Abstract
Background
Current malaria control and elimination strategies rely mainly on efficacious antimalarial drugs. However, drug resistance is a major threat facing malaria control programs. Determination of drug resistance molecular markers is useful in the monitoring and surveillance of malaria drug efficacy. This study aimed to determine the mutations and haplotypes frequencies of different genes linked with antimalarial drug resistance in certain areas in Sudan.
Methods
A total of 226 dried blood spots (DBS) of microscopically diagnosed P. falciparum isolates were collected from Khartoum and three other areas in Sudan during 2015–2017. Plasmodium falciparum confirmation and multiplicity of infection was assessed using the Sanger’s 101 SNPs-barcode and speciation was confirmed using regions of the parasite mitochondria. Molecular genotyping of drug resistance genes (Pfcrt, Pfmdr1, Pfdhfr, Pfdhps, exonuclease, Pfk13, parasite genetic background (PGB) (Pfarps10, ferredoxin, Pfcrt, Pfmdr2)) was also performed. All genotypes were generated by selective regions amplicon sequencing of the parasite genome using the Illumina MiSeq platform at the Wellcome Sanger Institute, UK then genotypes were translated into drug resistance haplotypes and species determination.
Findings
In total 225 samples were confirmed to be P. falciparum. A higher proportion of multiplicity of infection was observed in Gezira (P<0.001) based on the Sanger 101 SNPs -barcode. The overall frequency of mutant haplotype Pfcrt 72–76 CVIET was 71.8%. For Pfmdr1, N86Y was detected in 53.6%, Y184F was observed in 88.1% and D1246Y was detected in 1.5% of the samples. The most frequently observed haplotype was YFD 47.4%. For Pfdhfr (codons 51, 59,108,164), the ICNI haplotype was the most frequent (80.7%) while for Pfdhps (codons 436, 437, 540, 581, 613) the (SGEAA) was most frequent haplotype (41%). The Quadruple mutation (dhfr N51I, S108N + dhps A437G, K540E) was the highest frequent combined mutation (33.9%). In Pfkelch13 gene, 18 non‐synonymous mutations were detected, 7 of them were detected in other African countries. The most frequent Pfk13 mutation was E433D detected in four samples. All of the Pfk13 mutant alleles have not been reported to belong to mutations associated with delayed parasite clearance in Southeast Asia. PGB mutations were detected only in Pfcrt N326S\I (46.3%) and Pfcrt I356T (8.2%). The exonuclease mutation was not detected. There was no significant variation in mutant haplotypes between study areas.
Conclusions
There was high frequency of mutations in Pfcrt, Pfdhfr and Pfdhps in this study. These mutations are associated with chloroquine and sulfadoxine-pyrimethamine (SP) resistance. Many SNPs in Pfk13 not linked with delayed parasite clearance were observed. The exonuclease E415G mutation which is linked with piperaquine resistance was not reported.
Introduction
Malaria is considered a major public health problem in Sudan. According to the 2018 annual estimates, 1,617,499 confirmed malaria cases were reported and the reported deaths were 5,003 [1]. Plasmodium falciparum is responsible for 91.2% of malaria cases in the country while P. vivax makes 8.8% of the cases in Sudan [1]. The P. falciparum infections were most prevalent in eastern Sudan (86.8%), Gezira and Khartoum states (97.9% and 75%, respectively). Plasmodium vivax infections represent 12.5% of the total malaria infections in Khartoum and 7.5% in eastern Sudan while mixed infections represent 5.7% in eastern Sudan, 1.1% in central Sudan and 12.5% in Khartoum [2]. Effective malaria treatment, insecticide-treated bed nets, indoor residual spraying, and other vector control measures are the main pillars for malaria control [3].
In sub-Saharan countries including Sudan artemisinin-based combination therapy (ACT) is used as a first-line treatment of uncomplicated P. falciparum malaria and intravenous artesunate and quinine are used for the treatment of severe malaria [4].
In Sudan, ACT as artesunate and sulfadoxine-pyrimethamine (AS/SP) was introduced in 2004 for malaria treatment replacing chloroquine which became ineffective for the treatment of uncomplicated malaria [5]. Chloroquine had been used since the1960s for uncomplicated malaria, quinine for severe malaria and sulfadoxine-pyrimethamine for malaria in pregnancy and also as the second line of malaria treatment [6].
AS/SP remained in use until 2017 when it was replaced by Artemether-lumefantrine (AL) as the first line of treatment and dihydroartemisinin piperaquine (DHA-PPQ) as a second line for treatment of uncomplicated malaria [2]. Following the introduction of ACT in Sudan in 2004 malaria mortality declined from 1,814 to 612 deaths in 2011 [7,8]. In the subsequent years, mortality increased steadily reaching 1,446 deaths in 2017 [8].
Plasmodium falciparum resistance to antimalarial drugs is a major worldwide challenge for malaria control and elimination. The emergence of chloroquine-resistant parasites began in Southeast Asia in the 1960s following massive deployment of chloroquine. Similar patterns of resistance to alternative antimalarial drugs, such as sulfadoxine–pyrimethamine were reported in the same region [9].
Clinical in vivo efficacy trials are used to monitor the effectiveness of the combination therapies. However, this method does not differentiate between the different components of the combination therapies. Therefore, the study of malaria drug resistance molecular markers can be used to monitor each of the components of the ACT [10].
Chloroquine resistance was reported earlier in Sudan with a high level of the Pfcrt K76T mutation [11–13]. There is some evidence in African countries that withdrawal of chloroquine for several years was followed by re-emergence of the wild type 76K [14–16].
Mutations in bifunctional dihydrofolate reductase-thymidylate synthase (Pfdhfr) and dihydropteroate synthetase (Pfdhps) are linked with SP resistance [17]. In Sudan, mutations in Pfdhfr (N51I, S108N) and Pfdhps (A436G, K540E) were reported earlier [18,19]. Recently, the emergence of Pfdhfr (N59R) and Pfdhps (S436A, A581G) with an increased level of the combined mutations and hence the resistance to SP has been reported [20,21].
Mutations in Pfmdr1 are linked with many treatment failures in drugs such as mefloquine, chloroquine, amodiaquine, quinine, and halofantrine [22–25]. The mutation in Pfmdr1 (N86Y) linked with chloroquine failure was reported in different parts of Sudan [11,13,26]. Delayed parasite clearance was first described in Southeast Asia in 2013 and it was associated with mutations in P. falciparum kelch propeller protein gene (Pfk13) [27].
In Africa, a number of mutations were detected in the Pfk13 gene but not linked with delayed parasite clearance [28] except one isolate in Equatorial Guinea [27] and another in Uganda [28]. The latter mutations were C580Yand A675V respectively, similar to those associated with delayed parasite clearance in Southeast Asia [29,30]. Two recent studies from Sudan were performed on the Pfk13gene, the first one showed a single mutation (A621V) not linked with delayed parasite clearance, while the other study showed no mutations [21]. The parasite genetic background (PGB) is a group of mutations in genes including Pfarps10, ferredoxin, Pfcrt and Pfmdr2 which have been associated with samples with Pfk13 mutations [31].
It has been found that a mutation in exonuclease E415G was associated with piperaquine resistance [32]. This study aimed to assess antimalarial drug resistance molecular markers of P. falciparum isolates from different areas in Sudan during 2015–2017.
Materials and methods
Study design, areas and ethics statement
This study was a descriptive cross sectional study, carried out in four areas in Sudan, Khartoum (KH) central Sudan (15°37'35.39" N 32°31'35.39" E), New Halfa (NH) eastern Sudan (15°32'88" N 35°59'59.86" E), Gezira state (GS) central Sudan (14°29'59.99" N 33°09'60.00" E) and North Kordofan (NK) western Sudan (14°40'59.99" N 29°55'59.99" E) during October 2015- November 2017. Malaria transmission in all areas is unstable and seasonal with peaks following the rainy season between September to November. A second peak starts in January and extends up to March. The study areas were selected because they vary in their transmission intensity, epidemiology and entomological characteristics [2].
Samples from Khartoum were collected specifically for this study while the samples from the other sites were archived dried blood spots (DBS) from a previous study at the Institute of Endemic Diseases, University of Khartoum.
Ethical clearance for the Khartoum study was obtained from Al Neelain University Institutional Review Board (IRB No: NU-IRP-16-09-04-1) and for the other areas ethical clearance was obtained from the Institute of Endemic Diseases, Research Ethics Committee, University of Khartoum (Ref No 2/2014). Informed consent was obtained from each study participant or guardians of children prior to enrolment.
Study subjects and sample collection
A total of 226 DBS samples (KH n = 158, NH n = 30, GS n = 23, NK n = 15) were collected from subjects attending outpatient clinics with fever and other symptoms suggestive of malaria. Patients diagnosed positive for P. falciparum malaria were asked to participate in the study. Those who consented to participate were asked to give blood spots. Blood samples were collected from Fingerpicks (50 μl) on Whatman 3 filter paper (Whatman International Ltd Maidstone, England) using aseptic conditions. The spots were allowed to dry, kept in a sealed plastic bag, numbered and stored at room temperature until used. Diagnosis of malaria was performed by microscopic examination of thick and thin blood smears stained with 10% Giemsa solution according to standard protocols [33].
DNA extraction, amplicon sequencing, and molecular identification of species, drug resistance alleles, and multiplicity of infection
The DBS samples on filter papers were sent to the Wellcome Sanger Institute for processing, molecular genotyping and analysis. DNA extraction was carried out using the QIAGEN DNA Investigator Kit (No. 56504, Qiagen, Crawley, UK). DNA was eluted in 50 μl TE buffer and stored at − 20 °C for later use. Amplicon sequencing was performed on all samples using a custom protocol from the Wellcome Sanger Institute (Jacob et al. manuscript in preparation). In brief, targets for genotyping were identified and multiplex PCR primers were designed using the mPrimer software [34]. Primers were constructed to amplify products with a length of 190–250 bp and were combined into 3 pools. A two-step protocol was used to first amplify the selective regions of the parasite genome from extracted genomic DNA followed by a second PCR to incorporate sequencing and multiplexing adapters [35]. Plasmodium species was determined by analyzing highly conserved segments of the parasite mitochondrial genome common to all 5 human infecting species (P. falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi) [36]. Two separate 200bp segments (non-genic) were sequenced in multiplex and aligned to the reference sequences of P. falciparum and P. vivax and non-reference alleles determined which species were within each DNA sample. Quality and purity of amplicons were checked using the Agilent DNA 1000 assay kit on a 2100 Bioanalyzer (Agilent Technology). Batched samples (max n = 384) were sequenced in a single MiSeq lane combining all PCR products [37]. Samples reads were de-plexed using the multiplexing adapters and individual CRAM files were aligned to a modified amplicon reference genome (Pf3D7_v3). Genotyping was done using bcftools as well as custom scripts to filter and translate genotypes into drug resistance haplotypes [38]. Sequences data including nucleotide sequencing information were deposited in the public repository European Nucleotide Archive (ENA) with accession numbers provided as supplementary data (S2 File).
The multiplicity of infection (MOI) was determined using COIL and Real McCOIL programs [39,40]. Both programs used the SNP barcode of 101 bi-allelic SNPs genotyped by amplicon sequencing. The MOI was expressed as an integer, which is the estimated number of individual parasites within the sample.
Molecular genotyping of antimalarial resistance genes (Pfcrt, Pfmdr1, Pfdhfr, PfdhPfs, exonuclease, Pfk13, parasitegenetic background (Pfarps10, ferredoxin, Pfcrt, Pfmdr2) was also performed at specific loci outlined in the results section. Using the reference genome, SNPs were translated to amino-acids and compared with the relevant literature to determine association with antimalarial drug resistance.
Data analysis
Frequencies and percentages of mutant alleles and haplotypes were determined using Statistical Package for Social Sciences version 20 software (SPSS Software, Chicago Inc., USA) for data analysis. The variation of mutant haplotypes between study areas was measured using Chi-square test. Statistical significance level was defined as P-value ≤ 0.05.
Results
Plasmodium falciparum identification and multiplicity of infection
Characteristics of the study participants are presented in Table 1. Out of 226 samples diagnosed by microscopic examination as P. falciparum, 225 were confirmed to be P. falciparum by amplicon sequencing. One sample was identified as P. vivax and excluded from further analysis. Multiplicity of infection was successfully determined in 211 samples where (32/211) (15.1%) isolates were found to harbor multiclonal P. falciparum infection. The overall mean number of parasite clones was 1.15. A higher proportion of multiplicity of infection was seen in Gezira using either COIL or McCOIL methods (P<0.001) based on the Sanger 101 SNP-barcodes (Table 1).
Table 1. Baseline characteristics of study participants and multiplicity of infection (MOI).
| Khartoum (KH) | New Halfa (NH) | Gezira (G) | North Kordofan (NK) | Total | |
|---|---|---|---|---|---|
| No of samples | 158 | 30 | 23 | 15 | 226 |
| N (%) male | 101 (63.9%) | 16 (53.3%) | 15 (65.2%) | 9 (60%) | 142 (62%) |
| Median age (years) | 13.7 | 19 | 6.4 | 17.5 | 14.15 |
| Multiclonal infections (n = 21) | 20 (13.4%) | 4 (16%) | 6 (27.2%) | 2 (13.3%) | 32 (15.1%) |
| MOI* | 1.13 | 1.16 | 1.27 | 1.13 | 1.15 |
* P<0.001
Plasmodium falciparum chloroquine resistance transporter gene (Pfcrt)
Out of 225 samples, a total of 213 samples were successfully amplified and sequenced for Pfcrt. No mutations were detected at codons 72 and 97. However, 71–73% of the samples harbored the mutant alleles M74I, N75E, K76T, A220S, Q271E and R371I (Table 2).
Table 2. Frequency of mutant alleles in Pfcrt and Pfmdr1.
| Drug resistance maker | Mutant alleles | n (%) |
|---|---|---|
| Pfcrt (n = 213) | M74I | 153 (71.8%) |
| N75E | 153 (71.8%) | |
| K76T | 153 (71.8%) | |
| A220S | 154 (72.3%) | |
| Q271E | 155 (73%) | |
| R371I | 155 (73%) | |
| Pfmdr1 (n = 194) | N86Y | 104 (53.6%) |
| Y184F | 171 (88.1%) | |
| D1246Y | 3 (1.5%) |
Pfcrt: P. falciparum chloroquine resistance transporter gene; Pfmdr1: P. falciparum multidrug resistance protein 1 gene.
Regarding Pfcrt haplotypes, 153/213 (71.8%) samples carried the mutant haplotype CVIET while the wild haplotype CVMNK was detected in 60/213 (28.2%) of the samples. All samples that harbor the mutant haplotype of Pfcrt at positions 72–76 (CVIET) were also Pfcrt mutant at positions A220S, Q271E and R371I. The frequency of Pfcrt mutant haplotype CVIET in North Kordofan was 100%, Gezira 76%, New Halfa 75% and Khartoum 67%. The differences in frequencies between the different sites were not statistically significant (Table 3).
Table 3. Frequency of Pfcrt and Pfmdr1 haplotypes.
| Drug resistance maker | number of mutations | mutation haplotype | KH n = 149 | NH n = 29 | G n = 21 | NK n = 14 | Total n (%) | P. value |
|---|---|---|---|---|---|---|---|---|
| Pfcrt (n = 213) | None | Wild Type CVMNK | 48 (32.2%) | 7 (24.1%) | 5 (23.8%) | 0 (0%) | 60 (28.2%) | 0.17 |
| Triple | CVIET | 101 (67.8%) | 22 (75.9%) | 16 (76.2%) | 14 (100%) | 153 (71.8%) | 0.17 | |
| Pfmdr1 (n = 194) | None | Wild Type NYD | 9 (6.5%) | 0 (0%) | 4 (19.0%) | 0 (0%) | 13 (6.7%) | |
| Single | YYD | 6 (4.3%) | 1 (3.8%) | 1 (4.7%) | 1 (12.5%) | 9 (3.1%) | ||
| NFD | 51 (36.7%) | 14 (53.8%) | 9 (42.9%) | 3 (37.5%) | 77 (39.7%) | 0.42 | ||
| Double | YFD | 70 (50.4%) | 11 (42.3%) | 7 (33.3%) | 4 (50.0%) | 92 (47.4%) | 0.48 | |
| YYY | 1 (0.7%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.5%) | |||
| Triple | YFY | 2 (1.4%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (1%) |
Pfcrt: P. falciparum chloroquine resistance transporter gene; Pfmdr1: P. falciparum multidrug resistance protein 1 gene; KH: Khartoum; NH: New Halfa; G:Gezira; NK: North Kordofan.
Plasmodium falciparum multidrug resistance protein 1 gene (Pfmdr1)
A total of 194 samples were successfully amplified and sequenced. The N86Y mutation was detected in 104/194 (53.6%) samples, while Y184F was observed in 171/194 (88.1%) and D1246Y in 3/194 (1.5%) samples. There were no mutations detected in S1034, N1042 and F1226. The frequencies of Pfmdr1 haplotypes did not significantly vary between the different studied sites.
Pfmdr1 YFD haplotype was detected in 92/194 (47.4%) samples while NFD haplotype was observed in 77/194 (39.7%) samples (Table 3).
Plasmodium falciparum bifunctional dihydrofolate reductase–thymidylate synthase gene (Pfdhfr)
Out of 225 samples, a total of 187 samples were successfully amplified and sequenced for Pfdhfr. The N51I mutation was detected in 181/187 (96.7%) samples, while C59R was seen in 30/187 (16%) samples and Pfdhfr S108N was observed in 183/187 (97.8%) samples (Table 4). There were no mutations detected in A16 and I164.
Table 4. Frequency of Pfdhfr and Pfdhps mutant alleles.
| Mutant alleles | Frequency | |
|---|---|---|
| Pfdhfr (n = 187) | A16V | 0 (0%) |
| N51I | 181 (96.7%) | |
| C59R | 30 (16%) | |
| S108N | 183 (97.8%) | |
| Pfdhps (n = 183) | S436A | (4.3%) 8 |
| A437G | 139 (76%) | |
| K540E | 124 (67.8%) | |
| A581G | 48 (26.2%) |
Pfdhfr: P. falciparum bifunctional dihydrofolate reductase–thymidylate synthase gene; Pfdhps: P. falciparum dihydropteroate synthase gene.
Regarding genotyping of Pfdhfr, the wild haplotype (NCSI) was detected in 3 samples (1.6%) while double mutations in codon 51 and 108 (ICNI) was the most frequent haplotype 151/187 (80.7%). The triple mutant haplotype (IRNI) was detected in 29/187 (15.5%) samples (Table 5). There was no significant variation in the frequency of mutant haplotypes between the different areas (Table 5).
Table 5. Frequency of Pfdhfr and Pfdhps haplotypes.
| Number of mutations | Mutation haplotype | KH n = 134 | NH n = 23 | G n = 19 | NK n = 11 | Total n (%) | P. value | |
|---|---|---|---|---|---|---|---|---|
| Pfdhfr (n = 187) | None | Wild Type NCSI | 3 (2.3%) | 0 (0%) | 0 (0%) | 0 (0%) | 3 (1.6%) | |
| ICSI | 1 (0.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.53%) | |||
| NCNI | 2 (1.5%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (1.1%) | |||
| Double | ICNI | 104 (77.6%) | 20 (86.9%) | 17 (89.4%) | 10 (90.9%) | 151 (80.7%) | 0.37 | |
| NRNI | 1 (0.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.53%) | |||
| Triple | IRNI | 23 (17.2%) | 3 (13.04%) | 2 (10.5%) | 1 (9.1%) | 29 (15.5%) | 0.77 | |
| Pfdhps (n = 183) | None | Wild Type SAKAA | 33 (24.6%) | 1 (4.3%) | 3 (15.8%) | 2 (18.2%) | 39(21.3%) | 0.10 |
| Single | AAKAA | 4 (2.9%) | 0 (0%) | 0 (0%) | 1 (9%) | 5 (%) | ||
| SGKAA | 12 (8.9%) | 1 (4.3%) | 0 (0%) | 0 (0%) | 13(%) | |||
| Double | SGEAA | 50 (37.3%) | 14 (60.8%) | 6 (31.6%) | 5 (45.5%) | 75 (41%) | 0.24 | |
| AGKAA | 0 (0%) | 1 (4.3%) | 1 (5.2%) | 0 (0%) | 2 (1.09%) | |||
| Triple | SGEGA | 31 (23.1%) | 6 (26.1%) | 9 (47.3) | 3 (27.7%) | 48 (26.2%) | 0.19 | |
| AGEAA | 0 (0%) | 1 (4.3%) | 0 (0%) | 0 (0%) | 1 (%) | |||
| Pfdhps/ Pfdhfr (n = 183) | None | Wild Type NCSI + SAKAA | 3 (2.3%) | 0 (0%) | 0 (0%) | 0 (0%) | 3 (1.6%) | |
| NCNI + SAKAA | 2 (1.5%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.7%) | |||
| Double | ICNI +SAKAA | 26 (20.0%) | 1 (4.3%) | 2 (10.5%) | 1 (9.1%) | 30 (16.4%) | 0.18 | |
| NRNI + SAKAA | 1 (0.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.54%) | |||
| ICSI+ AAKAA | 1 (0.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.54%) | |||
| Triple | IRNI +SAKAA | 1 (0.8%) | 0 (0%) | 1 (5.2%) | 1 (9.1%) | 2(1.1%) | ||
| ICNI + AAKAA | 3 (2.3%) | 0 (0%) | 0 (0%) | 1 (9.1%) | 4 (2.2%) | |||
| ICNI + SGKAA | 7 (5.4%) | 1 (4.3%) | 0 (0%) | 0 (0%) | 8(4.4%) | |||
| Quadruple | IRNI+ SGKAA | 4 (3.1%) | 0 (0%) | 0 (0%) | 0 (0%) | 4 (2.2%) | ||
| ICNI + SGEAA | 40 (30.8%) | 11 (47.8%) | 6 (31.6%) | 5 (45.5%) | 62 (33.9%) | 0.42 | ||
| ICNI + AGKAA | 0 (0%) | 1 (4.3%) | 1 (5.3%) | 0 (0%) | 2 (1.1%) | |||
| IRNI+AAKAA | 1 (0.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.54%) | |||
| Quintuple | IRNI + SGEAA | 10 (7.7%) | 2 (8.7%) | 0 (0%) | 0 (0%) | 12 (6.5%) | ||
| ICNI + AGEAA | 0 (0%) | 1 (4.3%) | 0 (0%) | 0 (0%) | 1 (0.54%) | |||
| ICNI + SGEGA | 22 (16.9%) | 5 (21.7%) | 8 (42.1%) | 3 (27.3%) | 38 (20.7%) | 0.08 | ||
| Sextuple | IRNI + SGEGA | 9 (6.9%) | 1 (4.3%) | 1 (5.3%) | 0 (0%) | 11 (6%) |
Pfdhfr: P. falciparum bifunctional dihydrofolate reductase–thymidylate synthase gene; Pfdhps: P. falciparum dihydropteroate synthase gene.
Plasmodium falciparum dihydropteroate synthase gene (Pfdhps)
Out of 225 samples, 183 samples were successfully amplified and sequenced for Pfdhps. The mutation S436A was detected in 8/183 (4.3%) samples, while A437G was observed in 139/183 (76%), K540E in 124/183 (67.8%) and A581G was found in 48/183 (26.2%) samples (Table 4).
Regarding Pfdhps haplotypes, wild type SAKAA was detected in 39/183 (21.3%) samples. Double mutations in codons 437 and 540 (SGEAA) was seen in 75/183 (41%) samples and the triple mutant haplotype A437G, K540E and A581G (SGEGA) was observed in 48/183 (26.2%) samples. There was no significant variation in the frequency of mutant haplotypes between the different areas (Table 5).
Combined mutations of Pfdhfr and Pfdhps
Quadruple mutations (dhfr N51I, S108N + dhps A437G, K540E) were identified in 62/183 (33.9%) samples and Quintuple mutations (dhfr N51I, S108N + dhps A437G, K540E, A581G) were detected in 38/183 (20.7%) samples. There was no significant variation in the frequencies of mutant haplotypes between the different areas (Table 5).
Plasmodium falciparum kelch13 and other resistance genes
Out of 225 samples, a total of 176 samples were successfully amplified and sequenced for Pfk13. Twenty-two mutations were found in 25/176 (14.2%) samples, 18 non-synonymous mutations and 4 synonymous mutations. Pfk13E433D was the most frequent mutation observed in 4 samples in Khartoum and North Kordofan areas (Table 6).
Table 6. Frequency of mutant alleles in Pfk13.
| Mutation | Frequency | Area | |
|---|---|---|---|
| PfK13 n = 176 | K372K | 1 (0.4%) | Khartoum |
| K378R | 1 (0.8%) | Khartoum | |
| D389H | 1 (0.4%) | Khartoum | |
| E401Q | 1 (0.4%) | New Halfa | |
| K430E | 1 (0.4%) | Khartoum | |
| E433D | 4 (2%) | Khartoum (3) and North Kordofan (1) | |
| F442F | 1 (0.4%) | North Kordofan | |
| L488L | 1 (0.4%) | Khartoum | |
| V494I | 1 (0.4%) | Gezira | |
| A504T | 1 (0.4%) | Khartoum | |
| E509E | 1 (0.4%) | Khartoum | |
| Y541H | 1 (0.4%) | Khartoum | |
| C542Y | 1 (0.4%) | New Halfa | |
| W565STOP | 1 (0.4%) | North Kordofan | |
| R575T | 1 (0.4%) | Khartoum | |
| E606K | 1 (0.4%) | Khartoum | |
| G625R | 1 (0.4%) | New Halfa | |
| A626T | 1 (0.4%) | New Halfa | |
| Y635C | 1 (0.4%) | Khartoum | |
| Q661P | 1 (0.4%) | Khartoum | |
| Q661R | 1 (0.4%) | Khartoum | |
| T677I | 1 (0.4%) | Khartoum | |
| Wild type | 198 (87.5) | ||
| PGB (parasite genetic background) n = 207 | Pfcrt N326S | 96 (46.3%) | All sites |
| Pfcrt I356T | 17 (8.2%) | All sites |
fk13: P. falciparum kelch propeller protein gene; PGB: Parasite genetic background genes.
For the parasite genetic background (PGB) mutations. Out of 225 samples, 207 were successfully amplified and sequenced. No mutations were detected in arps (V127, D128), Pfmdr2 T484 and ferredoxin D193Y while 96/207 (46.3%) samples harbor mutations in Pfcrt N326S\I and 17/207 (8.2%) Pfcrt I356T (Table 6). For Pf exonuclease E415, a total of 220 samples were successfully amplified and sequenced. No mutation was detected in exonuclease E415.
Discussion
This study was conducted in three regions in Sudan (Western, Eastern and Central) which are characterized by unstable and seasonal malaria transmission. Molecular markers associated with anti-malarial drug resistance were analyzed.
Mutations of chloroquine resistance transporter gene reported in this study were associated with changes in CVMNK (wild haplotype) to CVIET (mutant haplotype) (Table 1). The percentage of CVIET in this study ranged between 67.8% in Khartoum to 100% in North Kordofan, in accordance with published studies from Sudan [12,21]. Previous studies reported that CVIET is the most widespread resistant haplotype in Africa and Asia, while SVMNT is dominant in South America and Oceania [41]. These results show no sign of reduction of chloroquine resistance due to withdrawal of chloroquine as reported earlier that withdrawal of chloroquine would lead to regaining of the sensitivity of malaria parasite to chloroquine [14,42]. This finding may indicate that chloroquine is still being used in these areas.
Mutations in the multidrug resistance gene (Pfmdr1) in this study showed that Y184F was the highest frequency (88.1%), with N86Y being intermediate (53.6%) and the lowest D1246Y (1.5%). The mutation at position 86 is associated with chloroquine resistance [25]. The results of this study are in agreement with previously published data in Sudan [11,13,26]. On the other hand, the Pfmdr1 86Y mutation and/or the Pfmdr1 86Y-Y184 haplotypes were reported to be significantly associated with increased in vitro susceptibility of P. falciparum parasites to lumefantrine [43,44].
There were no additional mutations in the multidrug resistance gene detected at positions 1034, 1042 and 1226 in this study, which have been shown to affect the parasite response to mefloquine, chloroquine, quinine, and halofantrine in vitro [24,43].
Pyrimethamine drug resistance is strongly-linked with mutations in the bifunctional dihydrofolate reductase-thymidylate synthase [45]. Characterization of resistant parasites is based on the number of mutations they carry (single, double, triple, quadruple mutants), which is taken to be an indicator of the level of resistance to the drug. In this study, the percentage of double mutant haplotype ICNI was 80.7% and 15.5% for the triple mutant haplotype IRNI. The results of these gene mutations were similar to recent studies conducted in Sudan [20,21]. The low prevalence of the triple mutant haplotype IRNI may be due to low level of C59R mutation which was reported to be absent in Sudan from isolates in 2003 [18,19]. However, it was first detected in one isolate from a study of 63 Isolates in 2012 [46], since then, the frequency of this mutation has increased gradually.
Results of mutations in dihydropteroate synthase, which mediates sulfadoxine drug resistance [17], showed that the occurrence of double mutant haplotype SGEAA was 41% and 26.2% for the triple mutant haplotype SGEGA. This result is similar to a previous study conducted in Sudan in 2016 [20]. In contrast, there is a recent study reporting that the most prevalent haplotype is SGKAA [21].
Since sulfadoxine and pyrimethamine are mostly used in combination (SP), the combined mutations in dhfr+dhps are important to be documented. The results of the frequency of combined mutation showed that the total number of quadruple, quintuple, and hextuple mutations was 131 (71.5%) which indicates a high level of SP resistance [47]. As SP was used in combination therapy as the first line of treatment in Sudan until March 2017 [2], the continued pressure of SP could explain the increasing resistance of the parasite to the drug.
Several polymorphisms in thePfk13 propeller gene have resulted in delayed parasite clearance. The results of Pfk13 showed the occurrence of 22 mutations in 25 (14.2%) samples, 18 non-synonymous mutations and 4 synonymous mutations. The polymorphisms found in these samples were not similar to reported mutations associated with delayed parasite clearance in South East Asia. The non-synonymous mutations described in this study are in agreement with several studies conducted in Africa [48–51]. Notably, only two studies in Africa, from Equatorial Guinea [29] and Uganda [30] have reported C580Y and A675V mutations that are similar to those in South East Asia and lead artemisinin resistance [52]. Seven of the 18 non-synonymous mutations reported in this study, were also previously reported in other African countries, namely, V494I in Mozambique, C542Y in Burkina Faso and Zambia, W565Stop Central Africa, R575T Chinese immigrant in Ghana, G625R, A626T in Gabon and Y635C in Rwanda [28,53–56]. The remaining eleven mutations are novel mutations and further in vitro studies are needed to explore their relationships with artemisinin resistance [57].
Mutations of artemisinin resistance genetic background have been analyzed for four genes. Mutations were observed only in one gene Pfcrt (N326S, I356T). Mutations in the genetic background genes may have lead collectively to the emergence of K13 gene mutations in South East Asia [31]. As it appears there are mutations in only one member of the group and hence favor of the absence of Pfk13 mutations.
Next generation sequencing was performed to detect the exonuclease gene mutation which has been reported together with plasmepsin II-III amplification to be linked with piperaquine resistance in South East Asia [32]. There was no mutation detected in the exonuclease gene in this study. However, we have not performed plasmepsin II-III amplification. Piperaquine is the partner drug of the DHA-PPQ, the second line of treatment in Sudan. Absence of exonuclease mutation is encouraging as DHA-PPQ will continue to be effective. Further studies are required to monitor P. falciparum plasmepsin genes in Africa.
Conclusions
This study has shown high frequency of mutations in Pfcrt, Pfdhfr and Pfdhps genes. Quadruple and Quintuple combination of mutations of DHFR and DHPS were highly frequent. The above mutations are associated with chloroquine and sulfadoxine-pyrimethamine (SP) resistance. Many SNPs in Pfk13 not linked with delayed parasite clearance were observed. Exonuclease E415G mutation which is linked with piperaquine resistance was not reported.
Supporting information
(XLSX)
(XLSX)
(PDF)
(DOCX)
Acknowledgments
The authors would like to thank with gratitude the MalariaGEN staff of Wellcome Sanger Institute Centre, UK staff of Wellcome Sanger Institute Centre, UK for their kind contribution and proofreading the final manuscript. Further information about MalariaGen can be accessed on https://www.malariagen.net/projects/spotmalaria [malariagen.net]; the project is coordinated by the MalariaGEN Resource Centre with funding from Wellcome (098051, 090770). MalariaGEN P. falciparum data release v6.3 is available online http://lookseq.sanger.ac.uk/mystudies.
Data Availability
This publication uses data generated using Sudanese samples in collaboration with MalariaGEN SpotMalaria Project (https://www.malariagen.net/projects/spotmalaria). Sequences data including nucleotide sequencing information were deposited in the public repository European Nucleotide Archive (ENA), with accession numbers provided as supplementary data (S2 Suppl).
Funding Statement
The authors received no specific funding for this work.
References
- 1.WHO. World Malaria Report 2019. Geneva: World Health Organization; 2019; https://www.who.int/publications-detail/world-malaria-report-2019. [Google Scholar]
- 2.Federal Ministry of Health. Sudan malaria treatment protocol. 2017; https://www.humanitarianresponse.info/sites/www.humanitarianresponse.info/files/2019/07/Sudan-Malaria-Treatment-Protocol_2017.pdf.
- 3.Winskill P., et al. , Prioritizing the scale-up of interventions for malaria control and elimination. Malar J, 2019. 18(1): p. 122 10.1186/s12936-019-2755-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.WHO. WHO malaria treatment protocol. Geneva: World Health Organization; 2018; https://www.who.int/malaria/areas/treatment/overview/en/. [Google Scholar]
- 5.Adeel A.A., Drug-resistant malaria in Sudan: A review of evidence and scenarios for the future. Sudan J Paediatr, 2012. 12(1): p. 8–20. [PMC free article] [PubMed] [Google Scholar]
- 6.Malik E.M., et al. , From chloroquine to artemisinin-based combination therapy: the Sudanese experience. Malar J, 2006. 5: p. 65 10.1186/1475-2875-5-65 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.WHO. World Malaria Report 2008. Geneva: World Health Organization; 2008; https://www.who.int/malaria/publications/atoz/9789241563697/en/. [Google Scholar]
- 8.WHO. World Malaria Report 2018. Geneva: World Health Organization; 2018; https://www.who.int/malaria/publications/world-malaria-report-2018/en/. [Google Scholar]
- 9.Mita T., Tanabe K., and Kita K., Spread and evolution of Plasmodium falciparum drug resistance. Parasitol Int, 2009. 58(3): p. 201–9. 10.1016/j.parint.2009.04.004 [DOI] [PubMed] [Google Scholar]
- 10.Picot S., et al. , A systematic review and meta-analysis of evidence for correlation between molecular markers of parasite resistance and treatment outcome in falciparum malaria. Malar J, 2009. 8: p. 89 10.1186/1475-2875-8-89 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Menegon M., et al. , Frequency distribution of antimalarial drug resistance alleles among Plasmodium falciparum isolates from Gezira State, central Sudan, and Gedarif State, eastern Sudan. The American journal of tropical medicine and hygiene, 2010. 83(2): p. 250–257. 10.4269/ajtmh.2010.09-0514 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Mohammed W.S.A., et al. , Cross sectional study to determine chloroquine resistance among Plasmodium falciparum clinical isolates from Khartoum, Sudan. F1000Research, 2018. 7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Tagelsir N., et al. , High frequency of Plasmodium falciparum PfCRT K76T and PfpghN86Y in patients clearing infection after chloroquine treatment in the Sudan. Acta tropica, 2006. 97(1): p. 19–25. 10.1016/j.actatropica.2005.07.030 [DOI] [PubMed] [Google Scholar]
- 14.Lu F., et al. , Return of chloroquine sensitivity to Africa? Surveillance of African Plasmodium falciparum chloroquine resistance through malaria imported to China. Parasites & vectors, 2017. 10(1): p. 355. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Sisowath C., et al. , In vivo selection of Plasmodium falciparum parasites carrying the chloroquine-susceptible pfcrt K76 allele after treatment with artemether-lumefantrine in Africa. J Infect Dis, 2009. 199(5): p. 750–7. 10.1086/596738 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Laufer M.K., et al. , Return of chloroquine antimalarial efficacy in Malawi. N Engl J Med, 2006. 355(19): p. 1959–66. 10.1056/NEJMoa062032 [DOI] [PubMed] [Google Scholar]
- 17.Gregson A. and Plowe C.V., Mechanisms of resistance of malaria parasites to antifolates. Pharmacol Rev, 2005. 57(1): p. 117–45. 10.1124/pr.57.1.4 [DOI] [PubMed] [Google Scholar]
- 18.Al-Saai S., et al. , Distinct haplotypes of dhfr and dhps among Plasmodium falciparum isolates in an area of high level of sulfadoxine-pyrimethamine (SP) resistance in eastern Sudan. Infect Genet Evol, 2009. 9(5): p. 778–83. 10.1016/j.meegid.2009.04.010 [DOI] [PubMed] [Google Scholar]
- 19.Osman M.E., et al. , Field-based evidence for linkage of mutations associated with chloroquine (pfcrt/pfmdr1) and sulfadoxine-pyrimethamine (pfdhfr/pfdhps) resistance and for the fitness cost of mutiple mutations in P. falciparum. Infect Genet Evol, 2007. 7(1): p. 52–9. 10.1016/j.meegid.2006.03.008 [DOI] [PubMed] [Google Scholar]
- 20.Adeel A.A., et al. , High efficacy of artemether-lumefantrine and declining efficacy of artesunate + sulfadoxine-pyrimethamine against Plasmodium falciparum in Sudan (2010–2015): evidence from in vivo and molecular marker studies. Malar J, 2016. 15(1): p. 285 10.1186/s12936-016-1339-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Bakhiet A., et al. , Evolution of Plasmodium falciparum drug resistance genes following artemisinin com bination therapy in Sudan. Transactions of The Royal Society of Tropical Medicine and Hygiene, 2019. [DOI] [PubMed] [Google Scholar]
- 22.Venkatesan M., et al. , Polymorphisms in Plasmodium falciparum chloroquine resistance transporter and multidrug resistance 1 genes: parasite risk factors that affect treatment outcomes for P. falciparum malaria after artemether-lumefantrine and artesunate-amodiaquine. Am J Trop Med Hyg, 2014. 91(4): p. 833–843. 10.4269/ajtmh.14-0031 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Nsobya S.L., et al. , In vitro sensitivities of Plasmodium falciparum to different antimalarial drugs in Uganda. Antimicrob Agents Chemother, 2010. 54(3): p. 1200–6. 10.1128/AAC.01412-09 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Reed M.B., et al. , Pgh1 modulates sensitivity and resistance to multiple antimalarials in Plasmodium falciparum. Nature, 2000. 403(6772): p. 906–9. 10.1038/35002615 [DOI] [PubMed] [Google Scholar]
- 25.Foote S.J., et al. , Several alleles of the multidrug-resistance gene are closely linked to chloroquine resistance in Plasmodium falciparum. Nature, 1990. 345(6272): p. 255–8. 10.1038/345255a0 [DOI] [PubMed] [Google Scholar]
- 26.Anderson T.J., et al. , Molecular assessment of drug resistance in Plasmodium falciparum from Bahr El Gazal province, Sudan. Tropical medicine & international health, 2003. 8(12): p. 1068–1073. [DOI] [PubMed] [Google Scholar]
- 27.Ariey F., et al. , A molecular marker of artemisinin-resistant Plasmodium falciparum malaria. Nature, 2014. 505(7481): p. 50–5. 10.1038/nature12876 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Taylor S.M., et al. , Absence of putative artemisinin resistance mutations among Plasmodium falciparum in Sub-Saharan Africa: a molecular epidemiologic study. J Infect Dis, 2015. 211(5): p. 680–8. 10.1093/infdis/jiu467 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Lu F., et al. , Emergence of indigenous artemisinin-resistant Plasmodium falciparum in Africa. New England Journal of Medicine, 2017. 376(10): p. 991–993. 10.1056/NEJMc1612765 [DOI] [PubMed] [Google Scholar]
- 30.Ikeda M., et al. , Artemisinin-resistant Plasmodium falciparum with high survival rates, Uganda, 2014–2016. Emerging infectious diseases, 2018. 24(4): p 718 10.3201/eid2404.170141 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Miotto O., et al. , Genetic architecture of artemisinin-resistant Plasmodium falciparum. Nat Genet, 2015. 47(3): p. 226–34. 10.1038/ng.3189 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Amato R., et al. , Genetic markers associated with dihydroartemisinin-piperaquine failure in Plasmodium falciparum malaria in Cambodia: a genotype-phenotype association study. Lancet Infect Dis, 2017. 17(2): p. 164–173. 10.1016/S1473-3099(16)30409-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.WHO. Basic malaria microscopy:Part I Learner’s guide. 2nd ed Geneva: World Health Organization; 2010; https://www.who.int/malaria/publications/atoz/9241547820/en/. [Google Scholar]
- 34.Shen Z., et al. , MPprimer: a program for reliable multiplex PCR primer design. BMC Bioinformatics, 2010. 11(1): p. 143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Oyola S.O., et al. , Whole genome sequencing of Plasmodium falciparum from dried blood spots using selective whole genome amplification. Malaria journal, 2016. 15(1): p. 597 10.1186/s12936-016-1641-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Lalremruata A., et al. , Species and genotype diversity of Plasmodium in malaria patients from Gabon analysed by next generation sequencing. Malar J, 2017. 16(1): p. 398 10.1186/s12936-017-2044-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Head S.R., et al. , Library construction for next-generation sequencing: overviews and challenges. Biotechniques, 2014. 56(2): p. 61–77. 10.2144/000114133 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Pearson R.D., Amato R., and Kwiatkowski D.P., An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples. bioRxiv, 2019: p. 824730. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Galinsky K., et al. , COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data. Malar J, 2015. 14: p. 4 10.1186/1475-2875-14-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Chang H.H., et al. , THE REAL McCOIL: A method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites. PLoS Comput Biol, 2017. 13(1): p. e1005348 10.1371/journal.pcbi.1005348 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Awasthi G. and Das A., Genetics of chloroquine-resistant malaria: a haplotypic view. Mem Inst Oswaldo Cruz, 2013. 108(8): p. 947–61. 10.1590/0074-0276130274 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Frosch A.E.P., et al. , Return of Widespread Chloroquine-Sensitive Plasmodium falciparum to Malawi. The Journal of Infectious Diseases, 2014. 210(7): p. 1110–1114. 10.1093/infdis/jiu216 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Veiga M.I., et al. , Globally prevalent PfMDR1 mutations modulate Plasmodium falciparum susceptibility to artemisinin-based combination therapies. Nat Commun, 2016. 7: p. 11553 10.1038/ncomms11553 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Malmberg M., et al. , Plasmodium falciparum drug resistance phenotype as assessed by patient antimalarial drug levels and its association with pfmdr1 polymorphisms. J Infect Dis, 2013. 207(5): p. 842–7. 10.1093/infdis/jis747 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Peterson D.S., Walliker D., and Wellems T.E., Evidence that a point mutation in dihydrofolate reductase-thymidylate synthase confers resistance to pyrimethamine in falciparum malaria. Proc Natl Acad Sci U S A, 1988. 85(23): p. 9114–8. 10.1073/pnas.85.23.9114 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Gadalla N.B., et al. , Selection of pfdhfr/pfdhps alleles and declining artesunate/sulphadoxine-pyrimethamine efficacy against Plasmodium falciparum eight years after deployment in eastern Sudan. Malar J, 2013. 12: p. 255 10.1186/1475-2875-12-255 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Naidoo I. and Roper C., Mapping 'partially resistant', 'fully resistant', and 'super resistant' malaria. Trends Parasitol, 2013. 29(10): p. 505–15. 10.1016/j.pt.2013.08.002 [DOI] [PubMed] [Google Scholar]
- 48.Cooper R.A., et al. , Lack of Artemisinin Resistance in Plasmodium falciparum in Uganda Based on Parasitological and Molecular Assays. Antimicrob Agents Chemother, 2015. 59(8): p. 5061–4. 10.1128/AAC.00921-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Kamau E., et al. , K13-propeller polymorphisms in Plasmodium falciparum parasites from sub-Saharan Africa. J Infect Dis, 2015. 211(8): p. 1352–5. 10.1093/infdis/jiu608 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Isozumi R., et al. , Novel mutations in K13 propeller gene of artemisinin-resistant Plasmodium falciparum. Emerg Infect Dis, 2015. 21(3): p. 490–2. 10.3201/eid2103.140898 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Conrad M.D., et al. , Polymorphisms in K13 and falcipain-2 associated with artemisinin resistance are not prevalent in Plasmodium falciparum isolated from Ugandan children. PLoS One, 2014. 9(8): p. e105690 10.1371/journal.pone.0105690 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Ashley E.A., et al. , Spread of artemisinin resistance in Plasmodium falciparum malaria. N Engl J Med, 2014. 371(5): p. 411–23. 10.1056/NEJMoa1314981 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Escobar C., et al. , Polymorphisms in Plasmodium falciparum K13-propeller in Angola and Mozambique after the introduction of the ACTs. PLoS One, 2015. 10(3): p. e0119215 10.1371/journal.pone.0119215 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Menard D., et al. , A Worldwide Map of Plasmodium falciparum K13-Propeller Polymorphisms. N Engl J Med, 2016. 374(25): p. 2453–64. 10.1056/NEJMoa1513137 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Feng J., et al. , Evaluation of antimalarial resistance marker polymorphism in returned migrant workers in China. Antimicrob Agents Chemother, 2015. 59(1): p. 326–30. 10.1128/AAC.04144-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Ouattara A., et al. , Polymorphisms in the K13-propeller gene in artemisinin-susceptible Plasmodium falciparum parasites from Bougoula-Hameau and Bandiagara, Mali. Am J Trop Med Hyg, 2015. 92(6): p. 1202–6 10.4269/ajtmh.14-0605 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Ghorbal M., et al. , Genome editing in the human malaria parasite Plasmodium falciparum using the CRISPR-Cas9 system. Nat Biotechnol, 2014. 32(8): p. 819–21. 10.1038/nbt.2925 [DOI] [PubMed] [Google Scholar]