Prevalence of pvmrp1 Polymorphisms and Its Contribution to Antimalarial Response

Abstract

As more sporadic cases of chloroquine resistance occur (CQR) in Plasmodium vivax (P. vivax) malaria, molecular markers have become an important tool to monitor the introduction and spread of drug resistance. P. vivax multidrug resistance-associated protein 1 (PvMRP1), as one of the members of the ATP-binding cassette (ABC) transporters, may modulate this phenotype. In this study, we investigated the gene mutations and copy number variations (CNVs) in the pvmrp1 in 102 P. vivax isolates from China, the Republic of Korea (ROK), Myanmar, Papua New Guinea (PNG), Pakistan, the Democratic People’s Republic of Korea (PRK), and Cambodia. And we also obtained 72 available global pvmrp1 sequences deposited in the PlasmoDB database to investigate the genetic diversity, haplotype diversity, natural selection, and population structure of pvmrp1. In total, 29 single nucleotide polymorphisms reflected in 23 non-synonymous, five synonymous mutations and one gene deletion were identified, and CNVs were found in 2.9% of the isolates. Combined with the antimalarial drug susceptibility observed in the previous in vitro assays, except the prevalence of S354N between the two CQ sensitivity categories revealed a significant difference, no genetic mutations or CNVs associated with drug sensitivity were found. The genetic polymorphism analysis of 166 isolates worldwide found that the overall nucleotide diversity (π) of pvmrp1 was 0.0011, with 46 haplotypes identified (Hd = 0.9290). The ratio of non-synonymous to synonymous mutations (dn/ds = 0.5536) and the neutrality tests statistic Fu and Li’s D* test (Fu and Li’s D* = −3.9871, p < 0.02) suggests that pvmrp1 had evolved under a purifying selection. Due to geographical differences, genetic differentiation levels of pvmrp1 in different regions were different to some extent. Overall, this study provides a new idea for finding CQR molecular monitoring of P. vivax and provides more sequences of pvmrp1 in Asia for subsequent research. However, further validation is still needed through laboratory and epidemiological field studies of P. vivax samples from more regions.

Keywords: Plasmodium vivax; genetic diversity; natural selection; pvmrp1.

Figure 1

Predicted PvMRP1 primary protein structure and gene mutation. (A) Diagram of PvMRP1 primary protein structure, orange, yellow and green colors indicate conserved domain, Pfam domains, and GPI-anchor, respectively. (B) PvMRP1 shows the 11 predicted transmembrane helices. The positions of all the different mutations identified from the analysis of 94 geographically diverse isolates are indicated by filled circles, solid lines represent non-synonymous mutations, dotted lines represent synonymous mutations. The red font indicates that the mutation was reported previously [10].

Figure 2

A scatter-gram depicting pvmrp1 copy number estimates for P. vivax isolates from seven countries. ROK, the Republic of Korea; PNG, Papua New Guinea; PRK, the Democratic People’s Republic of Korea.

Figure 3

Amino acid alignment of the 22 pvmrp1 haplotypes in 166 isolates. Polymorphic amino acids are listed for each haplotype. Amino acid residues are identical to the reference sequence Sal-I marked in pink. The dimorphic amino acid changes are marked in blue. The total number of sequences for each haplotype is listed in the right panel.

Figure 4

The haplotype network was created using 166 pvmrp1 nucleotide sequences by the median-joining method in the NETWORK v5.0 program. The size of the circles indicates the haplotype frequency, and the color shows the geographical origin of the sequences. The lines between haplotypes display mutational steps.

Figure 5

Linkage disequilibrium (LD) plot showing non-random association between nucleotide variants among 166 P. vivax isolates at 11 non-synonymous SNPs. R for each pair of genetic polymorphisms of pvmrp1.

Figure 6

Phylogenetic relationship of pvmrp1 full-length genes in 166 isolates based on the neighbor-joining method. The evolutionary history was inferred using the neighbor-joining method. The optimal tree with the sum of branch length = 51.8479 is shown. The evolutionary distances were computed using the number of differences method and are in the units of the number of base differences per sequence. The analysis involved 166 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 3373 positions in the final dataset. The color shows the geographical origin of the sequences.