Open Access

Analysis of Pvama1 genes from China-Myanmar border reveals little regional genetic differentiation of Plasmodium vivax populations

Parasites & Vectors20169:614

https://doi.org/10.1186/s13071-016-1899-1

Received: 7 August 2016

Accepted: 21 November 2016

Published: 29 November 2016

Abstract

Background

With the premise of diminishing parasite genetic diversity following the reduction of malaria incidence, the analysis of polymorphic antigenic markers may provide important information about the impact of malaria control on local parasite populations. Here we evaluated the genetic diversity of Plasmodium vivax apical membrane antigen 1 (Pvama1) gene in a parasite population from the China-Myanmar border and compared it with global P. vivax populations.

Methods

We performed evolutionary analysis to examine the genetic diversity, natural selection, and population differentiation of 73 Pvama1 sequences acquired from the China-Myanmar border as well as 615 publically available Pvama1 sequences from seven global P. vivax populations.

Results

A total of 308 Pvama1 haplotypes were identified among the global P. vivax isolates. The overall nucleotide diversity of Pvama1 gene among the 73 China-Myanmar border parasite isolates was 0.008 with 41 haplotypes being identified (Hd = 0.958). Domain I (DI) harbored the majority (26/33) of the polymorphic sites. The McDonald Kreitman test showed a significant positive selection across the ectodomain and the DI of Pvama1. The fixation index (F ST ) estimation between the China-Myanmar border, Thailand (0.01) and Myanmar (0.10) showed only slight geographical genetic differentiation. Notably, the Sal-I haplotype was not detected in any of the analyzed global isolates, whereas the Belem strain was restricted to the Thai population. The detected mutations are mapped outside the overlapped region of the predicted B-cell epitopes and intrinsically unstructured/disordered regions.

Conclusions

This study revealed high levels of genetic diversity of Pvama1 in the P. vivax parasite population from the China-Myanmar border with DI displaying stronger diversifying selection than other domains. There were low levels of population subdivision among parasite populations from the Greater Mekong Subregion.

Keyword

Plasmodium vivax Pvama1 Genetic diversity China-Myanmar border Malaria

Background

In South and Southeast Asia, Latin America and Oceania, Plasmodium vivax is the major malaria species; around 2.5 billion people are living in areas of P. vivax transmission [1]. In the Greater Mekong Subregion (GMS) where countries are pursuing regional malaria elimination (www.apmen.org), P. vivax is often sympatric with P. falciparum, P. ovale and P. malariae [2], although P. vivax has become the predominant species in recent years [3]. With the ability to form hypnozoites that are responsible for relapses, P. vivax presents a major challenge for malaria elimination. Within the GMS, malaria is distributed very unevenly; malaria transmission is concentrated along international borders, whereas central plains are mostly free from malaria [3, 4]. The more intensified control efforts in this region have led to a further reduction of malaria incidence, creating isolated areas or pockets of high malaria prevalence separated by areas with extremely low endemicity or malaria-free zones. In China, autochthonous malaria incidence is mostly located in counties bordering with Myanmar, where malaria burden is the highest in the GMS [5, 6]. In these border regions, cross-border human migration as a major source of malaria introduction presents a significant challenge to the malaria elimination course [7, 8]. Since control efforts are expected to have great impacts on the genetic diversity of the parasite populations [9, 10], tracking their spatial and temporal dynamics may provide timely measurement of the progress of regional malaria elimination.

The genetic diversity of antigens in malaria parasites has been extensively studied not only because of their importance as malaria vaccine candidates [11], but also due to their usefulness as molecular markers for differentiating parasite populations. Several P. vivax proteins, including Duffy-binding protein (DBP), apical membrane antigen 1 (AMA1), and merozoite surface proteins (MSPs), have been selected as vaccine candidates for their essential functions during erythrocytes invasion and their antigenicity in natural host immune response [1215]. Among them, AMA1 has been identified as an essential target of the host immune system, and considered an attractive malaria vaccine candidate [1517]. The ama1 gene has been extensively studied in a number of Plasmodium species [18]. As a type I transmembrane protein, AMA1 is secreted by microneme organelles. Together with RON proteins, AMA1 is involved in merozoite reorientation and tight junction formation during the invasion process [1924]. Antibodies raised against the AMA1 ectodomain have been shown to inhibit erythrocyte invasion, and AMA1 immunization protects against malaria infection [15, 2527]. The ectodomain of AMA1 was divided into three subdomains referred to as Domain I (DI), Domain II (DII) and Domain III (DIII) based on the conserved cysteine residues [28]. DI harbors higher levels of genetic variation compared to DII and DIII, suggesting this domain is a target of the host immune system [29]. Within DI of PfAMA1, eight polymorphic amino acids located in the cluster 1 loop (c1L) were identified as the targets of allele-specific, protective immune response [30]. Evidence of diversifying selection was observed in DII of AMA1 in some studies such as in the Sri Lankan parasites, suggesting that this region may also be targeted by host immunity [31, 32]. In addition, serological studies showed that DII is the most immunogenic of the three domains [33]. Due to the highly polymorphic feature of the ama1 gene, it has been used as a molecular marker for population genetic studies [34, 35].

Although the genetic diversity of P. vivax ama1 (Pvama1) has been extensively studied with samples from Asia, Oceania and South America [3639], there is a relative lack of data from Southeast Asia, where parasite populations are now being restricted to the international borders as the regional malaria elimination program is unfolding. Thus, in this study, we aimed to investigate the genetic diversity of Pvama1 gene from the China-Myanmar border area. We wanted to determine whether this potentially isolated parasite population was genetically different from those of other endemic regions. Furthermore, we wanted to learn whether the intensified malaria control efforts resulted in evident reduction of genetic diversity of the parasite population as observed elsewhere in Southeast Asia [9]. Our study revealed a considerably high level of genetic diversity of the Pvama1 gene in the China-Myanmar border parasite population.

Methods

Study sites and isolates

Parasite sample collection was carried out from April 2011 to October 2012 around the township of Laiza, which is located in the northeast Kachin State, along the China-Myanmar border [40]. This region has a subtropical climate with most of the precipitation occurring in June-August (the rainy season). The majority of the local inhabitants are ethnic Kachin (called Jingpo in China) with farming being their major occupation. In recent years, there has been a considerable decline of annual malaria incidence and P. vivax has become the predominant parasite species [40, 41]. Like other international borders within the GMS, the China-Myanmar border also has experienced an increase in cross-border migration with large migrant populations engaging in international trade, logging, quarry, plantation and construction activities, which may play an important role for introducing malaria [8, 42]. Filter paper blood spots were collected as our passive malaria case detection efforts in the township hospital and clinics servicing surrounding villages and two camps for internally displaced people. P. vivax infections were based on microscopy of Giemsa-stained thick smears. The study protocol was approved by the IRB of Pennsylvania State University and by the Health Department of Kachin.

DNA extraction, amplification and sequencing of the PvAMA1 gene

Genomic DNA from dried filter paper blood spots of slide-positive samples was extracted by using a QIAamp DNA Blood Mini kit (QIAGEN, Hilden, Germany). A DNA fragment of the Pvama1 gene encoding the extracellular region (1,290 bp, nucleotide region (nt) 148–1,437 of the Sal-I sequence; GenBank accession no. AF063138) was amplified and sequenced with six oligonucleotide primers listed in Additional file 1: Table S1. The amplifications were performed in a 20 μl volume reaction containing 1× KOD-Plus-Neo buffer, 200 μM dNTPs, 1 mM MgSO4, 250 nM of each primer, 0.4 units of KOD Plus neo polymerase (Toyobo, Osaka, Japan), and 1 μl genomic DNA as template. The reaction was run at 94 °C for 5 min, followed by 45 cycles of 94 °C for 15 s, 56 °C for 15 s, and 68 °C for 90 s, and extension at 68 °C for 5 min. PCR fragments were analyzed by electrophoresis on a 1.2% agarose gels. Direct sequencing of purified PCR fragments was carried out on both strands with primers listed in Additional file 1: Table S1 by using the ABI BigDye™ Terminator Reaction Ready kit (Applied Biosystems, CA, USA).

Sequence assembling and polymorphism analysis

Of the 78 P. vivax infections amplified by PCR, five samples showing dual peaks suggestive of a mixed infection were excluded from further analysis. Pvama1 was successfully sequenced from 73 samples (sequences submitted to GenBank under accession nos. KX495505–KX495577). A single contiguous 1,290 bp of Pvama1 (nt 148–1,437 and codons 50–479) was derived for each of the 73 Pvama1 sequences, which include DI (codons 94–247), DII (codons 265–363) and DIII (codons 388–451). The consensus of the sequences were aligned to the P. vivax Sal-I strain by using the CLUSTAL W program in MEGA6.0 [43]. Seven primate-adapted P. vivax isolates (Belem, Chesson I, India VII, Indonesia XIX, North Korea, Palo Alto and Simium; GenBank accession nos EU395595–EU395601) were also analyzed as additional reference sequences [44]. Aligned sequences were exported as FASTA alignment for statistical analysis using the DnaSP v5.10.01 software [45]. Sequencing was repeated to confirm singletons. The numbers of segregating sites (S), the total number of mutations (η), the average number of pairwise nucleotide differences (k), nucleotide diversity (π), the number of haplotypes (H) and haplotype diversity (Hd), and their corresponding standard deviation were computed using the options available in DnaSP v5.10.01 software [45]. The distribution of nucleotide diversity (π) across the DI-III of Pvama1 gene was analyzed using the sliding window approach.

Haplotype network construction, linkage disequilibrium (LD) and F ST analysis

A haplotype network based on the Pvama1 sequence was constructed by using the NETWORK software Version 4.6.1.3 with the Median-Joining method [46]. A total of 534 publically available Pvama1 sequences representing seven P. vivax populations were retrieved from the GenBank: South Korea [47], India [38], Sri Lanka [32], Thailand [48], Iran [49], Venezuela [50], and Papua New Guinea (PNG) [37]. LD was performed to calculate the minimum number of recombination events (R M) [51] and to give an estimation of the recombination parameter C [52]. The relationship between LD and distance between nucleotide sites was plotted by using indices D’ [53] and R 2 [54]. To assess the proportion of genetic variance due to population subdivision, Wright’s F ST among populations were calculated by using DnaSP v5.10.01 [45].

Statistical and phylogenetic analysis

To determine departure from neutrality, Tajima’s D, Fu and Li’s D* and F*, and McDonald-Kreitman indices were calculated using DnaSP v5.10.01 and via a sliding window method [45]. In Tajima’s D test, departure from neutrality is determined by comparing the values of θ (estimated nucleotide diversity) derived from π (observed average pairwise nucleotide diversity) and the total number of segregating sites (S) [55]. The Fu and Li’s D* and F* tests determine departure from neutrality by differences between estimation of θ derived from the number of singletons and that based on either the total number of mutations (D*) or the average pairwise diversity (F*) [56]. The McDonald-Kreitman test [57] was applied by using a single P. cynomolgi ama1 sequence (GenBank accession no. X86099; [58]) as the outgroup for comparison with the P. vivax populations. It allows for determination of the ratio of synonymous substitutions to nonsynonymous substitutions between and within species. A two-tailed Fisher’s exact test was computed to determine the statistical significance (P < 0.05). A phylogenetic analysis of Pvama1 sequences (nt 322–737 relative to Sal-I strain) with Myanmar samples [59] was performed by the neighbor-joining (NJ) method in the MEGA 6.0 software [43]. The bootstrap method with 1,000 replications was used to assess the reliability of the gene tree.

Structural modelling of PvAMA1

The potential B cell epitopes of DI-III in PvAMA1 were predicted by using the ABCpred server [60]. In order to consider a given region as a valid linear B-cell epitope, a threshold of 0.7 was used to predict the 16 residues. The prediction of intrinsically unstructured/disordered regions (IURs) in proteins, which is highly desirable in the design of vaccines and diagnostic tests, was carried out using the RONN server [61]. Residues with an output score above 0.5 were regarded as disordered. The overlapped regions between B-cell epitopes and IURs, as well as mutation sites across DI-III were mapped on a three dimensional structure of PvAMA1 (Protein Data Bank ID: 1W8K; [28]). ViewerLite 4.2 was used to visualize the surface distribution of mapped IURs, the polymorphism, and B-cell epitopes on the crystal structure of PvAMA1.

Results

Genetic diversity of Pvama1 among P. vivax isolates from the China-Myanmar border

The 1,290 bp sequence corresponding to the ectodomain (nt 148–1,437 encoding amino acids 50–479 relative to the Sal-I strain) of Pvama1 was amplified from 73 P. vivax samples acquired from the China-Myanmar border. Of the 73 Pvama1 sequences, there were 41 haplotypes, giving overall haplotype diversity (Hd) of 0.958 (Table 1). The average number of pairwise nucleotide differences (k) for the entire 1,290 bp sequenced region, DI, DII, and DIII were 10.895, 7.433, 1.385, and 0.419, respectively (Table 1). A total of 46 SNPs was detected, including 13 synonymous and 33 non-synonymous (Table 2). Nucleotide diversity (π) at DI, DII and DIII of Pvama1 among 73 examined P. vivax isolates was 0.016, 0.005, and 0.002, respectively, giving an overall π value of the sequenced region of 0.008 (Table 1). A sliding window plot of π with a window of 90 bp and step size of 3 bp revealed values ranging from 0.000 to 0.023 (Fig. 1a). The ectodomain contained 43 polymorphic sites, of which four (nt 162, 957, 1377, 1412) were novel compared to previous reports [32, 37, 38, 4750]. The majority of polymorphic sites were identified in DI (26 sites) and DII (5 sites) as compared to two sites in DIII (Fig. 1b). Of these polymorphic sites, five were trimorphic, while the rest were dimorphic, displaying only two alternative amino acids (Fig. 1b). Within DI, 10 of the 26 Pvama1 mutations were mapped to the same positions as the Pfama1 c1, c1L, c2, and c3 clusters. Among them, four mapped to the c1 cluster, and one was located within the Pvama1 c1L cluster (Additional file 2: Figure S1).
Table 1

Nucleotide diversity and summary statistics of Pvama1 in 73 P. vivax isolates from the China-Myanmar border area. The total sequenced region includes codons 50 to 479: Domain I codons 94 to 247 (nt, 280–741), Domain II codons 265 to 363 (nt, 793–1,089), and Domain III codons 388 to 451 (nt, 1,162–1,353)

 

k

H

Hd ± SD

S

η

π ± SD

θ ± SD

D

D*

F*

MK

Total

10.895

41

0.958 ± 0.014

43

46

0.008 ± 0.000

0.007 ± 0.002

0.495

0.772

0.796

0.0001***

D I

7.433

27

0.919 ± 0.022

26

28

0.016 ± 0.000

0.012 ± 0.004

0.912

0.269

0.608

0.004**

D II

1.385

9

0.783 ± 0.031

5

5

0.005 ± 0.000

0.003 ± 0.002

0.780

1.064

1.142

0.064

D III

0.419

3

0.330 ± 0.004

2

2

0.002 ± 0.000

0.002 ± 0.002

0.031

0.712

0.589

0.478

Abbreviations: SD standard deviation, k the average number of nucleotide differences, H number of haplotypes, Hd haplotype diversity, S number of polymorphic (segregating) sites, η the total number of mutations, π pairwise nucleotide diversity, θ the expected nucleotide diversity under neutrality derived from S. D Tajima’s D test, D* Fu and Li’s D* value, F* Fu and Li’s F* value, MK McDonald-Kreitman test

**P < 0.01; ***P < 0.0001

Table 2

Genetic diversity of Pvama1 in eight worldwide populations

Region

Country

n

S

η

k

π ± SD

NS

SP

H

Hd ± SD

GenBank accession numbers

East Asia

China-Myanmar

73

43

46

10.895

0.008 ± 0.000

33

13

41

0.958 ± 0.014

KX495505–KX495577

 

Korea

66

56

56

7.620

0.006 ± 0.000

35

21

27

0.950 ± 0.013

KM230319–KM230384

South Asia

India

10

27

25

10.822

0.008 ± 0.001

20

5

7

0.911 ± 0.077

EF025187–195, 197

 

Sri Lanka

23

34

32

10.130

0.008 ± 0.000

27

5

15

0.949 ± 0.028

EF218679–EF218701

Southeast Asia

Thailand

231

52

46

11.927

0.009 ± 0.000

34

12

94

0.934 ± 0.012

FJ784891–FJ785121

West Asia

Iran

29

40

43

12.936

0.010 ± 0.000

34

9

29

1.000 ± 0.009

JX624732–JX624760

South America

Venezuela

73

27

25

9.419

0.007 ± 0.000

19

6

18

0.909 ± 0.016

EU346015–EU346087

Oceania

PNG

102

39

38

10.668

0.008 ± 0.000

31

7

83

0.995 ± 0.002

KC702402–KC702503

 

Reference strains

8

43

45

15.607

0.012 ± 0.002

36

9

7

0.964 ± 0.077

EU395595–EU395601

Total

 

615

130

117

13.497

0.010 ± 0.000

79

38

308

0.988 ± 0.002

 

Abbreviations: n number of samples, S number of polymorphic sites, η the total number of mutations, k the average number of nucleotide differences, π nucleotide diversity, NS number of non-synonymous polymorphisms, SP number of synonymous polymorphisms, H number of haplotypes, Hd haplotype diversity, SD standard deviation

Fig. 1

Patterns of nucleotide diversity (a) and amino acid polymorphism (b) of Pvama1. A scheme of the ectodomain of Pvama1 is shown below. Nucleotide and amino acid positions are after the Sal-I sequence

Genetic diversity of Pvama1 in the eight worldwide parasite populations

The Pvama1 sequences obtained from the China-Myanmar border (n = 73) were then compared to previously published sequences from seven other geographic regions and primate-adapted P. vivax isolates (nt 148–1,437 encoding amino acids 50–479). A total of 117 mutations were identified among the 615 global and reference Pvama1 sequences, including 38 synonymous SNPs (SP SNPs) and 79 non-synonymous SNPs (NS SNPs) (Table 2). The majority of the NS SNPs (53.2%) were clustered within DI, resulting in a peak nucleotide diversity (π = 0.020) for this region (Additional file 3: Figure S2). A total of 308 haplotypes were identified among these global isolates, demonstrating an extremely high level of haplotype diversity (Hd = 0.988). Nucleotide diversity was the highest in the Iranian and Thai populations and lowest in the South Korean population (Table 2). Despite that the majority of haplotypes was unique to the China-Myanmar border and Myanmar populations, Pvama1 sequences from the China-Myanmar border population did not form distinct clades with the Myanmar isolates [59] by phylogenetic analyses (Additional file 4: Figure S3).

Recombination and linkage disequilibrium

Analysis of the ectodomain of Pvama1 from the China-Myanmar border samples provided estimates of the minimum number of recombination events of six, while values of the recombination parameter C between adjacent sites and per gene were 0.043 and 25.5, respectively (Table 3). These values within the China-Myanmar border population were higher compared to estimates from the South Korea, India, Sri Lanka and Venezuela populations, but lower than those of the Thailand, PNG and Iran populations, respectively (Table 3). Figure 2 shows the relationship between R 2, D’ with distance between sites. This LD analysis showed a decline of the LD index (R 2) with increasing nucleotide sites distance within the Pvama1 gene of the China-Myanmar border isolates, indicating a high meiotic recombination rate (Fig. 2).
Table 3

Comparison of different estimates of recombination events in Pvama1 among worldwide isolates

Locality (no.)

Ra

Rb

Rm

China-Myanmar (73)

0.043

25.5

6

South Korea (66)

0.003

1.6

2

India (10)

0.036

21.1

5

Sri Lanka (23)

0.012

7.2

5

Thailand (231)

0.047

27.8

10

Iran (29)

0.067

39.9

8

Venezuela (73)

0.021

12.5

5

PNG (102)

0.054

32

8

Abbreviations: R a recombinant parameter between adjacent sites, R b recombinant parameter for the whole gene, Rm minimum number of recombination events, China-Myanmar China-Myanmar border population, PNG Papua New Guinea population

Fig. 2

Linkage disequilibrium plots of R 2 (a) and D’ (b) for Pvama1 gene. Sites with significant linkage (P < 0.05) as calculated by Fisher’s exact test are shown as red circles, while all others are shown as black circles. Trace line represents the regression line

F ST analysis

In order to understand the distribution of diversity across global populations, F ST values of the China-Myanmar border population and seven worldwide populations with full-length ectodomain sequences were evaluated [45]. A high level of genetic differentiation (F ST = 0.47) was detected between the South Korean population and the China-Myanmar border population, whereas a low to moderate level of genetic differentiation was detected among other worldwide populations (ranging from 0.03 to 0.24). A moderate range of F ST values (0.13–0.16) were detected when comparing the China-Myanmar border populations with the India, Iran, Venezuela, and PNG populations, but a much lower genetic difference was identified when comparing the China-Myanmar border population with the Thai population (F ST = 0.03) (Table 4). Low F ST values (0.01–0.10) were also observed when comparing part of Pvama1 DI (nt 322–737) among Myanmar, Thai and China-Myanmar border populations (Additional file 5: Table S2).
Table 4

Geographical difference in Pvama1 sequences across all domains

Locality (n)

China-Myanmar

South Korea

India

Sri Lanka

Thailand

Iran

Venezuela

China-Myanmar (73)

       

South Korea (66)

0.47

      

India (10)

0.13

0.39

     

Sri Lanka (114)

0.24

0.54

0.20

    

Thailand (231)

0.03

0.47

0.12

0.21

   

Iran (29)

0.11

0.37

0.07

0.10

0.12

  

Venezuela (73)

0.12

0.48

0.17

0.25

0.17

0.01

 

PNG (102)

0.19

0.42

0.06

0.22

0.17

0.26

0.25

Abbreviations: China-Myanmar China-Myanmar border population, PNG Papua New Guinea population

Evidence of positive diversifying selection on Pvama1 gene

To examine whether natural selection contributed to the generation of the diversity in Pvama1 of the China-Myanmar border P. vivax population, Tajima’s D and Fu and Li’s D* and F* were performed. The values of Tajima’s D and Fu and Li’s D* and F* indices for the entire ectodomain and each domain separately are displayed in Table 1. Even though these values were not statistically significant, the positive value indicates deviation from neutral evolution and the tendency for positive diversifying selection. Meanwhile, a sliding window plot depicted significant positive values in DI, suggesting positive diversifying selection in this region (Fig. 3). Examination of the two sequence sets using a McDonald-Kreitman test showed that the entire sequenced region, particularly within DI, had significantly more non-synonymous substitutions than expected from comparison with P. cynomolgi (P < 0.0001 and P = 0.0037). This result suggests that polymorphisms found for Pvama1, especially in the DI, are maintained by diversifying selection, presumably due to host immune pressure.
Fig. 3

Natural selection on Pvama1 isolates from the China-Myanmar border area. Sliding-window plots of Tajima’s D test (a), Fu and Li’s D* (b) and F* (c) tests for Pvama1 were shown. Nucleotide numbers follow those of Sal-I. Window length is 90 bp, and step size is 3 bp. The three domains of AMA1 (Domain I, Domain II, and Domain III) are shown. Blue lines indicate the region with a significant departure from neutrality (P < 0.1, one-tailed). Red lines indicate regions with positive values (P < 0.05, one-tailed)

Haplotype network reconstruction

On the basis of the 34 polymorphisms in the Pvama1 DI global isolates, 162 unique haplotypes were identified in 615 sequences, of which 54.9% was singleton. Individual haplotype prevalence ranged from 0.6 to 45.1%. Of the reference strain Pvama1 sequences, only the Belem haplotype was detected, but was restricted to the Thai population. No haplotype matched that of the Sal-I strain. Twelve of the 27 China-Myanmar border haplotypes (44.4%) were shared with other populations, of which 91.7% (11/12) were identical to some of the Pvama1 haplotypes observed in the Thai population. Haplotype 21 is the predominant haplotype both in the China-Myanmar border and Thai populations, with a frequency of 24.7% and 23.8%, respectively. Intriguingly, an independent haplotype analysis performed among the China-Myanmar border, Myanmar, and Thai populations indicates that Haplotype 21 is also the only haplotype shared among these three populations (Additional file 6: Figure S4). Haplotype 10 is shared among the China-Myanmar border, Indian, Sri Lankan, Thai and Iranian populations, with a frequency of 2.7, 10.0, 30.4, 2.6, and 10.3%, respectively. Haplotype 30 is the only haplotype shared between the China-Myanmar border population and the outside Asian population. The haplotype network, drawn by excluding the 89 singletons and ≤ 2% frequency haplotypes from the analysis, showed that clusters from the South American, Oceania, and Asian populations overlapped (Fig. 4).
Fig. 4

The proportion of Pvama1 haplotype variations observed in different geographical populations. The size of the pie reflects the frequency of a particular haplotype. The lengths of the lines connecting the pies, measured from their centers, are in proportion to the number of base pair substitutions separating the haplotypes. Color of each pie represents different country. The torso of the haplotype network is shown with light red shadow. Abbreviation: H21, haplotype 21

Analysis of PvAMA1 structure and antigenicity

To determine the distribution of the B-cell epitopes, IURs, and the polymorphic residues found within the China-Myanmar border population, the modeled structure of PvAMA1 was used. The potential B-cell epitopes were identified across the ectodomain of PvAMA1, which also overlap with the locations of most of the SNPs (Additional file 7: Figure S5). Also, the putative IURs are distributed in five regions (amino acids - aa: 121–141, 171–183, 291–309, 392–406, and 427–441) within all three domains of the PvAMA1 protein with no polymorphic residues detected in aa 171–183 and 291–309. In Fig. 5, the overlap between the putative B-cell epitopes and IURs have been demonstrated in the 3-D model of PvAMA1 in yellow (with polymorphic residues, aa: 121–141, 392–406, and 427–441) and red colors (without polymorphic residues, aa: 171–183 and 291–309), respectively. The polymorphic residues clustered on one side of the PvAMA1 protein. Interestingly, the two overlapping non-polymorphic residues of the B-cell epitopes and IURs are located on the opposing faces of the PvAMA1 protein (Fig. 5).
Fig. 5

CPK-models of PvAMA1 with IURs, predicted B-cell epitopes, and polymorphic residues across DI-III mapped. Two opposite sides of the same 3-D structure are shown in (a) with and in (b) without the polymorphic residues. Residues in overlapped regions of B-cell epitopes and IURs with polymorphic residues (aa 121–141, 392–406, and 427–441) are shown in yellow, while overlapped regions without polymorphic residues (aa 171–183 and 291–309) are shown in red. Polymorphic residues across DI-III are shown in pink. Other amino acids are shown in white

Discussion

Consistent with worldwide reports, we detected high genetic diversity in the ectodomain of Pvama1 sequences obtained in 73 P. vivax isolates from the China-Myanmar border. Globally, substantial geographic variability has been observed, with lower diversity in East Asian (Korean, π = 0.006 [47]) and South American (Venezuelan, π = 0.007 [50]) populations, compared to higher diversity in Southeast Asian (Thai, π = 0.009 [48]) and West Asian (Iranian, π = 0.010 [49]) populations. As genetic diversity of P. vivax populations varies significantly due to transmission intensity [6264], it is likely that the higher genetic diversity observed in Thailand and Iran was due to higher P. vivax transmission intensity than in Korea and Venezuela. The detected high level of genetic diversity in Pvama1 in parasite population from the China-Myanmar border was not in line with the rapid decline of malaria incidence in recent years. While it is expected that genetic diversity diminishes following the reduction in malaria incidence, the relationship between the two aspects is complex and could vary according to many epidemiological parameters. In Thailand, for example, P. vivax population in the western border was highly diverse as compared to being almost clonal in the southern border [9, 10]. It remains to be determined whether these differences were due to different histories of malaria control efforts and levels of parasite introduction from neighboring highly endemic areas. Nevertheless, with the overall increased control efforts in the GMS and more isolated parasite populations on the international borders, future longitudinal tracking of parasite genetic diversity in the local parasite populations as well as in potential sources of parasite introduction will provide answers to these questions. Meanwhile, the use of more than one genetic marker such as a molecular barcode may provide a better resolution of the parasite populations [65].

The LD indices decline rapidly with the increasing distance between sites. Considering the high values of recombination parameter, C (C = 4Nr), these results indicate that recombination is very frequent in the Pvama1 gene of diverse geographic populations [32, 37, 38, 4750]. An estimated moderate level of the recombination parameter C (both between adjacent site, Ra and per gene, Rb) was detected for Pvama1 (0.043 and 25.5) in the China-Myanmar border population. This C value observed for Pvama1 is much higher than that of Pfama1 (0.003 and 3.8) from a sympatric population of P. falciparum [66], for which the effective population size (N e ) is only 1.3 × 103 when calculated by using the average recombination rate of P. falciparum (~6 × 10-7 Morgans/base) [67]. We conclude from these data that recombination events in Pvama1 of the China-Myanmar border population are common, and that this area appears to have a considerably larger effective population of P. vivax than P. falciparum. In P. falciparum, strong LD and low genetic diversity often are observed in low-transmission areas [68]. However, such a spectrum of population structures may not fit for P. vivax populations, as we observed LD and high-level haplotype diversity (0.958) of Pvama1 in the China-Myanmar border, where malaria transmission is low [8]. We speculate that two factors might contribute to the observed high genetic diversity in Pvama1 in the border regions. The ability to relapse in P. vivax increases the prevalence of mixed infections and chances for genetic recombination in the mosquito vectors. In addition, heavy human population flow across the porous international borders further favors mixing of parasite populations and increasing parasite genetic diversity.

Pairwise F ST comparisons only detected a moderate level of genetic differentiation (F ST = 0.23) among global populations. This may reflect the functional constraints of this protein and similar balancing selection from human immunity on this protein. Despite this, major geographical genetic differentiation does exist. For instance, the Korean parasite population was drastically different from other parasite populations from the world. The Thai P. vivax populations collected from three regions (northwestern, eastern and southern) from 1996 and 2007 also showed significant population subdivision [48], which may be due to temporal and spatial separations among these populations. Later studies confirmed that the southern Thai population had experienced a genetic bottleneck with significantly reduced genetic diversity [9, 10]. Yet, very little genetic differentiation was observed between the combined Thai parasite population and the China-Myanmar border population, despite that our parasite samples were acquired more recently. This demonstrates the persistence of highly diverse P. vivax populations with only slight genetic differentiation in different regions of the GMS, suggesting the lack of major gene flow barriers in this region. Together with the fact that similar allelic forms of Pvama1 are circulating in the Myanmar, China-Myanmar border, and Thai P. vivax populations [48, 59], the low genetic differentiation between these regions support the idea that a general malaria elimination or control strategy may be applicable for these endemic regions.

The pattern of polymorphisms observed in the ectodomain as well as DI of the China-Myanmar border Pvama1 showed that both domains are under diversifying selection, suggesting a significant departure from neutrality as confirmed by the McDonald and Kreitman test. These results are consistent with previous reports of Pvama1 DI from various global isolates [32, 37, 38, 4750]. Although DII of Pvama1 has been reported as highly immunogenic [33, 69], and there is evidence of positive selection in DII of Sri Lankan P. vivax populations [32], no evidence was found for diversifying selection on DII and DIII of the China-Myanmar border Pvama1 as confirmed by neutrality tests, which is in agreement with several other reports [37, 50]. These results suggest that DI is the dominant target of the host immune response.

A total of 308 haplotypes, with a haplotype diversity of 0.988, was identified in global isolates when analyzing the ectodomain of Pvama1. This extreme polymorphism indicates that each haplotype might be recognized as immunologically distinct by the immune system. Further observation of Pvama1 DI showed that only haplotype 30 in the China-Myanmar border is shared with populations outside of Asia, and haplotype 10 is the only one shared among the majority of analyzed Asian populations. Together with the complex network analysis results, covering diversity of P. vivax will be a great challenge for a PvAMA1-based vaccine design. Although highly diverse, the observation that the majority of the China-Myanmar border Pvama1 haplotypes (44.4%) are shared with Thai populations and that the dominant haplotype (H21) is identical in both populations suggested little differentiation of parasite populations within GMS, and a PvAMA1-based malaria vaccine may be effective in this entire region. Notably, the vaccine strain Sal-I haplotype was not identified in any of the analyzed population in the current study. Thus, the dominant Pvama1 alleles from field parasite populations should be considered in the future studies.

Compared to the Sal-I sequence, 46 SNPs resulting in 43 amino acid substitutions were identified in the China-Myanmar border Pvama1. The majority of the diversity clustered within Pvama1 DI, as has been reported previously for P. falciparum and P. vivax [29, 37, 50]. The 90.7% (39/43) polymorphic sites within the ectodomain identified in the China-Myanmar border Pvama1 are comparable to those previously reported [32, 37, 38, 4750], indicating that these sites may be under strong natural selection. Four clusters within DI (c1, c1L, c2 and c3) were mapped to the surface of the PfAMA1 protein and are potentially associated with antigenic escape [70, 71]. In P. falciparum, the c1 (positions 187 to 231) and c1L (positions 196–207) clusters contain the most polymorphic residues [70, 71]. However, only four Pvama1 polymorphic sites of the China-Myanmar border isolates were located in the Pfama1 c1 cluster. These mutation sites are comparable with those observed in the PNG isolates [37], supporting the hypothesis that the presentation of the PvAMA1’s DI loops is different from that of PfAMA1. Structural modeling of PvAMA1 from the China-Myanmar border isolates revealed that all of the polymorphic residues are mapped to one surface of the PvAMA1 protein, suggesting this is the side face exposed to the host immune system [29]. Previous studies by using invasion-inhibitory monoclonal antibodies specific for PfAMA1 revealed that DII of PvAMA1 is a target of the protective immune response. Furthermore, IUR region (aa 290–307) in the DII of PvAMA1 was found to be an important antigenic region during natural human infections [52]. Comparable to these previous reports, amino acid sequence conservation has also been identified in China-Myanmar border isolates, with no polymorphic sites in aa 171–183 (in DI) and 291–309 (in DII) of B-cell epitope and IUR overlapped region have been identified in all 73 sequenced samples. The current results support the inclusion of amino acid sequences aa 291–309 in DII in PvAMA1-based vaccine.

Conclusions

Our study demonstrated that the genetic diversity of the Pvama1 in 73 P. vivax isolates from the China-Myanmar border area, as well as global isolates, was exceptionally high, and that Pvama1 DI is the dominant target of positive diversifying selection. Furthermore, a low level of genetic differentiation among the Myanmar, China-Myanmar border and Thai populations suggests high levels of gene flow within the GMS.

Abbreviations

c1L: 

Cluster 1 loop

DBP: 

Duffy-binding protein

DI: 

Domain I

DII: 

Domain II

DIII: 

Domain III

F ST

Fixation index

IURs: 

Intrinsically unstructured/disordered regions

LD: 

Linkage disequilibrium

MK

McDonald Kreitman test

MSP1: 

Merozoite surface protein 1

NS SNPs: 

Non-synonymous SNPs

PNG: 

Papua New Guinea

PvAMA1: 

Plasmodium vivax apical membrane antigen 1

SP SNPs: 

Synonymous SNPs

Declarations

Acknowledgements

We would like to thank patients from the surrounding villages for participating in this study and providing the blood samples.

Funding

This work was supported by grants from NIAID, National Institutes of Health (U19AI089672) and grants from National Natural Science Foundation of China (Grant no. 81301455).

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article and its additional files.

Authors’ contributions

XZ, YC and LC designed the studies and drafted the manuscript. PZ and SW took part in the genomic DNA extraction, PCR amplification and writing of the manuscript. JL, FL, and JW participated in sequence analysis and writing of the manuscript. ZY, QF and GY performed epidemiology study, sample collection and writing of the manuscript. YC and LC revised the final manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The study protocol was approved by the IRB of Pennsylvania State University and by the Health Department of Kachin. Written informed consent/assent was obtained from all participants.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Immunology, College of Basic Medical Science, China Medical University
(2)
Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University
(3)
Department of Pathogen Biology and Immunology, Kunming Medical University
(4)
Program in Public Health, University of California
(5)
Dalian Institute of Biotechnology
(6)
Department of Entomology, The Pennsylvania State University

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