Skip to main content

Global diversity of the gene encoding the Pfs25 protein—a Plasmodium falciparum transmission-blocking vaccine candidate

Abstract

Background

Vaccines against the sexual stages of the malarial parasite Plasmodium falciparum are indispensable for controlling malaria and abrogating the spread of drug-resistant parasites. Pfs25, a surface antigen of the sexual stage of P. falciparum, is a leading candidate for transmission-blocking vaccine development. While clinical trials have reported that Pfs25-based vaccines are safe and effective in inducing transmission-blocking antibodies, the extent of the genetic diversity of Pfs25 in malaria endemic populations has rarely been studied. Thus, this study aimed to investigate the global diversity of Pfs25 in P. falciparum populations.

Methods

A database of 307 Pfs25 sequences of P. falciparum was established. Population genetic analyses were performed to evaluate haplotype and nucleotide diversity, analyze haplotypic distribution patterns of Pfs25 in different geographical populations, and construct a haplotype network. Neutrality tests were conducted to determine evidence of natural selection. Homology models of the Pfs25 haplotypes were constructed, subjected to molecular dynamics (MD), and analyzed in terms of flexibility and percentages of secondary structures.

Results

The Pfs25 gene of P. falciparum was found to have 11 unique haplotypes. Of these, haplotype 1 (H1) and H2, the major haplotypes, represented 70% and 22% of the population, respectively, and were dominant in Asia, whereas only H1 was dominant in Africa, Central America, and South America. Other haplotypes were rare and region-specific, resulting in unique distribution patterns in different geographical populations. The diversity in Pfs25 originated from ten single-nucleotide polymorphism (SNP) loci located in the epidermal growth factor (EGF)-like domains and anchor domain. Of these, an SNP at position 392 (GGA/GCA), resulting in amino acid substitution 131 (Gly/Ala), defined the two major haplotypes. The MD results showed that the structures of H1 and H2 variants were relatively similar. Limited polymorphism in Pfs25 could likely be due to negative selection.

Conclusions

The study successfully established a Pfs25 sequence database that can become an essential tool for monitoring vaccine efficacy, designing assays for detecting malaria carriers, and conducting epidemiological studies of P. falciparum. The discovery of the two major haplotypes, H1 and H2, and their conserved structures suggests that the current Pfs25-based vaccines could be used globally for malaria control.

Graphical Abstract

Background

The Plasmodium parasite must complete its development in a vertebrate host and transmit to a vector to continue its life cycle. Sexual stages of the malaria parasite, from gametocytes in the vertebrate host to ookinetes in the mosquito, offer potential targets for malaria intervention [1,2,3]. Although the numbers of gametocytes in the blood circulation are relatively fewer than the blood-stage parasites, and gametocytes can weakly induce immune responses [4], studies have shown that antibodies induced by vaccination with gametocyte and gamete antigens, such as Pfs48/45, Pfs47, and Pfs230, could interfere with gametocytogenesis and thereby may reduce the number of gametes and/or block fertilization [5,6,7]. Similarly, zygote- or midgut ookinete-targeting antibodies, such as Pfs25, have been experimentally induced and shown to effectively block malaria transmission [8,9,10]. These antigens are the leading candidates for transmission-blocking vaccine development. Such vaccines aim to reduce the spread of the malaria parasite among humans by preventing infections by Anopheles mosquito vectors, thereby representing an important tool for malaria control [11].

Pfs25, a Cys-rich protein comprised of 217 amino acid residues, has a molecular weight of 25 kDa [12] and is encoded by the Pfs25 gene that spans 654 bp in size and is located on chromosome 10 of P. falciparum [13, 14]. Pfs25 expression, which can be detected as early as in macrogametes, dramatically increases in the zygotes and maturing ookinetes [15, 16]. Pfs25 contains a predicted signal sequence at the N-terminus, followed by four tandem epidermal growth factor (EGF)-like domains attached to the anchor domain at the C-terminus; the structure is stabilized with 22 Cys forming 11 disulfide bonds [17]. The EGF-like domain acts as a ligand interacting with laminin, which is located at the basal lamina of the midgut epithelium of the mosquito. The interaction between Pfs25 and the laminin proteins forms the receptor/ligand complex, which can regulate the development of the malaria parasite in the mosquito vector [18]. Homologs of Pfs25 have been identified in other species of human malaria parasite P. vivax (Pvs25) and in a rodent malaria parasite P. berghei (Pbs25) [19,20,21]. The genetic disruption of Pbs25 results in a partial inhibition of malaria transmission to A. stephensi, whereas double knockout of Pbs25 and ookinete gene Pbs28 results in a nearly 100% reduction in oocyst formation, thereby blocking malaria transmission completely [22]. These studies demonstrate that Pfs25 could play an important role in the sexual stage development of the malaria parasite. Furthermore, P. berghei expressing Pfs25 is susceptible to anti-Pfs25 antibodies of humans [23, 24]. Thus, this system could provide a platform for assessing and optimizing Pfs25-based vaccines.

Currently, recombinant Pfs25 proteins have been produced in different heterologous expression systems and are the only sexual stage antigen tested in clinical trials [25,26,27,28,29]. The vaccine, Pfs25-B, was originally made from a synthetic antigen containing amino acids 22–190 of the natural 217 amino acid precursor protein of P. falciparum, 3D7 (cloned line originally derived from isolate NF54) [12, 25]. The antigen was modified by removing the signal peptide at the N-terminal and the hydrophobic region. Subsequently, a second-generation vaccine, TBV25H (later known as Pfs25H), was constructed by addition of the last Cys residue of the fourth EGF-like domain, mutagenesis of Asn-linked glycosylation sites with Glu rather than Ala, and addition of a 6 His-tag for efficient purification [30]. Subsequently, many modifications have been employed to increase the homogeneity and conformational integrity of the vaccine antigen and to boost immunogenicity [31, 32]. Data from phase 1 clinical trial have shown that the Pfs25 vaccine formulation, Montanide ISA 51 (Pfs25/ISA51), showed good immunogenicity; sera obtained from vaccinated volunteers contained transmission-blocking antibodies [33]. Subsequently, Pfs25 vaccine was formulated in Alhydrogel® and conjugated with a recombinant detoxified ExoProtein A from the common Gram-negative bacterium Pseudomonas aeruginosa [29, 34]. Phase 1 trial results showed that the vaccine was safe and well tolerated in healthy adults, supporting their further evaluation in clinical phase 2 trials. More recently, Pfs25 has been incorporated in a multi-stage malaria vaccine, RTS,S and Pfs25-IMX313, which has been tested in a pre-clinical trial [35]. Taken together, these studies support the view that Pfs25 is the leading candidate for malaria transmission-blocking vaccines.

One important aspect of vaccine development against the malaria parasite is the antigenic diversity of the vaccine candidates. Genetic polymorphisms in the malaria parasite, caused by mutations during the parasite development in the mammalian host and vector as well as through sexual recombination, could allow the malarial to escape the immunity of the host [36]. Additionally, this could impede vaccine development since the vaccines can target only a specific subset of antigens circulating in the malaria parasite populations [37]. Genetic analyses of the antigens expressed in the blood stage of the malaria parasite, including merozoite surface proteins and apical membrane antigens, have revealed extensive polymorphisms [38,39,40]. In contrast, the sexual stage antigens are believed to be less polymorphic, and so analysis of their genetic diversity is often neglected. To date, only a few studies have reported the sequence diversity of the ookinete antigen Pfs25. One study analyzed the promotor sequences of Pfs25 and identified short deletion mutations in the promotor region, which were associated with the inactivation of promoter activities and reduction of gametocyte production in P. falciparum [41]. Two studies have reported full-length Pfs25 sequences of P. falciparum, 10 laboratory strains, and 41 isolates from Burkina Faso and Thailand (from Tak province, Western Thailand) [10, 13]. The studies revealed that there were only two Pfs25 haplotypes (haplotype 1 and haplotype 2) that differed by one amino acid substitution at position A131G. Other studies have reported partial sequences of Pfs25 from P. falciparum isolates in India [42, 43]. Here, the authors identified the A131G mutation and a novel mutation at V131A (haplotype 3). However, none of these studies have combined P. falciparum sequence data from public databases to illustrate the global diversity of Pfs25 in the endemic population worldwide.

Thus, the objective of this study was to determine the global genetic diversity of Pfs25, a transmission-blocking candidate gene. We sequenced Pfs25 from 83 isolates of P. falciparum from malaria hotspots in Thailand and combined them with 224 sequences from public databases to construct a global database of Pfs25 in P. falciparum. The sequence analysis of our findings will provide an important insight into the diversity and evolutionary relationship among the Pfs25 variants and reveal useful information for vaccine design.

Methods

Malaria parasite P. falciparum from Thailand

Plasmodium falciparum was isolated from patients from six areas in different regions of Thailand (Fig. 1) from 2001 to 2018. A total of 15, 16, and 15 isolates were obtained from Mae Hong Son, Kanchababuri, and Ranong, respectively, in the northwestern region along the Thailand-Myanmar border. Thirteen isolates were obtained from Ubon Ratchathani located at the Thailand-Laos border. Eleven isolates were obtained from Trat at the Thailand-Cambodia border. Additionally, 13 isolates were obtained from Yala at the southern Thailand-Malaysia border. In total, 83 isolates of P. falciparum were included in this study. The malaria parasite was characterized genetically using various markers to ensure that the parasites were clonal [38, 44]. All samples are maintained at Malaria Laboratory, Department of Biology, Faculty of Science, Chulalongkorn University. The parasite pellets were harvested from in vitro cultures and stored at − 80 °C for genomic DNA extraction.

Fig. 1
figure1

Distribution of Pfs25 haplotypes in Plasmodium falciparum from Thailand. The proportion of Pfs25 haplotypes in a all P. falciparum populations in Thailand and b in six subpopulations. Four sites (Mae Hong Son, Tak, Kanchaburi, and Ranong) were located along the Thailand-Myanmar border. Trat, Ubol Ratchatani, and Yala were located at the Thailand-Laos, Thailand-Cambodia, and Thailand-Malaysia borders, respectively. *Data were from Da et al. [10]

Generation of Pfs25 sequences

Genomic DNA was extracted from the parasite pellets using Nucleospin Blood Kit (Qiagen, Thailand) according to the manufacturer’s instructions. The genomic DNA was dissolved in TE buffer and stored at − 20 °C. The genomic DNA was used as the DNA template for amplifying the Pfs25 sequence using a standard polymerase chain reaction (PCR). Forward and reverse primers used were: 5ʹ-TGTTTTAACCTTGATAATTTACCATTT-3ʹ and 5ʹ-TCTTTGTTTTCTTCAATTTATTCAT-3ʹ, corresponding to the nucleotide positions 1,253,362–1,253,388 and 1,254,216–1,254,240, respectively, of chromosome 10 of P. falciparum strain 3D7 (NCBI reference sequence: NC_037281.1 [45]). The PCR reaction mix (20 µl) contained 4 µM forward and reverse primers, 2.5–20 ng/µl DNA template, 0.2 mM dNTPs, 4 mM MgCl2, 1 × PCR buffer, and 5 units of Hotstart Taq DNA polymerase (Biotechrabbit, Germany). The PCR conditions were: denaturation at 95 °C for 5 min, followed by 40 cycles of 95 °C for 30 s, 56 °C for 30 s, and 72 °C for 1 min, and then a final 60 °C for 5 min. The PCR products were analyzed using standard agarose gel electrophoresis, and all PCR samples produced a single amplicon. The PCR products were submitted to commercial Sanger DNA sequencing (Bioneer, South Korea). Sequence reactions were conducted using the two PCR primers and one additional sequencing primer, 5ʹ-TTTGTTTCTTTTCCTTTTCATTCA-3ʹ. All the sequences were analyzed in triplicate. After the chromatograms had been manually inspected, the sequences were assembled to generate the full-length coding sequences of Pfs25.

Construction of the global database of Pfs25

The Pfs25 sequences of P. falciparum were downloaded from the NCBI and PlasmoDB public databases. To retrieve Pfs25 sequences from the NCBI website, BLASTn (version 2.10.0) queries were conducted and the reference sequence was set as the Pfs25 sequence of P. falciparum 3D7 (ID: NC_037281.1). The databases for BLASTn search included the nucleotide collection (nr/nt) and whole-genome shotgun contigs. The cutoff was E value > 0.1. Additionally, publications reporting Pfs25 sequences of P. falciparum were searched against the PubMed database in the NCBI website. Pfs25 sequences were also retrieved from PlasmoDB [46]. Partial sequences of Pfs25, sequences of the same parasites (same clones or isolates), and sequences with ambiguous nucleotides were excluded from the analysis. The names of the parasite strain or isolate, country, and sequence ID were recorded to generate the global database of Pfs25 sequences of P. falciparum.

Sequence polymorphism analysis

Full-length coding sequences of Pfs25 were aligned in molecular evolutionary genetics analysis (MEGA) version 7.0 [47]. Each unique sequence was identified and treated as a haplotype. The genetic diversity indices, including H (number of haplotypes), Hd (haplotype diversity index), π (average number of nucleotide differences per site between two sequences), and k (average pairwise nucleotide difference between the sequences), were calculated using DnaSP version 6.0 [48]. The sliding window plots of π values were plotted against the nucleotide position with a window length of 100 bases and by moving the window in 3-bp steps. The haplotype network was constructed using PopART software (version 1.7) [49]. The median-joining network model was chosen for constructing the haplotype network.

Evidence of natural selection

Three neutrality tests (Tajima’s D, Fu and Li’s D*, and Fu and Li’s F* [50, 51]) were used for detecting the signature of natural selection using the DnaSP 6.0 software. The neutrality tests determine whether a polymorphism occurs at higher or lower frequencies than expected under a neutral model. Additionally, comparison of the mean number of non-synonymous substitutions per non-synonymous site (dN) and synonymous mutations per synonymous site (dS) within each isolate were estimated using Nei and Gojobori’s method, with the Jukes and Cantor correction, as implemented in MEGA 7.0 software [47]. The dN˗dS values were calculated to investigate the evidence of natural selection, where dN˗dS values > 0 imply a positive selection (selection favors an excess of non-synonymous mutations over synonymous mutations); dN˗dS values < 0 imply a purifying selection [52]; and no difference between dN and dS (dN = dS) implies neutral selection. Sliding window plots, with a window length of 100 bases and a step size of 3 bp, were generated for the neutrality tests, and dN˗dS was used to identify regions of Pfs25 where a significant departure from neutrality was observed (P < 0.05).

Tests for population differentiation

Distribution patterns (ratios) of Pfs25 haplotypes of P. falciparum in different geographic populations were tested using Wright’s fixation index (Fst) analysis in Arlequin version 3.5 [53]. Significant Fst was deemed at P < 0.05, indicating population differentiation between parasite population pairs.

Phylogenetic tree construction

Multiple sequence alignments of Pfs25 were generated using the MUSCLE algorithm in MEGA 7.0 [47]. The dataset contained 11 unique Pfs25 nucleotide sequences (haplotypes). A phylogenetic tree analysis was performed using the Bayesian inference (BI) approach implemented in BEAST (version 1.10.4) [54]. Hasegawa-Kishino-Yano + G (HKY + G), combining different equilibrium frequency distributions with unequal transition and transversion rates, was chosen as the substitution model. The posterior probability of the Bayesian tree was calculated by Markov chain Monte Carlo probability distribution sampling algorithm with a chain length of 10,000,000 and log parameters every 1,000. The BI tree was annotated with TreeAnnotator 1.10.4 using a burn-in of 10%. A phylogenetic tree based on the neighbor-joining (NJ) approach was constructed using PAUP [55], using the HKY85 model for NJ tree construction [56]. The reliability of the NJ tree was assessed by the bootstrap method of 1,000 pseudo-replicates. All trees were visualized with FigTree 1.4.3. Sequences of Prs25 gene from Plasmodium reichenowi chromosome 10 (NCBI ID: LT969573.1 and LVLA01000011.1 at nucleotide positions 1,179,907–1,180,560 and 1,168,471–1,169,124, respectively [57]) were used as the outgroup.

Structural analyses of Pfs25 variants

SWISS-MODEL server [58,59,60,61,62] was employed to construct the homology model of the Pfs25 haplotype of P. falciparum 3D7 (haplotype 1) based on the crystal structure of Pfs25 in complex with the human transmission-blocking antibody (PDB ID: 6PHB [8]), which has the highest sequence identity to the target sequence and contains the unique amino acid residues of Q91, Q144, and Q166 that are different from H1 and H2. Employing the LEaP module of AMBER18 [63], a model of H2 was constructed from the homology model of H1 by mutating G131 to A131.

All ionizable amino acids of H1, H2, and the Pfs2 crystal structure were protonated at the physiological pH (pH 7.4) using the H++ server [64]. Using the LEaP module of AMBER18 [63] and protein ff14SB force field [65], each system was immersed in an isomeric truncated octahedral box of TIP3P water molecules with a buffer distance of 13 Å and was then minimized to remove unfavorable interactions using a five-step procedure [66,67,68,69,70,71,72,73,74]. All steps included 2,500 steps of steepest descent and 2,500 steps of conjugate gradient with different restraints on the proteins. Initially, a force constant of 10 kcal/(mol Å2) was applied to restrain the heavy atoms of the protein, whereas those of water molecules and hydrogen atoms were minimized. Force constants of 10, 5, and 1 kcal/(mol Å2) were subsequently applied to the protein backbone. Finally, the entire system was minimized without any restraining force.

The GPU (CUDA) version of the PMEMD module [75,76,77] was employed to simulate all systems under the periodic boundary condition. All bonds involving hydrogen atoms were constrained using the SHAKE algorithm [78], allowing 0.002 ps time step simulations. Temperatures of all simulations were controlled with a collision frequency of 1.0 ps˗1 using the Langevin dynamics technique [79]. All systems were simulated from 0 K to the physiological temperature of 310 K for 200 ps in the NVT ensemble, while a force constant of 10 kcal/(mol Å2) was applied to restrain the backbones of the proteins. The systems were subsequently equilibrated at 310 K for 300 ps with no restraining force in the NVT ensemble. Finally, these systems were subsequently simulated at 310 K and 1 atm for 100 ns in the NPT ensemble.

Employing the cpptraj module [80] of AMBER18, the root mean square deviation (RMSD) values of the simulated structures with respect to the minimized structures were calculated to analyze the stability of the system (Additional file 1: Fig. S1). Since the trajectories in the range of 80 to 100 ns of all systems were found to be stable, based on their RMSD values, these trajectories were used for further analyses. The values of root mean square fluctuation (RMSF) of the backbone atoms of each residue were computed to analyze the structural flexibility. Definition secondary structure of protein (DSSP) was calculated to elucidate the percentages of the secondary structures of all systems. The secondary structures of the Pfs25 variants were also predicted using JPred4: a protein secondary structure prediction server [81].

Results

Haplotype analyses of Pfs25 in Thailand

Pfs25 sequences of P. falciparum from Thailand were retrieved from GenBank and PubMed databases. Six full-length Pfs25 sequences (654 bp in size) of P. falciparum isolates from the Tak province, northwestern Thailand, were obtained [10]. The sequences were classified into two haplotypes: haplotype 1 (n = 4, same as that of P. falciparum 3D7) and H2 (n = 2).

To expand the database, genomic DNA of P. falciparum isolates from six other endemic regions in Thailand was obtained (n = 83) and used as templates for PCR amplification of the full-length coding sequences of Pfs25. All PCR products were single amplicons and subsequently sequenced. Combining these with the sequences from GenBank and PubMed, a database of 89 full-length sequences of Pfs25 of P. falciparum isolates in Thailand were generated (Additional file 2: Table S1).

Sequence analysis of Pfs25 identified five additional haplotypes: H3 to H7. In total, there were seven Pfs25 haplotypes in the P. falciparum population in Thailand (Fig. 1 and Additional file 3: Table S2). Most of the sequences were H2, representing 69% of the parasite population in Thailand, and H2 was also the most widely distributed haplotype as it was detected in all regions. H1 was the second major haplotype, representing 15% of the parasite population, and was highly prevalent in the northwestern regions of Thailand. The others were minor haplotypes and locality-specific. These included three haplotypes (H4, H5, and H7) that were specific to the P. falciparum populations in Yala, while H6 was detected in P. falciparum in Mae Hong Son and Kanchanaburi. More than one haplotypes co-existed in each parasite population, with an average haplotype diversity index (Hd) ± standard deviation (SD) of 0.507 ± 0.059. Interestingly, the highest diversity appeared in P. falciparum in Yala (southern Thailand), wherein four haplotypes were identified with Hd ± SD of 0.654 ± 0.106. The lowest diversity was detected in Trat (eastern Thailand), where two haplotypes were detected, with a Hd ± SD of 0.327 ± 0.153. This result indicates that the haplotype diversity of Pfs25 could vary geographically in different parasite localities in Thailand.

Next, the distribution patterns of Pfs25 haplotypes among the malaria parasite populations in Thailand were compared using Wright’s (Fst) statistics. Table 1 shows that the Fst values were non-significant when the Pfs25 haplotypes of P. falciparum from four provinces in the northwestern region (Mae Hong Son, Tak, Kanchanaburi, and Ranong) were compared. Non-significant Fst values were also detected between P. falciparum populations in eastern and southern Thailand (Ubol Ratchatani, Trat, and Yala). In contrast, significant Fst values were detected when the Pfs25 alleles from the northwestern region were compared with those from the eastern and southern regions. This result indicates genetic differentiation in the P. falciparum populations in Thailand, wherein one comprised P. falciparum in northwestern Thailand and the other in eastern and southern Thailand.

Table 1 Fst analysis of Pfs25 alleles in different populations of Plasmodium falciparum in Thailand

Global haplotype diversity of Pfs25

To compare the Pfs25 haplotype diversity of P. falciparum in Thailand with other populations of P. falciparum worldwide, Pfs25 sequences were retrieved from public databases. Our search identified 30 Pfs25 sequences (10 full-length sequences and 20 partial sequences) in the “nucleotide collections” and 37 full-length Pfs25 sequences in the “whole-genome shotgun” database in GenBank (https://www.ncbi.nlm.nih.gov/genbank/). Additionally, there were 218 sequences (202 full-length sequences and 16 partial sequences) in PlasmoDB (https://plasmodb.org/plasmo/app). Excluding the partial sequences as well as sequences of the same parasites or parasite with the same origins (i.e., 3D7 and NF54), there were a total of 218 full-length Pfs25 sequences in the public databases. On combining these with the Pfs25 sequences generated in this study, a global Pfs25 database from 307 geographically different isolates of P. falciparum was established. The origins of the P. falciparum parasites in the global database were from 22 countries, including 10 countries in Africa (n = 173, including 3D7), 4 in Central and South America (n = 29), and 8 in Asia (n = 105; Additional File 2: Table S1).

The haplotype analysis of the Pfs25 global database revealed 11 unique haplotypes. Of these, H1 and H2 were the dominant haplotypes, representing 70% and 22%, respectively, of the parasite populations (Fig. 2a). The other nine haplotypes were minor haplotypes, constituting 8% of the parasite population. The levels of Pfs25 haplotype diversity were different in P. falciparum from different continents. For instance, P. falciparum from Central and South America had only three Pfs25 haplotypes (Hd ± SD = 0.197 ± 0.095). Of these, H1 was detected in all countries, with a frequency of 90%, while H2 and H9 were detected in two and one P. falciparum isolates, respectively, in Brazil (Fig. 2b). Plasmodium falciparum from Africa also carried three haplotypes, H1, H8, and H10 (Hd ± SD = 0.034 ± 0.019). H1 was detected in all countries in Africa with a 98% frequency; meanwhile, H8 and H10 were rare haplotypes that were identified in two and one P. falciparum isolates in Gambia and Senegal, respectively, (Fig. 2c).

Fig. 2
figure2

Global distribution of Pfs25 haplotypes in Plasmodium falciparum. a The proportion of Pfs25 in P. falciparum in all populations and in three continents. Numbers in the pie charts indicate the percentage of individual haplotypes. n indicates the number of samples. The distributions of Pfs25 haplotypes in P. falciparum in b Central and South America, c Africa, and d Asia. Numbers in the circles in b to d indicate the number of parasites. Abbreviations: BR, Brazil; CG, Congo DR; CN, People's Republic of China; GF, French Guiana; GH, Ghana, GM, the Gambia; GN, Guinea; HN, Honduras; IN, India; KE, Kenya; KH, Cambodia; LA, Laos; ML, Mali; MY, Malaysia; PH, the Philippines; SD, Sudan; SN, Senegal; SV, El Salvador; TG, Togo; TH, Thailand; UG, Uganda; VN, Vietnam; 3D7, Plasmodium falciparum 3D7

Interestingly, eight haplotypes were identified in P. falciparum in Asia (Hd ± SD = 0.564 ± 0.049), where H1 and H2 were the two major haplotypes, representing 19% and 63% of the parasite population in Asia. In addition to Thailand, H2 was also detected in Laos, People’s Republic of China, and Vietnam, whereas H1 was detected in Cambodia, Malaysia, the Philippines, and India (Fig. 2d). This result indicates that the highest Pfs25 diversity in P. falciparum was detected in Asia. Additionally, the distribution patterns of Pfs25 haplotypes in different parasite populations varied geographically, with H1 being the major haplotype in P. falciparum in Africa and South America and H2 in Asia.

To compare the Pfs25 haplotype patterns among P. falciparum populations in three continents, Wright’s statistics were calculated between pairs of parasite populations. Significant Fst values were detected between all parasite pairs, being 0.67745 (P < 0.0001), 0.44847 (P < 0.0001), and 0.7858 (P = 0.00901) between P. falciparum in Asia and Africa, Asia, and South America, and Africa and South America, respectively. This finding indicated that population differentiation exists among P. falciparum populations in Asia, Africa, and South America, because unique haplotypes existed among different populations. As shown in Fig. 2, H8 and H10 were only detected in P. falciparum in Gambia and Senegal, H9 only in Brazil, and five other haplotypes (H4, H5, H6, H7, and H11) in Thailand and Vietnam.

Haplotype network of Pfs25

To postulate the origins of Pfs25 haplotypes, a Pfs25 haplotype network was constructed. As shown in Fig. 3, the majority of rare Pfs25 haplotypes were associated with one of the two major haplotypes, H1 and H2. Four minor haplotypes (H6, H8, H9, and H10) were closely associated with H1, while four other haplotypes (H3, H4, H5, and H7) were closely related to H2. Interestingly, H11, which was present in a single parasite isolate in Vietnam, was associated with H3. This result suggested that Pfs25 minor haplotypes in P. falciparum from Africa, South America, and Central America could arise from H1, whereas Pfs25 minor haplotypes from Asia could arise from H2.

Fig. 3
figure3

Haplotype network of Pfs25 gene of Plasmodium falciparum. Each circle indicates a unique haplotype, and the sizes of the circles are proportional to the haplotype frequencies of each network. Each cross line represents one mutation step. Colors inside the circles indicate the origins of the P. falciparum isolates. Purple, Africa; green, Asia; red, Central and South America

To further study the genetic relationship of Pfs25 haplotypes, a BI phylogenetic tree was constructed. Consistent with the haplotype network, Pfs25 haplotypes were clustered into three major clades (Fig. 4). The H1 clade was comprised of five haplotypes: H1, H6, H8, H9, and H10. The H2 clade was comprised of H4, H5, and H7, but two sub-clades were detected. H3 and H11 were separated into a distinct clade, although the H3 clade was more closely related to the H2 clade rather than the H1 clade. Unfortunately, the NJ tree was multifurcated and so excluded from analysis (Additional file 4: Fig. S2). Taken together, the results from the haplotype network and the phylogenetic tree consistently support that H1 and H2 could mainly contribute to the genetic diversity of Pfs25 in P. falciparum populations.

Fig. 4
figure4

Bayesian inference phylogenetic tree (HKY + G model) of the Pfs25 sequence of Plasmodium falciparum. Posterior probabilities > 0.5 are shown above the branches. Branch lengths are drawn to scale with the scale bar, representing 0.09 nucleotide substitution per site. Sequences of Prs25, the homolog gene of Pfs25, from P. reichenowi strains [57] were included

Molecular basis of Pfs25 variations

To investigate the sequence polymorphisms in Pfs25, nucleotide sequences of 11 unique haplotypes of Pfs25 were aligned. The analysis identified ten single-nucleotide polymorphisms (SNPs) (Table 2 and Fig. 5a), with an average pairwise nucleotide difference between sequences (k) of 0.559 and an average nucleotide diversity at each locus (π) ± SD of 0.00085 ± 0.00007 (Additional File 5: Table S3). Of these, three SNPs at nucleotide positions 117 (AGT/AGC), 333 (AAG/AAA), and 519 (GGA/GGG) resulted in synonymous amino acid substitutions at amino acid residues 39 Ser, 111 Lys, and 173 Gly, respectively. The SNP frequencies at positions 117, 333, and 519 were T/C (0.992/0.001), A/G (0.997/0.003), and A/G (0.997/0.003), respectively. The other SNPs detected at the nucleotide positions 226 (GAT/AAT), 392 (GGA/GCA), 412 (GGC/AGC), 428 (GTA/GCA), 433 (GAT/AAT), 561 (AAT/AAA), and 651 (ATG/ATA) resulted in non-synonymous amino acid substitutions at amino acid residues 76 Asp/Asn, 131 Gly/Ala, 141 Gly/Ser, 143 Val/Ala, 145 Asp/Asn, 187 Asn/Lys, and 217 Met/Ile, respectively. The SNP frequencies at positions 226, 392, 412, 418, 433, 561, and 651 were G/A (0.987/0.013), G/C (0.726/0.274), G/A (0.997/0.003), T/C (0.964/0.036), G/A (0.997/0.003), T/A (0.997/0.003), and G/A (0.994/0.006), respectively.

Table 2 Single-nucleotide polymorphism (SNP) sites in the Pfs25 gene of Plasmodium falciparum
Fig. 5
figure5

Nucleotide diversity in the Pfs25 gene of Plasmodium falciparum. a Ten single-nucleotide polymorphism (SNP) sites in Pfs25. Each site contains two polymorphic nucleotides. b Seven amino acid substitution sites in Pfs25 antigen. c Sliding window of nucleotide diversity index (π). The π values were calculated using DnaSP version 6 with a window length of 25 bp and a step size of 3 bp. Bar shows regions corresponding to signal peptide (S), four EGF-like domains (D1 to D4), and transmembrane domain (A) in Pfs25

The SNP frequency analysis showed that the frequencies of the H1 allele were higher than 0.95 at all SNP sites, except at position 392, where the frequency was 0.726. This indicated that most SNPs detected in Pfs25 were rare. Notably, eight SNPs (positions 116, 226, 333, 412, 433, 519, 516, and 651) were haplotype-specific (Table 2). Interestingly, the SNP at nucleotide position 392 differentiated the two major haplotypes, H1 and H2. In the BI phylogenetic tree (Fig. 4), all Pfs25 haplotypes (H6, H8, and H8) in the H1 clade carried 392 G, whereas all haplotypes in the H2 clade carried 392 C.

The SNP distribution analysis of Pfs25 revealed that nine SNPs were located in the EGF domains and one SNP was mapped to the transmembrane (anchor) domain (Fig. 5b). Of these, five SNPs were mapped to EGF domain 3. No SNPs were observed in the signal peptide sequences. To further compare the levels of nucleotide diversity in different domains of Pfs25, a sliding window plot of the nucleotide diversity index (π) was analyzed (Fig. 5c). Results showed that the average π for EGF domains 1, 2, 3, and 4, and the transmembrane domain were 0.00017, 0.0018, 0.00361, 0.00011, and 0.00018, respectively. Thus, the sequence diversity was highest in the EGF domain 3 of Pfs25.

Additionally, the nucleotide diversity indices of Pfs25 were calculated to compare the level of diversity among different malaria parasite populations. In agreement with the analysis of the haplotype diversity, the highest π and k values were detected in the P. falciparum population in Asia (Additional File 5: Table S3). Notably, π and k values of the Pfs25 sequence from P. falciparum population in Asia were higher than the average values. Interestingly, although P. falciparum in Africa and South America were comprised of three haplotypes of Pfs25, the π value of Pfs25 in P. falciparum in Africa was lower than that of South and Central America. When the levels of nucleotide diversity were analyzed for P. falciparum in individual countries (excluding countries with one sample), Pfs25 in Asia (Thailand, Cambodia, India, and Vietnam) and Brazil had a nucleotide diversity higher than the average (Additional File 5: Table S3). In contrast, Pfs25 from the parasite population from all African countries and in French Guiana exhibited an extremely low sequence diversity. No sequence variation was observed in P. falciparum in Mali (n = 24), Uganda (n = 11), and French Guiana (n = 23). This reveals that haplotype and nucleotide sequence diversity in Pfs25 of P. falciparum in Asia is higher than that in the other parasite populations.

Signature of natural selection against Pfs25

To determine the evidence of natural selection on Pfs25, three neutrality tests were performed. Fu and Li’s D* and Fu and Li’s F* statistic tests were negative and significant (D* = − 2.78081, P < 0.05; F* = − 2.74867, P < 0.05), whereas Tajima’s D test was negative, but not significant (D = − 1.43957, P > 0.10; Additional File 5: Table S3). When the neutrality tests were analyzed using the sequence data from the parasite populations of each continent, non-significant values were detected in all tests. Furthermore, the sliding window plots of Tajima’s D, Fu and Li’s D*, and Fu and Li’s F* values were constructed. The evidence of negative selection was detected in EGF domain 3 of Pfs25 in the sliding window plots of Fu and Li’s D* and Fu and Li F* tests (Fig. 6). Additionally, the dN˗dS value of Pfs25 was also analyzed using all parasite populations. The test showed a positive, but non-significant value (z test = 1.01, P = 0.31). When the dN˗dS values were calculated using the sequence datasets, the results were positive and non-significant for the parasite populations in Asia and South America (Additional File 5: Table S3). Negative and non-significant dN˗dS value was detected in the parasite populations in Africa. This result showed the tendency of negative selection operating in Pfs25.

Fig. 6
figure6

Sliding window plots of a Tajima’s D values, b Fu and Li’s D* values, c Fu and Li’s F* values, and d dN-dS values of the Pfs25 gene of Plasmodium falciparum. The X axis shows the midpoint of the contiguous windows of 25 bp with a step size of 3 bp for the portions of the genes sequenced (nucleotide positions of each gene are given as those in the allele of the reference genome strain 3D7 [45]). Significant D* and F* values, representing the windows with significant departures from zero, were detected at the same nucleotide positions 409 to 436, respectively. The red lines indicate P values of < 0.05. Bar shows regions corresponding to signal peptides (S), four EGF-like domains (D1 to D4), and transmembrane domain (A) in Pfs25

Contribution of the G131A mutation to the structural conformation of Pfs25

To predict the consequences of amino acid substitutions on the structure conformation of Pfs25, secondary structures of Pfs25 variants were predicted using JPred4 [81]. Analysis of the H1 variant identified coil structures at nine sites of amino acid residues (39, 76, 111, 138, 143, 145, 173, 187, and 217) and a beta-sheet structure at amino acid residue 131. The analyses of the ten other variants revealed the states of the secondary structures were similar to that of H1 (Additional file 6: Fig. S3), suggesting that the amino acid substitutions in Pfs25 are unlikely to affect the structural conformation of Pfs25.

Furthermore, MD was performed on the crystal structure of Pfs25 (PDB ID: 6PHB [8]) and the homology models of Pfs25 haplotypes H1 and H2 to gain insight into the effects of the G131A mutation of H2 on the structural conformation. This mutation was mapped to EGF-domain 3, which contains binding sites of transmission-blocking antibodies [82,83,84]. The crystal structure of Pfs25 contains the unique amino acid residues of Q91, Q144, and Q166, whereas they are N112, N165, and N187 in H1 and H2. The MD results showed that the RMSF value trends of the crystal structure of Pfs25 and homology models of H1 and H2 were relatively similar (Fig. 7a), indicating that the flexibilities of these three proteins are quite similar. The structure closest to the average structure of the 80–100-ns trajectory of each system was selected as the representative structure for the crystal structure of Pfs25 and homology models of H1 and H2. The superimposition of the three representative structures showed that their overall structures were relatively similar (Fig. 7b). Specifically, the backbone RMSD values of the differences between the crystal structure and H1, crystal structure and H2, and H1 and H2 were 1.19 Å, 1.04 Å, and 1.17 Å, respectively. The percentages of secondary structures (helix, β-sheet, and random coil) of all three proteins (Table 3 and Additional file 7: Fig. S4) were also predicted to be relatively similar, suggesting that the structural conformations of H1, H2, and the crystal structure of Pfs25 were relatively similar despite the fact that the crystal structure of Pfs25 had three unique residues that were different from those in H1 and H2 and that H2 was different from H1 because of the G131A mutation.

Fig. 7
figure7

Predicted structures of the haplotypes 1 and 2 of Pfs25 of Plasmodium falciparum. a Root mean square fluctuation (RMSF) plots of the crystal structure of Pfs25 (black) and the homology models of Pfs25 haplotypes H1 (pink) and H2 (green). b The representative structures, which were the structures closest to the average structures of the 80–100 ns molecular dynamics (MD) trajectories of the crystal structure of Pfs25 (black) and the homology models of Pfs25 haplotypes H1 (pink) and H2 (green)

Table 3 Percentages of β-sheet, helix, and random coil of the crystal structure of Pfs25 and the homology models of Pfs25 haplotypes H1 and H2 as calculated by defined secondary structure of protein (DSSP)

Overall, these findings suggest that the polymorphisms in the major Pfs25 haplotypes (G131A mutation) do not cause significant structural changes in terms of the secondary structures and stability. As Pfs25 is essential to the malaria parasite, it should, therefore, be a potential target for a malaria transmission-blocking vaccine.

Discussion

Here, a database containing 307 full-length Pfs25 sequences of P. falciparum isolates worldwide was generated, revealing the extent of genetic diversity of Pfs25 in different malaria parasite populations. To date, only three haplotypes of Pfs25 sequences of P. falciparum are known (H1, H2, and H3). The first sequence was obtained from P. falciparum 3D7 (clone of NF54) [12]. Then, in an analysis of P. falciparum Pfs25 sequences from a small number of isolates from Thailand [10], one SNP at nucleotide position 392 (GGA/GCA) was identified. This SNP classified Pfs25 into two haplotypes: H1 (392G) and H2 (392C). Subsequently, in a partial sequence analysis of Pfs25 from India (n = 155) [42, 43], another SNP was reported at nucleotide position 428 (GTA/GCA), resulting in the identification of a novel Pfs25 haplotype, named H3. Thus, the three haplotypes constitute: H1 (392G and 428 T), H2 (392C and 428 T), and H3 (392C and 428C). Since then, there has been no systematic sequence analysis of Pfs25 in the global P. falciparum population. Here, 224 sequences deposited in public databases were retrieved and combined with the Pfs25 sequences of 83 isolates of P. falciparum from malaria hotspots in different regions of Thailand. Our sequence analysis revealed 11 haplotypes, of which 8 (H4–H11) were novel.

Of the 11 haplotypes identified, H1 and H2 represented 70% and 22% of the parasite populations, respectively, and so were considered the major Pfs25 haplotypes. H1 was the most widely distributed haplotype in P. falciparum populations in three continents (Asia, Africa, and America), whereas H2 haplotype was distributed mainly in Asia (including Thailand, China, Laos, and Vietnam) and Brazil, but was absent in P. falciparum in Africa. Haplotype frequency analysis revealed that H1 accounted for approximately 90% of the P. falciparum populations in Africa and South America, while H1 and H2 had 19% and 63% frequencies, respectively, in P. falciparum in Asia. This result indicated that different major haplotypes of Pfs25 represented different malaria geographical locations.

Our study also revealed the different levels of genetic diversity of Pfs25 between P. falciparum populations in Asia, Africa, and South America. The highest diversity was detected in P. falciparum in Asia, where eight haplotypes were reported. This included the two major haplotypes (H1 and H2) and six minor haplotypes (H3–H7 and H11). Seven haplotypes were detected in P. falciparum in Thailand, while in other P. falciparum populations only one or two haplotypes were identified. Interestingly, haplotypes H1, H2, and H3 could be detected in China and many countries in Southeast Asia. Moreover, these three haplotypes are present in P. falciparum populations in India, indicating a close genetic relatedness and gene flow between these P. falciparum populations. This result was in agreement with our analysis of MSP-3 sequences [40].

In addition, P. falciparum in Asia had the highest number of rare haplotypes. According to the haplotype network analysis, the minor haplotypes may have originated from different major haplotypes, where H4, H5, and H7 were most closely related to H2, whereas H6 was closely related to H1. Additionally, H11 and H3 were more closely related to each other than any other haplotypes. Although the number of haplotypes in P. falciparum in Asia was the highest, the real number of haplotypes in the malaria populations is likely to be underestimated since a large dataset (n < 50) was available from only the P. falciparum population in Thailand. Therefore, P. falciparum samples from other countries in Southeast Asia should be included in further studies to generate a complete view of the parasite diversity in Asia.

In contrast, a lower genetic diversity appeared in P. falciparum populations in Africa, even though the dataset comprised 171 Pfs25 sequences. Of the three haplotypes identified, H1 was present in all countries in Africa and accounted for 98% of the populations. Additional novel haplotypes H8 and H10 were identified in P. falciparum in Gambia and Senegal. Based on the haplotype network, these haplotypes were closely related to H1, indicating that the origins of Pfs25 diversity of P. falciparum in Africa were mainly from H1. A low genetic diversity of Pfs25 was also detected in P. falciparum populations in South America. Of the three haplotypes identified, H1 was detected in all countries in South America, while H2, the major haplotype in Asia, was detected in two isolates in Brazil. This result implies that H2 could be due to a single mutation from H1, rather than the introduction of the parasites from Asia. In accord, H9 was also a minor haplotype in Brazil, and according to the haplotype network analysis, H9 could have arisen from the H1 haplotype. Taken together, the haplotype network analysis demonstrated the extent of genetic diversity of Pfs25 in endemic malaria populations, which could have originated from the mutations of the two major haplotypes, H1 and H2.

Our data showed that P. falciparum populations in different endemic regions had unique Pfs25 haplotype distribution patterns. This was supported by Wright’s Fst statistics, which indicated population subdivision among the P. falciparum populations in Asia, Africa, and South America. This finding was consistent with our previous analyses, wherein AMA-1 and MSP-3 sequences of P. falciparum from different endemic populations were sequenced [39, 40]. In these studies, significant Fst values were observed between P. falciparum in Thailand and countries in Africa and South America. Similarly, in an analysis of Pfs48/45 sequences of P. falciparum in western Kenya, Thailand, and Venezuela [85], a strong population subdivision existed between the parasites of different continents. Genetic isolation among these malaria parasite populations is likely because of strong constraints in gene flow. In contrast, our study showed that H3, a minor haplotype, was prevalent in many parasite populations in Asia, including Thailand, Cambodia, Vietnam, and India. Similarly, in our previous study, shared rare haplotypes of AMA-1, MSP-3, and GLURP have also been detected in P. falciparum populations from Thailand, Myanmar, and India [38,39,40]. Taken together, these results reveal a high gene flow among the parasite populations in Southeast and South Asian countries.

Surprisingly, the genetic diversity of Pfs25 in P. falciparum in Asia was higher than that in Africa. This was in contrast to many genetic studies that have shown that the transmission intensity of the malaria parasite is highest in P. falciparum in Africa, which contributes to the extensive polymorphism of the parasites [86,87,88]. Recently, genome sequence analysis using Illumina Sequencing Technology was conducted to explore the nucleotide variations in the genomes of 7113 P. falciparum isolates worldwide [89]. According to the MalariaGen database (https://wellcomeopenresearch.org/articles/6-42/v1), P. falciparum isolates in Africa are genetically more diverse than those in Asia. In the MalariaGen, additional 31 novel SNPs were identified, which were not reported in the present study (Additional file 8: Table S4a). These findings were, however, not unexpected since the numbers of P. falciparum isolates in our database were much smaller than those in the MalariaGen. Almost all these SNPs were region-specific and could only be detected in very small numbers (< 10 isolates per site) of P. falciparum isolates. The origins of the isolates with the novel SNPs included Benin, Cameroon, Congo DR, Ghana, Guinea, Kenya, Mali, Malawi, and Tanzania in Africa. Novel rare region-specific SNPs were also found in P. falciparum from Thailand, Bangladesh, and Papua New Guinea. However, it should be noted that two-thirds of the SNPs were synonymous and so were unlikely to result in novel haplotypes. According to the SNP data in the MalariaGen [89], the genetic diversity in Pfs25 of P. falciparum in Africa could be underestimated or much higher than in Asia. Thus, further investigation should be continued in these parasite populations to obtain a more complete global view of Pfs25 diversity.

In addition, the number of parasites with at least one SNP (or the parasites with non-H1 haplotype) in the MalariaGen could also be identified (Additional file 8: Table S4b). Of the 7,113 samples in the MalariaGen database, sequence polymorphisms in Pfs25 were detected in 2,677 parasites, so the ratio of H1: non-H1 haplotypes was approximately 2:1 (62%: 37%) (Additional file 8: Table S4c). Of these, 2,555 parasites (80% of the parasites in Asia) with non-H1 haplotypes were identified in Asia, while only 106 (3% of the parasites in Africa) and 6 (15% of the parasites in South America) parasites with non-H1 haplotypes were identified in Africa and South America, respectively. Consistent with the present study, H1 was the major haplotype of Pfs25 in all P. falciparum parasite populations, except in Asia.

High levels of antigenic polymorphisms may be the result of positive selection acting to maintain the genetic diversity and allow the parasite to escape the adaptive immune responses of the host [90]. However, on analyzing Pfs25, there was no evidence of positive selection, as revealed by three neutrality tests (Tajima’s D test, Fu and Li’s D*, and Fu and Li’s F*) and analysis of dN˗dS values. The lack of positive selection pressure in Pfs25 was because the Pfs25 gene is mainly expressed in the post-fertilization stages (mainly in zygote and ookinetes) [12]. Possibly, the genetic diversity of the sexual stage antigens is driven by factors of the mosquito vectors. Molina-Cruz et al. (2020) have shown that parasites in different continents express different variants of the surface protein Pf47 [91]. The Pfs47 protein serves as “the key” that interacts with the receptor P47Rec (“the lock”) in the midgut of the mosquito, allowing it to evade the immune system of the mosquito. Pfs25 antigen interacts with laminin, a protein expressed on the surface of the epithelium in the midgut of the mosquitos [18]. It would be interesting to study the diversity of the laminin-coding gene (LANB2) in different species of Anopheles mosquitoes. Currently, there is one study showing that the laminin sequences of A. gambiae is highly conserved [92]. This could be beneficial to the transmission of P. falciparum isolates in Africa where the majority of the isolates carried the H1 haplotype. Interestingly, the global distribution map of the Anopheles vector shows that the species diversity of Anopheles in Asia is greater than in Africa and South America [93]. Therefore, future studies should focus on investigating whether the different mosquito species exhibit sequence diversity in LANB2 and/or whether Pfs25 haplotypes are associated with the distributions of species of the malaria vectors. Understanding the extent of genetic diversity of the mosquito receptors in other continents would reveal newer insight into the evolution of antigenic genes expressing the sexual stages of the malaria parasites.

The nucleotide sequence alignment showed that the overall genetic polymorphism of Pfs25 was low. Similarly, there are relatively few genetic polymorphisms in Pfs28 of P. falciparum. In the gamete surface protein Pfs28, two polymorphic sites (72 Lys/Arg and 104 Asp/Ala) have been reported [94]. This could imply that these genes could be essential in the survival of the parasites [22]. Likewise, a low sequence diversity was observed in genes encoding antigens of the sexual stages, including Pfs48/45 and Pfs47 [85, 95]. The nucleotide diversity indices of Pfs48/45 and Pfs47 were similar to those of Pfs25. In contrast, genes expressing surface antigens of the blood stages exhibited extensive sequence polymorphism [38, 39]. This is likely to be because the numbers of blood stage malaria parasites are larger than the gametocytes in the host blood circulation and antigens of the blood stages could be exposed to host immunity for a longer period, thereby generating a stronger immune selection pressure. Therefore, the sexual stage antigens, including Pfs25, could potentially serve as candidates for transmission-blocking vaccines to fight against the antigenically diverse parasites [96].

The SNP distribution analysis revealed that, of the ten SNPs detected in the present study, nine were detected in all four EGF-like domains and one in the anchor domain of Pfs25. Interestingly, most non-synonymous SNPs were mapped to the EGF-domain 3, which has been implicated as a target of the transmission-blocking monoclonal antibodies, including 4B7, 1D2, and 32F81 [82, 83]. The SNP that defined the two major haplotypes, H1 and H2, was mapped to nucleotide 392 (GGA/GCA), which resulted in amino acid substitution at residue 131 (Gly/Ala). According to the MD results, no significant structural changes, in terms of the secondary structures (helix, beta-sheet, and random coil) and flexibility, were detected between H1 and H2. Sera from volunteers vaccinated with Pfs25 vaccine (derived from H1) could effectively block the transmission of parasites from Thailand and Burkin Faso and could be attributed to identical structures of major Pfs25 haplotypes from different parasite isolates [10]. Additionally, two non-synonymous SNPs sites at positions 226 and 561, resulting in the amino acid substitutions at positions 76 (Asp/Asn) and 187 (Asn/Lys), were mapped to EGF-domains 2 and 4 that also contained Pfs25-specific antibody binding sites [84]. According to the secondary structure predictions using the JPred 4 server, these two amino acid substitutions are unlikely to cause changes in the secondary structure of Pfs25. Given that the H1 and H2 haplotypes represent > 90% of the parasite populations and both variants were predicted to be structurally similar (based on JPred 4 and MD), these results suggest that current Pfs25 vaccines formulated using the Pfs25 H1 haplotype (or sequences of 3D7 or NF54) should act effectively in all P. falciparum populations worldwide.

Conclusions

The genetic diversity of Pfs25 in different malaria parasite populations was low. H1 was the single major haplotype in P. falciparum in Africa and South and Central America, whereas H1 and H2 were the two dominant haplotypes circulating in P. falciparum in Asia. The low sequence diversity in natural populations of the malaria parasites could be due to negative selection, driven by the functional constraints of the protein. This presents a great opportunity for applying the existing Pfs25-based vaccines to control malaria worldwide. Understanding the sequence diversity of Pfs25 could aid in monitoring the vaccine efficacy as well as developing an assay for detecting the malaria parasites in the mosquito stages to detect the prevalence of malaria transmission in the vectors.

Availability of data and materials

Nucleotide sequences of Pfs25 reported in this article are available in GenBank® database with the accession numbers: OK318571 to OK318653.

Abbreviations

BI:

Bayesian inference

DSSP:

Defined secondary structure of protein

EGF:

Epidermal growth factor

H :

The number of haplotypes

Hd :

Haplotype diversity index

MD:

Molecular dynamics

K :

Average pairwise nucleotide difference between sequences;n, number of samples

NJ:

Neighbor-joining

PCR:

Polymerase chain reaction

π :

Average nucleotide diversity at each locus

RMSD:

Root mean square deviation

RMSF:

Root mean square fluctuation

SNP:

Single-nucleotide polymorphism

SD:

Standard deviation

SNP:

Total number of single-nucleotide polymorphism sites

nsSNP:

Non-synonymous SNP

ssSNP:

Synonymous SNP

References

  1. 1.

    Prajapati SK, Ayanful-Torgby R, Pava Z, Barbeau MC, Acquah FK, Cudjoe E, et al. The transcriptome of circulating sexually committed Plasmodium falciparum ring stage parasites forecasts malaria transmission potential. Nat Commun. 2020;11:6159.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    van Biljon R, van Wyk R, Painter HJ, Orchard L, Reader J, Niemand J, et al. Hierarchical transcriptional control regulates Plasmodium falciparum sexual differentiation. BMC Genomics. 2019;20:920.

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Poran A, Notzel C, Aly O, Mencia-Trinchant N, Harris CT, Guzman ML, et al. Single-cell RNA sequencing reveals a signature of sexual commitment in malaria parasites. Nature. 2017;551:95–9.

    PubMed  PubMed Central  Google Scholar 

  4. 4.

    Chan JA, Drew DR, Reiling L, Lisboa-Pinto A, Dinko B, Sutherland CJ, et al. Low levels of human antibodies to gametocyte-infected erythrocytes contrasts the PfEMP1-dominant response to asexual stages in P. falciparum malaria. Front Immunol. 2018;9:3126.

    CAS  PubMed  Google Scholar 

  5. 5.

    Graves PM, Doubrovsky A, Sattabongkot J, Battistutta D. Human antibody responses to epitopes on the Plasmodium falciparum gametocyte antigen PFS 48/45 and their relationship to infectivity of gametocyte carriers. Am J Trop Med Hyg. 1992;46:711–9.

    CAS  PubMed  Google Scholar 

  6. 6.

    Coelho CH, Tang WK, Burkhardt M, Galson JD, Muratova O, Salinas ND, et al. A human monoclonal antibody blocks malaria transmission and defines a highly conserved neutralizing epitope on gametes. Nat Commun. 2021;12:1750.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Canepa GE, Molina-Cruz A, Yenkoidiok-Douti L, Calvo E, Williams AE, Burkhardt M, et al. Antibody targeting of a specific region of Pfs47 blocks Plasmodium falciparum malaria transmission. NPJ Vaccines. 2018;3:26.

    PubMed  PubMed Central  Google Scholar 

  8. 8.

    McLeod B, Miura K, Scally SW, Bosch A, Nguyen N, Shin H, et al. Potent antibody lineage against malaria transmission elicited by human vaccination with Pfs25. Nat Commun. 2019;10:4328.

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Kumar R, Angov E, Kumar N. Potent malaria transmission-blocking antibody responses elicited by Plasmodium falciparum Pfs25 expressed in Escherichia coli after successful protein refolding. Infect Immun. 2014;82:1453–9.

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    Da DF, Dixit S, Sattabonkot J, Mu J, Abate L, Ramineni B, et al. Anti-Pfs25 human plasma reduces transmission of Plasmodium falciparum isolates that have diverse genetic backgrounds. Infect Immun. 2013;81:1984–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Duffy PE. Transmission-blocking vaccines: harnessing herd immunity for malaria elimination. Expert Rev Vaccines. 2021;20:185–98.

    CAS  PubMed  Google Scholar 

  12. 12.

    Kaslow DC, Quakyi IA, Syin C, Raum MG, Keister DB, Coligan JE, et al. A vaccine candidate from the sexual stage of human malaria that contains EGF-like domains. Nature. 1988;333:74–6.

    CAS  PubMed  Google Scholar 

  13. 13.

    Kaslow DC, Quakyi IA, Keister DB. Minimal variation in a vaccine candidate from the sexual stage of Plasmodium falciparum. Mol Biochem Parasitol. 1989;32:101–3.

    CAS  PubMed  Google Scholar 

  14. 14.

    Gardner MJ, Shallom SJ, Carlton JM, Salzberg SL, Nene V, Shoaibi A, et al. Sequence of Plasmodium falciparum chromosomes 2, 10, 11 and 14. Nature. 2002;419:531–4.

    CAS  PubMed  Google Scholar 

  15. 15.

    Vermeulen AN, Ponnudurai T, Beckers PJ, Verhave JP, Smits MA, Meuwissen JH. Sequential expression of antigens on sexual stages of Plasmodium falciparum accessible to transmission-blocking antibodies in the mosquito. J Exp Med. 1985;162:1460–76.

    CAS  PubMed  Google Scholar 

  16. 16.

    Vermeulen AN, van Deursen J, Brakenhoff RH, Lensen TH, Ponnudurai T, Meuwissen JH. Characterization of Plasmodium falciparum sexual stage antigens and their biosynthesis in synchronised gametocyte cultures. Mol Biochem Parasitol. 1986;20:155–63.

    CAS  PubMed  Google Scholar 

  17. 17.

    Lee SM, Plieskatt J, King CR. Disulfide bond mapping of Pfs25, a recombinant malaria transmission blocking vaccine candidate. Anal Biochem. 2018;542:20–3.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Sharma B. Structure and mechanism of a transmission blocking vaccine candidate protein Pfs25 from P. falciparum: a molecular modeling and docking study. In Silico Biol. 2008;8:193–206.

    CAS  PubMed  Google Scholar 

  19. 19.

    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;4:772–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    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;69:536–41.

    CAS  PubMed  Google Scholar 

  21. 21.

    del Carmen RM, 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. 2000;110:147–59.

    Google Scholar 

  22. 22.

    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;20:3975–83.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Mlambo G, Maciel J, Kumar N. Murine model for assessment of Plasmodium falciparum transmission-blocking vaccine using transgenic Plasmodium berghei parasites expressing the target antigen Pfs25. Infect Immun. 2008;76:2018–24.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Sala KA, Angrisano F, Da DF, Taylor IJ, Churcher TS, Blagborough AM. Immunization with transgenic rodent malaria parasites expressing Pfs25 induces potent transmission-blocking activity. Sci Rep. 2018;8:1573.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Barr PJ, Green KM, Gibson HL, Bathurst IC, Quakyi IA, Kaslow DC. Recombinant Pfs25 protein of Plasmodium falciparum elicits malaria transmission-blocking immunity in experimental animals. J Exp Med. 1991;174:1203–8.

    CAS  PubMed  Google Scholar 

  26. 26.

    Kaslow DC, Bathurst IC, Lensen T, Ponnudurai T, Barr PJ, Keister DB. Saccharomyces cerevisiae recombinant Pfs25 adsorbed to alum elicits antibodies that block transmission of Plasmodium falciparum. Infect Immun. 1994;62:5576–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Patra KP, Li F, Carter D, Gregory JA, Baga S, Reed SG, et al. Alga-produced malaria transmission-blocking vaccine candidate Pfs25 formulated with a human use-compatible potent adjuvant induces high-affinity antibodies that block Plasmodium falciparum infection of mosquitoes. Infect Immun. 2015;83:1799–808.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Chichester JA, Green BJ, Jones RM, Shoji Y, Miura K, Long CA, et al. Safety and immunogenicity of a plant-produced Pfs25 virus-like particle as a transmission blocking vaccine against malaria: a phase 1 dose-escalation study in healthy adults. Vaccine. 2018;36:5865–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Sagara I, Healy SA, Assadou MH, Gabriel EE, Kone M, Sissoko K, et al. Safety and immunogenicity of Pfs25H-EPA/Alhydrogel, a transmission-blocking vaccine against Plasmodium falciparum: a randomised, double-blind, comparator-controlled, dose-escalation study in healthy Malian adults. Lancet Infect Dis. 2018;18:969–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Kaslow DC, Shiloach J. Production, purification and immunogenicity of a malaria transmission-blocking vaccine candidate: TBV25H expressed in yeast and purified using nickel-NTA agarose. Biotechnology (N Y). 1994;12:494–9.

    CAS  Google Scholar 

  31. 31.

    Zou L, Miles AP, Wang J, Stowers AW. Expression of malaria transmission-blocking vaccine antigen Pfs25 in Pichia pastoris for use in human clinical trials. Vaccine. 2003;21:1650–7.

    CAS  PubMed  Google Scholar 

  32. 32.

    Kapoor N, Vanjak I, Rozzelle J, Berges A, Chan W, Yin G, et al. Malaria derived glycosylphosphatidylinositol anchor enhances anti-Pfs25 functional antibodies that block malaria transmission. Biochemistry. 2018;57:516–9.

    CAS  PubMed  Google Scholar 

  33. 33.

    Wu Y, Ellis RD, Shaffer D, Fontes E, Malkin EM, Mahanty S, et al. Phase 1 trial of malaria transmission blocking vaccine candidates Pfs25 and Pvs25 formulated with montanide ISA 51. PLoS ONE. 2008;3:e2636.

    PubMed  PubMed Central  Google Scholar 

  34. 34.

    Talaat KR, Ellis RD, Hurd J, Hentrich A, Gabriel E, Hynes NA, et al. Safety and immunogenicity of Pfs25-EPA/Alhydrogel(R), a transmission blocking vaccine against Plasmodium falciparum: an open label study in malaria naive adults. PLoS ONE. 2016;11:e0163144.

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Brod F, Miura K, Taylor I, Li Y, Marini A, Salman AM, et al. Combination of RTS, S and Pfs25-IMX313 induces a functional antibody response against malaria infection and transmission in mice. Front Immunol. 2018;9:2780.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    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;1:2ra5.

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Genton B, Betuela I, Felger I, Al-Yaman F, Anders RF, Saul A, et al. A recombinant blood-stage malaria vaccine reduces Plasmodium falciparum density and exerts selective pressure on parasite populations in a phase 1–2b trial in Papua New Guinea. J Infect Dis. 2002;185:820–7.

    PubMed  Google Scholar 

  38. 38.

    Pattaradilokrat S, Trakoolsoontorn C, Simpalipan P, Warrit N, Kaewthamasorn M, Harnyuttanakorn P. Size and sequence polymorphisms in the glutamate-rich protein gene of the human malaria parasite Plasmodium falciparum in Thailand. Parasit Vectors. 2018;11:49.

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Lumkul L, Sawaswong V, Simpalipan P, Kaewthamasorn M, Harnyuttanakorn P, Pattaradilokrat S. Unraveling haplotype diversity of the apical membrane antigen-1 gene in Plasmodium falciparum populations in Thailand. Korean J Parasitol. 2018;56:153–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Pattaradilokrat S, Sawaswong V, Simpalipan P, Kaewthamasorn M, Siripoon N, Harnyuttanakorn P. Genetic diversity of the merozoite surface protein-3 gene in Plasmodium falciparum populations in Thailand. Malar J. 2016;15:517.

    PubMed  PubMed Central  Google Scholar 

  41. 41.

    Dechering KJ, Kaan AM, Mbacham W, Wirth DF, Eling W, Konings RN, et al. Isolation and functional characterization of two distinct sexual-stage-specific promoters of the human malaria parasite Plasmodium falciparum. Mol Cell Biol. 1999;19:967–78.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Kaur H, Sehgal R, Goyal K, Makkar N, Yadav R, Bharti PK, et al. Genetic diversity of Plasmodium falciparum merozoite surface protein-1 (block 2), glutamate-rich protein and sexual stage antigen Pfs25 from Chandigarh, North India. Trop Med Int Health. 2017;22:1590–8.

    CAS  PubMed  Google Scholar 

  43. 43.

    Patel P, Bharti PK, Bansal D, Raman RK, Mohapatra PK, Sehgal R, et al. Genetic diversity and antibody responses against Plasmodium falciparum vaccine candidate genes from Chhattisgarh, Central India: implication for vaccine development. PLoS ONE. 2017;12:e0182674.

    PubMed  PubMed Central  Google Scholar 

  44. 44.

    Simpalipan P, Pattaradilokrat S, Siripoon N, Seugorn A, Kaewthamasorn M, Butcher RD, et al. Diversity and population structure of Plasmodium falciparum in Thailand based on the spatial and temporal haplotype patterns of the C-terminal 19-kDa domain of merozoite surface protein-1. Malar J. 2014;13:54.

    PubMed  PubMed Central  Google Scholar 

  45. 45.

    Gardner MJ, Hall N, Fung E, White O, Berriman M, Hyman RW, et al. Genome sequence of the human malaria parasite Plasmodium falciparum. Nature. 2002;419:498–511.

    CAS  PubMed  Google Scholar 

  46. 46.

    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(Database issue):D539–43.

    CAS  PubMed  Google Scholar 

  47. 47.

    Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Rozas J, Ferrer-Mata A, Sanchez-DelBarrio JC, Guirao-Rico S, Librado P, Ramos-Onsins SE, et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol. 2017;34:3299–302.

    CAS  PubMed  Google Scholar 

  49. 49.

    Leigh JW, Bryant D. POPART: full-feature software for haplotype network construction. Methods Ecol Evol. 2015;6:1110–6.

    Google Scholar 

  50. 50.

    Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585–95.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Fu YX, Li WH. Statistical tests of neutrality of mutations. Genetics. 1993;133:693–709.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Kryazhimskiy S, Plotkin JB. The population genetics of dN/dS. PLoS Genet. 2008;4:e1000304.

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform Online. 2007;1:47–50.

    PubMed  PubMed Central  Google Scholar 

  54. 54.

    Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 2018;4:vey016.

    PubMed  PubMed Central  Google Scholar 

  55. 55.

    Wilgenbusch JC, Swofford D. Inferring evolutionary trees with PAUP*. Curr Protoc Bioinformatics. 2003;Chapter 6:Unit 6.4.

  56. 56.

    Hasegawa M, Kishino H, Yano T. Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol. 1985;22:160–74.

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Sundararaman SA, Plenderleith LJ, Liu W, Loy DE, Learn GH, Li Y, et al. Genomes of cryptic chimpanzee Plasmodium species reveal key evolutionary events leading to human malaria. Nat Commun. 2016;7:11078.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Bertoni M, Kiefer F, Biasini M, Bordoli L, Schwede T. Modeling protein quaternary structure of homo-and hetero-oligomers beyond binary interactions by homology. Sci Rep. 2017;7:10480.

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Bienert S, Waterhouse A, de Beer TA, Tauriello G, Studer G, Bordoli L, et al. The SWISS-MODEL Repository—new features and functionality. Nucleic Acids Res. 2017;45(D1):D313–9.

    CAS  PubMed  Google Scholar 

  60. 60.

    Guex N, Peitsch MC, Schwede T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: a historical perspective. Electrophoresis. 2009;30(Suppl 1):S162–73.

    PubMed  Google Scholar 

  61. 61.

    Studer G, Rempfer C, Waterhouse AM, Gumienny R, Haas J, Schwede T. QMEANDisCo—distance constraints applied on model quality estimation. Bioinformatics. 2020;36:1765–71.

    CAS  PubMed  Google Scholar 

  62. 62.

    Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46(W1):W296-303.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Case D, Ben-Shalom I, Brozell S, Cerutti D, Cheatham T III, Cruzeiro V, et al. AMBER 2018. San Francisco: University of California; 2018.

    Google Scholar 

  64. 64.

    Gordon JC, Myers JB, Folta T, Shoja V, Heath LS, Onufriev A. H++: a server for estimating p K as and adding missing hydrogens to macromolecules. Nucleic Acids Res. 2005;33(Web Server issue):W368–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65.

    Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C. ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput. 2015;11:3696–713.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66.

    Charoenwongpaiboon T, Punnatin P, Klaewkla M, Pramoj Na Ayutthaya P, Wangpaiboon K, Chunsrivirot S, et al. Conserved Calcium-binding residues at the Ca-I site involved in fructooligosaccharide synthesis by Lactobacillus reuteri 121 inulosucrase. ACS Omega. 2020;5:28001–11.

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67.

    Kanjanatanin P, Pichyangkura R, Sitthiyotha T, Charoenwongpaiboon T, Wangpaiboon K, Chunsrivirot S. Computational design of Bacillus licheniformis RN-01 levansucrase for control of the chain length of levan-type fructooligosaccharides. Int J Biol Macromol. 2019;140:1239–48.

    CAS  PubMed  Google Scholar 

  68. 68.

    Klaewkla M, Pichyangkura R, Charoenwongpaiboon T, Wangpaiboon K, Chunsrivirot S. Computational design of oligosaccharide producing levansucrase from Bacillus licheniformis RN-01 to improve its thermostability for production of levan-type fructooligosaccharides from sucrose. Int J Biol Macromol. 2020;160:252–63.

    CAS  PubMed  Google Scholar 

  69. 69.

    Mokmak W, Chunsrivirot S, Assawamakin A, Choowongkomon K, Tongsima S. Molecular dynamics simulations reveal structural instability of human trypsin inhibitor upon D50E and Y54H mutations. J Mol Model. 2013;19:521–8.

    CAS  PubMed  Google Scholar 

  70. 70.

    Mokmak W, Chunsrivirot S, Hannongbua S, Yuthavong Y, Tongsima S, Kamchonwongpaisan S. Molecular dynamics of interactions between rigid and flexible antifolates and dihydrofolate reductase from pyrimethamine-sensitive and pyrimethamine-resistant Plasmodium falciparum. Chem Biol Drug Des. 2014;84:450–61.

    CAS  PubMed  Google Scholar 

  71. 71.

    Pramoj Na Ayutthaya P, Chanchao C, Chunsrivirot S. Insight into the substrate specificity change caused by the Y227H mutation of α-glucosidase III from the European honeybee (Apis mellifera) through molecular dynamics simulations. PLoS ONE. 2018;13:e0198484.

    Google Scholar 

  72. 72.

    Punnatin P, Chanchao C, Chunsrivirot S. Molecular dynamics reveals insight into how N226P and H227Y mutations affect maltose binding in the active site of α-glucosidase II from European honeybee, Apis mellifera. PLoS ONE. 2020;15(3):e0229734.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Sitthiyotha T, Chunsrivirot S. Computational design of 25-mer peptide binders of SARS-CoV-2. J Phys Chem B. 2020;124:10930–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74.

    Sitthiyotha T, Pichyangkura R, Chunsrivirot S. Molecular dynamics provides insight into how N251A and N251Y mutations in the active site of Bacillus licheniformis RN-01 levansucrase disrupt production of long-chain levan. PLoS ONE. 2018;13:e0204915.

    PubMed  PubMed Central  Google Scholar 

  75. 75.

    Salomon-Ferrer R, Götz AW, Poole D, Le Grand S, Walker RC. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh Ewald. J Chem Theory Comput. 2013;9:3878–88.

    CAS  PubMed  Google Scholar 

  76. 76.

    Götz AW, Williamson MJ, Xu D, Poole D, Le Grand S, Walker RC. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born. J Chem Theory Comput. 2012;8:1542–55.

    PubMed  PubMed Central  Google Scholar 

  77. 77.

    Le Grand S, Götz AW, Walker RC. SPFP: Speed without compromise—a mixed precision model for GPU accelerated molecular dynamics simulations. Comput Phys Commun. 2013;184:374–80.

    Google Scholar 

  78. 78.

    York DM, Darden TA, Pedersen LG. The effect of long-range electrostatic interactions in simulations of macromolecular crystals: A comparison of the Ewald and truncated list methods. J Chem Phys. 1993;99:8345.

    CAS  Google Scholar 

  79. 79.

    Wu X, Brooks BR. Self-guided Langevin dynamics simulation method. Chem Phys Lett. 2003;381:512–8.

    CAS  Google Scholar 

  80. 80.

    Roe DR, Cheatham TE III. PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput. 2013;9:3084–95.

    CAS  PubMed  Google Scholar 

  81. 81.

    Drozdetskiy A, Cole C, Procter J, Barton GJ. JPred4: a protein secondary structure prediction server. Nucleic Acids Res. 2015;43:W389–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  82. 82.

    Stura EA, Satterthwait AC, Calvo JC, Stefanko RS, Langeveld JP, Kaslow DC. Crystallization of an intact monoclonal antibody (4B7) against Plasmodium falciparum malaria with peptides from the Pfs25 protein antigen. Acta Crystallogr D Biol Crystallogr. 1994;50:556–62.

    CAS  PubMed  Google Scholar 

  83. 83.

    Stura EA, Kang AS, Stefanko RS, Calvo JC, Kaslow DC, Satterthwait AC. Crystallization, sequence and preliminary crystallographic data for transmission-blocking anti-malaria Fab 4B7 with cyclic peptides from the Pfs25 protein of P. falciparum. Acta Crystallogr D Biol Crystallogr. 1994;50:535–42.

    CAS  PubMed  Google Scholar 

  84. 84.

    Scally SW, McLeod B, Bosch A, Miura K, Liang Q, Carroll S, et al. Molecular definition of multiple sites of antibody inhibition of malaria transmission-blocking vaccine antigen Pfs25. Nat Commun. 2017;8:1568.

    PubMed  PubMed Central  Google Scholar 

  85. 85.

    Escalante AA, Grebert HM, Chaiyaroj SC, Riggione F, Biswas S, Nahlen BL, et al. Polymorphism in the gene encoding the Pfs48/45 antigen of Plasmodium falciparum. XI. Asembo bay cohort project. Mol Biochem Parasitol. 2002;119:17–22.

    CAS  PubMed  Google Scholar 

  86. 86.

    Anderson TJ, Haubold B, Williams JT, Estrada-Franco JG, Richardson L, Mollinedo R, et al. Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum. Mol Biol Evol. 2000;17:1467–82.

    CAS  PubMed  Google Scholar 

  87. 87.

    Manske M, Miotto O, Campino S, Auburn S, Almagro-Garcia J, Maslen G, et al. Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing. Nature. 2012;487:375–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88.

    Tetteh KK, Stewart LB, Ochola LI, Amambua-Ngwa A, Thomas AW, Marsh K, et al. Prospective identification of malaria parasite genes under balancing selection. PLoS ONE. 2009;4:e5568.

    PubMed  PubMed Central  Google Scholar 

  89. 89.

    Malaria G, Ahouidi A, Ali M, Almagro-Garcia J, Amambua-Ngwa A, Amaratunga C, et al. An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples. Wellcome Open Res. 2021;6:42.

    Google Scholar 

  90. 90.

    Conway DJ. Natural selection on polymorphic malaria antigens and the search for a vaccine. Parasitol Today. 1997;13:26–9.

    CAS  PubMed  Google Scholar 

  91. 91.

    Molina-Cruz A, Canepa GE, Alves ESTL, Williams AE, Nagyal S, Yenkoidiok-Douti L, et al. Plasmodium falciparum evades immunity of anopheline mosquitoes by interacting with a Pfs47 midgut receptor. Proc Natl Acad Sci U S A. 2020;117:2597–605.

    CAS  PubMed  PubMed Central  Google Scholar 

  92. 92.

    Crawford JE, Rottschaefer SM, Coulibaly B, Sacko M, Niare O, Riehle MM, et al. No evidence for positive selection at two potential targets for malaria transmission-blocking vaccines in Anopheles gambiae s.s. Infect Genet Evol. 2013;16:87–92.

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    Sinka ME, Bangs MJ, Manguin S, Rubio-Palis Y, Chareonviriyaphap T, Coetzee M, et al. A global map of dominant malaria vectors. Parasit Vectors. 2012;5:69.

    PubMed  PubMed Central  Google Scholar 

  94. 94.

    Richards JS, MacDonald NJ, Eisen DP. Limited polymorphism in Plasmodium falciparum ookinete surface antigen, von Willebrand factor A domain-related protein from clinical isolates. Malar J. 2006;5:55.

    PubMed  PubMed Central  Google Scholar 

  95. 95.

    Molina-Cruz A, Canepa GE, Kamath N, Pavlovic NV, Mu J, Ramphul UN, et al. Plasmodium evasion of mosquito immunity and global malaria transmission: The lock-and-key theory. Proc Natl Acad Sci U S A. 2015;112:15178–83.

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96.

    Saxena AK, Wu Y, Garboczi DN. Plasmodium p25 and p28 surface proteins: potential transmission-blocking vaccines. Eukaryot Cell. 2007;6:1260–5.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank Dr. Robert Butcher (Chulalongkorn University, Thailand) for reviewing and language editing. We thank Dr. Xin-zhuan Su (National Institutes of Health, USA) and Mr. Vorthon Sawaswong (Chulalongkorn University, Thailand) for providing excellent technical support. We also thank the editor and two anonymous reviewers for their suggestions, which helped us to improve the manuscript.

Funding

This research was financially supported by the 90th Anniversary Chulalongkorn University Fund (Ratchadapiseksomphot Endowment Fund). Pornpawee Sookpongthai was a recipient of the Science Achievement Scholarship of Thailand (SAST). Surasak Chunsrivirot and Thassanai Sitthiyotha were partially supported by the Structural and Computational Biology Research Unit, Faculty of Science, Rachadaphiseksomphot Endowment Fund, Chulalongkorn University.

Author information

Affiliations

Authors

Contributions

PS, KU, and SP performed the molecular genetic analyses. MK performed the statistical analyses and provided guidance for data interpretation. TS, KW, and SC performed molecular modeling analysis and provided guidance for data interpretation. TP and PH were responsible for parasite collection and maintenance. SC and SP wrote the manuscript. SP provided the conceptual framework for the project, guidance for interpretation of the data, performed data analysis, and participated in the manuscript preparation, revision, and coordination. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sittiporn Pattaradilokrat.

Ethics declarations

Ethics approval and consent to participate

The study protocol was reviewed and approved by the Institutional Biosafety Committee of Chulalongkorn University (SC CU-IBC-004/2020).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Figure S1.

Root mean square deviation (RMSD) plots of a the crystal structure of Pfs25, b Pfs25 haplotype H1, and c Pfs25 haplotype H2. The RMSD values of all atoms and backbone atoms are shown in black and gray, respectively.

Additional file 2: Table S1.

List of P. falciparum isolates with full-length sequences of the Pfs25 gene

Additional file 3: Table S2.

Allelic distribution of the Pfs25 gene in Plasmodium falciparum from Thailand. Abbreviations: H, the number of haplotypes; Hd, haplotype diversity index; SD, standard deviation.

Additional file 4: Figure S2.

Neighbor-joining phylogenetic tree (HKY85 model) of the Pfs25 sequence of Plasmodium falciparum. Bootstrap values (> 50%) are shown. Sequences of Prs25, the homolog gene of Pfs25, from P. reichenowi strains were used [57].

Additional file 5: Table S3

Nucleotide diversity and signature of natural selection in Pfs25 in the global population of Plasmodium falciparum. Abbreviations: n, number of samples, H, the number of haplotypes; Hd, haplotype diversity index; SNP, total number of single-nucleotide polymorphism sites; nsSNP, non-synonymous SNP; ssSNP, synonymous SNP; k, average pairwise nucleotide difference between sequences; π, average nucleotide diversity at each locus; nd, not determined because of insufficient sequence data.

Additional file 6: Figure S3.

Secondary structure analysis of Pfs25 variants using JPred 4. H1 to H11 represent the variants of Pfs25 identified in the present study. Black and red asterisks are synonymous and non-synonymous SNPs, respectively. Blue vertical lines indicate the coil structure, mapped to amino acid positions 39, 76, 111, 138, 143, 145, 173, 187, and 217. Green vertical line indicates the β-structure at position 131. The topmost bar shows regions corresponding to signal peptides (S), four epidermal growth factor (EGF)-like domains (D1 to D4), and transmembrane domain (A) in Pfs25.

Additional file 7: Figure S4.

Defined secondary structure of protein (DSSP) plots of a the crystal structure of Pfs25, b Pfs25 haplotype H1, and c Pfs25 haplotype H2.

Additional file 8: Table S4. a

The list of SNPs in Pfs25 from the MalariaGen database [89]. *SNPs detected the present study. Gray and blue boxes indicate SNPs specific to P. falciparum isolates in Africa and Asia regions. b The geographical distributions of the P. falciparum isolates with polymorphic SNPs in Pfs25 in the MalariaGen database. c The estimated proportions of the H1 and non-H1 haplotypes of Pfs25 in P. falciparum populations in three continents (Asia, Africa, and South America).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sookpongthai, P., Utayopas, K., Sitthiyotha, T. et al. Global diversity of the gene encoding the Pfs25 protein—a Plasmodium falciparum transmission-blocking vaccine candidate. Parasites Vectors 14, 571 (2021). https://doi.org/10.1186/s13071-021-05078-6

Download citation

Keywords

  • Plasmodium falciparum
  • Malaria
  • Vaccine
  • Transmission-blocking
  • Diversity
  • Haplotype