National genomic profiling of Plasmodium falciparum antimalarial resistance in Zambian children participating in the 2018 Malaria Indicator Survey

doi:10.21203/rs.3.rs-4888948/v1

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National genomic profiling of Plasmodium falciparum antimalarial resistance in Zambian children participating in the 2018 Malaria Indicator Survey

https://doi.org/10.21203/rs.3.rs-4888948/v1

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The emergence of antimalarial drug resistance is a major threat to malaria control and elimination. Using whole genome sequencing of 282 P. falciparum samples collected during the 2018 Zambia National Malaria Indicator Survey, we determined the prevalence and spatial distribution of known and candidate antimalarial drug resistance mutations. High levels of genotypic resistance were found across Zambia to pyrimethamine, with over 94% (n = 266) of samples having the Pfdhfr triple mutant (N51I, C59R, and S108N), and sulfadoxine, with over 84% (n = 238) having the Pfdhps double mutant (A437G and K540E). In northern Zambia, 5.3% (n = 15) of samples also harbored the Pfdhps A581G mutation. Although 29 mutations were identified in Pfkelch13, these mutations were present at low frequency (< 2.5%), and only three were WHO-validated artemisinin partial resistance mutations: P441L (n = 1, 0.35%), V568M (n = 2, 0.7%) and R622T (n = 1, 0.35%). Notably, 91 (32%) of samples carried the E431K mutation in the Pfatpase6 gene, which is associated with artemisinin resistance. No specimens carried any known mutations associated with chloroquine resistance in the Pfcrt gene (codons 72–76). P. falciparum strains circulating in Zambia were highly resistant to sulfadoxine and pyrimethamine but remained susceptible to chloroquine and artemisinin. Despite this encouraging finding, early genetic signs of developing artemisinin resistance highlight the urgent need for continued vigilance and expanded routine genomic surveillance to monitor these changes.

Health sciences/Diseases

Health sciences/Diseases/Infectious diseases

Health sciences/Diseases/Infectious diseases/Malaria

Malaria

Plasmodium falciparum

drug resistance

genomic epidemiology

Zambia

Among all Plasmodium species that infect humans, P. falciparum is of the greatest significance, accounting for over 95% of malaria deaths.^1,2 The World Health Organization (WHO) recommends front line artemisinin combination therapy (ACT), such as artemether-lumefantrine (AL), artesunate-amodiaquine (ASAQ) or dihydroartemisinin-piperaquine (DHAP), in most African countries for treatment of malaria.³ For prevention, sulfadoxine-pyrimethamine (SP) is recommended for intermittent preventive treatment in pregnancy (IPTp) and for infants (IPTi) living in high-transmission areas.^3,4 Antimalarial drugs have played a major role in achieving a significant reduction in the malaria burden globally since 2000 but progress towards malaria elimination has stalled, with resurgence in several endemic countries.^5,6 A major threat to control and elimination is the emergence and spread of antimalarial drug resistance.

P. falciparum parasites have developed resistance to nearly every available antimalarial drug and resistant strains have spread across malaria endemic countries.⁷ For example, P. falciparum resistance to chloroquine (CQ) emerged in 1957 in Thailand, spread to Southeast Asia in the 1970’s, and by 1982 resistance had spread across the entire African continent.⁸ Several alleles are associated with CQ resistance around codon 72–76 in the P. falciparum CQ resistance transporter gene (Pfcrt), including the diagnostic K76T mutation.⁹ Similarly, mutations in the enzymes dihydropteroate synthase (Pfdhps) (S436A, A437G, K540E, A581G, A613S) and dihydrofolate reductase (Pfdhfr) (N51I, C59R, S108N, I164L) are associated with varying degree of resistance to sulfadoxine and pyrimethamine, respectively,^10,11 and are widespread in Africa, Asia, South America, and Oceania.¹² Combinations of these mutations i.e., triple Pfdhfr mutations of N51I, C59R, and S108N, plus double Pfdhps mutations of A437G, K540E (IRNGE - ‘Quintuple mutant’) confer full resistance to SP.^4,13 Moreover, parasites that have the additional Pfdhps A581G mutation (IRNGEG - ‘Sextuple-mutant’) are associated with enhanced SP resistance in vitro that contribute to super SP resistance and IPTp failure.^14,15

Since 2008, P. falciparum parasites resistant to first-line artemisinin (ART) treatments have emerged in Southeast Asia^16,17 and spread in the Greater Mekong Subregion (GMS).¹⁸ Studies identified point mutations in the beta-propeller domain of kelch 13 (Pfkelch13) that were associated with reduced susceptibility to ART and its derivatives, manifested by delayed parasite clearance times.¹⁹ To classify ART resistant (ART-R) parasites, WHO provided a list of 9 “validated” and 12 “associated/candidate” kelch13 ART resistance markers.²⁰ Resistance to partner drugs has also been identified, specifically mutations N86Y, Y184F and D1246Y in the P. falciparum multidrug resistance gene 1 (Pfmdr1), which have been associated with reduced susceptibility to lumefantrine.²¹ With reports of decreased ACT efficacy and treatment failure in Africa,^22–24 and genotypic identification of an increasing prevalence of WHO-validated kelch13 ART-R marker (R561H),^25,26 the threat of antimalarial resistance is increasing such that surveillance should be high priority.^27,28

In Zambia, despite the continued use of SP for IPTp and AL for the treatment of uncomplicated malaria since 2002 (the first African country to adopt AL as a first-line treatment policy nationwide), only a few small-scale studies in Southern, Western, and Luapula Provinces have investigated the prevalence of CQ and ACT resistance markers.^29,30 However, our recent nationwide genomic study,³¹ aimed at understanding malaria transmission across Zambia and establishing a baseline for parasite genetic metrics, identified strong positive selection signatures in genes involved in SP and ACT resistance that warrants further investigation into the regional prevalence and spatial variations of drug resistance markers. Moreover, genetic background mutations that could augment ART-R and other novel mutations that may confer antimalarial resistance have yet to be thoroughly assessed in Zambia.

To address these important knowledge gaps and support the Zambian National Malaria Elimination Program, we conducted a genomic surveillance study nested within the 2018 Zambia Malaria Indicator Survey (MIS), which comprises nationwide representative samples.³¹ We generated 282 P. falciparum whole genome sequences (WGS) from seven provinces and mined these data for known and candidate antimalarial resistance mutations across 5 key P. falciparum drug resistance genes (Pfdhfr, Pfdhps, Pfkelch13, Pfcrt, and Pfmdr1) and other genes that may contribute to ART-R phenotypes: apicoplast ribosomal protein S10 precursor (Pfarps10), multidrug resistance protein 2 (Pfmdr2), ferredoxin (Pffd), adaptor protein 2 complex subunit mu gene (Pfap2mu), ubiquitin carboxyl-terminal hydrolase 1 gene (Pfubp1),^32,33 and reticulum Ca²⁺ ATPase (Pfatp6).³⁴ This study defines the most complete genetic landscape of antimalarial drug resistance markers in Zambia, allows spatial and temporal trends to be identified, and provides the foundation for future studies.

Whole genome sequencing and mining of drug resistance markers

A total of 282 specimens collected during the 2018 Zambia MIS from children younger than five years of age (Fig. 1), and were whole genome sequenced (Figure S1) with high coverage across 13 P. falciparum genes associated with antimalarial drug resistance (Table S1). Within the open-reading frames of these genes, 489 non-synonymous (NS) mutations (Table S2 and Figure S2) were identified with variable spatial frequencies across Zambia (Table S3). The prevalence of key mutations associated with antimalarial drug resistance is shown in Table 1.

Table 1

Prevalence of key mutations associated with mono- and multiple antimalarial drug resistance across Zambia in 2018. n = number of samples that carried the mutant allele out of the total sequenced samples (282)
Associated Resistance	Gene	Mutation	n	Prevalence (%)
Chloroquine	Pfcrt	C72S,V73L,M74I, N75E/D,K76T	0	0
Chloroquine	Pfmdr1	N86Y	0	0
Lumefantrine	Pfmdr1	Y184F	155	55
Pyrimethamine	Pfdhfr	N51I	277	98.2
		C59R	272	96.5
		S108N	281	99.6
		IRN (triple)	267	94.7
Sulfadoxine	Pfdhps	A437G	263	93.3
		G540E	247	87.6
		GE (double)	237	84.0
		A581G	15	5.3
Sulfadoxine-Pyrimethamine	Pfdhfr & Pfdhps	IRNGE (Quintuple)	234	83.0
Artemisinin	Pfkelch13 (WHO-validated or candidate)	P441L	1	0.4
		V568M	2	0.7
		R622T	1	0.4
	Pfkelch13 (Not yet validated)	V637I	1	0.4
		L631F	11	3.9
		A578S	7	2.5
		I416V	2	0.7
		L407F	2	0.7
		Y328F	4	1.4

Chloroquine resistance

The Pfcrt K76T mutation associated with CQ resistance was not identified in the analyzed samples (Table 1, Table S2), indicating reversal of CQ sensitive P. falciparum strains across Zambia.^31,35 Seven NS mutations not associated with CQ resistance were identified at very low frequencies in other codons across the Pfcrt gene (PF3D7_0709000), but 94.0% (265/282) of sequenced samples did not carry any of these mutations (Figure S3, Table S2). All sequenced specimens were wild-type (N) at codon 86 in the multidrug resistance transporter Pfmdr1 gene, which has been shown to enhance resistance to CQ in some genetic backgrounds,³⁶ further supporting reversal to CQ sensitive parasites in Zambia.

Antifolate resistance

Key mutations (N51I, C59R, S108N) in the Pfdhfr gene were identified in 98.2% (277/282), 96.5% (272/282), and 99.6% (281/282) of samples, respectively, with 94.6% (267/282) classified as a Pfdhfr triple (IRN) mutants (Table 1 and Fig. 2A). Moreover, key mutations A437G and K540E, in the Pfdhps gene were identified in 93.3% (263/282) and 87.6% (247/282) of sequenced samples, respectively, with 84.0% (237/282) classified as a Pfdhps double (GE) mutant (Table 1 and Fig. 2C). We found some degree of spatial heterogeneity for both Pfdhfr triple mutants and Pfdhps double mutants at the cluster level across the country (Fig. 2B and Fig. 2D, respectively).

Overall, 83.0% (234/282) of sequenced samples were typed as quintuple mutants (Pfdhfr IRN, Pfdhps GE, Fig. 3A), a genotype associated with near complete SP resistance (Table 1). In the Pfdhps gene, the A581G mutation was found in 5.3% (15/282) of the analyzed samples with high geographic variation across Zambia and with clustering in the adjacent Luapula and Northern Provinces (Fig. 3B). There was no evidence for the presence of Pfdhfr I164L or Pfdhps A613S/T, mutations that can enhance the quintuple mutant SP resistance profile.

Partial artemisinin resistance

A total of 29 mutations were identified across the entire kelch13 gene, of which 8 were located inside the propeller domain (Fig. 4). Of these, three mutations (P441L: n = 1 from Western Province, V568M: n = 2 from Luapula Province and R622T: n = 1 from Western Province) were WHO-validated mutations associated with partial artemisinin resistance. Apart from the K189T mutation that was found in 20.6% (58/282) of sequenced samples and was reported in other clinical studies, all other mutations were found at low frequency (< 2.5%). The A578S mutation, which was identified in seven specimens (2.5%), has been commonly reported in other African countries, although this mutation is not associated with ART resistance in vitro and/or delayed parasite clearance. Overall, 35.1% (99/282) of sequenced samples carried one or more Pfkelch13 mutations with variable prevalence at the provincial level (Table S3), suggesting high polymorphism in the Pfkelch13 gene due to increased ACT pressure in Zambia.

Lumefantrine resistance

P. falciparum parasite harboring N86 (wild-type), 184F (mutant), and D1246 (wild-type) genotypes in the multi-drug resistance gene 1 (Pfmdr1), are associated with decreased sensitivity to lumefantrine. Our analysis revealed that 99.3% (280/282) of the samples carried N86, 55.0% (155/282) of the samples carried 184F, and 98.2% (277/282) carried D1246 (Fig. 5A). Overall, 53.9% (152/282) of samples carried N86/184F/D1246 (NFD) genotype with marked spatial variation across districts (Fig. 5B).

Additional ART resistance-associated mutations

Several mutations in the Pfatp6 gene, a sarcoplasmic and endoplasmic reticulum Ca²⁺ ATPase (SERCA)-type protein previously associated with artemisinin resistance were identified (Table S2). Most mutations occurred at low frequency except for Pfatp6 N569K (54.6%), E431K (32.3%), L402V (9.6%), and H243Y (3.5%). Of the mutations previously shown to mediate resistance, E431K (32.3%) and A623E (0.35%) were identified, while S769N and L263E were not reported (Figure S4). No other mutations were identified in Pfarps10, Pffd, Pfmdr2, Pfpib, Pfpp, Pfap2mu, Pfubp1, and Pfcrt, that could potentially augment artemisinin resistance. Several mutations of variable but generally low frequency (Table S2) and variable spatial distribution (Table S3) were identified in these genes (Figure S5).

Intense control activities, especially the continuous use of effective antimalarial drugs, apply significant selective pressure on the malaria parasite population. As transmission declines, most infected individuals carry single clones promoting a higher rate of inbreeding³⁷ that favors the spread of drug resistance phenotypes when they arise.^38,39 The independent emergence or spread of artemisinin resistance in Zambia due to drug selection pressure could significantly increase the malaria burden leading to malaria resurgence and increased morbidity and mortality.⁴⁰ Close monitoring of the efficacy of available antimalarial drugs and improved surveillance for resistance mutations will be key to inform control strategies such that rapid action can be taken to mitigate the impact and slow or prevent the spread of drug resistant parasites.^22,23

This nationally representative spatial analysis of antimalarial drug resistance mutations supports several conclusions that together strongly suggest that individual genes are under markedly different selection pressures. Firstly, there was a noticeable lack of mutations in Pfcrt codons 72–76 and a low number of polymorphisms (only seven unique NS mutations) across the gene. Zambia withdrew CQ treatment and therefore drug selective pressure on the Pfcrt gene in 2003 allowing reversion to the wild-type. While other studies have previously identified this reversion,^35,41 the selection patterns in Zambia lacked a commonly selected region on chromosome 7 (Pfcrt), contrasting with parasite populations from other regions. Similarly, we did not observe selection signatures in Pfaat1, the second important transporter gene for chloroquine resistance.⁴² This is consistent with other African countries where CQ withdrawal resulted in declines in CQ resistance alleles and reductions in CQ median IC₅₀ values.^43,44 While this finding is encouraging in terms of the potential to reintroduce CQ as part of the chemotherapeutic arsenal in Zambia, preferably as a combination therapy, however additional phenotype-genotype association studies would be needed to confirm the susceptibility of this wild-type strain to CQ.

In contrast to CQ, SP resistance markers were highly prevalent throughout Zambia, suggesting strong selective pressure is maintained through national IPTp implementation and high private sector SP utilization without prescription for self-medication of suspected malaria.⁴⁵ Pyrimethamine associated resistance in Pfdhfr was very high, with 95% of samples having triple mutants (IRN) and codon S108N (99.6%) approaching fixation with negligible spatial variation. A similar picture was observed for sulfadoxine associated Pfdhps mutations, with 84% double mutants (codons A437G and K540E). Overall, 82.9% of samples were Pfdhfr and Pfdhps quintuple mutants Pfdhfr-dhps (IRNGE) correlating with full genotypic SP resistance and expected treatment failure. Furthermore, with a concentration in Luapula and Northern Provinces, 5.3% (15/282) of samples also carried the Pfdhps A581G mutation in addition to the Pfdhfr-dhps IRNGE background. This genotype confers extreme SP resistance and is of concern for SP efficacy in Zambia. While some variation between this study and historical data^29,46 may be explained by study differences (subject selection, sites, implementation period) and data type (PCR genotyping vs. WGS), overall a marked increase in SP genotypic resistance has occurred. Our findings are consistent with our previous evidence of positive selection for SP markers,³¹ as well as with other African countries where Pfdhfr–Pfdhps quintuple mutant prevalence is high, while the sextuple mutant remains rare,^45,47 albeit with high spatial heterogeneity.^4,48 While overall SP resistance is clearly high in Zambia, two mutations (Pfdhfr I164L⁴⁹ and Pfdhps A613S/T^47,50) that confer even higher SP resistance were not identified in Zambia.

The high prevalence of SP resistance (> 90%) are in children younger than five years) indicates a strong selective pressure has been applied to these genes, even though SP is primarily only used for IPTp. The WHO recommends that countries withdraw SP for IPTp use when the prevalence of Pfdhps K540E is > 95% and Pfdhps A581G is > 10%.¹¹ At 87.6% and 5% respectively, Zambia as a country remains below these thresholds, although some districts e.g., Nchelenge and Mansa in Luapula Province, did exceed them. Based on these findings, SP should continue to be used for IPTp. In contrast, the WHO threshold for SP-based IPTi withdrawal is when K540E is > 50% and thus, SP would not be recommended to be used for IPTi in Zambia at this time.

Until novel therapies are developed, maintaining the efficacy of ART based treatments is fundamental to global control and elimination efforts. In Zambia, AL has been used as a first line combination antimalarial treatment for uncomplicated P. falciparum malaria since 2002.⁵¹ Considering the historical use and importance of ART to malaria control in Zambia, increased polymorphisms in the kelch13 gene and the identification three WHO-validated mutations associated with partial artemisinin resistance suggest an early signal of partial artemisinin resistance in Zambia. Close monitoring of local emerging or spreading kelch13 mutations (R561H, A675V and C469Y)^52–54 that were recently reported from East Africa and confer partial artemisinin resistance is warranted. While not unexpected, it was also encouraging to note that no mutations (Pfcrt I356T, Pffd D193Y, Pfmdr2 T484I, Pfap2mu S160N and Pfubp1 E1528D) associated with ART resistance in Southeast Asia⁵⁵ were identified. Nevertheless, considering the variation between Asian and African parasite populations,⁵⁶ it is possible that other Africa-specific mutations may augment ART resistance. Similarly, we must continue to track all mutations in any key genes, irrespective of their genotypic resistance status. For example, 26 Pfkelch13 mutations were identified, including one (A578S) that has been commonly reported in Africa,^2,29 the implications of which remains unclear. Unfortunately, while ART appears to be efficacious, the main partner drug lumefantrine does not fare as well, with all but two specimens containing one or more key mutations in Pfmdr1. In fact, more than 50% of all specimens carried mdr1 (NFD) haplotype. This confirms results provided by other studies performed in the Southern and Western Provinces of Zambia^2,29,57 but, as with SP, the trend is that genotypic resistance is increasing. While this may not correlate with ACT clinical treatment failure with AL, it does potentially remove the partner drug from the combination therapy leaving ART exposed as monotherapy. Such an environment would be primed to enable rapid selection and spread of ART resistance irrespective of resistance evolving independently or through an introduction event into Zambia.

In summary, this study support two worrying and two encouraging conclusions with respect to antimalarial drug resistance. Firstly, Zambia has very high, and for some loci almost fixed, resistance to SP. While still under WHO recommended limits, this warrants further SP efficacy studies in pregnancy to assess the drugs’ ability to reduce deleterious maternal and birth outcomes, especially in Luapula and Northern Provinces where WHO frequency thresholds were crossed. Secondly, there are also very high levels of genotypic resistance to lumefantrine, the main ART partner ACT drug used in Zambia. While therapeutic efficacy studies have not identified significant treatment failure several years after these samples were collected, it may be prudent to switch to an alternative ACT in the near future, or at least prepare for a switch should treatment failures occur. Finally, there is some encouraging data, namely that CQ sensitivity has been restored and there is no evidence of ART resistance in Zambia. Together these findings along with the recent evidence of strong positive selection signatures genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance³¹ highlight the need of sustained surveillance of antimalarial drug resistance across the country. Furthermore, this work underlines the utility of high-quality genomic surveillance, which if performed and acted upon, gives every chance of effective malaria treatment continuing for the foreseeable future despite the constant threat of drug resistance. Without surveillance, resistance will only be detected following treatment failure, at which point options to respond will be limited.

Sample selection and whole-genome sequencing

This work is a secondary analysis of a larger parent study focused on understanding malaria transmission across Zambia and establishing a baseline for parasite genetic metrics.³¹ Briefly, whole-genome sequencing was performed on 459 P. falciparum PET-PCR positive dried blood spots (DBS) collected from children in all ten provinces of Zambia as part of the 2018 Zambia National Malaria Indicator Survey (MIS).⁵⁸ The samples were processed for genomic DNA extraction as previously described.^{31, 59} We adopted a 4-plex hybrid capture method using SeqCap EZ custom probes⁶⁰ to selectively enrich P. falciparum genomes prior to sequencing as previously described.³¹ Genomic libraries and hybridization capture were prepared using a modified Roche/Nimblegen SeqCap EZ Library Short Read protocol and sequenced on Illumina NextSeq 6000 (2 × 101-bp) at Yale Center for Genomic Analysis with a target of 30 million reads per sample. Raw sequence reads are available at the Sequence Read Archive (PRJNA932927).

Variant identification

We identified P. falciparum genomic variation from whole genome sequence data with the pipeline previously described.^31,61 Briefly, Illumina raw paired-end reads were aligned to the P. falciparum 3D7 reference genome with BWA-MEM 0.7.17⁶² and removed using Picard Tools 2.20.8. For this study, variant calling was performed only on samples with > 30% P. falciparum 3D7 reference genome with > 5X coverage, resulting in a total of 282 P. falciparum samples. Variants were called using GATK v4.1.4.121 following best practices (https://software.broadinstitute.org/gatk/best-practices). We used GATK HaplotypeCaller in GVCF mode to call single-sample variants (ploidy 2 and standard-min-confidence-threshold for calling = 30), followed by GenotypeGVCFs to genotype the parasites. Prior to variant filtering, we scored 1,219,517 SNPs with a VQSLOD > 0 across the 282 genomes. The VCF was functionally annotated with SnpEff v4.3 (build 2017-11-24 10:18). Variants removed included those located in telomeric and hypervariable regions (ftp://ngs.sanger.ac.uk/production/malaria/pf-crosses/1.0/regions-20130225.onebased.txt), SNPs with > 20% missingness, and minor allele frequency (MAF) > 0.02, leaving a total of 27,163 high quality biallelic SNPs.

Mining drug resistance loci and estimating mutation prevalence

SNPs located in 13 genes associated with antimalarial drug resistance (Table S1) were identified using the VariantAnnotation R package. All non-synonymous mutations with high read coverage (≥ 30x) were identified and classified as mutant (heterozygous or homozygous mutant) or wild-type (homozygous reference). The reference allele for Pfdhps 437 encodes the mutant allele and was therefore re-coded to A437G for clarity as the reference carries a mutant allele unlike all other alleles. The prevalence of each mutation was calculated as (p = m/n*100, where p = prevalence, m = number of infections with mutant alleles, n = number of successfully genotyped infections) using R software version 4.2.0. Mutant combinations were plotted and visualized using the UpSet package in R⁶³ and maps were created using the sf package in R.⁶⁴

Ethical statement

All study participants, and/or their parents or legal guardians, provided written informed consent, and this study was conducted with the approval of the Biomedical Research Ethics Committee from the University of Zambia (Ref 011-02-18) and from the Zambian National Health Research Authority.

The study adhered to the ethical principles outlined in the Declaration of Helsinki. All participants provided written informed consent, and for individuals falling below the age of 18 years but exceeding three months, informed assent and consent from a parent or guardian were obtained. Participants had the right to voluntarily withdraw from the study and have their samples removed at any time. Sequence analysis using parasite genomes from de-identified samples and data were deemed nonhuman subjects of research at Purdue University (IN, USA).

Data availability

The sequence data for the parent project are available in the NCBI Sequence Read Archive, in BioProject PRJNA932927.

Acknowledgments

The authors are grateful to the Zambian communities, particularly the volunteers and their families, for providing samples during the MIS. We would like to thank the staff of the Zambia National Malaria Elimination Centre for their generous support, especially the field researchers who conducted the nationwide survey.

Funding information

This work was supported by funds to G.C. from the Purdue Department of Biological Sciences. Partial funding was provided by the Bill & Melinda Gates Foundation through a grant to PATH (OPP1134518 / INV-009984 to D.J.B.) The Southern and Central Africa International Center of Excellence for Malaria Research was supported by funding from the National Institute of Allergy and Infectious Diseases (U19AI089680 to W.J.M.).

Authors’ contributions

G.C., W.J.M and D.J.B. contributed to funding acquisition, project resources and supervision. G.C., A.A.F., W.J.M., and D.J.B., conceived and designed the study. A.A.F., D.J.B. and G.C., coordinated sample selection and curation. M.C.M., B.M., C.M., R.K., M.B.H., B.H., J.M.M. and D.J.B. collected samples and epidemiological data. A.A.F., I.C., and J.D. performed laboratory analysis. A.A.F., D.J.B, G.C. contributed to formal genomic analysis, visualization, interpretation and writing the original draft. All authors contributed to review and editing the manuscript.

Blasco, B., Leroy, D. & Fidock, D. A. Antimalarial drug resistance: linking Plasmodium falciparum parasite biology to the clinic. Nat. Med. 23, 917–928 (2017).
Menard, D., Dondorp, A. & Antimalarial Drug Resistance A Threat to Malaria Elimination. Cold Spring Harbor Perspectives in Medicine vol. 7 a025619 Preprint at (2017). https://doi.org/10.1101/cshperspect.a025619
Conrad, M. D. & Rosenthal, P. J. Antimalarial drug resistance in Africa: the calm before the storm? Lancet Infect. Dis. 19, e338–e351 (2019).
Amimo, F. et al. Plasmodium falciparum resistance to sulfadoxine-pyrimethamine in Africa: a systematic analysis of national trends. BMJ Glob Health 5, (2020).
Dhiman, S. Correction to: Are malaria elimination efforts on right track? An analysis of gains achieved and challenges ahead. Infect. Dis. Poverty. 8, 19 (2019).
Makenga, G. et al. Prevalence of malaria parasitaemia in school-aged children and pregnant women in endemic settings of sub-Saharan Africa: A systematic review and meta-analysis. Parasite Epidemiol. Control. 11, e00188 (2020).
Thu, A. M., Phyo, A. P., Landier, J., Parker, D. M. & Nosten, F. H. Combating multidrug-resistant Plasmodium falciparum malaria. FEBS J. 284, 2569–2578 (2017).
Wellems, T. E. & Plowe, C. V. Chloroquine-resistant malaria. J. Infect. Dis. 184, 770–776 (2001).
Djimdé, A. et al. A Molecular Marker for Chloroquine-Resistant Falciparum Malaria. New England Journal of Medicine vol. 344 257–263 Preprint at (2001). https://doi.org/10.1056/nejm200101253440403
Kublin, J. G. et al. Molecular markers for failure of sulfadoxine-pyrimethamine and chlorproguanil-dapsone treatment of Plasmodium falciparum malaria. J. Infect. Dis. 185, 380–388 (2002).
Okell, L. C., Griffin, J. T. & Roper, C. Mapping sulphadoxine-pyrimethamine-resistant Plasmodium falciparum malaria in infected humans and in parasite populations in Africa. Sci. Rep. 7, 7389 (2017).
Abdul-Ghani, R., Farag, H. F. & Allam, A. F. Sulfadoxine-pyrimethamine resistance in Plasmodium falciparum: a zoomed image at the molecular level within a geographic context. Acta Trop. 125, 163–190 (2013).
Desai, M. et al. Impact of Sulfadoxine-Pyrimethamine Resistance on Effectiveness of Intermittent Preventive Therapy for Malaria in Pregnancy at Clearing Infections and Preventing Low Birth Weight. Clinical Infectious Diseases vol. 62 323–333 Preprint at (2016). https://doi.org/10.1093/cid/civ881
van Eijk, A. M. et al. Effect of Plasmodium falciparum sulfadoxine-pyrimethamine resistance on the effectiveness of intermittent preventive therapy for malaria in pregnancy in Africa: a systematic review and meta-analysis. The Lancet Infectious Diseases vol. 19 546–556 Preprint at (2019). https://doi.org/10.1016/s1473-3099(18)30732-1
Gutman, J. et al. The A581G mutation in the gene encoding Plasmodium falciparum dihydropteroate synthetase reduces the effectiveness of sulfadoxine-pyrimethamine preventive therapy in Malawian pregnant women. J. Infect. Dis. 211, 1997–2005 (2015).
Phyo, A. P. et al. Emergence of artemisinin-resistant malaria on the western border of Thailand: a longitudinal study. Lancet. 379, 1960–1966 (2012).
Imwong, M. et al. The spread of artemisinin-resistant Plasmodium falciparum in the Greater Mekong subregion: a molecular epidemiology observational study. Lancet Infect. Dis. 17, 491–497 (2017).
Roberts, L. Malaria wars. Science. 352, 398–402 (2016).
Miotto, O. et al. Multiple populations of artemisinin-resistant Plasmodium falciparum in Cambodia. Nat. Genet. 45, 648–655 (2013).
World Health Organization. Report on Antimalarial Drug Efficacy, Resistance and Response: 10 Years of Surveillance (2010–2019) (World Health Organization, 2020).
Grais, R. F. et al. Molecular markers of resistance to amodiaquine plus sulfadoxine–pyrimethamine in an area with seasonal malaria chemoprevention in south central Niger. Malar. J. 17, 1–9 (2018).
Ekland, E. H. & Fidock, D. A. Advances in understanding the genetic basis of antimalarial drug resistance. Curr. Opin. Microbiol. 10, 363–370 (2007).
Guyant, P. et al. Past and new challenges for malaria control and elimination: the role of operational research for innovation in designing interventions. Malar. J. 14, 279 (2015).
Arya, A., Kojom Foko, L. P., Chaudhry, S., Sharma, A. & Singh, V. Artemisinin-based combination therapy (ACT) and drug resistance molecular markers: A systematic review of clinical studies from two malaria endemic regions – India and sub-Saharan Africa. International Journal for Parasitology: Drugs and Drug Resistance vol. 15 43–56 Preprint at (2021). https://doi.org/10.1016/j.ijpddr.2020.11.006
Uwimana, A. et al. Emergence and clonal expansion of in vitro artemisinin-resistant Plasmodium falciparum kelch13 R561H mutant parasites in Rwanda. Nat. Med. 26, 1602–1608 (2020).
Uwimana, A. et al. Author Correction: Emergence and clonal expansion of in vitro artemisinin-resistant Plasmodium falciparum kelch13 R561H mutant parasites in Rwanda. Nat. Med. 27, 1113–1115 (2021).
Takala-Harrison, S. & Laufer, M. K. Antimalarial drug resistance in Africa: key lessons for the future. Ann. N Y Acad. Sci. 1342, 62–67 (2015).
Ndiaye, Y. D. et al. Genetic surveillance for monitoring the impact of drug use on Plasmodium falciparum populations. Int. J. Parasitol. Drugs Drug Resist. 17, 12–22 (2021).
Sitali, L. et al. Surveillance of molecular markers for antimalarial resistance in Zambia: Polymorphism of Pfkelch 13, Pfmdr1 and Pfdhfr/Pfdhps genes. Acta Trop. 212, 105704 (2020).
Ippolito, M. M. et al. Therapeutic Efficacy of Artemether-Lumefantrine for Uncomplicated Falciparum Malaria in Northern Zambia. Am. J. Trop. Med. Hyg. 103, 2224–2232 (2020).
Fola, A. A. et al. Genomics reveals heterogeneous Plasmodium falciparum transmission and selection signals in Zambia. Commun. Med. 4, 67 (2024).
Henriques, G. et al. Directional selection at the pfmdr1, pfcrt, pfubp1, and pfap2mu loci of Plasmodium falciparum in Kenyan children treated with ACT. J. Infect. Dis. 210, 2001–2008 (2014).
Adams, T. et al. Prevalence of Plasmodium falciparum delayed clearance associated polymorphisms in adaptor protein complex 2 mu subunit (pfap2mu) and ubiquitin specific protease 1 (pfubp1) genes in Ghanaian isolates. Parasites & Vectors vol. 11 Preprint at (2018). https://doi.org/10.1186/s13071-018-2762-3
Afonso, A. et al. Malaria parasites can develop stable resistance to artemisinin but lack mutations in candidate genes atp6 (encoding the sarcoplasmic and endoplasmic reticulum Ca2 + ATPase), tctp, mdr1, and cg10. Antimicrob. Agents Chemother. 50, 480–489 (2006).
Mwanza, S. et al. The return of chloroquine-susceptible Plasmodium falciparum malaria in Zambia. Malar. J. 15, 584 (2016).
Shafik, S. H., Richards, S. N., Corry, B. & Martin, R. E. Mechanistic basis for multidrug resistance and collateral drug sensitivity conferred to the malaria parasite by polymorphisms in PfMDR1 and PfCRT. PLoS Biol. 20, e3001616 (2022).
Wirth, D. F. & Alonso, P. L. Malaria: Biology in the Era of Eradication (Cold Spring Harbor Laboratory Press, 2017).
Carrasquilla, M. et al. Resolving drug selection and migration in an inbred South American Plasmodium falciparum population with identity-by-descent analysis. PLoS Pathog. 18, e1010993 (2022).
Auburn, S. & Barry, A. E. Dissecting malaria biology and epidemiology using population genetics and genomics. Int. J. Parasitol. 47, 77–85 (2017).
Bødker, R., Kisinza, W., Malima, R., Msangeni, H. & Lindsay, S. Resurgence of Malaria in the Usambara Mountains, Tanzania, An Epidemic of Drug-Resistant Parasites. Global Change Hum. Health. 1, 134–153 (2000).
Verity, R. et al. The impact of antimalarial resistance on the genetic structure of Plasmodium falciparum in the DRC. Nat. Commun. 11, 2107 (2020).
Amambua-Ngwa, A. et al. Chloroquine resistance evolution in Plasmodium falciparum is mediated by the putative amino acid transporter AAT1. Nat. Microbiol. 8, 1213–1226 (2023).
Wamae, K. et al. No evidence of P. falciparum K13 artemisinin conferring mutations over a 24-year analysis in Coastal Kenya, but a near complete reversion to chloroquine wild type parasites. Antimicrob. Agents Chemother. 63, (2019).
Lu, F. et al. Return of chloroquine sensitivity to Africa? Surveillance of African Plasmodium falciparum chloroquine resistance through malaria imported to China. Parasit. Vectors. 10, 355 (2017).
Alifrangis, M. et al. Independent Origin of Plasmodium falciparumAntifolate Super-Resistance, Uganda, Tanzania, and Ethiopia. Emerging Infectious Diseases vol. 20 1280–1286 Preprint at (2014). https://doi.org/10.3201/eid2008.131897
Siame, M. N. P., Mharakurwa, S., Chipeta, J., Thuma, P. & Michelo, C. High prevalence of dhfr and dhps molecular markers in Plasmodium falciparum in pregnant women of Nchelenge district, Northern Zambia. Malar. J. 14, 190 (2015).
Naidoo, I. & Roper, C. Mapping ‘partially resistant’, ‘fully resistant’, and ‘super resistant’ malaria. Trends Parasitol. 29, 505–515 (2013).
Chaturvedi, R. et al. Geographical spread and structural basis of sulfadoxine-pyrimethamine drug-resistant malaria parasites. Int. J. Parasitol. 51, 505–525 (2021).
Jiang, T. et al. Molecular surveillance of anti-malarial resistance Pfdhfr and Pfdhps polymorphisms in African and Southeast Asia Plasmodium falciparum imported parasites to Wuhan, China. Malaria Journal vol. 19 Preprint at (2020). https://doi.org/10.1186/s12936-020-03509-w
Nkoli Mandoko, P. et al. Prevalence of Plasmodium falciparum parasites resistant to sulfadoxine/pyrimethamine in the Democratic Republic of the Congo: emergence of highly resistant pfdhfr/pfdhps alleles. J. Antimicrob. Chemother. 73, 2704–2715 (2018).
Sipilanyambe, N. et al. From chloroquine to artemether-lumefantrine: the process of drug policy change in Zambia. Malar. J. 7, 25 (2008).
Uwimana, A. et al. Association of Plasmodium falciparum kelch13 R561H genotypes with delayed parasite clearance in Rwanda: an open-label, single-arm, multicentre, therapeutic efficacy study. Lancet Infect. Dis. 21, 1120–1128 (2021).
Juliano, J. J. et al. Country wide surveillance reveals prevalent artemisinin partial resistance mutations with evidence for multiple origins and expansion of high level sulfadoxine-pyrimethamine resistance mutations in northwest Tanzania. medRxiv doi: (2023). 10.1101/2023.11.07.23298207
Young, N. W. et al. High frequency of artemisinin partial resistance mutations in the great lake region revealed through rapid pooled deep sequencing. medRxiv doi: (2024). 10.1101/2024.04.29.24306442
Miotto, O. et al. Genetic architecture of artemisinin-resistant Plasmodium falciparum. Nat. Genet. 47, 226–234 (2015).
Amambua-Ngwa, A. et al. Major subpopulations of Plasmodium falciparum in sub-Saharan Africa. Science. 365, 813–816 (2019).
Fola, A. A. et al. Temporal genomic analysis of Plasmodium falciparum reveals increased prevalence of mutations associated with delayed clearance following treatment with artemisinin-lumefantrine in Choma District, Southern Province, Zambia. medRxiv doi: (2024). 10.1101/2024.06.05.24308497
Zambia National Malaria Indicator Survey (MIS). (2018). https://www.path.org/resources/zambia-natl-malaria-indicator-survey-mis-2018/
Fola, A., Dorman, A., Levy, J., Ciubotariu, M. & Carpi, G. I. Optimized HT gDNA extraction from dried blood spot using QIAcube HT for malaria genomic epidemiology studies v1. doi: (2020). 10.17504/protocols.io.bh69j9h6
Carpi, G. et al. Whole genome capture of vector-borne pathogens from mixed DNA samples: a case study of Borrelia burgdorferi. BMC Genom. 16, 434 (2015).
Carpi, G., Gorenstein, L., Harkins, T. T., Samadi, M. & Vats, P. A GPU-accelerated compute framework for pathogen genomic variant identification to aid genomic epidemiology of infectious disease: a malaria case study. Brief. Bioinform 23, (2022).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv [q-bio.GN] (2013).
Conway, J. R., Lex, A. & Gehlenborg, N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics. 33, 2938–2940 (2017).
Pebesma, E. Simple features for R: Standardized support for spatial vector data. R J. 10, 439 (2018).

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National genomic profiling of Plasmodium falciparum antimalarial resistance in Zambian children participating in the 2018 Malaria Indicator Survey

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Abstract

Figures

Introduction

Results

Whole genome sequencing and mining of drug resistance markers

Chloroquine resistance

Antifolate resistance

Partial artemisinin resistance

Lumefantrine resistance

Additional ART resistance-associated mutations

Discussion

Methods

Sample selection and whole-genome sequencing

Variant identification

Mining drug resistance loci and estimating mutation prevalence

Declarations

Ethical statement

Data availability

Acknowledgments

Funding information

Authors’ contributions

References

Additional Declarations

Supplementary Files

Status:

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