Prevalence of potential mediators of artemisinin resistance in African isolates of Plasmodium falciparum

Abstract

The devastating public health impact of malaria has prompted the need for effective interventions. Malaria control gained traction after the introduction of artemisinin-based combination therapies (ACTs). However, the emergence of artemisinin (ART) resistance in South-East Asia and reports of delayed parasite sensitivity to ACTs in African parasites signal an imminent treatment failure. Monitoring the prevalence of mutations associated with artemisinin resistance in African populations is required to stop resistance in its tracks. Plasmodium falciparum Kelch-13 (Pfk13), Pfcoronin and PfATPase6 gene mutations have been associated with ART resistance. In this review, we collated findings from published research articles to establish the prevalence of Pfk13, Pfcoronin and PfATPase6 polymorphisms in Africa. We searched PubMed, Embase and Google Scholar for relevant articles reporting polymorphisms in these genes across Africa between 2014 to 2021. Seventy-two studies which passed the inclusion criteria reported 739 single nucleotide polymorphisms (331 unique variants) from 34,353 samples collected in 26 African countries. Four validated Pfk13 resistant markers linked with delayed parasite clearance were identified in Africa: R561H in Rwanda and Tanzania, M476I in Tanzania, and F446I in Mali, and P553L in Angola. In Tanzania, three (L263E, E431K, and S769N) of the four mutations (L263E, E431K, A623E, and S769N) in PfATPase6 gene previously associated with delayed parasite clearance in presence of artemisinin were reported. Pfcoronin polymorphisms were reported in Senegal, Gabon, Ghana, Kenya and Congo, with P76S being the most prevalent Pfcoronin mutation. Our findings demonstrate independent emergence and widespread distribution of Pfk13, Pfcoronin and PfATPase6 mutations in Africa. Understanding the phenotypic consequences of these mutations can provide information on the efficacy status of artemisinin-based treatment of malaria in Africa.

Introduction

Malaria is a leading cause of mortality and morbidity especially among children under five years in Africa (WHO, 2020). Interventions such as insecticide-treated nets, space spraying, indoor residual spraying, larval control and antimalarial therapeutics have been adopted to reduce malaria burden across the continent (Bhatt et al., 2015). However, these strategies have been hampered by the emergence of resistant strains of both mosquitoes and parasites (Akinola et al., 2019; Baraka et al., 2018; Okell et al., 2008).

A major setback in malaria control is the emergence and spread of artemisinin-resistant strains of Plasmodium falciparum in South-East Asia (SEA) where decreased parasite susceptibility to artemisinin is associated with polymorphisms in the parasite Kelch-13 propeller gene (Amaratunga et al., 2012; Ariey et al., 2014; Dondorp et al., 2009; Noedl et al., 2008; Takala-Harrison et al., 2015). The Kelch-13 (Pfk13) gene mutations that have been associated with delayed artemisinin parasite clearance in SEA include C580Y, R561H, F446I, N458Y, I543T M476I, R539T, Y493H, and P553L (Ariey et al., 2014). In addition, polymorphisms in P. falciparum coronin (Pfcoronin) gene have been linked artemisinin resistance (Sharma et al., 2020). The Pfcoronin protein belongs to the actin-binding protein family which has been associated with the motility of sporozoites (Olshina et al., 2015). Pfcoronin gene polymorphism (P76S) has been identified in three different countries in Africa (Delandre et al., 2020; Velavan et al., 2019). This polymorphism has been suspected to have a correlation with delayed parasite clearance (Velavan et al., 2019).

Earlier reports also suspected the contribution of PfATPase6 mutations to reduced sensitivity of African parasites (Li et al., 2016; Yobi et al., 2020). The dependency on artemisinin derivatives for falciparum malaria treatment has stressed the need for a synergistic effort to monitor the emergence and spread of artemisinin resistant strains of P. falciparum in Africa. Here, we dissected published research documents to determine the prevalence of Pfk13, Pfcoronin and PfATPase6 mutations across Africa.

Methodology

This article followed the guidelines for systematic reviews and meta-analyses (Moher et al., 2009). Two electronic biomedical databases (PubMed and Embase) were methodically explored for peer-reviewed articles published between 2014 and 2021 which had the relevant study population, study design and expected outcomes for this review. Google Scholar was also combed for relevant peer-reviewed articles. Both interventional and observational studies were retrieved and included in the review using the “MeSH” search terms “OR” and “AND’’: “kelch13” OR “kelch-13” OR “Pfk13” OR “Pfkelch13” OR “Pfkelch-13” OR “Plasmodium falciparum drug resistance” OR “ATP6” OR ““Plasmodium falciparum ATP6” OR “Plasmodium falciparum ATPase6” OR “PfATP6” “PfATPase6” OR “Plasmodium falciparum coronin” OR “Pfcoronin” OR “Plasmodium falciparum coronin” OR “molecular marker” OR “Plasmodium falciparum” “P. falciparum” OR “falciparum malaria” AND (“African” OR “Africa” OR  with each name of the 54 countries in Africa). The citations of the individual search were saved and sent to the reference manager (EndNote version 9.0). The full text of retrieved citations was downloaded using EndNote. Articles with data from unknown countries and/or sampling sites as well as systematic reviews, conference presentations, letters or correspondence to editors and abstracts with insufficient information were removed.

Inclusion criteria

The articles included in this review strictly reported P. falciparum artemisinin resistance markers, single nucleotide polymorphisms (SNPs) in African countries, polymorphisms in Pfk13-gene, Pfcoronin and PfATPase6 confirmed through targeted or whole-genome sequencing. Articles from cross-sectional studies such as clinical or community surveys were included in addition to longitudinal studies of treatment efficacy. Specific studies reporting synonymous and nonsynonymous SNPs in Pfk13, PfATpase6 and Pfcoronin were eligible for this meta-analysis.

Exclusion criteria

Articles reporting molecular markers other than Pfk13, PfATpase6, and Pfcoronin were excluded from this review. In addition, studies with no definite Pfk13, PfATpase6, and Pfcoronin SNPs reported either in the main manuscript or supplementary files were excluded. Studies reporting Pfk13, PfATpase6, and Pfcoronin polymorphisms without sequencing techniques were not included.

Definitions 

P. falciparum artemisinin resistance is defined as delayed, slow or decreased parasite clearance rate (WHO, 2019). This delayed parasite clearance results in partial resistance that affects ring-stage parasites (WHO, 2019). P. falciparum artemisinin resistance mutations are described polymorphisms in the major genes (Pfk13, Pfcoronin, and PfATPase6) associated with ACT resistance in vitro, ex vivo or in vivo. This review utilized the World Health Organisation (WHO) updated list of P. falciparum artemisinin resistance SNPs (WHO, 2019) classifying Pfk13 mutations into validated and candidate SNPs. Pfk13 validated SNPs are significantly associated with reduced drug susceptibility in laboratory assays and a slow parasite clearance rate in field studies. Validated Pfk13 SNPs include C580Y, R561H, F446I, N458Y, I543T M476I, R539T, P553L and Y493H (WHO, 2019). On the other hand, candidate SNPs are mutations strongly associated with slow parasite clearance in clinical trials but not confirmed in vitro. These include A675V, P441L, P574L, G449A, C469F, N537I, P527H, G538V, V1568G, F673I, and A481V (WHO, 2019).

Data extraction

The extracted data from each article captured first and last author affiliations, the year the studies were conducted (Figure 1), year of article publication (Figure 2), geographic location of the study area, duration of the study, age of the participants and the type of study design (that is, interventional vs observational). Data involving sampling strategies, molecular assays performed, clinical status of the study population, markers (synonymous and non-synonymous mutations) and publication affiliation were also reported (Figures 3 and 4). 

Results

This review searched PubMed, Embase, and Google Scholar databases for all the relevant articles. Our search yielded a total of 421 articles of which 284 articles on P. falciparum k13, Pfcoronin and PfATPase6 genes single nucleotide polymorphisms (SNPs) met inclusion conditions. Following an adjustment for duplication, redundant articles were discarded. Eleven articles with unobtainable full texts were removed. After prior screening and filtering, a total number of 72 articles (66 on Pfk13, two on Pfcoronin and six on PfATPase 6) from 34,353 samples collected in 26 African countries were included in this review (supplementary data sheet). 

Structure of Kelch-13 protein

P. falciparum Kelch-13 encodes 726 amino acids. The polypeptide consists of a poorly conserved N-terminal region (Apicomplexa-specific; amino acid from 1 to 211) and three highly conserved regions (Ariey et al., 2014). It has a coiled-coil-containing (CCC; amino acid from 212–341), broad-complex, tram track, and bric-a-brac (BTB; amino acid from 350–437) and a C-terminal kelch-repeat propeller (KREP; amino acid from 443–726) which harbours virtually all Pfk13 allelic variants associated with artemisinin resistance (Anderson et al., 2017) (Figure 5). Kelch-13 gene is putatively associated with intraerythrocytic growth and proliferation of both P. falciparum asexual parasites (Bushell et al., 2017; Zhang et al., 2017).

Sample pre-processing and Pfk13 genotyping

Majority of the studies collected blood samples for genotyping on filter paper (Abubakar et al., 2020; Ahouidi et al., 2021; Balikagala et al., 2017; Conrad et al., 2019; Djaman et al., 2017) while others did not report the method used for collection (Uwimana et al., 2020; Velavan et al., 2019) P. falciparum polymerase chain reaction positive (PCR+) samples were 18,292 out of 32,406 total samples collected (Mayengue et al., 2018; Nzoumbou-Boko et al., 2020; Oboh et al., 2018; Ocan et al., 2016; Pacheco et al., 2020; Tornyigah et al., 2020; Uwimana et al., 2020). Five studies did not report the number of PCR+ samples (Castaneda-Mogollon et al., 2019; Chebore et al., 2018; de Laurent et al., 2018; Hemming-Schroeder et al., 2018; Ikeda et al., 2018). Pfk13 gene was successfully genotyped in 15,861 (86.71%) samples. The variant calling algorithms and data analysis software used include Mega software, Jalview, phylo, DnaSp, Genescan, Genome Assembly Program, PROVEAN and R software (Gaye et al., 2020; Guerra et al., 2017; Gupta et al., 2020; Hussien et al., 2020)

Polymorphisms in Pfk13 gene

Three hundred and thirty-one (331) non-synonymous mutations were reported, of which 291 (87.92%) occurred inside the propeller domain of Pfk13 gene (amino acid from 441). Only 12.08% (Ahouidi et al., 2021; Balikagala et al., 2017; Castaneda-Mogollon et al., 2019; Pacheco et al., 2020) mutations were observed outside the propeller domain (amino acid below 440). The reported Pfk13 non-synonymous SNPs  occurring inside the propeller domain include A578S/D/V (88 isolates); R561H (20 isolates); R622G/K/I (20); N587K/I (16 isolates); V555A/L (9 isolates); S522C/M/N (9 isolates); T677A/K/R (9 isolates); Q613E/H (7 isolates), F509G (7 isolates) and V637I (6 isolates); N554H/K/D and A626S/T/V (5 isolates each); and N609D/L/S (5) (Ahouidi et al., 2021; Ishengoma et al., 2019; Kakolwa et al., 2018; Kayiba et al., 2021; Yobi et al., 2021). The most frequently reported mutations outside the propeller domain include K189T/N (105 isolates), E208K (10 isolates), N142NN (9 isolates), T149S (6 isolates), E433D (6 isolates), and E401Q (5 isolates)  (Guerra et al., 2017; Lu et al., 2017; Madamet et al., 2017; Ocan et al., 2016). Apart from D389H/N/Y (3 isolates), K378R (2 isolates) and D281V (2 isolates), other reported mutations outside the propeller domain (31/40) occurred singly (Bayih et al., 2016; Boussaroque et al., 2016b; Hussien et al., 2020; Igbasi et al., 2019). We also found that K189T/N mutation had a high prevalence in Senegal  (Boussaroque et al., 2016a; Gaye et al., 2020; Torrentino-Madamet et al., 2015). 

Prevalence of Pfk13 non‑synonymous mutations across Africa

The articles reviewed in this study reported 331 unique non-synonymous mutations in Pfk13 gene across Africa (Figure 6). An insertion was recorded in nine samples (N142NN). Of the nine validated Pfk13 mutations (C580Y, R561H, F446I, N458Y, I543T M476I, R539T, P553L, and Y493H) causing a delay in artemisinin parasite clearance (Menard et al., 2016), three (R561H, P553L, and M476I) were identified in Africa (Kakolwa et al., 2018; Talundzic et al., 2017; Uwimana et al., 2020).  R561H was identified in Rwanda and Tanzania (Uwimana et al., 2020), P553L in Angola (Xu et al., 2018), and M476I in Tanzania (Kakolwa et al., 2018). In two isolates from Ghana (Tornyigah et al., 2020), asparagine in position 458 (N458) was found to be replaced by aspartate (D) instead of tyrosine (Y). Though their link with delayed parasite clearance is yet to be established, other non-synonymous mutations reported are A481C in Ghana, A675V in Kenya (3 isolates), Rwanda (2 isolates) and Uganda (2 isolates); C469W/Y/F in Ghana, Kenya, Rwanda and Uganda; G538S in Democratic Republic of the Congo; G449S/C in Mali and Tanzania; N672I in Ghana (2 isolates); P574L in Uganda and Rwanda (1 and 3 isolates respectively); R539I/K in Kenya and Senegal as well as V568G in Kenya (3 isolates). The most frequent Pfk13 mutations reported are K189T/N (105, 14.21%, A578S/D (88, 11.91%), R561H (20, 2.71%) which is a validated Pfk13 linked with artemisinin resistance, and N587K/I (16, 2.17%). Furthermore, non‑synonymous SNPs outside Pfk13 propeller region (< 440) have been described. K189T variant is most frequently reported non-propeller Pfk13 mutation (Gaye et al., 2020; Torrentino-Madamet et al., 2014). It was reported in 105 isolates from three countries (Equatorial Guinea, Eritrea, and Senegal). E208K was also reported in 10 isolates from Eritrea occurred at codon position. Non-propeller mutation at codon position 189 (K to T) has been associated with delayed ACTs P. falciparum parasite clearance (Gaye et al., 2020; Torrentino-Madamet et al., 2014). 

Structure of Pfcoronin and PfATPase6 proteins

Pfcoronin encodes 602 amino acids. The propeller domain of Plasmodium falciparum coronin gene has seven blades. This domain is made up of the WD40 repeats (tryptophan-aspartic acid 40) and a β-propeller in the N terminus region (Ashley et al., 2014). The Pfcoronin gene is structurally similar to the six-bladed PfKelch13 propeller domain. (Ashley et al., 2014). PfCoronin is involved in organization of F-actin via its N-terminal propeller region and localizes to the parasite membrane (Olshina et al., 2015). On the other hand, Pfatpase6 contains 925 amino acids sequence. The function of PfATPase 6 is mainly related to calcium metabolism (Jambou et al., 2005). The amino acid sequence from 1-47 is the cation ATPase N-ternimus (cation transporter), region 69-318 is the E1-E2 ATPase (a superfamily of ion-pumping ATPases), region 647-700 is the cation ATPase (P-type) while region 842-920 is the soluble P-type ATPase (conserved domain).

Prevalence of Pfcoronin and PfATPase6 non‑synonymous mutations in Africa

The two studies reporting Pfcoronin mutation collected a total number of 624 samples, the whole samples were PCR+. Pfcoronin gene was sequenced in 624 (100%) isolates (Delandre et al., 2020; Velavan et al., 2019).  On the other hand, six studies reported PfATPase6 polymorphisms. The six studies involved 1323 samples of which 752 P. falciparum isolates were PCR+, 644(85.63%) were successfully sequenced (Heuchert et al., 2015; Koukouikila-Koussounda et al., 2017; Kwansa-Bentum et al., 2011; J. Li et al., 2016). In Tanzania (Chilongola et al., 2015), three  (L263E, E431K, and S769N) of the four mutations (L263E, E431K, A623E, and S769N) in PfATPase6 gene associated with delayed parasite clearance in presence of artemisinin were reported (Table 1). PfATPase 6 E431K was reported in Congo and Ethiopia (Figure 8). 

Pfcoronin mutations were reported in five countries (Senegal, Gabon, Ghana, Kenya, and Democratic Replublic of the Congo) P76S polymorphism was identified in four countries (Sengal, Gabon, Ghana, and Kenya) (Delandre et al., 2020; Velavan et al., 2019). The frequency of occurrence of P76S was higher in Senegal compared with the three other countries. Likewise, V62M was reported in Ghana and Gabon. (Table 2).

Table 1: The prevalence of PfATPase6 single nucleotide polymorphisms in Africa

Table 2: The prevalence of Pfcoronin single nucleotide polymorphisms in Africa

Discussion

The emergence of P. falciparum artemisinin-resistance in SEA is an imminent danger to the successful treatment and a potential public health burden. The large spectrum of mutations associated with artemisinin resistance reported so far in Africa raises concern about potential adaptation of P. falciparum to artemisinin. Consequently, African health workers and policymakers are reminded of the need for accurate and effective use of artemisinin derivatives for malaria treatment.

Compared to SEA, low prevalence of Pfk13 SNPs were recorded across Africa. This could be associated with the late introduction of artemisinin in Africa (between 2000–2005), accompanied by a shorter period of artemisinin drug pressure unlike in SEA which experienced an early adoption of artemisinin in the 1970s (Li et al., 1994). Reports from SEA identified 31 major Pfk13 SNPs nine of which were validated by the World Health Organization (WHO) as Pf-artemisinin resistance markers (Ishengoma et al., 2019; Talundzic et al., 2017). Seven of these polymorphisms (V568G, F446I, P553L, M476I, A675, R539I/K, and P574L) have shown a strong association in delayed in vivo parasite clearance (Ariey et al., 2014; Ashley et al., 2014; Bonnington et al., 2017; Cheeseman et al., 2015). Meanwhile, P533L, M476I and F446I have shown a decrease in in-vitro response to artemisinin (Ariey et al., 2014; Straimer et al., 2015; Wang et al., 2018). Some validated Pfk13 markers have been identified in African isolates. For instance, P553L was identified in Ghana and Senegal (Talundzic et al., 2017). R561H was identified in Rwanda and Tanzania (Uwimana et al., 2020) and M476I was detected in Tanzania (Kakolwa et al., 2018). R539I was reported in Senegal, and in Kenya, lysine replaced isoleucine in R539 mutation (R539K) (de Laurent et al., 2018; Talundzic et al., 2017).

Furthermore, seven of the eleven unvalidated Pfk13 mutations have been found in Africa. Though not listed as validated SNPs, some of these markers have been associated with reduced susceptibility to artemisinin in vitro. V568G and A481C were identified in Kenya and Ghana, respectively (de Laurent et al., 2018; Tornyigah et al., 2020) while A675V was reported in Kenya, Rwanda, and Uganda (Ikeda et al., 2018; Tacoli et al., 2016). The other associated markers identified were C469Y/W (Escobar et al., 2015; Talundzic et al., 2017; Uwimana et al., 2020), G538S (Doudou 2021), G449S/C (Ouattara et al., 2014), N672I (Tornyigah et al., 2020) and P574L (Rwanda and Uganda), (Tacoli et al., 2016; Uwimana et al., 2020). The other Pfk13 mutations reported in African parasites such as C469Y, S522C, R575I/K, and P667R (Uwimana et al., 2020) were found at low frequencies and have not been substantially linked with artemisinin resistance in Africa (WHO, 2019) contrary to what was observed in SEA (WWARN, 2019). In the same vein, C469K mutation has been linked to low parasite clearance in SEA (WWARN, 2019) but not in Africa (Ikeda et al., 2018).

Therefore, it is possible that African parasites may have an artemisinin selection background that is different from SEA parasites. The suspected association of PfATPase6 and Pfcoronin with artemisinin resistance suggests the potential emergence of other non-Pfk13 mutations. PfATPase6 variants have been incriminated in delayed parasite clearance in Tanzania (Chilongola et al., 2015). PfATPase6 E431K was reported in Congo, Ethiopia and Ghana (Heuchert et al., 2015; Koukouikila-Koussounda et al., 2017; Kwansa-Bentum et al., 2011). The variant was also reported, in in vitro studies, to be associated with delayed artesunate-treated parasite clearance in Senegal (Jambou et al., 2005). However, a later study in Iran suggested that the role of E431K variant in artemisinin resistance was suspect (Zakeri, 2012). PfATPase6 E431K mutation often co-occurs with other PfATPase6 gene polymorphisms, usually the S769N and L623E mutations (Tahar et al., 2009).

Research on Pfcoronin as a potential marker of artemisinin resistance in African parasites is relatively recent and still evolving. Pfcoronin mutations reported so far include I53I, V62M, K69K/I/R, P76S, N110Y/D, N112Y/D, K115E, L121F, K127E, K127I/R, N134Y/D, N137Y/D, N137I/S (Delandre et al., 2020; Velavan et al., 2019). In five countries where Pfcoronin was genotyped, P76S variant was observed in all the populations at varying frequencies: 15% in Senegal, 11% in Gabon, 16% in Ghana, 4% in Kenya and 17% in DR Congo. None of the variants suspected to be associated with delayed parasite clearance in the presence of artemisinin pressure (E107V, G50E, and R100K) in laboratory isolates was reported in natural African populations. Even though Pfcoronin polymorphisms (Delandre et al., 2020; Velavan et al., 2019) have not yet been validated in clinical isolates as markers of delayed parasite clearance, their structural similarity with Pfkelch13 suggests the possibility of a common mechanism of resistance emergence (Delandre et al., 2020; Henrici and Sutherland, 2018). Detailed analysis of the phenotypic effects of these mutations can provide information on the continued efficacy or otherwise of artemisinin-based treatment of malaria in Africa.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Not Applicable

Consent for publication

Not applicable

Availability of data and materials

The datasets generated and/or analysed during the current study are included in this published article and its supplementary information file. All codes generated and/or analysed during the current study are available in Github (https://github.com/CeGRIB/pfk13.coronin.atpase6).

Funding

K.M.O was supported by the European and Developing Countries Clinical Trials Partnership (EDCTP) Career Development Fellowship (TMA2019CDF-2782). The views expressed in this publication are those of the authors and not necessarily those of the European Union.

Authors’ contributions

A.O. and K.M.O. conducted the literature review and drafted the manuscript. A.O., M.J.O., E.T.I. and K.M.O reviewed the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We appreciate the authors of all the articles reviewed in this paper.

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