Skip to main content

Characteristics of molecular markers associated with chloroquine resistance in Plasmodium vivax strains from vivax malaria cases in Yunnan Province, China

Abstract

Background

Chloroquine (CQ) has been the preferred clinical treatment for vivax malaria in Yunnan Province since 1958, with over 300,000 patients. This study aimed to help make trend predictions regarding variations the in anti-malarial drug susceptibility of Plasmodium vivax distributed in Yunnan Province and effectively implement monitoring measures on the efficacy of anti-malarial drugs for vivax malaria.

Methods

Blood samples collected from patients with mono-P. vivax infections were employed in this study based on the principle of cluster sampling. The whole gene of P. vivax multidrug resistance 1 protein gene (pvmdr1) was amplified by nested-PCR techniques and the PCR amplification produce were sequenced by Sanger bidirectional sequencing. The mutant loci and haplotypes of coding DNA sequence (CDS) were identified by comparison with the reference sequence (NC_009915.1) of the P. vivax Sal I isolate. Parameters such as Ka/Ks ratio were calculated using MEGA 5.04 software.

Results

A total of 753 blood samples from patients infected with mono-P. vivax were collected, of which 624 blood samples yielded the full gene sequence (4392 bp) of the pvmdr1 gene, with 283, 140, 119, and 82 sequences from 2014, 2020, 2021 and 2022, respectively. A total of 52 single nucleotide polymorphic (SNP) loci were detected for the 624 CDSs, of which 92.3% (48/52), 34.6% (18/52), 42.3% (22/52), and 36.5% (19/52) SNPs were detected in 2014, 2020, 2021 and 2022, respectively. All of 624 CDSs were defined for a total of 105 mutant haplotypes, with CDSs of 2014, 2020, 2021, and 2022 containing 88, 15, 21, and 13 haplotypes, respectively. Of the 105 haplotypes, the threefold mutant haplotype (Hap_87) was the starting point for stepwise evolution, and the most drastic tenfold mutations were Hap_14 and Hap_78, and the fivefold, sixfold, sevenfold, and eightfold mutations.

Conclusions

In the majority of vivax malaria cases in Yunnan Province, most of them were infected with strains carrying demonstrating highly mutated in pvmdr1 genes. However, the dominant mutation strains types varied from year to year, which warrants further exploration in order to confirm the correlation between with phenotypic changes in P. vivax strains and their susceptibility to anti-malarial drugs such as chloroquine.

Background

Chloroquine (CQ) was first synthesized in 1934 [1], and has been widely used in Yunnan Province since 1960 [2]. In the late 1950s, CQ-resistant Plasmodium falciparum was found in Colombia and along the Thai-Cambodian border [3], and also in 1973 [4, 5] and 1974 [6], the emergence of CQ-resistant P. falciparum was reported in the Yunnan and Hainan provinces of China. Increasing prevalence of CQ-resistant P. falciparum has been continuously observed thereafter [5], and negative effects of drug resistance has also been noted.

Initially, CQ-resistant P. falciparum was tested in Yunnan Province using the in vivo test method recommended by the World Health Organization (WHO) [7]. Between 1981 and 1983, the widespread distribution of CQ-resistant P. falciparum in the major malaria-endemic areas of Yunnan Province was found by using the in vivo 4-week method [7]. In view of this, artemisinin, pyronaridine, and the compound of piperaquine with sulfadoxine have been used to replace CQ in the treatment of falciparum malaria patients in Yunnan since 1983 [8]. However, the "4-week method" with its low compliance and the test results easily affected by the patients immunity are encountering difficulties in practice when being applied to the large-scale and longitudinal monitoring of malaria CQ sensitivity [8]. Therefore, Liu et al. [9] successfully introduced the in vitro microscopic method for testing CQ resistance in P. falciparum in China [10], and used WHO standardized CQ applicator plates [10, 11], self-developed CQ applicator plates, and accompanying reagents [8] to investigate the susceptibility of P. falciparum to CQ, amodiaquine, piperaquine, and various other anti-malarial drugs in Yunnan and Hainan provinces of China from 1984 to 2002. The monitoring results showed that P. falciparum distributed in Yunnan and Hainan provinces were highly resistant to CQ, amodiaquine, and piperaquine, but the susceptibility of P. falciparum to CQ was restored after discontinuing or reducing the use of CQ [12].

CQ has been the preferred treatment for clinical episodes of vivax malaria in Yunnan Province since 1958 [2, 13,14,15], with over 300,000 patients (treated with a total dose of 1200 mg orally over 3 days) in the last four decades alone, according to incomplete statistics[16,17,18,19,20,21]. However, while the challenge of CQ resistance in P. falciparum has been a subject of great concern, evaluation of CQ's efficacy in treating vivax malaria patients has been rarely conducted. From April 2016, when the last indigenous vivax malaria case in China was reported in Yunnan Province [22], to the end of 2022, a cumulative total of 1371 imported cases infected with Plasmodium vivax parasites abroad were identified, including cases introduced abroad in Myanmar, Nigeria, the Democratic Republic of the Congo (DRC), Angola, and Cameroon, but predominantly in Southeast Asian countries, particularly Myanmar, which had the highest number of introduced cases [16, 22, 23].

Data show that CQ resistance in P. vivax was first identified in Papua New Guinea in 1989 [24], followed by reports of cases infected with CQ resistance P. vivax in Indonesia [25], northern Myanmar [26], India [27], and Vietnam [28]. Myanmar, which is located between South and Southeast Asia, is considered a high-risk transmission area for drug-resistant parasites [29]. Zeng et al. [30], using an in vitro microscopic method, observed that in the border area between Myanmar and China 4.4% (2/46) of all clinical isolates of P. vivax had CQ 50% inhibition concentration (IC50) values of above 220 nM, which exceed the susceptibility threshold by a factor of 1.5. A study conducted on amodiaquine (AQ) and CQ, each in combination with sulfadoxine-pyrimethamine (SP) in Papua New Guinea had a failure rate of more than 10% in the treatment of vivax malaria patients [31]. Ratcliff et al. [32] used CQ alone to treat vivax malaria patients in Indonesia and had a failure rate of 15% in the early stages and up to 65% by 28 days, but the possibility that this data was confounded by relapse events has not been excluded, which causes difficulty in assessing the efficacy of anti-malarials for P. vivax in vivo [33, 34]. New rounds of infections and recurrent intraerythrocytic infections caused by the activation of P. vivax hypnozoite parasites are confounding factors that must be guarded against in the in vivo assessment of anti-malarial drug efficacy in highly endemic areas [35]. Secondly, the lack of in vitro culture methods for P. vivax makes it difficult to directly transfer P. vivax, and these in vitro testing methods, such as isotopic methods [36] and microfluorimetric methods [37], have always been used for the drug susceptibility assays of P. falciparum. Animal model methods, which can compensate for the inability to obtain batches of P. vivax for in vitro testing are also impractical due to the difficulty in establishing animal models and the unsustainability in supply of primates [38]. Furthermore, with the continuous effectiveness of malaria control interventions, it has become increasingly challenging to find vivax malaria cases that meet the eligibility criteria for evaluating P. vivax drug resistance [39]. Therefore, the WHO proposed in 2018 that the lack of systematic evaluation of anti-malarial efficacy could be compensated by the optional use of molecular marker surveillance [39].

Previous studies have demonstrated that mutations in dihydrofolate reductase gene (pvdhfr) and dihydropteroate synthase gene (pvdhps) are associated with the development of resistance to SP in P. vivax [40, 41], while mutations in multidrug resistance 1 protein gene (pvmdr1) of P. vivax is one of the markers indicative of those with resistance to CQ [42]. A survey by Zeng et al. [30] found that the G698S substitution in the pvmdr1 of P. vivax population distributed in the border area between Myanmar and China was associated with reduced susceptibility to CQ, artesunate and dihydroartemisinin. In Indonesia, Suwanarusk et al. [43] found that the geometric mean CQ half-inhibition concentration of 283 nM in Y976F mutant isolates was significantly higher than that of 44.5 nM in wild-type strains. In Thailand, monitoring the distribution and extent of both Y976F and F1076L mutations in the pvmdr1 has facilitated stage-specific evaluation of changes in the susceptibility of P. vivax to anti-malarial drugs [44]. Although there have been instances of CQ treatment failure in vivax malaria cases in Guyana, molecular marker monitoring has not further shown specific polymorphisms in the pvmdr1. The country chose not to adjust its current anti-malarial drug policy, indicating that the susceptibility of P. vivax to antimalarials remains stable [45]. However, among numerous studies on the mutation polymorphism of pvmdr1 gene, only a few ones are based on whole gene sequences [46, 47]. The main reason for not always targeting full gene sequences is that the 3′ end of pvmdr1 gene is not easily sequenced due to the presence of many special structures.

In order to help fully revealing of the pvmdr1 gene polymorphism degree in P. vivax strains infected in vivax malaria cases from Yunnan Province, China, and avoid forming a single-faceted experience of taking the research results around the China-Myanmar border as the currently actual situation in Yunnan Province, and begin carrying out the molecular surveillance plan on anti-malarial drug susceptibility of P. vivax in Yunnan Province [39], this study not only explored a realistic first-generation sequencing methods for pvmdr1 whole gene, one of the molecular markers of CQ resistance, but also finished the longitudinal comparison on the pvmdr1 characteristics in P. vivax strains collected from vivax malaria patients diagnosed in Yunnan Province in 2014 and from 2020 to 2022 following the strategy of segmented sequencing of the pvmdr1 full gene, and the findings are reported below.

Methods

Study subjects and blood samples

A cohort study was conducted using all vivax malaria cases diagnosed in Yunnan Province, that were available in the China Disease Surveillance Information Reporting System (CDSIRS). However, this study only included the cases in 2014, 2020, 2021, and 2022 based on the principle of cluster sampling due to the limited workload of whole gene sequencing for pvmdr1. Each case was initially diagnosed by local county-level laboratories in Yunnan province, and then confirmed by the Yunnan Province Malaria Diagnosis Referent Laboratory (YPMDRL) to be mono-P. vivax infection through both light microscopy and genetic testing. The genetic test for P. vivax was conducted by the YPMDRL. The primer sequences, reaction conditions, and reaction system of the genetic test for P. vivax are shown in (Additional file 1). The information on sex, age, initial diagnosis, place of detection, and place of introduction of the vivax malaria cases was obtained from the registration files in CDSIRS. Peripheral venous blood was collected from all vivax malaria cases during acute episodes and dried blood dots (DBD) on filter paper were gathered for in-depth analysis of Plasmodium genetic sequencing.

Confirmation of the malaria infection source

The indigenous infection malaria cases included those who had no history of travel to epidemic areas outside Yunnan Province within 30 days before the onset of malaria; The introduced malaria cases included those who had a history of migration from malaria endemic areas, such as Myanmar and Africa, within 30 days of malaria onset.

Extraction of Plasmodium genomic DNA and PCR amplification of pvmdr1 gene

Three 5 mm diameter DBDs were used to extract Plasmodium genomic DNA according to the instructions given in the QIAgen Mini Kit (DNA Mini Kit, QIAamp, Germany), which were stored at − 20 °C.

A strategy of segmented PCR amplification and sequencing was adopted in order to obtain the whole gene sequence of pvmdr1. The chromosomal reference sequence (ID: NC_009915.1) of P. vivax Sal I strain was used as a template to design the amplification of fragment 1 (F1, 365277-366271 nt), fragment 2 (F2, 364360-365400 nt), fragment 3 (F3, 363489-364447 nt), fragment 4 (F4, 362559-363620), and fragment 5 (F5, 361387-362957 nt) of the pvmdr1 gene (Additional file 2). The primers names and thieves’ sequences, target fragment lengths, and reaction conditions for the nested PCR amplification of the five regions are detailed in Table 1. The amplification products of the second round of the five regions were expected to be 995 bp, 1041 bp, 959 bp, 1062 bp, and 1571 bp long, respectively.

Table 1 The primers names and thieves sequences, target fragment lengths for the nested PCR amplification the pvmdr1 gene in P. vivax strains

The system used for all 10 PCR reactions was 1.5 μl of DNA template, 14.0 μl of PCR mix for 2 × Taq, and 0.5 μl each of upstream and downstream primers (10 μmol/l), and the volume was made to be 25.0 μl with the addition of ddH2O. The conditions for the 10 PCR reactions were the following: pre-denaturation at 95 °C for 4 min, followed by 32 cycles of amplification, with steps including denaturation at 95 °C for 45 s, annealing at 55–61 °C for 45 s, and extension at 72 °C for 90–150 s. The PCR amplification was terminated at 72 °C for 10 min. The end products of the second round of PCR amplification of the five regions were observed by 1.2% agarose gel electrophoresis, and the positive samples were sent to Guangzhou Tianyi Huiyuan Gene Technology Co for Sanger bidirectional sequencing.

Gene polymorphism analysis

The sequencing results were collated using DNAStar 11.0 and BioEdit 7.2.5 software. Sequences from primer pairs DonMD-1F/DonMD-1R, DonMD-2F/DonMD-2R, DonMD-3F/DonMD-3R, DonMD-4F/DonMD-4R, and DonMD-5F/DonMD-5R amplification products were retrieved in order to obtain the coding DNA sequency (CDS) of 1 aa-250 aa, 251 aa-567 aa, 565 aa-847 aa, 848 aa-1154 aa, and 1153 aa-1464 aa of the pvmdr1 gene. The overlap region of each CDS sequence was then removed and assembled along the 5′ → 3′ direction in order to obtain the CDS sequence of the pvmdr1 whole gene (4392 bp), which was compared with the mRNA reference sequence of the pvmdr1 gene (ID: XM_001613678.1), and when both Query Cover and Identifiers were > 98%, it indicated that the collated pvmdr1 whole gene CDS sequence was correct.

The CDS sequence alignment file and the deduced amino acid sequence were created using MEGA 5.04 software, and then DnaSP 6.11.01 software was used to identify the haplotypes and single nucleotide polymorphism (SNP) loci of the CDS strand of the pvmdr1 gene and their mutation types (synonymous/missense). Nucleotide diversity (π), expected heterozygosity (He) and Ka/Ks ratio were calculated, and sequence multiplicity mutations were identified. All base substitutions were confirmed by checking the sequence file ".seq" against the corresponding ".ab1" file; Ka/Ks ratios > 1, = 1, and < 1 indicated positive, neutral and negative selection in the population, respectively. Network 10.0 software was used to create an evolutionary mediated network map of the various haplotypes, where the same locus in the CDS strand of the pvmdr1 gene was repeated across haplotypes, showing a locus mutation that was defined as a 'reverse mutation'.

Statistical analysis

The database for polymorphic analysis of the pvmdr1 gene was created using Excel software, and the differences in SNP and haplotype detection rates between years were evaluated by Chi-square test (χ2) at the level of 0.05 in the "Data and descriptive statistics" module of IBM SPSS Statistics 21 software.

Results

Sample amplification information and PCR product amplification sequencing

A total of 753 cases infected with mono-P. vivax were diagnosed and confirmed in Yunnan Province in 2014, 2020, 2021, and 2022. The patients were predominantly young adult males (84.0%, 632/753), with a smaller number of females (16.0%, 121/753); 81.8% (616/753) of the patients were between 21 and 60 years of age (Table 2). The source of infection was predominantly Myanmar, accounting for 94.0% (708/753) of all cases, and the only indigenous cases of infection in Yunnan Province were reported in 2014 (4.0%, 15/338) (Table 2). The places of initial diagnosis were the following: 450 cases in Dehong (59.8%), 175 cases in Baoshan (23.2%), 41 cases in Lincang (5.4%), 22 cases in Kunming (2.9%), 18 cases in Dali (2.4%), 14 cases in Pu'er (1.9%), 7 cases in Nujiang (0.9%), 7 cases in Xishuangbanna (0.9%), 5 cases in Honghe (0.7%), 3 cases in Lijiang (0.4%), 3 cases in Wenshan (0.4%), 2 cases in Chuxiong (0.3%), 2 cases in Qujing (0.3%), 2 cases in Yuxi (0.3%), 1 case in Zhaotong (0.1%), and 1 case in Diqing (0.1%). The number of cases diagnosed in different years and prefectures can be seen in Additional file 3.

Table 2 Information on vivax malaria cases diagnosed in Yunnan Province from January to December 2014 and from January 2020 to December 2022

Out of the 753 vivax malaria cases mentioned above, the P. vivax strains from 624 cases were amplified by segmented PCR and the products were sequenced to obtain the pvmdr1 full gene sequence, with a success rate of 82.9% (624/753). The second round of product electrophoresis for the segmented nested PCR amplification of the pvmdr1 gene from fragment F1 to fragment F5 is shown in Additional file 4, with target electrophoretic bands at approximately 1000 bp, 1000 bp, 1000 bp, 1100 bp and 1600 bp (Additional file 4).

Nucleotide diversity of gene sequences

The complete CDSs of 624 pvmdr1 genes with similarities (Identifiers) and coverage (Query Cover) > 98% regarding the reference sequences had been submitted for GenBank (GenBank ID including: BankIt2643392: OP559204-OP559462 and BankIt2680229: OQ614893-OQ615257. Two times submissions are to be held confidential until June 30 2023 and Oct 1, 2023, respectively). Nucleotide diversity (π) and Ka/Ks ratio were equal to 0.00087 and 3.6012, respectively, while π and Ka/Ks ratio were equal to 0.00096, 0.00078, 0.00075, 0.00076, and 3.6019, 3.6008, 3.6003, and 3.6004, in 2014, 2020, 2021 and 2022, respectively.

There were base pair substitutions at 52 loci comparison of 624 CDSs and referent sequences (ID: XM_001613678.1) (Tables 3, 4; Additional file 5). Of these, non-synonymous and synonymous mutations accounted for 46.2% (24/52) and 53.8% (28/52), respectively. Substitutions in the first, second, and third positions of the triplet codon accounted for 25.0% (13/52), 25.0% (13/52), and 50.0% (26/52), respectively. MAF (Minor allele frequency) locus is c.1587A > G (91.2%, 569/624) (Table 3). There were 19 single variable sites (36.5%, 19/52). In 2014, 2020, 2021, and 2022, the figures were 78.9% (15/19), 15.8% (3/19), and 5.3% (1/19), respectively, and no singleton mutation sites were detected in the 2020 sequence. The detection rates of single occurrence mutations were 73.7% (14/19), 10.5% (2/19), 5.3% (1/19), 5.3% (1/19), and 5.3% (1/19) for the Myanmar, African, Lao, Pakistani, and indigenous Yunnan strains, respectively (Table 4b); 21 new SNPs were detected, all of which occurred in the 2014 sequences. The detection rates of new SNPs were 95.2% (40/42), 2.4% (1/42), and 2.4% (1/42) for the Myanmar strain, the Lao strain, and the indigenous Yunnan strain, respectively (Tables 3, 4).

Table 3 SNPs of the pvmdr1 gene in P. vivax strains
Table 4 SNPs of pvmdr1 gene in P. vivax strains

The detection sizes of the 52 SNPs in the 2014, 2020, 2021, and 2022 sequences were 48 (92.3%, 48/52), 18 (34.6%, 18/52), 22 (43.3%, 22/52), and 19 (36.5%, 19/52), respectively (Tables 3, 4).

The trends in SNPs detected in different years mainly include the following:

  1. (1)

    Of the 48 SNPs in 2014, 29 of them, including c.96G > C, c.516C>T, c.543C>T, and c.553T>C were individually detected, but only the disappearance of the c.1477T>C loci after 2014 was statistically significant (χ2 = 32.691, P < 0.001) (Tables 3, 4; Fig. 1; Additional file 6).

  2. (2)

    The 18 SNPs detected in 2020 were all also detected in the other 3 years, but only 2 SNPs, c.23C>T and c.930G>A, were detected at a lesser rate of 1.8% (5/283) and 0.7% (2/283) in 2014, compared with 13.6% (19/140), 21.0% (25/119), 18.3% (15/82) and 13.6% (19/140), 21.0% (25/119), and 20.7% (17/82) in the other 3 years. These differences were statistically significant (χ2 = 44.531, P < 0.001; χ2 = 55.180, P < 0.001). In addition, the lower detection rate of c.3226T>C in 2014 of 62.2% (176/283) was comparable to the lower detection rates of 92.4% (110/119) and 89.0% (73/82) in 2021 and 2022, respectively, and this was statistically significant (χ2 = 58.105, P < 0.001). In contrast, when comparing the two SNPs with higher detection rates in 2014, c.1539T>A (25.1%, 71/283) and c.4179G>C (25.1%, 71/283) with the detection rates of 10.1% (12/119) in 2021 (χ2 = 17.645, P < 0.001) and the detection rates of 10.8% (28/259) during 2020 and 2021 (χ2 = 18.599, P < 0.001), respectively, the differences were statistically significant (Table 3). In the fourth case, for the sudden increase and decrease in detection of c.2533 C>T and c.2582C>A in recent years, c.2533 C>T had a lesser detection rate (8.6%, 12/140) in 2020 compared to 28.0% (23/82) in 2022 (χ2 = 14.772, P < 0.001), which was statistically significant; c.2582C>A had a higher detection rate of 14.1% to 16.4% from 2014 to 2021 compared to 2.4% (2/82) detection rate in 2022 (χ2 = 10.361, P < 0.05), which was statistically significant (Tables 3, 4; Fig. 1; Additional file 6).

Fig. 1
figure 1

The change of detection frequency of 52 SNPs during in different years

Multiple mutations in pvmdr1 gene CDSs

The complete CDS of the 624 pvmdr1 genes were compared with the reference sequence (ID: XM_001613678.1) (haplotype Hap_1), and 105 haplotypes were identified (Hap_2 to Hap_106) (Table 5; Additional file 7), all are mutants of the reference sequence, with a total He equal to 0.9515, while the He was equal to 0.974, 0.886, 0.891, and 0.879 for 2014, 2020, 2021, and 2022, respectively. Of the 105 sample sequence haplotypes, there were always three to seven non-synonymous mutations in multiple mutation loci, with the nonsynonymous mutation c.2927A>T (Y976F) occurring in only four haplotypes (Hap_6, Hap_7, Hap_34 and Hap_60).

Table 5 Composition of haplotypes of pvmdr1 gene CDSs from P. vivax strains in 2014 and 2020–2022

The detection sizes of the 105 haplotypes in the 2014, 2020, 2021, and 2022 sequences were 88 (83.8%, 88/105), 15 (14.3%, 15/105), 21 (20.0%, 21/105), and 13 (12.4%, 13/105), respectively (Additional files 7, 8). In addition, of the 105 haplotypes, the most moderate multiple mutation was threefold (Hap_87) and the most drastic multiple mutation was tenfold (Hap_14 and Hap_78) (Table 5; Additional file 7), and fivefold, sixfold, sevenfold and eightfold loci mutation haplotypes were predominant, and all these together accounted for 88.8% (554/624); threefold, fourfold, ninefold, and tenfold loci mutation haplotypes accounted for 0.2% (1/624), 2.7% (27/624), 2.9% (18/624), and 3.8% (24/624), respectively.

Furthermore, there was variance in detected haplotypes between different years. For example, the threefold loci mutation haplotype was detected in only one sample in 2014.

The trends in multiplex detections include the following:

  1. (1)

    a statistically significant difference between the 9.2% (26/283) detection rate of the fourfold mutant haplotype in 2014 and its decrease to 0.7% (1/140) in 2020, with no further detections in 2021 or 2022 (χ2 = 29.654, P < 0.001) (Table 5; Fig. 2; Additional file 8).

  2. (2)

    The increase in the detection of sevenfold loci mutant haplotypes between 2014 (30.0%, 85/283) and 2021 (45.4%, 54/119) was statistically significant (χ2 = 8.718, P < 0.05) (Table 5; Fig. 2; Additional file 8).

  3. (3)

    The detection rate of 5.7% (16/283) of the eightfold loci mutant haplotype in 2014 was statistically significant (χ2 = 15.089, P < 0.05) compared to the results from 2020 and 2021, where it was not detected (Table 5; Fig. 2; Additional file 8).

  4. (4)

    The detection rate of 6.0% (17/283) for the ninefold loci mutant haplotype in 2014 was statistically significant (χ2 = 8.762, P < 0.05) compared to results from 2020, wherein it was not detected (Table 5; Fig. 2; Additional file 8).

Fig. 2
figure 2

The change of detection frequency of 105 haplotypes during in different years

Evolutionary analysis of multiple mutations in pvmdr1 gene CDSs

The haplotype medium network diagram shows that the 105 sample sequence haplotypes starting with the reference sequence (ID: XM_001613678.1) (haplotype Hap_1), evolved via the most moderate threefold loci mutation (Hap_87, "G698S/M908L/T958M"), and further evolved stepwise along two branches of the fourfold mutation (Hap_56) and (Hap_64) (Fig. 3).

Fig. 3
figure 3

The medium network diagram for 105 haplotypes of pvmdr1 CDS chain

The evolution continued along the direction of Hap_56, after accumulating 11–12 loci mutations, to the most distal haplotypes Hap_78, Hap_19, Hap_28, Hap_61, Hap_88, and Hap_102. During the evolutionary path from Hap_64 to Hap_96 which involved undergoing four sequential loci mutations, 80.0% (12/15) of the haplotypes consisted only of sequences from 2014. Seven haplotypes, including Hap_64, were not affected by reverse mutations at nine loci (c.132, c.1477, c.1539, c.1559, c.1587, c.2092, c.3226, c.4074, c.4179), and the network evolution showed mutational multiplicity consistent with the mutational multiplicity identified by the sequences (Fig. 3; Additional file 7). The sequences from 2020 to 2022 show a relatively high concentration of these haplotypes that continue to evolve 1 to 5 steps from Hap_96, including Hap_40, Hap_91, Hap_2, Hap_11, Hap_86, Hap_14, Hap_24, and Hap_4, to the near end of the evolutionary direction of Hap_64, again showing a predominance of sequences from 2014, with 12 of the 14 haplotypes after Hap_4 all consisting entirely of 2014 sequences (Fig. 3).

In addition, out of the 105 haplotypes examined, only 15 demonstrated consistent results of multi-locus joint mutations between the network evolution analysis and sequence alignment (Additional file 7), while the remaining 90 haplotypes (87.5%, 90/105) showed a higher degree of multiplicity in the network evolutionary analysis compared to the sequence comparison owing to reverse mutations at c.132, c.1477, c.1539, c.1559, c.1587, c.2092, c.3226, c.4074, and c.4179, usually with 2–4 times reverse mutations (Additional file 9). Of the 90 haplotypes, the proportions of haplotypes with more than twofold, fourfold, sixfold, eightfold, and tenfold loci mutations in network evolution analysis were 6.7% (6/90), 50% (45/ 90), 36.7% (33/90), 5.6% (5/90), and 1.1% (1/90), respectively (Additional file 9).

Discussion

The pvmdr1 gene is located on chromosome 10, far from the telomere, in approximately 1/4 (366095/1419739) of P. vivax, which starts at the base of the gene (5'-ATG), consists of a complete open reading frame that can encode the 1464 amino acids of PvMDR1, which belong to the membrane structural protein with 12 transmembrane domains located at the P. vivax digestive vesicles [48, 49]. The sequences length of the pvmdr1 gene obtained in this study all showed highly conservative with the fixed a 1464 aa amino acid chain, which may be related to the fact that the pvmdr1 gene is located far from the telomeres of chromosome 10 and is less likely to undergo fragment deletion or insertion due to genetic recombination [50, 51]. The success rate of 82.9% (624/753) obtained the pvmdr1 full gene sequence also indicates that the experimental method for fragment PCR amplification and sequencing of pvmdr1 gene has good stability in this study.

A total of 52 SNPs were detected in 624 pvmdr1 gene sequences in this study, except for the 31 SNPs reported before, including c.23C>T (P8L), c.132G>A (K44K), and c.516C>T (G172G), etc., [43, 46, 47, 52], there were 21 other newly detected SNPs (Tables 3, 4), which may be due to the large sample size of this study and the analysis of the pvmdr1 whole gene sequence. The concentration of newly detected SNPs and low-frequency SNPs in 2014 may be due to the fact that the study sample in that year included a richer population of P. vivax than in subsequent years and even included all the indigenous Yunnan strains (Tables 3, 4). But, based on that fewer new SNPs and fewer low-frequency SNPs were detected in the indigenous Yunnan strains than in other populations, it may suggest that the P. vivax population should be less intensely screened than the others populations.

Of the 18 SNPs that were detected in all years, eight loci mutations were frequently detected in Burmese strains, including c.1539T>A (S513R), c.2092G>A (G698S), c.2533C>T (L845F), c.2582C>A (A861E), c.2822A>C (M908L), c.2873C>T (T958M), c.3226T>C (F1076L), and c.4179G>C (K1393N) [46]. Of which, c.2822A>C ( M908L) and c.2873C>T (T958M) reached 100% detection, which was consistent with previous results of nearly 100% of these isolates found in the Myanmar Laza city [53], the China-Myanmar border [46, 51, 54], the Thai-Myanmar border [55, 56], and the Thai-Cambodia-Thailand-Lao border [47], which is also consistent with previous studies that have shown that the pvmdr1 gene sequences all came from P. vivax populations in Southeast Asia, and P. vivax strains of the present study were mainly composed of Burmese strains, accounting for 94.0% (708/753). Meanwhile, although the Ka/Ks ratios in this study were much greater than 1, in view of no positive selection pattern of low-frequency mutation surges in the mediator network map, it may still be attributed to the combination of neutral selection and drug pressure screening that the c.2822A>C (M908L) and c.2873C>T (T958M) mutations were detected in all samples strains [46, 57]. Another mutation, c.3226T>C (F1076L), also produced by a combination of neutral selection and drug pressure [58], showed an increase in detection from 2014 to 2022 (Table 3; Fig. 1), approaching the previous detection rates of 75.7% (143/189) to 85% (97/113) of the Myanmar population [55, 59], but not reaching the level of the Ethiopian populations with 100% (55/55 and 28/28) detection [42, 60], which suggests that the Myanmar population is stably screened from both the neutral selection and drug pressure, and that the screening for the c.3226T>C (F1076L) mutation is still incomplete.

In contrast to the gradual increase in the detection of the c.3226T>C (F1076L) mutation, the 29 SNPs represented by the c.2927A > T (Y976F) mutation were only detected in the early 2014 sequence (Tables 3, 4), and the c.2927A>T (Y976F) mutation was not detected again after 2020, which is consistent with the conclusions drawn by several authors on P. vivax. The c.2927A>T (Y976F) mutation was detected at a rate of 30.8% (4/13) in 2008 [45], decreasing to 3.3% [45] to 7.1% [46] in 2012, and was not detected again after 2015 [45, 46]. So far, the factors that have caused the reduction and disappearance of the c.2927A>T (Y976F) mutation is still unclear. However, given that the c.2927A>T (Y976F) mutation is considered to be associated with the failure of CQ monotherapy for vivax malaria patients [35], it may be prudent to consider that CQ is still a reasonable option for treatment of the P. vivax population of Myanmar, as the c.2927A>T (Y976F) mutation is not detected in this specific population.

In this study, the He obtained from 624 pvmdr1 gene sequences was 0.9515, within the interval of (0.869–0.983 vs. 0.879–0.974) [46] calculated by other scholars for P. vivax strains in the China–Myanmar border region. However, a total of 105 haplotypes were more than the 75 [46] species that had been previously identified in the China–Myanmar border region by other scholars in 2015, and the 10 [61] to 27 [33] species found in the South-North Amazon Basin, the North Coast of Peru, and India. In terms of haplotype species, except for the seven haplotypes including threefold mutations (G698S/M908L/T958M) [51, 62], fourfold mutations (G698S/M908L/T958M/F1076L) [30, 51], fivefold mutations (G698S/L845F/M908L/T958M/F1076L) [30, 51] and (G698S/M908L/T958M/Y976F/F1076L) [51], sixfold mutations (K44K/G698S/L845F/M908L/T958M/F1076L) and (T529T/G698S/L845F/M908L/T958M/F1076L) [63], and eightfold mutation (L493L/T529T/G698S/L845F/M908L/T958M/F1076L/E1233E) [63]. the remaining 98 haplotypes had been not previously reported; furthermore, unprecedented ninefold and tenfold mutant haplotypes were also detected. These differences may be due to the fact that more and longer pvmdr1 sequences were analysed in this study.

Although 105 haplotypes were identified in this study, there was a trend of gradual decrease in the number of haplotypes detected annually, from 88 in 2014 to 15 in 2020, then 21 in 2021, and most recently only 13 in 2022, with low frequency haplotypes being more common only in the early years, particularly 2014 (Table 5; Fig. 3; Additional file 7). In contrast, the mutability of haplotypes shifted towards increasingly complex types, with threefold mutant haplotypes and fourfold mutant haplotypes mostly detected in 2014 and, in recent years, an increase in haplotypes with 10–13-fold loci mutations, such as Hap_40, Hap_91, Hap_2 (Fig. 3). This concentration of joint mutations in a small number of types has facilitated the generation of relatively uniform management strategies, but new adaptive strategies are necessary in order to deal with the problem of multiple mutations.

It is important to mention that in this study, an unexpected occurrence was observed in the description of the pvmdr1 whole gene sequence, such that the fold of multiple loci mutations obtained from the sequence alignment was inconsistent with those identified by the network evolutionary analysis, where only 15 haplotypes (14.3%, 15/105) remained consistent with the multi-locus joint mutations identified by both methods, whereas the remaining haplotypes (85.7%, 90/105) always experienced more multiple mutations in the network evolutionary analysis (Additional file 7). The reason is that reverse mutations occurring 2–4 times at nine loci, including c.132, c.1477, c.1539, c.1559, c.1587, c.2092, c.3226, c.4074 and c.4179, could not be identified in sequence alignment, which makes it more difficult to accurately describe the sequence diversity of the pvmdr1 gene. However, this study can provide readers with a better understanding of the polymorphism of the pvmdr1 gene, and thus is valuable to the public.

In this study, 12 SNPs were found during the TMD of PvMDR1, with only one deleterious mutation c.2533C > T (L845F), and 37 SNPs were found within the digestive vesicle (Additional file 10), with one deleterious mutation c.4179G>C (K1393N) identified in 2.7% (1/37) of samples. PROVEAN and SIFT analyses suggest that these deleterious mutations may lead to altered amino acid charge and hydrophobicity, resulting in a lack of protein structural integrity [46]. Additionally, high-frequency mutations were observed, including c.1539T>A (S513R) (18.9%, 118/624) and c.4349C>T (S1450L) (15.4%, 96/624) within the digestive vesicle and c.3226T>C (F1076L) (75.6%, 472/624) at TMD domain (Additional file 10), which could also affect protein function based on previous research [47, 64].

In this study, the prevalent trend of the molecular markers associated with drug resistance in P. vivax strains infected with vivax malaria cases in Yunnan Province are systematically revealed, and a set of pvmdr1 full gene sequencing of P. vivax strains from the Myanmar population were obtained in batch, which will provide valuable information and enrich the GenBank data. However, there are some limitations to this study. Firstly, the copy number of pvmdr1 genes was not assessed. Secondly, due to limitation on the length of the article, the others molecular markers for drug resistance monitoring other than pvmdr1 were not included in the analyses. Future research should conduct a study on the association between resistance molecular markers and anti-malarial drug susceptibility phenotypes, as well as improving the monitoring data on molecular markers for drug resistance of P. vivax.

Conclusion

Most P. vivax strains of vivax malaria infections in Yunnan Province had been highly mutated in pvmdr1 gene, with variations in predominant mutation type from year to year. In recent years, more of the five to sevenfold mutation haplotypes have been detected, but with fewer deleterious mutation loci. It is worth further exploring the dynamics of pvmdr1 mutation polymorphism accumulation and reasonably verifying the correlation between the special mutation of pvmdr1 gene and the phenotypic changes in the susceptibility of anti-malarial drugs for treating vivax malaria, such as CQ.

Availability of data and materials

Not applicable.

Abbreviations

CQ:

Chloroquine

WHO:

World Health Organization

DRC:

Democratic Republic of the Congo

P. falciparum :

Plasmodium falciparum

P. vivax :

Plasmodium vivax

IC50:

50% Inhibition concentration

AQ:

Amodiaquine

SP:

Sulfadoxine-pyrimethamine

pvdhfr :

Plasmodium vivax Dihydrofolate reductase gene

pvdhps :

Plasmodium vivax Dihydropteroate synthase gene

pvmdr1 :

Plasmodium vivax Multidrug resistance 1 protein gene

YPMDRL:

Yunnan Province Malaria Diagnosis Referent Laboratory

CDSIRS:

China Disease Surveillance Information Reporting System

DBD:

Dried blood dots

CDS:

Coding DNA sequences

SNP:

Single nucleotide polymorphism

π:

Nucleotide diversity

He:

Heterozygosity

PvMDR1:

Plasmodium vivax Multidrug resistance protein 1

χ2 :

Chi-square test

MAF:

Minor allele frequency

OD:

Order

TMD:

Transmembrane domain

AL:

Alleles

AAV:

Coding amino acid variation

IP:

Imported

ID:

Indigenous

PROVEAN:

Protein variation effect analyzer

SIFT:

Sorting intolerant from tolerant

References

  1. Wellems TE, Plowe CV. Chloroquine-resistant malaria. J Infect Dis. 2001;184:770–6.

    Article  CAS  PubMed  Google Scholar 

  2. Yang HL, Yang PF, Li XL, Gao BH, Zhang ZY, Yang YM. Changes of chloroquine resistance of Plasmodium falciparum in Yunnan Province (in Chinese). J Pathog Biol. 2005;5:54–6.

    Google Scholar 

  3. Payne D. Spread of chloroquine resistance in Plasmodium falciparum. Parasitol Today. 1987;3:241–6.

    Article  CAS  PubMed  Google Scholar 

  4. Che LG, Chen WC, Yang HL. [Investigation on geographical distribution of chloroquine-resistant strains of falciparum malaria in Yunnan Province] (in Chinese). Chin J Parasitol Parasit Dis. 1991;12:31–3.

    Google Scholar 

  5. Yang HL, Yang PF, Dong Y, Che LG, He H, Liu DQ, et al. [Longitudinal monitoring of chloroquine resistance of Plasmodium falciparum in Yunnan Province] (in Chinese). Chin J Parasitol Parasit Dis. 1994;1:33–5.

    Google Scholar 

  6. Cai XZ. [Research progress in the prevention and control of chloroquine-resistant falciparum malaria since the establishment of Hainan Province (1988–1996)](in Chinese). Hainan Med J. 1997;3:153–5.

    Google Scholar 

  7. WHO. Chemotherapy of malaria and resistance to antimalarials. Geneva: World Health Organization; 1973.

    Google Scholar 

  8. Feng XP, Liu DQ. [Drug resistance monitoring of falciparum malaria and rational use of antimalarial drugs in China] (in Chinese). J Pathog Biol. 2014;9:664–9.

    Google Scholar 

  9. Liu DQ, Ren DX, Liu RJ, Qiu CP, Gao DQ. [A culture medium convenient for on-site determination of drug resistance of Plasmodium falciparum](in Chinese). Chin J Parasitol Parasit Dis. 1989;2:34–6.

    Google Scholar 

  10. Rieckmann KH, Campbell GH, Sax LJ, Mrema JE. Drug sensitivity of Plasmodium falciparum. An in-vitro microtechnique Lancet. 1978;1:22–3.

    CAS  PubMed  Google Scholar 

  11. WHO. In vitro micro-test (MarkIII) for assessment of the response of Plasmodium falciparum to chloroquine, mefloquine, quinine, amodiaquine. Geneva: World Health Organization; 2001.

    Google Scholar 

  12. Liu DQ, Feng XP, Yang HL, Lin SG, Chen WJ, Yang PF. [Growth and decline of chloroquine resistance of Plasmodium falciparum in China] (in Chinese). Chin J Parasitol Parasit Dis. 2005;1:29–33.

    CAS  Google Scholar 

  13. Department of Health of China. [Specification for use of antimalarial drugs] (in Chinese). The People's Republic of China. 1958.

  14. Yang HL. [Review and prospect of the application of antimalarial drugs in Yunnan] (in Chinese). J Pract Parasitic Dis. 1999;4:174–6.

    Google Scholar 

  15. The National Health and Family Planning Commission. [Technical regulations for application of antimalarials (WS/T 485-2016)] (in Chinese). The People's Republic of China. 2016. http://www.nhc.gov.cn/ewebeditor/uploadfile/2016/05/20160530092853121.pdf

  16. Zhang L, Feng J, Tu H, Yun JH, Xia ZG. [Epidemiological characteristics of malaria in China, 2020] (in Chinese). Chin J Parasitol Parasit Dis. 2021;39:195–9.

    CAS  Google Scholar 

  17. YIPD. [Histories of the Yunnan Institute of Malaria Prevention and Control] (in Chinese). Yunnan Institute of Parasitic Diseases. 2011.

  18. Sheng CX, Zhang ZX, Zhou S, Wang LB. [Malaria surveillance report in Yunnan Province from 1991 to 2000] (in Chinese). J Pathog Biol. 2003;16:16–8.

    Google Scholar 

  19. Li HX, Chen GW, Yang YC, Jiang H, Zhang ZX, Yang HL, et al. [Current situation and trend of malaria epidemic in Yunnan Province from 2001 to 2010] (in Chinese). Chin J Vector Biol Control. 2013;24:147–51.

    Google Scholar 

  20. Zhou YW, Lin ZR, Sun XD, Zhao XT, Lu Q, Wei C, et al. [Analysis on epidemic characteristics of malaria elimination in Yunnan Province from 2011 to 2019] (in Chinese). J Pathog Biol. 2020;11:94–7.

    Google Scholar 

  21. Zhang L, Yi BY, Xia ZG, Yun JH. [Epidemiological characteristics of malaria in China, 2021](in Chinese). Chin J Parasitol Parasit Dis. 2022;40:135–9.

    Google Scholar 

  22. Wei C, Lu N, Yang R, Tang HR, Lu Q, Jiang JY. [Epidemic situation of malaria in Yunnan Province from 2014 to 2019](in Chinese). Chin J Schistosomiasis Control. 2020;32:483–8.

    CAS  Google Scholar 

  23. Zhang L, Feng J, Zhang SS, Xia ZG, Zhou SS. [Analysis of the progress and epidemic characteristics of malaria elimination nationwide in 2017](in Chinese). Chin J Parasitol Parasit Dis. 2018;36:201–9.

    Google Scholar 

  24. Rieckmann KH, Davis DR, Hutton DC. Plasmodium vivax resistance to chloroquine? Lancet. 1989;2:1183–4.

    Article  CAS  PubMed  Google Scholar 

  25. Baird JK, Basri H, Purnomo, Bangs MJ, Subianto B, Patchen LC, et al. Resistance to chloroquine by Plasmodium vivax in Irian Jaya, Indonesia. Am J Trop Med Hyg. 1991;44:547–52.

  26. Myat-Phone-Kyaw, Myint-Oo, Myint-Lwin, Thaw-Zin, Kyin-Hla-Aye, Nwe-Nwe-Yin. Emergence of chloroquine-resistant Plasmodium vivax in Myanmar (Burma). Trans R Soc Trop Med Hyg. 1993;87:687.

  27. Dua VK, Kar PK, Sharma VP. Chloroquine resistant Plasmodium vivax malaria in India. Trop Med Int Health. 1996;1:816–9.

    Article  CAS  PubMed  Google Scholar 

  28. Phan GT, de Vries PJ, Tran BQ, Le HQ, Nguyen NV, Nguyen TV, et al. Artemisinin or chloroquine for blood stage Plasmodium vivax malaria in Vietnam. Trop Med Int Health. 2002;7:858–64.

    Article  CAS  PubMed  Google Scholar 

  29. WHO. World Malaria Report 2018. Geneva: World Health Organization; 2018.

    Google Scholar 

  30. Zeng W, Zhao H, Zhao W, Yang Q, Li X, Li X, et al. Molecular surveillance and ex vivo drug susceptibilities of Plasmodium vivax isolates from the China-Myanmar border. Front Cell Infect Microbiol. 2021;11: 738075.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Marfurt J, Müeller I, Sie A, Maku P, Goroti M, Reeder JC, et al. Low efficacy of amodiaquine or chloroquine plus sulfadoxine-pyrimethamine against Plasmodium falciparum and P. vivax malaria in Papua New Guinea. Am J Trop Med Hyg. 2007;77:947–54.

    Article  CAS  PubMed  Google Scholar 

  32. Ratcliff A, Siswantoro H, Kenangalem E, Wuwung M, Brockman A, Edstein MD, et al. Therapeutic response of multidrug-resistant Plasmodium falciparum and P. vivax to chloroquine and sulfadoxine-pyrimethamine in southern Papua, Indonesia. Trans R Soc Trop Med Hyg. 2007;101:351–9.

    Article  CAS  PubMed  Google Scholar 

  33. Ganguly S, Saha P, Guha SK, Das S, Bera DK, Biswas A, et al. In vivo therapeutic efficacy of chloroquine alone or in combination with primaquine against vivax malaria in Kolkata, West Bengal, India, and polymorphism in pvmdr1 and pvcrt-o genes. Antimicrob Agents Chemother. 2013;57:1246–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Pukrittayakamee S, Imwong M, Looareesuwan S, White NJ. Therapeutic responses to antimalarial and antibacterial drugs in vivax malaria. Acta Trop. 2004;89:351–6.

    Article  CAS  PubMed  Google Scholar 

  35. Marfurt J, de Monbrison F, Brega S, Barbollat L, Müller I, Sie A, et al. Molecular markers of in vivo Plasmodium vivax resistance to amodiaquine plus sulfadoxine-pyrimethamine: mutations in pvdhfr and pvmdr1. J Infect Dis. 2008;198:409–17.

    Article  PubMed  Google Scholar 

  36. Desjardins RE, Canfield CJ, Haynes JD, Chulay JD. Quantitative assessment of antimalarial activityin vitro by a semiautomated microdilution technique. Antimicrob Agents Chemother. 1979;16:710–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Corbett Y, Herrera L, Gonzalez J, Cubilla L, Capson TL, Coley PD, et al. A novel DNA-based microfluorimetric method to evaluate antimalarial drug activity. Am J Trop Med Hyg. 2004;70:119–24.

    Article  CAS  PubMed  Google Scholar 

  38. Li JY, Li Q, Fang Q. [Research progress on chloroquine resistance of Plasmodium vivax](in Cinese). Chin J Schistosomiasis Control. 2014;26:326–31.

    CAS  Google Scholar 

  39. WHO. Malaria Surveillance, Monitoring & Evaluation: A Reference Manua. Geneva: World Health Organization; 2018.

    Google Scholar 

  40. Hastings MD, Sibley CH. Pyrimethamine and WR99210 exert opposing selection on dihydrofolate reductase from Plasmodium vivax. Proc Natl Acad Sci USA. 2002;99:13137–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Korsinczky M, Fischer K, Chen N, Baker J, Rieckmann K, Cheng Q. Sulfadoxine resistance in Plasmodium vivax is associated with a specific amino acid in dihydropteroate synthase at the putative sulfadoxine-binding site. Antimicrob Agents Chemother. 2004;48:2214–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Chung DI, Jeong S, Dinzouna-Boutamba SD, Yang HW, Yeo SG, Hong Y, et al. Evaluation of single nucleotide polymorphisms of pvmdr1 and microsatellite genotype in Plasmodium vivax isolates from Republic of Korea military personnel. Malar J. 2015;14:336.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Suwanarusk R, Russell B, Chavchich M, Chalfein F, Kenangalem E, Kosaisavee V, et al. Chloroquine resistant Plasmodium vivax: in vitro characterisation and association with molecular polymorphisms. PLoS ONE. 2007;2:e1089.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Nomura T, Carlton JM, Baird JK, del Portillo HA, Fryauff DJ, Rathore D, et al. Evidence for different mechanisms of chloroquine resistance in 2 Plasmodium species that cause human malaria. J Infect Dis. 2001;183:1653–61.

    Article  CAS  PubMed  Google Scholar 

  45. Musset L, Heugas C, Naldjinan R, Blanchet D, Houze P, Abboud P, et al. Emergence of Plasmodium vivax resistance to chloroquine in French Guiana. Antimicrob Agents Chemother. 2019;63:e02116-e2118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. NgassaMbenda HG, Wang M, Guo J, Siddiqui FA, Hu Y, Yang Z, et al. Evolution of the Plasmodium vivax multidrug resistance 1 gene in the Greater Mekong Subregion during malaria elimination. Parasit Vectors. 2020;13:67.

    Article  CAS  Google Scholar 

  47. Kittichai V, Nguitragool W, NgassaMbenda HG, Sattabongkot J, Cui L. Genetic diversity of the Plasmodium vivax multidrug resistance 1 gene in Thai parasite populations. Infect Genet Evol. 2018;64:168–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sá JM, Nomura T, Neves Jd, Baird JK, Wellems TE, del Portillo HA. Plasmodium vivax: allele variants of the mdr1 gene do not associate with chloroquine resistance among isolates from Brazil, Papua, and monkey-adapted strains. Exp Parasitol. 2005;109:256–9.

    Article  PubMed  Google Scholar 

  49. Carlton J. The Plasmodium vivax genome sequencing project. Trends Parasitol. 2003;19:227–31.

    Article  CAS  PubMed  Google Scholar 

  50. Walliker D, Quakyi IA, Wellems TE, McCutchan TF, Szarfman A, London WT, et al. Genetic analysis of the human malaria parasite Plasmodium falciparum. Science. 1987;236:1661–6.

    Article  CAS  PubMed  Google Scholar 

  51. McConkey GA, Waters AP, McCutchan TF. The generation of genetic diversity in malaria parasites. Annu Rev Microbiol. 1990;44:479–98.

    Article  CAS  PubMed  Google Scholar 

  52. Li J, Zhang J, Li Q, Hu Y, Ruan Y, Tao Z, et al. Ex vivo susceptibilities of Plasmodium vivax isolates from the China-Myanmar border to antimalarial drugs and association with polymorphisms in Pvmdr1 and Pvcrt-o genes. PLoS Negl Trop Dis. 2020;14: e0008255.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Huang F, Li S, Tian P, Pu LJS, Cui Y, Liu H, et al. Genetic polymorphisms in genes associated with drug resistance in Plasmodium vivax parasites from northeastern Myanmar. Malar J. 2022;21:66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Wang Z, Wei C, Pan Y, Wang Z, Ji X, Chen Q, et al. Polymorphisms of potential drug resistant molecular markers in Plasmodium vivax from China-Myanmar border during 2008–2017. Infect Dis Poverty. 2022;11:43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Orjuela-Sánchez P, de Santana Filho FS, Machado-Lima A, Chehuan YF, Costa MR, Alecrim Md, et al. Analysis of single-nucleotide polymorphisms in the crt-o and mdr1 genes of Plasmodium vivax among chloroquine-resistant isolates from the Brazilian Amazon region. Antimicrob Agents Chemother. 2009;53:3561–4.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Rungsihirunrat K, Muhamad P, Chaijaroenkul W, Kuesap J, Na-Bangchang K. Plasmodium vivax drug resistance genes; Pvmdr1 and Pvcrt-o polymorphisms in relation to chloroquine sensitivity from amalaria endemic area of Thailand. Korean J Parasitol. 2015;53:43–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Diez Benavente E, Ward Z, Chan W, Mohareb FR, Sutherland CJ, Roper C, et al. Genomic variation in Plasmodium vivax malaria reveals regions under selective pressure. PLoS ONE. 2017;12: e0177134.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Imwong M, Pukrittayakamee S, Pongtavornpinyo W, Nakeesathit S, Nair S, Newton P, et al. Gene amplification of the multidrug resistance 1 geneof Plasmodium vivax isolates from Thailand, Laos, and Myanmar. Antimicrob Agents Chemother. 2008;52:2657–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Zhao Y, Wang L, Soe MT, Aung PL, Wei H, Liu Z, et al. Molecular surveillance for drug resistance markers in Plasmodium vivax isolates from symptomatic and asymptomatic infections at the China-Myanmar border. Malar J. 2020;19:281.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Golassa L, Erko B, Baliraine FN, Aseffa A, Swedberg G. Polymorphisms in chloroquine resistance-associated genes in Plasmodium vivax in Ethiopia. Malar J. 2018;17:188.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Tacoli C, Gai PP, Siegert K, Wedam J, Kulkarni SS, Rasalkar R, et al. Characterization of Plasmodium vivax pvmdr1 polymorphisms in isolates from Mangaluru. India Am J Trop Med Hyg. 2019;101:416–7.

    Article  CAS  PubMed  Google Scholar 

  62. Bong JJ, Lee W, Lee CH, Park Q, Noh KT. Single nucleotide polymorphism analysis of pvmdr-1 in Plasmodium vivax isolated from military personnel of Republic of Korea in 2016 and 2017. Malar J. 2022;21:205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Siddiqui FA, Cabrera M, Wang M, Brashear A, Kemirembe K, Wang Z, et al. Plasmodium falciparum falcipain-2a polymorphisms in Southeast Asia and their association with artemisinin resistance. J Infect Dis. 2018;218:434–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Lu F, Lim CS, Nam DH, Kim K, Lin K, Kim TS, et al. Genetic polymorphism in pvmdr1 and pvcrt-o genes in relation to in vitro drug susceptibility of Plasmodium vivax isolates from malaria-endemic countries. Acta Trop. 2011;117:69–75.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We appreciate the support from the Centers for Disease Control and Prevention in states/cities and counties such as Dehong, Baoshan, Kunming, Pu'er, Lincang, Dali, Nujiang, Lijiang, Xishuangbanna, Yuxi, Chuxiong, Honghe, Zhaotong, Diqing, Qujing, and Wenshan.

Funding

This study was supported by the National Science Foundation, China (No. 81960579, 82160637).

Author information

Authors and Affiliations

Authors

Contributions

DH was responsible for the study design, carried out genetic testing and wrote the manuscript; YD was responsible for the study design and coordinated the project and statistical analysis, as well as edited the text, including an English check; Yan Deng, YX, YL, JW, MC, CZ and ZW performed the collection of blood samples, microscopy examination and re-testing the Plasmodium species in malaria cases. All authors read and approved the final version.

Corresponding authors

Correspondence to Ying Dong or Weibin Zheng.

Ethics declarations

Ethics approval and consent to participate

The study was approved by Yunnan Institute of Parasitic Diseases and by the Ethical Committee. Genetic testing and other experiments were performed on stored blood samples obtained as part of routine diagnostic work-up on patients with fever suspected of malaria. Although there was no risk and the data processing after sample collection was done anonymously, informed consent was obtained. Yunnan Institute Parasitic Diseases does not allow retrieving and saving the personal identification information into the project database. It is our commitment to not provide information about patients to any person unrelated to the study.

Consent for publication

All authors provided their consent for the publication of this report.

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:

Confirmation of malaria case infected with mono-Plasmodium vivax in Yunnan Province.

Additional file 2:

Using NC_009915.1 reference sequence as the template of pvmdr1 gene for designment the different primers.

Additional file 3:

The distribution of vivax malaria cases diagnosed in different years and prefectures.

Additional file 4:

Electrophoresis of PCR amplification products of pvmdr1 gene in P. vivax from vivax malaria cases in Yunnan Province.

Additional file 5:

Identify true base substitutions.

Additional file 6:

Fig. S1 The subfigure of SNPs composition at 2014, Fig. S2 The subfigure of SNPs composition at 2020, Fig. S3 The subfigure of SNPs composition at 2021 and Fig. S4 Subfigure of SNPs composition at 2022, respectively.

Additional file 7.

The composition of 105 haplotypes identified from 624 pvmdr1 gene sequences.

Additional file 8:

Fig.S1 The subfigure of haplotypes composition at 2014, Fig. S2 The subfigure of haplotypes composition at 2020, Fig. S3 The subfigure of haplotypes composition at 2021, Fig. S4 The subfigure of haplotypes composition at 2022, respectively.

Additional file 9.

The difference of multiplicity degree in 90 haplotypes identified by between gene sequence alignment and network evolutionary analysis.

Additional file 10.

The predicted 3D structural diagram of P. vivax multidrug resistance protein 1 (PvMDR1).

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ding, H., Dong, Y., Deng, Y. et al. Characteristics of molecular markers associated with chloroquine resistance in Plasmodium vivax strains from vivax malaria cases in Yunnan Province, China. Malar J 22, 181 (2023). https://doi.org/10.1186/s12936-023-04616-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12936-023-04616-0

Keywords