs25
For both genes, p28 and p25, independent alignments of their nucleotide sequences for P. vivax and their close NHPs malaria species were performed by using the MUSCLE algorithm [25] implemented in SeaView4 [26] on translated sequences followed by visual inspection and manual editing. The protein domains (signal peptide, EGF-like domains and GPI anchor) were assigned in the alignments following the description used by Saxena et al. 2006 [5]. In the case of pvs28, the low complexity regions (LCRs) were not included in the polymorphism and phylogenetic analyses; however, those were studied separately as defined by Rich et al. 1997 [27].
We estimated the polymorphism by gene and by domain within each Plasmodium species by using the population statistics π (the average number of substitutions between any two sequences), number of segregating polymorphic sites (S), and haplotype diversity (Hd). The polymorphism was also explored by computing Tajima’s D statistic [28]. The distribution of the genetic diversity across the p28 and p25 gene-sequences was described by calculating π on a sliding-window of 50 base pairs (bp) with a step size of 10 sites. The statistic was calculated in each window, assigned to the nucleotide at the midpoint of the window and plotted against the nucleotide position. All these calculations were performed using DnaSP v5.10.01 [29].
Evidence of natural selection was explored by estimating the average number of synonymous substitution per synonymous site (dS) and non-synonymous substitutions per non-synonymous site (dN) between a pair of sequences under the Nei Gojobori method [30], with the Jukes and Cantor corrections as implemented in the MEGA6 [31]. The difference between dS and dN and its standard error was estimated by using bootstrap with 1,000 pseudo-replications, as well as a two tailed codon based Z-test on the difference between dS and dN as described in Nei and Kumar 2000 [32]. Under the neutral model, synonymous substitutions accumulate faster than non-synonymous because they do not affect the parasite fitness and/or purifying selection is expected to act against nonsynonymous substitutions (dS≥dN). Conversely, if positive selection is maintaining polymorphism, a higher incidence of nonsynonymous substitutions is expected (dS<dN). We assumed as a null hypothesis that the observed polymorphism was not under selection (dS = dN).
We also used the random effects likelihood (REL) method as implemented in HyPhy, which uses flexible, but not overly parameter-rich rate distributions [33] and allows both dS and dN to vary across sites independently. REL allows for tests of selection at a single codon site while taking into consideration rate variation across synonymous sites. It is often considered the only method for inferring selection from low divergence alignments such as pvs28 and pvs25. Evidence for natural selection was also explored in P. vivax by using the McDonald & Kreitman (MK) test which compares intra and inter-specific number of synonymous and non-synonymous changes [34]. In this analysis we compared P. vivax with their close NHPPs P. cynomolgi, P. inui and P. knowlesi for both p28 and p25 genes. Significance was assessed using a Fisher’s exact test for the 2 x 2 contingency table as implemented in the DnaSP.
Population structure and haplotype network of pvs28 and pvs25
In order to study the genetic relationships among worldwide haplotypes, a median joining network was estimated for a set of 284 cosmopolitan sequences of pvs28 and 325 of pvs25 genes by using Network v4.6.1.0 (Fluxus Technologies 2011). Transversions were set equal to transitions and the epsilon parameter set equal to 0 with only one round of star contraction, which collapses star-like structures in the network into single nodes. The total number of sites included in these analyses excluding gaps or missing data were 547 out of 744 for pvs28 and 558 out of 660 for the pvs25 genes. In addition, we also used DnaSP to estimate the fixation index (FST) based on haplotype-frequencies among these geographical regions.
In order to investigate whether intragenic recombination generates allelic diversity in the P. vivax ookinete genes, the genetic algorithms for recombination detection (GARD) were used to screen for the recombination breakpoints in both alignments, as implemented in Datamonkey (http://www.datamonkey.org/)[35,36]. Default parameters for the detection of recombination breakpoints and donor-recipient pairs were used with a significance cut-off of 0.05.
Phylogenetic analyses
The evolutionary relationships among the p28 and p25 genes in Plasmodium spp. were investigated using Bayesian methods implemented in MrBayes v3.2 with the default priors [37]. A General Time-Reversible model (GTR+I+Γ) was used because it had the lowest likelihood value and possessed the fewest number of parameter that best fit the data (p28 and p25) as was estimated by MEGA6. For both phylogenies (p28 and p25), two independent chains were sampled every 200 generations in runs lasting 6 × 106 Markov Chain Monte Carlo steps, and after convergence was reached, we discarded 50% of the sample as ‘burn-in’ period. Convergence is reached when the value of the potential scale reduction factor is between 1.00 and 1.02 and the average standard deviation of the posterior probability is below 0.01 [37].
Additionally, the adaptive branch-site random effects likelihood (aBSREL) approach [38], implemented in Datamonkey, was run to detect evidence of episodic positive selection on all branches using both phylogenies (p28 and p25). It allows for different Ka/Ks ratios among sites and branches. We performed a likelihood ratio test (LRT) comparing the null model (ω = 1) against the alternative, where the branch was undergoing some form of selection (ω ≠ 1). In addition, we used BUSTED, implemented also in Datamonkey, which is an approach to identify gene-wide evidence of episodic positive selection, where the non-synonymous substitution rate is transiently greater than the synonymous rate [39]. In these analyses we selected both human malarias P. vivax and P. falciparum branches because BUSTED requires pre-specified subset of lineages.
Results
Evolutionary analyses of pvs28 and pvs25
A total of 284 and 325 sequences were studied for the pvs28 and pvs25 genes respectively. Tables 1 and 2 describe the polymorphism found in the complete gene-sequences and their subsequent domains for both genes. The overall genetic diversity, as estimated by π, revealed that both genes are relatively conserved when compared to other vaccine candidates as has been reported by previous studies analyzing a smaller sample size [3,12–17]. The pvs28 gene showed a slightly higher, but not significant polymorphism level (π = 0.0037 ± 0.0011) than pvs25 (π = 0.0023 ± 0.0010). When we compared the polymorphism observed between isolates from Asia and the Americas, we found that pvs28 samples from Asia were slightly more polymorphic (π = 0.0035 ± 0.0012) than the ones from the Americas (π = 0.0024 ± 0.0011) (Table 1). In contrast, we observed a similar genetic diversity in the pvs25 sequences from both Asia (π = 0.0017 ± 0.0008) and the Americas (π = 0.0018 ± 0.0010) (Table 2). Nevertheless, in both genes the standard errors for π overlapped when Asia and the Americas were compared.
Because of P28 and P25 EGF-like domains carry critical epitopes recognized by P. vivax TB antibodies [5,8], we also estimated π by gene-domain in addition to the geographic regions. In both genes, the EGF2 and EGF3 were the most polymorphic domains of the proteins (Tables 1 and 2). Fig 1 shows the distribution of the polymorphism across the pvs28 and pvs25 genes using a sliding window approach of the nucleotide diversity π. The polymorphism for both genes was distributed unevenly; the most conserved areas were located at the secretory signal sequence at the N-terminus, the EGF1 and EGF4 like domains, and the GPI anchor at the C-terminus. In contrast, central regions like the EGF2 and EGF3 domains accumulated higher variability.
Genetic diversity (π) was estimated using a sliding window of 50 base pairs (bp) with a step size of 10 sites. The LCR of tandem repeats of the pvs28 gene was not included but its location is indicated by a blue arrow.
We also studied the polymorphism found in pvs28 (Table 3) and pvs25 (Table 4) genes by country. Regardless of sampling differences, the haplotype diversity Hd was similar for both genes (pvs28-Hd = 0.765, pvs25-Hd = 0.724). Yet, the number of haplotypes found in pvs28 (H = 53) seems to be slightly higher than the ones found in the pvs25 gene (H = 35). We report estimates by country with at least 10 sequences or more in our alignment. A high haplotype diversity was observed for pvs28 in Bangladesh (Hd = 0.895), Thailand (Hd = 0.993) for Asia, and Venezuela (Hd = 0.873) from the Americas (Table 3). For pvs25, high haplotype diversity was observed in samples from China (Hd = 0.6478), Venezuela (Hd = 0.8000), and Mexico (Hd = 0.6513) (Table 4).
In order to explore how natural selection was involved in the maintenance of the observed polymorphism, we estimated the average number of synonymous (dS) and non-synonymous (dN) changes between two sequences (Tables 1–4). Overall, we found a significant excess of non-synonymous over synonymous polymorphic changes in pvs28 sequences (p = 0.0271, Table 1). Nevertheless, when we estimated the average dS and dN by region, this pattern was maintained in Asia (p = 0.0318) but not in the Americas (p = 0.4926), specifically in Thailand (p = 0.0280), India (p = 0.0090), and Bangladesh (p = 0.0238). Although there was an excess of non-synonymous (dN = 0.0027) over synonymous substitutions (dS = 0.0007) in pvs25 polymorphism (Table 2 and Table 4), the differences were not significant (p = 0.1040) (Table 2).
We examined the amino acid replacements observed in the P28 and P25 proteins by using P. vivax Salvador I strain as a reference; our observations are summarized in S1 and S2 Tables respectively. In the Pvs28 protein, we observed 44 amino acid changes, most of them in low frequency (<0.1% on 284 sequences). The EGF1 domain had the lowest number of amino acid replacements with only the replacement 52(M/L) found in 25% (S1 Table). In contrast, the EGF2 domain showed the highest number of changes (12 replacements) but most of them observed in low frequency (<1%). The most frequent replacements were at 65(T/K) found in 21.8% of the sequences, followed by 87(D/N) and 98(L/I) with 8.5% and 4.2% frequency respectively. The EGF3 domain displayed a total of 13 amino acid changes, the most common were in positions 110(N/Y) found in 5.6%, 116(L/V) in 10.9% and 140(T/S) in 16.2% of the total samples. The EGF4 domain (no including LCR of tandem repeats) and the GPI anchor region showed together only 14 changes in low frequency (<3.0%). It is important to emphasize that the polymorphisms in positions 87(D/N) and 110(N/Y) were observed only in the 40 sequences from the Americas with a frequency of 60% and 40% respectively. Here, we report these polymorphisms for the first time in Colombia, El Salvador (Sal II, [40]), Honduras, Nicaragua, Panama and Venezuela. Moreover, some of the frequent amino acid changes observed in Pvs28 (52M/L, 65T/K and 116L/V) were also present in P. cynomolgi and P. inui (S1 Table).
A similar analysis for the Pvs25 antigen (n = 325) showed a total of 34 low frequency (<1%) amino acid substitutions (S2 Table). The most frequent changes for the EGF2 were 87(Q/K) found in 12.7% and 97(E/Q) in 50.3% of the worldwide sequences. Glutamine (Q) at position 87 is one of the contacting residues involved in the binding of the transmission blocking antibody 2A8 (Fab VH domain) with the ß loop (EGF2) of the Pvs25 protein [5]. This amino acid was found to be mutated to lysine (K) in several field isolates from Iran, Mauritania, Brazil, Colombia, Mexico and Venezuela. In the EGF3 domain, changes at positions 130(I/T) in 89.1% of the sequences in addition to 131(Q/K) in 8.2% were the most common. In the case of p25 orthologous genes in close NHP malarias, different amino acid changes were also identified in all these positions (S2 Table). To show the location of the observed mutations on the Pvs28 and Pvs25 structures, the three dimensional structure for Salvador I Pvs28 was modelled by using Phyre2 [41] on the Pvs25 structure as template [5]; 65% of the Pvs28 structure was modelled with 99.4% confidence. Positions of mutations for both Pvs25 and Pvs28 were visualized using Visual Molecular Dynamics (VMD [42]). Mutations with a frequency >1% were mapped by residue location and colored according to domain (Fig 2, S1 and S2 Tables). Residues putatively under positive selection were indicated with arrows (see results from REL method explained later in the text).
The mapped amino acid substitutions are those with a frequency >1%. Arrows indicate codons putatively under positive selection under the model implemented in the random effects likelihood (REL) method (blue arrows: Bayes Factor >10<50; red arrows: >50). All substitutions with their frequencies and structural location are listed in S1 and S2 Tables.
Worldwide pvs28 and pvs25 haplotype networks and population structure
The haplotype networks based on the pvs28 and pvs25 sequences are shown in Figs 3 and 4 respectively. We identified 63 distinct haplotypes among 284 pvs28 sequences from 18 regions/countries. Although the sampling effort per country did not allow us to reliably estimate and compare the haplotypes’ relative frequencies, there were some emerging patterns. In particular, we focused on the number of countries/areas where a given haplotype had been found since it is informative of its geographic range.
Branch lengths are proportional to divergence; node sizes are proportional to the total haplotype frequencies. The network shows 63 haplotypes found in 284 sequences with a haplotype diversity of 0.765. The most frequent haplotypes are indicated. Every color corresponds to a different geographic origin. Lines separating haplotypes represent mutational steps.
Branch lengths are proportional to divergence; node sizes are proportional to the total haplotype frequencies. The network shows 35 haplotypes found in 325 sequences with an overall haplotype diversity of 0.724. The most frequent haplotypes are indicated. Each color corresponds to a different geographic origin. Lines separating haplotypes represent mutational steps.
The pvs28 network presented two distinctive features referred here to as A and B. The feature A suggests a star-like shape consistent with an expansion of the P. vivax population for part of the network [18] while the feature B refers to the reticulated structure observed in Asia. Only 12 haplotypes (19.1%) were shared by two countries or more whereas 51 haplotypes (81.0%) were restricted to single countries. Importantly, only three haplotypes were found with a relatively broad distribution (H1, H2, H35; see Fig 3).
The haplotype denominated as H1 was the most frequent (40.1%, 114/284) and showed a worldwide distribution (Fig 3). The haplotype H35 with 59 sequences (20.8%) was the second most predominant and the most common in the Indian samples included in this study (77.3%). It was not only found in five distant Indian regions [17] but also in Bangladesh, China, Iran, and Thailand (Fig 3). The third haplotype in terms of its frequency was H2 (4.6%, 13/284) and belongs to a more divergent cluster which includes only samples from the Americas; specifically, Mexico, Colombia, El Salvador (Sal II strain), Nicaragua, Panama, and Venezuela. The network results suggest that the haplotype H2 could have originated from the most frequent H1 haplotype. Because of the study performed in Korea, which is geographically smaller, involved a large sample collected between 1996 and 2007 [15], we can speculate that haplotype H1 might be the most common in that region. Feature B of the pvs28 network (Fig 3) showed a group of haplotypes from Bangladesh, China, India, Malaysia, Thailand, and Vietnam forming reticulations. This pattern corresponds to several divergent haplotypes found in very low frequency in this set of samples.
The pvs25 haplotype network depicts 35 distinct haplotypes among 325 sequences from 15 regions/countries. We found five haplotypes in high frequency (H1, H4, H20, H23, and H25; see Fig 4). The haplotype denominated as H4 corresponded to 152 (46.8%) sequences from Bangladesh, China, India, Indonesia, Iran, Korea, and Thailand. This haplotype is related to H1, the second most predominant with 70 (21.5%) sequences distributed in China, India, Korea, Mexico, and Thailand. The other three haplotypes (H20, H23 and H25) were linked to the most frequent H1 and H4 by long branches. Finally, haplotype 25 was only found in Mexico and Venezuela.
To further determine genetic differentiation among populations, the FST fixation index was estimated. Supporting our median joining network results, FST values estimated for both genes suggest high genetic differentiation among P. vivax ookinete genes in different regions (FST > 0.15, Tables 5 and 6). Pairwise comparisons between Venezuela and Asia regions (China, Korea, India, Thailand, and Bangladesh), produced high FST values for both genes ranging from 0.426 to 0.542 in pvs28 (Table 5) and from 0.457 to 0.748 for the pvs25 gene (Table 6). As expected, a similar pattern was observed in pairwise comparisons between Mexico and Asia regions in both genes, suggesting some degree of differentiation between Asia and the Americas populations. However, when Mexico and Venezuela populations were compared, high FST values were also observed in the pvs28 (0.251) and pvs25 (0.457) coding genes. In contrast, P. vivax populations from Bangladesh compared to China and Thailand, are consistent with a minimal genetic divergence, suggesting no genetic population structure among these regions for pvs28 (FST <0.05). Tajima’s D produced consistent negative values for both pvs28 (Table 1) and pvs25 (Table 2) genes for all populations. In most cases, the results of the test were statistically significant with the exception of the American populations.
In order to investigate if recombination generated allelic diversity, the genetic algorithm recombination detection (GARD [35]) was performed. No evidence of intragenic recombination was detected in these ookinete genes.
Evolutionary analyses of p28 and p25 orthologous genes in NHP malarias
In accordance with previous reports, the amino acid sequence alignments of the P28 and P25 proteins suggest that both are conserved among Plasmodium spp. (S1 Fig) [2,5,6,23]. All the p28 and p25 sequences included in this study have a conserved hydrophobic signal sequence at the N-terminus (residues 1–23, SignalP 4.1 Server) [43], followed by four cysteine-rich epidermal growth factor EGF-like domains and a short GPI anchor region at the C-terminus (S1 Fig). An invariable number of 20 (~9.7%) and 22 (~10%) cysteine residues were found in all NHPPs P28 and P25 proteins respectively. The EGF4-like domain in P28 proteins contains four rather than six cysteines lacking of the 5–6 disulfide bridge. P28 orthologs showed a high average content of Lys (~7.50%), Leu (~7.23%), Asn (~8.92%), Thr (~7.79%) and Val (~7.47%) (S2A Fig). Likewise, for P25 proteins we found an average content of Glu (~9.25), Gly (~6.86), Lys (~9.67), Leu (~7.54) and Val (~8.32) (S2B Fig).
We compared the polymorphism of pvs28 and pvs25 with their orthologs in P. cynomolgi, P. inui and P. knowlesi. S3 and S4 Tables show the genetic variation found in the coding sequence (CDS) and the different domains of p28 and p25 genes respectively. We found that P. cynomolgi (P28-π = 0.0340 ± 0.0049, P25-π = 0.0284 ± 0.0041) and P. inui (P28-π = 0.0400 ± 0.0045, P25-π = 0.0133 ± 0.0026) had higher genetic polymorphism than their orthologs in P. vivax. In contrast, the p28 and p25 polymorphisms observed in P. knowlesi (P28-π = 0.0023 ± 0.0011, P25-π = 0.0038 ± 0.0015) were similar to pvs28 and pvs25 (Tables 1 and 2). The P. knowlesi orthologs also have shown no polymorphism in most of the gene domains (S3 and S4 Tables). Although, the P. cynomolgi p28 paralog PCYB_007100 had similar genetic diversity (π = 0.0340 ± 0.0044) to the one considered the P. cynomolgi ortholog to pvs28, PCYB_062530 (π = 0.0340 ± 0.0049), the nucleotide diversity was different across both genes (PCYB_062530 and PCYB_007100, S3B Fig).
We estimated the average pairwise dS and dN for NHPPs orthologs to p28 and p25. In the case of p28, especially for P. cynomolgi, the diversity found in both paralogous genes was biased toward synonymous sites, a pattern consistent with purifying selection (S3 Table). This contrasts with the pattern of positive selection found in pvs28. Nevertheless, a similar pattern was found in P. inui. Although there was an excess of synonymous over non-synonymous polymorphisms in P. cynomolgi and P. knowlesi p25 CDS, the differences were not significant using the codon based Z-test (S4 Table). Interesting, the dS-dN estimated by domains suggests different patterns of selection acting in the EGF1 (negative selection) and EGF3 (positive selection) like domains in P. cynomolgi (p < 0.05, S4 Table). Again, a similar number of synonymous (dS) and non-synonymous (dN) substitutions was found for p25 in P. inui (S4 Table). The assumption of neutrality was further examined in pvs28 and pvs25 against their orthologs in P. cynomolgi and P. inui by using the MK test. This test showed an excess of nonsynonymous over synonymous polymorphisms in the pvs25 gene when divergence was compared in P. cynomolgi and P. inui (p < 0.05, S5 Table). In both cases, the neutrality indexes (NI) were bigger than 1 and the significance of the test was explained by an excess of replacement polymorphisms in pvs25. These results suggest a possible pattern of balancing selection since a preponderance of non-synonymous intra-species polymorphisms was observed. Similar trends but no significant departures from neutrality were found for pvs28 (S5 Table).
The results of the REL method are depicted in Fig 5 (see S1 Table for reference) and the estimated Bayes Factors (BF) summarize the evidence provided by the data in favor of positive selection. The method detected three codons in pvs28 where the data provided strong evidence for positive selection with BFs bigger than 50 (codon 52 with a BF of 97.69, codon 113 with a BF of 101.51, and codon 116 with a BF of 367.92; see S1 Table for reference) and five with some evidence for positive selection with BFs bigger than 10 but less than 50 (codons 53, 65, 95, 98, and 123; S1 Table). In the case of pvs25, we found only five codons (35, 97, 130, 132, and 135; see S2 Table for reference) where the data provided some evidence of those being under positive selection with BFs bigger than 10 but less than 50 (Fig 5). Residues with mutations in high frequency (>1%) were mapped on the pvs25 and pvs28 protein structures depicted in Fig 2.
The estimated dN-dS (E[dN-dS]) per codon across the pvs28 and pvs25 genes are depicted against their position using Salvador I as a reference (see S1 and S2 Tables). Schematic diagrams of Pvs28 and Pvs25 indicate their EGF domains. Pvs28 codons 52, 113, and 116 yield Bayes factors (BF) of 97.69, 101.51, and 367.92 respectively, indicating that the data provided strong evidence for positive selection. Codons 52, 65, 95, 98, and 123 for Pvs28 and 35, 97, 130, 132, and 135 for pvs25 have BF higher than 10 but lower than 50, indicating that the data provided some evidence for positive selection acting at those codons. The LCR of pvs28 was not included in this analysis.
The Bayesian phylogenies of p28 and p25 are depicted in Fig 6. The avian malarial parasite P. gallinaceum was included as outgroup. Overall, they are comparable with previous published phylogenies using nuclear and mitochondrial genes [19,44–47]. Briefly, in both phylogenies, three major clades were identified: 1) the Laverania subgenus, 2) the clade of rodent malarias, and 3) the P. vivax clade. Plasmodium vivax is part of a monophyletic group with closely related NHPPs found in Southeast Asia. The African primate parasite P. gonderi was consistently placed at the base of this monophyletic group in both phylogenies. The difference between p28 and p25 phylogenies was the relative position of P. ovale (Fig 6). The p28 phylogeny resembled the phylogenetic tree obtained previously based on the nuclear genes ß-tubulin, CDC-2 and the plastid gene tufA [19].
Bayesian phylogenetic hypothesis constructed with nucleotide sequences of the p28 (A) and p25 (B) genes in Plasmodium spp. The values above branches are posterior probabilities (see Methods section). For both phylogenies (p28 and p25), two independent chains were sampled every 200 generations in runs lasting 6 × 106 Markov Chain Monte Carlo steps.
Two additional phylogenies containing all p28 and p25 strains obtained in this study for P. cynomolgi, P. inui, and P. knowlesi were estimated using P. gonderi as outgroup (S4A and S4B Fig respectively). The three p28 paralogs found in P. cynomolgi genome (B strain, PlasmoDB) were included (S4A Fig). The p28 phylogeny was slightly different to one that included all species; however, the major relationships were maintained (e. g. P. inui-P. hylobati, P. fieldi-P. simiovale and P. knowlesi-P. coatneyi). We could amplify the three different copies only for the P. cynomolgi strain Berok (S4A Fig), thus we could not confirm that all the P. cynomolgi strains have the two recent paralogs. Noteworthy, all p28 P. cynomolgi paralogs formed a monophyletic group that included the ortholog (PCYB-062530) to pvs25. This suggests duplication events in P. cynomolgi that took place after divergence from the common ancestor shared with P. vivax. To the best of our knowledge, only P. ovale and P. cynomolgi have reported paralogs to the p28 gene. However, we cannot rule out that such duplication events have occurred in others Plasmodium spp. In the case of p25 (S4B Fig), the relationship among NHP malarias from Southeast Asia were the same as those obtained in the phylogeny containing all the species (Fig 6).
Phylogenetic-based methods were used to explore the role that positive selection may have played in the divergence of these two loci. In the case of p28, no evidence of episodic diversifying selection was found in any of the 31 total branches using aBSREL (p ≤ 0.05, corrected for multiple testing). However, BUSTED revealed evidence for positive selection acting only on the P. falciparum lineage (p = 0.002, S6 Table). In contrast, no evidence of episodic diversifying selection was found in the p25 gene using aBSREL and BUSTED (S6 Table).
Characterization of the low complexity region (LCR) of the p28 gene
In order to fully characterize p28 polymorphism, we examined the LCR of short tandem repeats located at the big C-loop of the EGF4 domain [6]. The description of P28 motifs and amino acid variation is summarized in S7 and S8 Tables. This LCR is also present in all NHPPs that form part of the monophyletic group with P. vivax including P. gonderi from Africa and the Pos28-1 of P. ovale (S7 Table, S1 Fig). In contrast, such LCR is almost absent in species belonging to the Laverania clade (P. falciparum and related species) and rodent malarias with the exception of P. yoelii (S7 Table, S1 Fig). In the case of P. vivax, the consensus tandem repeat unit consists of five amino acid motif (GSGGE). The pattern from all P. vivax sequences can be summarized as [(G/E/S)S(G/R/D)GE]2–6, where the first and third positions are polymorphic (S7 and S8 Tables). Interestingly, all the amino acid changes were observed in Asia. The last tandem unit was not a repetitive motif, showing aspartic acid (D) in high frequency at the fifth position, but lower for glutamic acid (E) and glycine (G): [(G/S)S(G/D)G(D/E/G)]. This terminal unit was not included in our polymorphism estimations. Noteworthy, glycine was also the most abundant amino acid in the LCR in all NHP malarias included here (S7 Table).
Since proteins domains containing LCRs might be natural immunogenic carrying possible targets for antigenic epitopes [48], we explored the role of natural selection acting on the observed polymorphism. When the repetitive motifs were aligned among them, a significant (p < 0.05) excess of synonymous over non-synonymous substitutions was observed in P. vivax and NHP malarias (S8 Table), suggesting that the motif is conserved and its sequence might be under purifying selection.
Discussion
Although pvs28 shows slightly higher polymorphism than pvs25, those differences appear not to be significant. The genetic diversity found in sequences from Asia and the Americas for both genes was similar. This pattern was observed even when there were fewer sequences from the Americas than Asia. This is consistent with studies based on mitochondrial genome sequences (potentially neutral loci) and complete genomes showing that the diversity of P. vivax population in the Americas is comparable to Asia [18,49].
Pvs28 and pvs25 showed higher genetic variability compared to other sexual stage TB antigens reported in P. vivax as pvs48/45 (π = 0,00053), the Willebrand factor A domain-related protein (WARP) (π = 0.00010) and also previous estimations of pvs25 (π = 0.00065) and pvs28 (π = 0.00000) in Korea [50]. The Korean study likely differs from ours because of its limited geographic scope. It is worth noticing that whereas the observed polymorphism is lower than those reported in many merozoite surface antigens such as AMA-1 [51], there are merozoite stage antigens such as MSP-8 and MSP-10 with similar levels of polymorphism to those reported here for the pvs28 and pvs25 genes [45].
The neighbor haplotype-network for both pvs28 and pvs25 genes formed a star-like shape consistent with the suggested underlying demographic history of a population expansion for P. vivax [18]. This could also explain the significant and negative Tajima’s D estimated for the gene (Tables 1 and 2). The low global proportion of haplotypes shared between countries for both genes suggests substantial genetic differentiation among P. vivax populations, as confirmed by high FST values (Tables 5 and 6). We also observed some degree of geographic clustering for haplotypes from the Americas; specifically, a divergent clade for the pvs28 gene characterized by the replacements located at the positions 87(D/N) and 110(N/Y) that were only found in the Americas (S1 Table). Both networks suggest that some of the haplotypes from the Americas could be derived from Asian populations [52,53]; however, the pattern is consistent with previous finding indicating that there was not a recent or single introduction of P. vivax into the continent [18].
We performed a comparative polymorphism analysis between pvs25 and pvs28 and their orthologous genes in the Asian Old World monkey parasites that are closely related: P. cynomolgi, P. inui and P. knowlesi. In contrast to the relatively low genetic diversity observed in P. vivax and P. knowlesi, the orthologs in P. cynomolgi and P. inui exhibited significantly higher variability. Similar observations have been also reported for genes expressed in asexual Plasmodium stages [19,45]. This pattern could be the result of the different demographic histories of these two parasites when compared to P. vivax and P. knowlesi. Consistently with the effect of demographic differences, the same pattern has been found in the mtDNA and other genes that are considered neutral [19, 54].
Interestingly, both Pvs28 and Pvs25 proteins showed higher variation at the EGF2 and EGF3 like domains where epitope recognition sites have been identified for blocking antibodies in Pvs25 [5], and predicted for Pvs28 [6] and Pb28 in P. berghei [55]. Noteworthy, EGF-like domains in the orthologous protein Pfs25 have shown differential immune blocking activity after being separately expressed as a yeast-secreted recombinant protein. In particular, antibodies against the EGF2 domain elicited the strongest blocking activity indicating that this domain might be a good target for TBVs [56].
The EGF-like domains in Plasmodium spp. are relatively conserved among genes and closely related species (S1 Fig). A similar pattern has been described in other EGF-like domains expressed in surface proteins from the merozoite, including MSP-4 [57], MSP-5 [58], MSP-8 and MSP-10 [45]. When we estimated the genetic diversity in P. cynomolgi, P. inui, and P. vivax, we observed regions with relatively high polymorphism in EGF2 and EGF3 in both genes (S3 Fig). How this variation affects protein folding and functionality is a matter that remains elusive. However, it has been proposed that EGFs domains can accommodate genetic changes such as gene polymorphism, mutations, insertions and deletions [55]. Consequently, structural folds in the P28 and P25 proteins may not be significantly affected by the observed amino acid changes in natural populations thereby preserving functionality.
Previous investigations suggested that the p28 and p25 coding genes were originated as result of a gene duplication event that was prior to the origin of the species included in this investigation [4]. When a duplicated gene neither adapts to a more specialized function nor is silenced by deleterious mutations and continues producing a functional protein, purifying selection could act on both paralogs keeping some level of functional redundancy [59]. Consistently, gene knockouts of either p25 (P25Sko) or p28 (P28Sko) alone in P. berghei have non-significant effects on oocyst production in infected Anopheles stephensi mosquitoes. However, concomitant disruption of both genes (Dko) strongly inhibited oocyst production up to 99% [4].
It is worth noting that duplication events have been reported for p28 in P. ovale [23] and P. cynomolgi [24] (confirmed here in the Berok strain, S4 Fig). Furthermore, in the case of P. cynomolgi, we found evidence of an excess of synonymous over nonsynonymous substitutions in the p28 paralogous gene PCYB-007100 and PCYB-062530 suggesting purifying selection (S3 Table, S4 Fig). Thus, without evidence indicating pseudogenization and patterns consistent with purifying selection, we can speculate that both p28 paralogous remain functional in P. cynomolgi.
We searched for evidence of episodic selection as a consequence of changes in ecology/vectors during the evolution of the species include in this study; however, we did not find it. Only the branch leading to P. falciparum indicated positive selection in p28, a finding that is worth exploring whenever additional Laverania species become available. We also explored the effect of selection on the pvs28 and pvs25 polymorphisms by performing the MK test and applying codon models such as REL. Their caveat is that these tests usually underperform even when adaptive evolution is present so they are regarded as conservative [60]. The MK test detected evidence for balancing selection in pvs25. A similar pattern of synonymous/non-synonymous sites within P. vivax and its divergence to P. cynomolgi and P. inui was found for pvs28 (see S5 Table), but not significant (p > 0.05). The Bayesian base method (REL), however, detected codons under selection in pvs28. In particular, the data provided very strong evidence for selection on three pvs28 codons with two of those codons, 113 and 116 (Fig 2), yielding BF factors above 100. These two codons are located in the EGF3 domain. We also found other codons in pvs28 and pvs25 where the data provided some evidence of those being under positive selection but their BF did not exceed our 50 threshold defined a priori. Those residues are indicated with yellow arrows in Fig 2.
The patterns consistent with positive selection acting on the pvs28 and pvs25 polymorphism deserve special attention. Whereas the genetic polymorphism observed on surface antigens from the asexual stage has been commonly associated to the selective pressure exerted by the vertebrate immune system [61,62], proteins expressed in the sexual stage may adapt to diverse microenvironments inside Anopheles mosquitoes where parasites have to go through in order to complete their life cycle [63]. The fact that anti-Pvs28 and anti-Pvs25 polyclonal antibodies completely block parasite transmission (Pv-Sal I) in four species of Anopheles mosquitoes [8] indicates that these proteins are essential during this phase of the parasite life-cycle. Whether pvs25 and pvs28 facilitate the Plasmodium transit through Anopheles physical barriers and by so doing, increase the parasite (and may be the vector) fitness is a matter that needs to be investigated [64,65].
The evolutionary and functional implications of LCR in P28 proteins are still elusive. In the case of asexual Plasmodium stages, they may have a role interacting with the host adaptive immune system [66,67]. However, such adaptive immune responses are absent in Anopheles vectors with the exception of some components from the vertebrate immune system contained in the blood bolus. The P28 LCR has been predicted to be part of a big C-loop, a fast evolving region forming a sheet over the ookinete surface that may affect the binding properties of the protein [6]. Furthermore, other studies have found that terminal LCR, like the one observed in P28, may confer more protein binding capacity [68]. This evidence suggests that the P28 LCR is functionally important. This possibility finds also support on the significant excess of synonymous over nonsynonymous changes on the motifs of most of the NHPPs P28 studied (p >0.05) (S7 Table), which indicate evolutionary constrains and not simply conservation from continued homogenization due to gene conversion. Nevertheless, assessing the importance of the LCR on P28 requires experimental evidence that is not currently available.
In summary, we explored the genetic polymorphism of pvs28 and pvs25, and investigated the long term evolution of the genes encoding these antigens within the genus Plasmodium. Although they were less diverse than many pre-erythrocytic and erythrocytic stage expressed antigens; their polymorphisms were comparable to others such as MSP-8 and MSP-10. We also found that these genes exhibit comparable diversities in the Americas and in Asia indicating that the use of TBVs against Pvs28 and Pvs25 will likely face similar challenges in both regions. Furthermore, we found two amino acid replacements in Pvs28 (positions 87(D/N) and 110(N/Y)) that appear to be specific for the Americas. Finally, there are polymorphisms that could be maintained by positive selection in both genes and the importance of such observation deserves to be explored. The observation that anti-Pvs28 and anti-Pvs25 polyclonal antibodies can block parasite transmission in some species of Anopheles mosquitoes [8] indicates that polymorphism in these proteins could indeed affect the parasite fitness. In particular, pvs25 and pvs28 polymorphisms could be the result of differences in vectors acting as selective pressure in some ecological contexts. Consequently, it is possible that a vaccine elicited transmission blocking immune response may not be equally effective across all vector-parasite associations in all epidemiological settings. In this context, exploring the diversity of local alleles and their interactions with specific Anopheles species could provide useful information on how to assess TBV efficacy, as well as, how to better deploy these vaccines, even partially effective ones, in the context of malaria control and elimination.
Supporting Information
S1 Table. Pvs28 worldwide amino acids polymorphisms in P. vivax and closely NHPs malarias.
The amino acid variants of the Pvs28 protein were compared against the Salvador I strain (GenBank: AF083503.2) in according to the gene domain and geographic region. Amino acids changes in NHPPs orthologous genes for the correspondent nonsynonymous change in P. vivax are also showed. LCR of tandem repeats were excluded. [*] denotes new substitutions found to either a specific region or not previously reported. (&): Present work; AA: amino acid.
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S2 Table. Pvs25 worldwide amino acids polymorphisms in P. vivax and closely NHPs malarias.
The amino acid variants of the Pvs25 protein were compared against the Salvador I strain (GenBank: AF083502.1) in according to the gene domain and geographic region. Amino acids changes in NHPP orthologous genes for the correspondent nonsynonymous change in P. vivax are also showed. LCR of tandem repeats were excluded. [*] denotes new substitutions found to either a specific region or not previously reported. (&): Present work; AA: amino acid.
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S3 Table. P28 polymorphism by gene CDS and gene-domain in Plasmodium spp.
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S4 Table. P25 polymorphism by gene CDS and gene-domain in Plasmodium spp.
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S5 Table. McDonald & Kreitman test for the pvs28 and pvs25 genes.
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S6 Table. Likelihood ratio test statistics for Adaptive BSREL and BUSTED analysis of the p28 and p25 genes (18 and 17 species respectively).
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S7 Table. Worldwide short tandem repeats in the Pvs28 and NHPPs orthologs.
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S8 Table. Polymorphism in the repetitive motif of the Pvs28 protein and closely NHPPs orthologs.
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S1 Fig. Alignment of the deduced amino acid sequences of the P28 and P25 genes.
All genes shared a similar gene structure consisting of a signal sequence of 23 amino acids at the N-terminus followed by four cysteine-rich EGF-like domains and a short GPI anchor region at the C-terminus. Cysteines are conserved among Plasmodium spp. The species names are abbreviated as follow: Pv, P. vivax; Pcy, P. cynomolgi; Pfi, P. fieldi; Psi, P. simiovale; Pin, P. inui; Phy, P. hylobati; Pco, P. coatneyi; Pk, P. knowlesi; Pgo, P. gonderi; Pov, P. ovale; Pyo, P. yoelii; Pbe, P. berghei; P. vin, P. vinckei; Pcha, P. chabaudi; Pga, P. gallinaceum; Pre, P. reichenowi; Pf, P. falciparum, and Pga, P. gaboni.
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S2 Fig.
Amino acid composition of the P28 (A) and P25 (B) proteins for P. vivax and closely NHP malarias.
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S3 Fig.
Sliding window analysis of the nucleotide diversity (π) of the p28 gene (A), P. cynomolgi p28 paralogous genes (B), and the p25 gene (C). The genetic diversity was estimated by calculating (π) on a window of 50 base pairs moving it in steps of 10 sites. LCR were not included.
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S4 Fig.
Bayesian phylogenetic hypothesis constructed using nucleotide sequences of the genes encoding the P28 (A) and P25 (B) antigens from Plasmodium spp. and strains amplified in this study. The values above branches are posterior probabilities (see Methods section). For both phylogenies (p28 and p25), two independent chains were sampled every 200 generations in runs lasting 6 × 106 Markov Chain Monte Carlo steps. In the case of P28 (A), the clade of P. cynomolgi consists of three subgroups (1–3). “1” refers to the lineage “PCYB-062530”, which includes strains of its orthologous gene (Ceylonensi, Smithsonian, Gombak). The “2” and “3” subgroups refer to the lineages “PCYB-007100” (Mulligan, PT-1, BX-20, RO) and “PCYB-062510” (Cambodia) respectively, which contain strains corresponding to its paralogous genes.
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Acknowledgments
We thank Amanda Poe, Ascanio Rojas, Harold de Vladar, and Milagro Rinaldi for productive discussions and technical support. We thank the late William E. Collins from the Centers for Disease Control and Prevention for providing access to valuable specimens. We thank Judith Recht for editing the manuscript. The authors also thank the DNA laboratory at the School of Life Sciences, Arizona State University, for their technical support. The content is solely the responsibility of the authors and does not represent the official views of the NIH.
Author Contributions
Conceived and designed the experiments: MAP SH AAE. Performed the experiments: RAC MAP ED. Analyzed the data: MAP OEC CES AIC. Contributed reagents/materials/analysis tools: CES SH AAE. Wrote the paper: RAC MAP OEC CES AIC SH AAE.
References
- 1. Wu Y, Sinden RE, Churcher TS, Tsuboi T, Yusibov V. Development of malaria transmission-blocking vaccines: from concept to product. Adv Parasitol. 2015;89: 109–152. pmid:26003037
- 2. Tsuboi T, Kaslow DC, Cao YM, Shiwaku K, Torii M. Comparison of Plasmodium yoelii ookinete surface antigens with human and avian malaria parasite homologues reveals two highly conserved regions. Mol Biochem Parasitol. 1997;87: 107–111. pmid:9233679
- 3. Tsuboi T, Kaslow DC, Gozar MM, Tachibana M, Cao YM, Torii M. Sequence polymorphism in two novel Plasmodium vivax ookinete surface proteins, Pvs25 and Pvs28, that are malaria transmission-blocking vaccine candidates. Mol Med. 1998;4: 772–782. pmid:9990863
- 4. Tomas AM, Margos G, Dimopoulos G, van Lin LH, de Koning-Ward TF, Sinha R, et al. P25 and P28 proteins of the malaria ookinete surface have multiple and partially redundant functions. EMBO J. 2001;20: 3975–3983. pmid:11483501
- 5. Saxena AK, Singh K, Su HP, Klein MM, Stowers AW, Saul AJ, et al. The essential mosquito-stage P25 and P28 proteins from Plasmodium form tile-like triangular prisms. Nat Struct Mol Biol. 2006;13: 90–91. pmid:16327807
- 6. Sharma B, Ambedkar RD, Saxena AK. A very large C-loop in EGF domain IV is characteristic of the P28 family of ookinete surface proteins. J Mol Model. 2009;15: 309–321. pmid:19057932
- 7. del Carmen Rodriguez M, Gerold P, Dessens J, Kurtenbach K, Schwartz RT, Sinden RE, et al. Characterisation and expression of pbs25, a sexual and sporogonic stage specific protein of Plasmodium berghei. Mol Biochem Parasitol. 2002;110: 147–159.
- 8. Hisaeda H, Stowers AW, Tsuboi T, Collins WE, Sattabongkot JS, Suwanabun N, et al. Antibodies to malaria vaccine candidates Pvs25 and Pvs28 completely block the ability of Plasmodium vivax to infect mosquitoes. Infect Immun. 2000;68: 6618–6623. pmid:11083773
- 9. Arévalo-Herrera M, Solarte Y, Yasnot MF, Castellanos A, Rincón A, Saul A, et al. Induction of transmission-blocking immunity in Aotus monkeys by vaccination with a Plasmodium vivax clinical grade PVS25 recombinant protein. Am J Trop Med Hyg. 2005;73: 32–37.
- 10. Malkin EM, Durbin AP, Diemert DJ, Sattabongkot J, Wu Y, Miura K, et al. Phase 1 vaccine trial of Pvs25H: a transmission blocking vaccine for Plasmodium vivax malaria. Vaccine 2005;23: 3131–3138. pmid:15837212
- 11. Kubler-Kielb J, Majadly F, Wu Y, Narum DL, Guo C, Miller LH, et al. Long-lasting and transmission-blocking activity of antibodies to Plasmodium falciparum elicited in mice by protein conjugates of Pfs25. Proc Natl Acad Sci USA. 2007;104: 293–298. pmid:17190797
- 12. Sattabongkot J, Tsuboi T, Hisaeda H, Tachibana M, Suwanabun N, Rungruang T, et al. Blocking of transmission to mosquitoes by antibody to Plasmodium vivax malaria vaccine candidates Pvs25 and Pvs28 despite antigenic polymorphism in field isolates. Am J Trop Med Hyg. 2003;69: 536–541. pmid:14695092
- 13. Feng H, Zheng L, Zhu X, Wang G, Pan Y, Li Y, et al. Genetic diversity of transmission-blocking vaccine candidates Pvs25 and Pvs28 in Plasmodium vivax isolates from Yunnan Province, China. Parasit Vectors. 2011;4: 224. pmid:22117620
- 14. Gonzalez-Ceron L, Alvarado-Delgado A, Martinez-Barnetche J, Rodriguez MH, Ovilla-Munoz M, Pérez F, et al. Sequence variation of ookinete surface proteins Pvs25 and Pvs28 of Plasmodium vivax isolates from Southern Mexico and their association to local anophelines infectivity. Infect Genet Evol. 2010;10: 645–654. pmid:20363376
- 15. Han ET, Lee WJ, Sattabongkot J, Jang JW, Nam MH, An SS, et al. Sequence polymorphisms of Plasmodium vivax ookinete surface proteins (Pvs25 and Pvs28) from clinical isolates in Korea. Trop Med Int Health. 2010;15: 1072–1076. pmid:20545923
- 16. Prajapati SK, Joshi H, Dua VK. Antigenic repertoire of Plasmodium vivax transmission-blocking vaccine candidates from the Indian subcontinent. Malar J. 2011;10: 111. pmid:21535892
- 17. Zakeri S, Razavi S, Djadid ND. Genetic diversity of transmission blocking vaccine candidate (Pvs25 and Pvs28) antigen in Plasmodium vivax clinical isolates from Iran. Acta Trop. 2009;109: 176–180. pmid:18950597
- 18. Taylor JE, Pacheco MA, Bacon DJ, Beg MA, Machado RL, Fairhurst RM, et al. The evolutionary history of Plasmodium vivax as inferred from mitochondrial genomes: parasite genetic diversity in the Americas. Mol Biol Evol. 2013;30: 2050–2064. pmid:23733143
- 19. Escalante AA, Cornejo OE, Freeland DE, Poe AC, Durrego E, Collins WE, et al. A monkey's tale: the origin of Plasmodium vivax as a human malaria parasite. Proc Natl Acad Sci USA. 2005;102: 1980–1985. pmid:15684081
- 20. Tsuboi T, Kaneko O, Cao YM, Tachibana M, Yoshihiro Y, Nagao T, et al. A rapid genotyping method for the vivax malaria transmission-blocking vaccine candidates, Pvs25 and Pvs28. Parasitol Int. 2004;53(3):211–6. pmid:15468527
- 21.
Coatney RG, Collins WE, Warren M, Contacos PG. The Primate Malarias. Washington, DC: US Government Printing Office; 1971.
- 22. Aurrecoechea C, Brestelli J, Brunk BP, Dommer J, Fischer S, Gajria B, et al. PlasmoDB: a functional genomic database for malaria parasites. Nucleic Acids Res. 2009;37: D539–543. pmid:18957442
- 23. Tachibana M, Tsuboi T, Templeton TJ, Kaneko O, Torii M. Presence of three distinct ookinete surface protein genes, Pos25, Pos28-1, and Pos28-2, in Plasmodium ovale. Mol Biochem Parasitol. 2001;113: 341–344. pmid:11295191
- 24. Tachibana S, Sullivan SA, Kawai S, Nakamura S, Kim HR, Goto N, et al. Plasmodium cynomolgi genome sequences provide insight into Plasmodium vivax and the monkey malaria clade. Nat Genet. 2012;44: 1051–1055. pmid:22863735
- 25. Edgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004;5: 113. pmid:15318951
- 26. Gouy M, Guindon S, Gascuel O. SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol Biol Evol. 2010;27: 221–224. pmid:19854763
- 27. Rich SM, Hudson RR, Ayala FJ. Plasmodium falciparum antigenic diversity: evidence of clonal population structure. Proc Natl Acad Sci USA. 1997;94: 13040–13045. pmid:9371796
- 28. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123: 585–595. pmid:2513255
- 29. Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics. 2003;19: 2496–2497. pmid:14668244
- 30. Nei M, Gojobori T. Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol Biol Evol. 1986;3: 418–426. pmid:3444411
- 31. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol. 2013;30: 2725–2729. pmid:24132122
- 32.
Nei M, Kumar S. Molecular evolution and phylogenetics. NY: Oxford University Press; 2000.
- 33. Kosakovsky Pond SL, Frost SD. Not so different after all: a comparison of methods for detecting amino acid sites under selection. Mol Biol Evol. 2005;22: 1208–1222. pmid:15703242
- 34. McDonald JH, Kreitman M. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 1991;351: 652–654. pmid:1904993
- 35. Kosakovsky Pond SL, Posada D, Gravenor MB, Woelk CH, Frost SD. GARD: a genetic algorithm for recombination detection. Bioinformatics. 2006;22: 3096–3098. pmid:17110367
- 36. Delport W, Poon AF, Frost SD, Kosakovsky Pond SL. Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics. 2010;26: 2455–2457. pmid:20671151
- 37. Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012;61: 539–542. pmid:22357727
- 38. Smith MD, Wertheim JO, Weaver S, Murrell B, Scheffler K, Kosakovsky Pond SL. Less is more: an adaptive branch-site random effects model for efficient detection of episodic diversifying selection. Mol Biol Evol. 2015;32: 1342–1353. pmid:25697341
- 39. Murrell B, Weaver S, Smith MD, Wertheim JO, Murrell S, Aylward A, et al. Gene-wide identification of episodic selection. Mol Biol Evol. 2015;32: 1365–1371. pmid:25701167
- 40. Collins WE, Richardson BB, Morris CL, Sullivan JS, Galland GG. Salvador II strain of Plasmodium vivax in Aotus monkeys and mosquitoes for transmission-blocking vaccine trials. Am J Trop Med Hyg. 1998;59: 29–34. pmid:9684622
- 41. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Prot. 2015;10: 845–858.
- 42. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J Mol Graph. 1996;14: 33–38. pmid:8744570
- 43. Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8: 785–786. pmid:21959131
- 44. Escalante AA, Freeland DE, Collins WE, Lal AA. The evolution of primate malaria parasites based on the gene encoding cytochrome b from the linear mitochondrial genome. Proc Natl Acad Sci USA. 1998;95: 8124–8129. pmid:9653151
- 45. Pacheco MA, Elango AP, Rahman AA, Fisher D, Collins WE, Barnwell JW, et al. Evidence of purifying selection on merozoite surface protein 8 (MSP8) and 10 (MSP10) in Plasmodium spp. Infect Genet Evol. 2012;12: 978–986. pmid:22414917
- 46. Pacheco MA, Poe AC, Collins WE, Lal AA, Tanabe K, Kariuki SK, et al. A comparative study of the genetic diversity of the 42kDa fragment of the merozoite surface protein 1 in Plasmodium falciparum and P. vivax. Infect Genet Evol. 2007;7: 180–187. pmid:17010678
- 47. Pacheco MA, Ryan EM, Poe AC, Basco L, Udhayakumar V, Collins WE, et al. Evidence for negative selection on the gene encoding rhoptry-associated protein 1 (RAP-1) in Plasmodium spp. Infect Genet Evol. 2010;10: 655–661. pmid:20363375
- 48. Przysiecki C, Lucas B, Mitchell R, Carapau D, Wen Z, Xu H, et al. Sporozoite neutralizing antibodies elicited in mice and rhesus macaques immunized with a Plasmodium falciparum repeat peptide conjugated to meningococcal outer membrane protein complex. Front Cell Infect Microbiol. 2012;2: 146. pmid:23226683
- 49. Winter DJ, Pacheco MA, Vallejo AF, Schwartz RS, Arevalo-Herrera M, Herrera S, et al. Whole Genome Sequencing of Field Isolates Reveals Extensive Genetic Diversity in Plasmodium vivax from Colombia. PLoS Negl Trop Dis. 2015;9: e0004252. pmid:26709695
- 50. Kang JM, Ju HL, Moon SU, Cho PY, Bahk YY, Sohn WM, et al. Limited sequence polymorphisms of four transmission-blocking vaccine candidate antigens in Plasmodium vivax Korean isolates. Malar J. 2013;12: 144. pmid:23631662
- 51. Takala SL, Coulibaly D, Thera MA, Batchelor AH, Cummings MP, Escalante AA, et al. Extreme polymorphism in a vaccine antigen and risk of clinical malaria: implications for vaccine development. Sci Transl Med. 2009;14:1(2):2ra5. pmid:20165550
- 52. Cornejo OE, Escalante AA. The origin and age of Plasmodium vivax. Trends Parasitol. 2006;22: 558–563. pmid:17035086
- 53. Culleton R, Coban C, Zeyrek FY, Cravo P, Kaneko A, Randrianarivelojosia M, et al. The origins of African Plasmodium vivax; insights from mitochondrial genome sequencing. PLoS One. 2011;6: e29137. pmid:22195007
- 54. Pacheco MA, Reid MJ, Schillaci MA, Lowenberger CA, Galdikas BM, Jones-Engel L, Escalante AA. The origin of malarial parasites in orangutans. PLoS One. 2012;7: e34990. pmid:22536346
- 55. Sharma B, Jaiswal MK, Saxena AK. EGF domain II of protein Pb28 from Plasmodium berghei interacts with monoclonal transmission blocking antibody 13.1. J Mol Model. 2009;15: 369–382. pmid:19066995
- 56. Stowers AW, Keister DB, Muratova O, Kaslow DC. A region of Plasmodium falciparum antigen Pfs25 that is the target of highly potent transmission-blocking antibodies. Infect Immun. 2000;68: 5530–5538. pmid:10992450
- 57. Putaporntip C, Jongwutiwes S, Ferreira MU, Kanbara H, Udomsangpetch R, Cui L. Limited global diversity of the Plasmodium vivax merozoite surface protein 4 gene. Infect Genet Evol. 2009;9: 821–826. pmid:19409511
- 58. Gomez A, Suarez CF, Martinez P, Saravia C, Patarroyo MA. High polymorphism in Plasmodium vivax merozoite surface protein-5 (MSP5). Parasitology. 2006;133: 661–672. pmid:16978450
- 59. Innan H, Kondrashov F. The evolution of gene duplications: classifying and distinguishing between models. Nat Rev Genet. 2010;11: 97–108. pmid:20051986
- 60. Charlesworth J, Eyre-Walker A. The McDonald-Kreitman test and slightly deleterious mutations. Mol Biol Evol. 2008;25: 1007–1015. pmid:18195052
- 61. Conway DJ, Polley SD. Measuring immune selection. Parasitology. 2002;125 Suppl: S3–16. pmid:12622324
- 62. Escalante AA, Cornejo OE, Rojas A, Udhayakumar V, Lal AA. Assessing the effect of natural selection in malaria parasites. Trends Parasitol. 2004; 20: 388–395. pmid:15246323
- 63. Moreno-Garcia M, Recio-Totoro B, Claudio-Piedras F, Lanz-Mendoza H. Injury and immune response: applying the danger theory to mosquitoes. Front Plant Sci. 2014;5: 451. pmid:25250040
- 64. Churcher TS, Dawes EJ, Sinden RE, Christophides GK, Koella JC, Basáñez MG. Population biology of malaria within the mosquito: density-dependent processes and potential implications for transmission-blocking interventions. Malar J. 2010;9: 311. pmid:21050427
- 65. Sinden RE, Dawes EJ, Alavi Y, Waldock J, Finney O, Mendoza J. Progression of Plasmodium berghei through Anopheles stephensi is density-dependent. PLoS Pathog. 2007;3: e195. pmid:18166078
- 66. Hughes AL. The evolution of amino acid repeat arrays in Plasmodium and other organisms. J Mol Evol. 2004;59: 528–535. pmid:15638464
- 67. Battistuzzi FU, Schneider KA, Spencer MK, Fisher D, Chaudhry S, Escalante AA. Profiles of low complexity regions in Apicomplexa. BMC Evol Biol. 2016;16: 47. pmid:26923229
- 68. Coletta A, Pinney JW, Solis DY, Marsh J, Pettifer SR, Attwood TK. Low-complexity regions within protein sequences have position-dependent roles. BMC Syst Biol. 2010;4: 43. pmid:20385029