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Article

Drug Resistance Molecular Markers of Plasmodium falciparum and Severity of Malaria in Febrile Children in the Sentinel Site for Malaria Surveillance of Melen in Gabon: Additional Data from the Plasmodium Diversity Network African Network

by
Jacques Mari Ndong Ngomo
*,
Denise Patricia Mawili-Mboumba
,
Noé Patrick M’Bondoukwé
,
Bridy Moutombi Ditombi
,
Jeanne Vanessa Koumba Lengongo
,
Fanny Bertrande Batchy Ognagosso
and
Marielle Karine Bouyou-Akotet
Faculty of Medicine, Department of Parasitology and Mycology, Université des Sciences de la Santé, Libreville BP 4009, Gabon
*
Author to whom correspondence should be addressed.
Trop. Med. Infect. Dis. 2023, 8(4), 184; https://doi.org/10.3390/tropicalmed8040184
Submission received: 16 January 2023 / Revised: 22 February 2023 / Accepted: 24 February 2023 / Published: 23 March 2023

Abstract

:
The objective of this study was to analyze the relationship between the frequency of artemisinin-based combination (ACT) drug resistance molecular markers and clinical forms of P. falciparum malaria and parasitemia. A cross-sectional study was carried out between January and April 2014 at the Operational Clinical Research Unit of Melen in febrile children aged 12 to 240 months with a Plasmodium sp. infection. A total of 3 mL of peripheral blood collected from an EDTA tube was used for leukocyte depletion. DNA mutation detection was performed by next generation sequencing (NGS). A total of 1075 patients were screened for malaria. Among them, 384 had a Plasmodium infection. P. falciparum mono-infection was found in 98.9% of the patients. Pfcrt-326T mutation was found in all isolates, while 37.9% had Pfmdr2-484I mutant allele. The highest median parasite densities were found in patients infected by parasites carrying the CVIET haplotype of the Pfcrt gene. The different genetic profiles found here, and their variations according to clinical and biological signs of severe malaria, are additional arguments for the surveillance of P. falciparum strains.

1. Introduction

Malaria cases were estimated at 247 million in the world in 2021. During this year, the number of malaria deaths was 619,000, of which 80% were children under the age of 5 [1]. Plasmodium (P.) falciparum is responsible for a severe form of the disease. Since the start of the 2000s, the World Health Organization (WHO) has recommended the use of sulfadoxine-pyrimethamine combination for preventive treatment against malaria during pregnancy, and artemisinin-based combinations (ACTs) for the treatment of uncomplicated malaria. The main combinations are artemether-lumefantrine (AL), artesunate-amodiaquine (AS-AQ), dihydroartemisinin piperaquine (DH-PQ), artesunate-mefloquine (AS-MQ) and artesunate-sulfadoxine-pyrimethamine (AS-SP). Severe malaria is treated with injectable artesunate (intramuscular or intravenous), followed by a complete three-day ACT course once the patient can tolerate oral medicines. Artemether and quinine may also be used in the absence of artesunate [2].
These recommendations have been adopted after the spread of P. falciparum strains multiresistant to conventional antimalarials, some of which are partner’s molecules of artemisinin derivatives in ACTs. ACTs led to a significant reduction in malaria morbidity and mortality in populations at risk [1,3]. Thus, WHO recommends regular monitoring of the efficacy of these antimalarial medicines to ensure that the chosen treatments are still efficacious.
In Southeast Asia, the resistance of parasites against artemisinin (ART) derivatives, as well as Piperaquine, has been shown [4]. Resistance to ART and its derivatives is characterized by an extension of the parasite clearance time in treated individuals [4,5]. Indeed, the persistence of parasites after three days of ACT treatment has been observed [5].
Moreover, the genetic background of ART resistant P. falciparum strains has been analyzed through a genome-wide association study [5]. Mutations Y493H, R539T, R561H, I543T and C580Y, located on the P. falciparum klech 13 (Pfk13) gene in resistant parasites have been related to artemisinin resistance [6,7,8,9,10].
Other mutations have been found in other genes, such as P. falciparum ferrodoxine (Pffd- D193Y), P. falciparum apicoplast ribosomal precursor S10 (Pfarps-V127M), P. falciparum multidrug resistance protein 2 (Pfmdr2-T484I) and P. falciparum chloroquine resistance transporter (Pfcrt- I356T and Pfcrt- N326S) [11,12]. These mutations may contribute to the development of the parasite’s resistance to ART [13]. Likewise, the T484I mutation of P. falciparum multidrug resistance protein 2 (Pfmdr2) has been associated with artemisinin drug resistance [10,13]. Such resistance may be related to a higher risk of developing severe malaria linked to a change in the fitness of the P. falciparum strains.
Monitoring the resistance of malaria parasites to partner drugs is also necessary [14]. Two genes, Pfcrt and Pfmdr-1, are associated with resistance to the three main partner drugs: amodiaquine (AQ), lumefantrine and mefloquine. The 74I-75E-76T mutations of the Pfcrt gene and those of the Pfmdr1 gene, N86Y-F184Y-D1246Y, are related to the parasite’s resistance to chloroquine (CQ) and AQ [15,16]. The N86-F184-D1246 haplotype of the Pfmdr1 gene and the mutation detected at the E415G codon of the gene (exo-E415G) coding for exonuclease are associated with a decrease in parasite susceptibility to lumefantrine and piperaquine, respectively [17,18].
In Gabon, the treatment of uncomplicated malaria is based on the administration of AS-AQ and AL as first-line treatment and dihydroartemisinin-piperaquine phosphate (DHA-PQ) as second-line treatment. The injectable form of artesunate or quinine (if artesunate is unavailable) is recommended for the treatment of complicated malaria. Studies performed in different areas of this country reported a high frequency of molecular markers associated with resistance to aminoquinoline antimalarials and antifolates [19,20]. Otherwise, malaria prevalence in Gabon, after a drop between 2005 and 2011, has increased again in patients aged less than 20 years: 25% in 2011 and 36.3% in 2014 [21]. The prevalence of P. falciparum malaria was 32.8% among 1962 patients received in 2021 in the sentinel site for malaria surveillance of Melen (unpublished data). Children under 5 years old and those over 5 years old accounted for 68.9% and 54.5%, respectively (unpublished data). Among those aged over 5 years, 45.4% concerned children aged over 11 years (unpublished data). Likewise, the prevalence of severe malaria increased and a change in the clinical-biological profile was observed, with neurological forms being predominant [22].
Thus, the aim of this study was to analyze the relationship between the frequency of drug resistance molecular markers to ACTs and clinical forms of P. falciparum malaria according to parasite density level.

2. Materials and Methods

2.1. Study Area

A cross-sectional study was conducted between January and April 2014 in the Operational and Clinical Research Unit (OCRU), located in the Regional Hospital of Melen (RHM) in the north of Libreville. The RHM is located 11 km north of Libreville, as previously described [21]. Its equatorial climate is subdivided in four seasons: a short dry season from December to January, a long dry season from May to September, a short rainy season from October to November and a long rainy season from February to June. The malaria transmission is perennial in the country. P. falciparum is the cause of 99% of the symptomatic infections [20]. The major vector species are Anopheles (A.) gambiae and A. funestus [23].

2.2. Study Population

The participants were children aged 12 to 240 months mainly living in the district surrounding the RHM. Children meeting the following criteria were invited to participate: being febrile (with a tympanic temperature of >37.5 °C) or having a 24 h to 48 h history of fever before the day of consultation. A clinical examination was performed to identify the criteria of complicated malaria, looking for repeated convulsions, iterative vomiting and icterus in particular. Complicated malaria was defined and classified according to WHO indications [24]. Biological analyses were also performed for each patient. Indeed, health workers appointed in pediatric wards directed all patients towards the OCRU to benefit from the blood smear and cell blood count tests. Those who had a P. falciparum mono infection and parasite density of >2000 trophozoïtes per microliter of blood (p/µL) were included. Non-inclusion criteria were the presence of a mixed Plasmodium infection and non-falciparum infection.
Approximately 3 mL of blood sample in a EDTA tube were used for the malaria diagnoses.

2.3. Malaria Diagnosis

Giemsa-stained thick and thin blood smears of peripheral blood were taken for each patient, as previously described [25]. A smear was only considered negative if no malaria parasites were seen in 100 microscopic fields using immersion oil. The thin blood smear made it possible to identify Plasmodium species. All patients infected with Plasmodium species were treated according to national recommendations.

2.4. Leukocyte Depletion

Leukocyte depletion consists of the elimination of blood leukocytes before malaria parasite DNA extraction using CF11 columns containing cellulose powder. It reduces the amount of human DNA (contained in the nucleus of leukocytes) in a Plasmodium infected blood sample to obtain P. falciparum purified DNA. Leucocyte depletion was carried out at the Department of Parasitology-Mycology of the Faculty of Medicine. Venous blood sample from each patient was depleted of leucocytes within 6 hours following the sample collection. After the depletion of the leucocytes, a quality control of the sample was done based on microscopy.

2.5. Molecular Analysis

Parasite genomic DNA was then extracted from samples after leucocytes depletion using a commercial Kit QIAamp DNA Blood Midi (100), according to the manufacturer’s instructions. DNA was kept in 100 µL of elution buffer at −80 °C for long-term conservation. The genes analyzed are reported in Table 1.
The NGS was carried out at the Wellcome Trust Sanger Institute (United Kingdom) for the detection of mutations related to resistance to ART and quinolines. To characterize ART, the resistance genes designated parasite genetic background (PGB) were sequenced (Table 1). Polymorphism on the Pfcrt (at codons 72–76) and Pfmdr1 (at codons 86, 184 and 1246) genes was also analyzed in order to characterize the genetic profile of Plasmodium strains resistant to quinolines. All single nucleotide polymorphisms (SNPs) were further assessed using the 3D7 strain as a reference genome.
This work was carried out as part of a multicenter study by different teams in 10 African countries for PfK13 gene polymorphism analysis [30]. These teams gathered in the "Plasmodium Diversity Network African (PDNA)" network, aiming to study the genetic diversity of P. falciparum. This includes the study of molecular markers associated with resistance to artemisinin and partner molecules in P. falciparum isolates [26]. This network has established a collaboration with the Wellcome Trust Sanger Institute in order to generate standardized data.

2.5.1. Genetic Report Card User Guide

The Genetic Report Card (GRC) contains malaria parasite genetic data, derived from the analysis of patient blood samples. For each sample, we determined the genotype for several variations (single nucleotide polymorphisms, or SNPs) that are known to be associated with resistance to antimalarials. The report also contains data on Plasmodium species found in the sample. The following is a guide to interpreting the Genetic Report Card data, linking the genotyped mutations (molecular markers) with resistance to different antimalarial drugs (Table A1 and Table A2).

2.5.2. Drug Resistance Genes and Haplotypes

Several columns in the GRC show the genotypes of drug resistance mutations. For consistency with the published literature, these genotypes are reported as amino acid positions and alleles. For genes that carry multiple SNPs of interest, we concatenated the genotypes to form a haplotype, which is also common in the literature. In the haplotypes, we also used the following special characters:
A dash (“-”) indicates a missing genotype, either because the sample could not be genotyped, or because the assay is still under development/refinement. An asterisk (“*”) indicates that two alleles were detected (a heterozygous call) (Table A2).

2.5.3. Sample Barcodes

The sample barcodes are formed by concatenated genotypes at 101 SNPs across the P. falciparum genome. These SNPs are all biallelic, i.e., only two alleles are observed. They were chosen for their usefulness in analyses of relationship between parasites, and are not associated with drug resistance. The full list of SNPs used is given in Appendix A. SNPs within the barcode are represented by the observed nucleotide (A, T, C and G). If the genotype is missing (could not be detected), the symbol “X” is used; the symbol “N” indicates that both alleles were observed (heterozygous call).

2.5.4. Species Co-Infections

We detected the presence of different Plasmodium species by testing an SNP in the parasite mitochondria (PfMIT: 270) that carries different alleles in three different parasite species: P. falciparum, P. vivax and P. knowlesi. This assay has not yet been published but has been validated with quantitative PCR assays for detecting P. vivax and P. falciparum.

2.5.5. Artemisinin Drug Resistance

Parasite genetic background (PGB) mutations showed evidence of a genetic background of mutations that allowed for the emergence of PfK13 mutations [11]. These mutations are: V127M in the Pfarp-s10 (PF3D7_1460900) protein, D193Y in ferredoxin (PF3D7_1318100), N326S and I356T in Pfcrt (PF3D7_0709000) and T484I in Pfmdr2 (PF3D7_1447900). These are displayed in a concatenated haplotype form, with the reference allele (WT) being VDNIT.

2.5.6. Chloroquine Drug Resistance

Chloroquine drug resistance is primarily mediated by mutations in the chloroquine resistance transporter (Pfcrt, PF3D7_0709000) [31]. An accessory mutation at position 86 in the multidrug resistance protein (Pfmdr1, PF3D7_0523000) has been shown to accentuate this resistance phenotype in parasites [32]. The loci in Pfcrt are represented as a 5-amino acid haplotype at positions 72–76, with the wild-type haplotype being CVMNK [29]. The CVIET haplotype is the most widespread resistant haplotype in Asia and Africa, while SVMNT is common in resistant parasites in South America and Oceania. The Pfmdr1 mutation at position 86 is the first in the three amino-acid haplotypes reported for this gene. The WT variant is N, while the Y variant in MDR-1 86 enhances resistance to chloroquine.

2.5.7. Amodiaquine Drug Resistance

Mutations in the multidrug resistance protein (Pfmdr1, PF3D7_0523000) have been associated with parasite response to amodiaquine. There is limited evidence that mutations at positions 86 and 1246 can mediate the response to this drug, and these positions constitute the haplotype reported for this gene [33]. In vitro experiments have shown that haplotypes containing the mutant 86Y have increased IC50’s to chloroquine and amodiaquine.

2.5.8. Mefloquine and Lumefantrine Drug Resistance

Mutations in the multidrug resistance protein (Pfmdr1, PF3D7_0523000) have been associated with parasite response to the drugs mefloquine and lumefantrine [28]. There is limited evidence that variations at positions 86, 184 and 1246 increase susceptibility to these drugs [28].

2.5.9. Piperaquine Drug Resistance

In a recent genome-wide association study (GWAS), an SNP in a putative exonuclease gene (PF3D7_1362500) was associated with ex vivo piperaquine IC50 of parasite isolates from Cambodia [17]. This molecular marker is at position 415, and a G allele was shown to be significantly associated with increased tolerance of piperaquine with respect to the WT allele E.

2.6. Ethical Considerations

In Gabon, the Gabonese Ministry of Health, represented by the Malaria National Control Program, has committed the Department of Parasitology-Mycology and Tropical Medicine of the Faculty of Medicine of Libreville to perform an evaluation of malaria prevalence and antimalarial drug resistance monitoring in sentinel sites throughout the country. In this study, all patients were enrolled in the sentinel site for malaria surveillance in the RHM (Melen). In this context, patients and the guardian or parent of the children included were informed of the activities in this sentinel site and their signed consent was obtained. Children over the age of 12 gave their consent to participate in the study. In addition, in this site, a standardized procedure on the conservation of blood aliquots of febrile patients in the biobank was established. Being in a sentinel site, the participants were treated according to national recommendations.

2.7. Statistical Analysis

Data were analyzed using Epi InfoTM7. All variables were compared using Chi 2 or the Fisher test to compare the exact proportions, and Student’s t-test and analysis of variance (ANOVA) or the Kruskal-Wallis test, as appropriate for continuous variables. p-value < 0.05 was considered statistically significant.

3. Results

3.1. Characteristics of the Study Population

A total of 1074 patients were screened for malaria. Median age of the population was 69 (66–72) months, with a sex ratio of 1.23 (with 55.1% of patients of male sex). Among them, 384 had a Plasmodium infection. P. falciparum mono-infection was found in 98.9% of blood samples. Among those, sixty-one samples were selected for molecular studies (Figure 1).
Amplification and sequencing of the Pfcrt, Pfmdr2, Pfarps10, Pffd and Pfmdr1 genes were successfully performed in 58 samples. These samples were from febrile patients, of whom 70.7% (n = 41/58) had uncomplicated malaria (UM) (Table 2). The median parasitemia was 32,200 (25,900–39,200) p/µL in clinical samples. The highest median parasite density was found in samples from patients with complicated malaria (CM) (p < 0.01) (Table 2). Hyperparasitemia (parasite density ≥200,000 p/µL) was found in six samples from patients with CM. Likewise, diarrhea, vomiting and convulsions were observed in two, three and six patients with CM, respectively. The use of antimalarial drugs before consultation applied to 17.6% of patients with CM and 82.3% of those with UM.

3.2. Artemisinin Resistance Related Molecular Markers Prevalence

Analysis of PGB Pfarps10, ferredoxin, Pfcrt and Pfmdr2 genes showed that 37.9% of samples carried the mutant allele Pfmdr2-484I. The Pfcrt-326T mutant allele was found in all samples, while the mutant Pfarps10-127M and Pffd-193Y were not detected. The haplotypes identified were the double mutant VDNTI (27.5%, n = 16/58) and the single mutant VDNTT (62.0%, n = 36/58) (p < 0.01). Six isolates carried both haplotypes.

3.3. Piperaquine, Amodiaquine and Lumefantrine Resistance Related Molecular Markers Prevalence

Exonuclease mutation E415G related to piperaquine resistance was not found in any isolates. Analysis of Pfcrt and Pfmdr1 genes polymorphism showed that the Pfmdr1-86N allele and Pfmdr1-184Y allele were detected in 22 (37.9%) and 3 (5.2%) isolates, respectively. A single (1.72%) isolate had a Pfmdr1-1246Y mutant type allele. Three-quarters of the isolates had mutant alleles Pfcrt-76T, Pfcrt-74I and Pfcrt-75E (Figure 2a). No mutations were found at codon Pfcrt-72 and Pfcrt-73.
The Pfcrt mutant haplotypes CVIET and wild type CVMNK, based on codons 72–76, and the mutant Pfmdr1 haplotypes YFD, NFD and wild type NYD, based on codons 86, 184 and 1246 were the main haplotypes detected (Figure 2c). The triple mutant haplotype CVIET was found in 60.4% of the samples. One sample contained a mixed infection (CVIET/CVMNK) (Figure 2c). The NFD single mutant allele was found more frequently than the double mutant haplotype YFD (43.1% vs. 20.7%) (p = 0.01) and the wild type haplotype NYD (43.2% vs. 15.5%) (p = 0.001).

3.4. Frequency of Haplotypes According to Malaria Clinical Forms

Considering the different haplotypes identified, the double mutant VDNTI haplotype was 1.4-fold (35.3% vs. 24.4%) more frequent in isolates from patients with CM, although the difference was not statistically significant (p = 0.3). Similarly, wild type haplotype NYD was almost twice as frequent in the isolates of these patients (23.5%; n = 4/17 vs. 12%; n = 5/41 in isolates of patients with uncomplicated malaria) (p = 0.4; OR 2.2154 [0.5146–9.5372]).
The haplotype CVMNK was found in the majority of the isolates of patients with uncomplicated malaria. In these, the proportion of the NFD haplotype tends to be more frequent: 58.8% (n = 10/17) vs. 48.7% (n = 20/41) (p = 0.5). Likewise, the double mutant allele YFD was twice as frequent (24.4%; n = 10/41 vs. 11.7%; n = 2/17 in isolates of patients with CM) (p = 0.4; OR 2.4194 (0.4700–12.4547)).
The frequency of the triple mutant haplotype CVIET was comparable between patients with CM (58.8%; n = 10/17) and those with uncomplicated malaria (61%; n = 25/41).

3.5. Haplotypes and Clinical and Biological Signs of Severe Malaria

Patients with hyperparasitemia or hyperparasitemia associated with convulsion were frequently infected by parasites with the CVIET triple mutant haplotype, VDNTT haplotype, NFD and YFD haplotypes of Pfmdr1 gene. The VDNTI haplotype was frequent in isolates from patients with icterus and convulsions.
The combination of PGB and Pfcrt 72-76 haplotypes showed the presence of five haplotypes (H0 to H4) (Table 3). H0 and H2 were the most frequent (Table 3).

4. Discussion

In the present study, the monitoring of drug resistance molecular markers related to antimalarial drugs used in Gabon revealed mutations T484I (>37.8%) and I356T (100%) on the Pfmdr2 and Pfcrt genes, respectively. In Asia, these are associated with a delayed clearance of parasites in patients treated with AL, DHA-PQ and AS-AQ, respectively [13]. The appearance of these mutations suggests that P. falciparum strains are under drug pressure. Thus, the occurrence of additional mutations on the Pfarps and Pffd genes may be expected, although none were found in these isolates. Similarly, molecular markers such as Exo-E415G SNP related to piperaquine resistance and DH-PQ treatment failure were not detected in the isolates. Nevertheless, P. falciparum strains carrying multiple copies of the Plasmepsin 2 gene have been collected in previous studies carried out in Gabon, Burkina Faso, the Democratic Republic of Congo, Mozambique and Uganda [34]. Taken altogether, these data suggest a delayed appearance of the Exo-E415G mutation, compared to the Plasmepsin 2 gene’s amplification in isolates circulating in areas where these molecules are used. Furthermore, the mutant Pfmdr1-86Y (43%) allele, which is less frequent than the mutant Pfcrt-76T allele (60%) in P. falciparum isolates from Melen was also detected. Its frequency confirms a decreasing frequency of this haplotype since the implementation of ACTs [19,35].
It is notable that multiple mutations are generally required to functionally confer and increase the level of drug resistance. The Pfcrt CVIET triple mutation was found in 60.4% of P. falciparum isolates from Melen. This proportion is similar to those reported in the Congo (71%) and south-east Gabon (70.6%) [36,37]. This haplotype was reported to be more frequently detected in isolates from West Africa (44%) and East Africa (38%), than in those from South Africa (21%) and Central Africa (26%) [38]. Among the Pfmdr1 haplotypes, the NFD haplotype related to lumefantrine resistance was the most prevalent, found in almost one out of two isolates, several years after the introduction of AL and AS-AQ in Gabon. Similar frequencies, varying from 35% to 46%, were found in other areas of Gabon and in Tanzania [20,36]. In contrast, a higher prevalence of the NFD haplotype was found in Senegal (62.26%), Kenya (51%) and Ghana (60%) [38]. The circulation of P. falciparum strains carrying the NFD haplotype is frequently related to pressure due to the use of AL [20,39].
In addition to the use of antimalarial drugs as self-medication, as well as the non-observance of the recommended dosage, other factors, such as the parasite’s genetic background, may lead to an increase in the number of complicated malaria cases in Gabon [22].
In the present study, specific haplotypes varied according to malaria severity, as well as clinical and biological signs. Haplotypes NFD, YFD and CVMNK were more common in isolates from patients with uncomplicated malaria. In contrast, in those from patients with severe malaria, NYD and VDNTI were the most frequent, although these differences were not statistically significant. The CVIET haplotype was common in both groups of patients. The relationship between these haplotypes and the occurrence of severe malaria needs to be confirmed. Specific haplotypes have been identified, but no significant relationship between the clinical forms of malaria—or biological modifications and the frequency of drug resistance molecular markers—has been found. More specifically, patients with hyperparasitemia were infected by parasites with the CVIET and VDNTT haplotypes. The VDNTI haplotype was found in isolates from patients with icterus and convulsion. NFD and YFD were detected in parasites from patients with convulsion. A relationship between NYD and high parasitemia (p = 0.04) has been reported elsewhere [40]. In the current study, the combined haplotypes H2 (VDNTT + CVIET), H3 (VDNTT + CVIET/CVMNK) and H4 (VDNTT + CVIET/CVMNK) were found in patients infected with high parasite densities, suggesting their involvement in the parasite’s ability to multiply.

5. Conclusions

More than one decade after the withdrawal of CQ and the introduction of ACTs in Gabon, monitoring of drug resistance molecular markers remains critical to providing data on the propagation of artemisinin resistant parasites, as done in the present study. Moreover, the different genetic profiles found here and their variations according to the clinical and biological signs of severe malaria are additional arguments for their monitoring, and for an in-depth analysis of their role of the CIVIET haplotype of the Pfcrt gene on the fitness of the parasite.

6. Patents

This section is not mandatory but may be added if there are patents resulting from the work reported in this manuscript.

Author Contributions

Conceptualization, M.K.B.-A.; methodology, D.P.M.-M.; software N.P.M.; validation, N.P.M.; formal analysis, J.V.K.L.; investigation, J.M.N.N., N.P.M., B.M.D. and F.B.B.O.; data curation, J.V.K.L.; writing—original draft preparation, J.M.N.N.; writing—review and editing, J.M.N.N.; supervision, D.P.M.-M.; project administration, M.K.B.-A. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Medical Research Council UK (grant G0600718) and the Wellcome Trust (grant 098051) and carried out by the Plasmodium Diversity Network African (PDNA).

Institutional Review Board Statement

The Gabonese Ministry of Health, but represented by the Malaria National Control Program. The study was conducted according to the guidelines of the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Acknowledgments

We thank the study participants, Plasmodium Diversity Network African (PDNA)/DELGEME which provided the funds to carry out this project, all the authors as well as the team of the Department of Parasitology-Mycology.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. List of barcode SNPs.
Table A1. List of barcode SNPs.
MultiplexChromosomePositionMutationMultiplexChromosomePositionMutation
W369602376222K1929EW369627704373389E
W369602470013G75EW3696271066698G483S
W369603656861129VW3696271213486S543N
W369604110442G285EW3696283394061283C
W3696048815711081RW369628701557394G
W3696053509331369NW3696281313202799F
W369605369740907LW3696294526901018I
W369606900278P696SW369629599655E654D
W3696071044052686KW36962101383789N114H
W3696084130671044VW36962101385894815P
W36960813148311342KW36962111006911D124E
W3696099002771534EW36962111295068E405K
W369601110188991199LW36962111802201450S
W36960111815412E765QW3696212858501Q469K
W369601310564521234DW369621216675932381N
W36960131466422N66KW36962121934745241L
W36960141376221179VW369621315908621R
W369601421642252830SW3696213388365S1236R
W369611145515294IW36962131419519Q208R
W369613548178R2LW36962132161975D252V
W369614139051K438NW36962132573828I1153M
W369614286542H586NW3696214438592N348T
W3696145295001477YW36962142625887M238I
W3696141102392E808DW36962143126219S628F
W369615796714396KW369631179347311G
W369617461139M361IW369631180554D714N
W369617619957675RW369631283144H664D
W3696171256331L321FW3696315352112521F
W369618417335R244KW369632839620260L
W369618417335R244KW369634426436D560A
W3696110317581311IW369634531138A992E
W3696110336274I1677VW369634891732R4468S
W3696111477922H147YW369635172801E218K
W36961111020397G700EW369636574938I2934L
W3696111129410784AW369637635985T598A
W36961111935227R73SW3696371308383G1945R
W369611216634921014EW3696371358910K286E
W36961122171901V140DW3696371359218K388N
W36961131233218N277SW3696381500331315I
W36961131867630M4911IW369638399774421K
W369611323778872002SW3696381056829L474I
W36961142355751H1589QW3696391379145R398Q
W36961143046108417VW36963101386850927K
W369622529709F487LW36963114086681058I
W369622714480D258GW3696311828596K240E
W369623155697150PW36963111935031I139L
W36962464810151VW3696312857245E50G
W36962410376562776IW3696314107014215K
W36962512041551338IW36963141757603D1365G
W3696261282691803KW36963142733656557C
W3696261289212125T
Table A2. Data base after sequencing.
Table A2. Data base after sequencing.
IDSpeciesCRTMDR1PGBEXO
QW0009-CWPfCVMNKNYDVDNTIE
QW0010-CWPfCVIETYYYVDNTTE
QW0010-CxWPfCVIETYFDVDNTTE
QW0014-CWPfCVMNKNYDVDNTIE
QW0016-CWPfCVMNKNYDVDNTIE
QW0018-CWPfCVIET,CVMNK**DVDNT*E
QW0019-CWPfCVIET,CVMNKNYDVDNT*E
QW0020-CWPfCVMNKNFDVDNTIE
QW0021-CWPfCVIETNFDVDNTTE
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Figure 1. Profile of outcomes obtained before sequencing.
Figure 1. Profile of outcomes obtained before sequencing.
Tropicalmed 08 00184 g001
Figure 2. Frequency of molecular markers of amino-4-quinoleine resistance (Pfcrt-72-76 + Pfmdr1-86-184-1246). (a) Frequency of Pfcrt mutations related to amino-4-quinoleines resistance; (b) Frequency of Pfmdr1 mutations related to AQ and lumefantrine resistance; (c) Frequency of haplotypes of Pfcrt gene, Pfmdr1 gene and Pfcrt + Pfmdr1 genes. YYY: 86Y-184Y-1246Y; YYD: 86Y-184Y-D1246; NYD: N86-184Y-D1246; YFD: 86Y-F184-D1246; NFD: N86-F184-D1246; CVMNK: 72C-73V-74M-75N-76K; CVIET: 72C-73V-74I-75E-76T; CVIET/CVMNK: mixed infection.
Figure 2. Frequency of molecular markers of amino-4-quinoleine resistance (Pfcrt-72-76 + Pfmdr1-86-184-1246). (a) Frequency of Pfcrt mutations related to amino-4-quinoleines resistance; (b) Frequency of Pfmdr1 mutations related to AQ and lumefantrine resistance; (c) Frequency of haplotypes of Pfcrt gene, Pfmdr1 gene and Pfcrt + Pfmdr1 genes. YYY: 86Y-184Y-1246Y; YYD: 86Y-184Y-D1246; NYD: N86-184Y-D1246; YFD: 86Y-F184-D1246; NFD: N86-F184-D1246; CVMNK: 72C-73V-74M-75N-76K; CVIET: 72C-73V-74I-75E-76T; CVIET/CVMNK: mixed infection.
Tropicalmed 08 00184 g002
Table 1. Molecular markers of antimalarial resistance.
Table 1. Molecular markers of antimalarial resistance.
ProteinAntimalarialGeneAmino-Acid PositionWildMutantReferences
PGB
Artemisinin genetic background
ART
AS
AL
DHA
 
Pfarps10
Ferredoxine
Pfcrt
Pfmdr2
 
127
193
326
356
484
V
D
N
I
T
M
Y
S
T
I
[11]
[26]
[12]
EXOPQExonuclease415E [17]
MDR1CQPfmdr186NY[27]
[28]
AQ 184FY
LUM 1246DY
MQ
CRTCQ
AQ
Pfcrt72CS[29]
73VM
74MI
75NE
76KT
CQ: Chloroquine, AQ: amodiaquine, LUM: lumefantrine, DHA: dihydroartemisinin.
Table 2. Characteristics of the study population.
Table 2. Characteristics of the study population.
CharacteristicsAll Participants
N = 58
Uncomplicated Malaria N = 41Complicated Malaria N = 17p-Value
Median age, months69 (66–72)48 (40–60)60 (36–66)<0.01
Gender (Male/Female) ratio1.230.482.6<0.01
Median parasite density (µ/L)32,200 (25,900–39,200)21,000 (19,600–25,200)105,700 (87,500–156,100)<0.01
Mean T °C (±SD)37.5 ± 0.7737.8 ± 0.7639.5 ± 0.850.02
T °C: temperature in degrees Celsius, SD, standard deviation.
Table 3. Genetic profile of P. falciparum isolates according to median parasite density.
Table 3. Genetic profile of P. falciparum isolates according to median parasite density.
PGB
(Aminos Acids)
Pfcrt
(Aminos Acids)
Total
N = 58 n(%)
Median PD
(25–75%)
Haplotype 0 (H0)VDNTICVMNK14 (24.2)9100 (7700–10,500)
Haplotype 1 (H1)VDNTICVIET2 (3.4)87,675 (4900–170,450)
Haplotype 2 (H2)VDNTTCVIET34 (58.6)39,900 (39,200–40,600)
Haplotype 3 (H3)VDNTT/I *CVIET, CVMNK5 (8.6)67,200 (42,000–133,000)
Haplotype 4 (H4)VDNTTCVIET, CVMNK3 (5.2)49,000 (9100–101,500)
PD: parasite density; Pfarps10-V127M-Pffd-D193Y- Pfcrt-N326-Pfcrt-I356T-Pfmdr2-T484I (VDNTT/ VDNTI); * Mixed infections at codon 484T/I of Pfmdr2 gene; H0 is a combination of VDNTI and CVMNK; H1 is a combination of VDNTI and CVIET; H2 is a combination of VDNTT and CVIET; H3 is a combination of VDNTT * (* Mixed infection on 484T/I codon of Pfmdr2 gene), CVIET and CVMNK); H4 is a combination of VDNTI, CVIET and CVMNK: The underline indicate the mutant allele.
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Ndong Ngomo, J.M.; Mawili-Mboumba, D.P.; M’Bondoukwé, N.P.; Ditombi, B.M.; Koumba Lengongo, J.V.; Batchy Ognagosso, F.B.; Bouyou-Akotet, M.K. Drug Resistance Molecular Markers of Plasmodium falciparum and Severity of Malaria in Febrile Children in the Sentinel Site for Malaria Surveillance of Melen in Gabon: Additional Data from the Plasmodium Diversity Network African Network. Trop. Med. Infect. Dis. 2023, 8, 184. https://doi.org/10.3390/tropicalmed8040184

AMA Style

Ndong Ngomo JM, Mawili-Mboumba DP, M’Bondoukwé NP, Ditombi BM, Koumba Lengongo JV, Batchy Ognagosso FB, Bouyou-Akotet MK. Drug Resistance Molecular Markers of Plasmodium falciparum and Severity of Malaria in Febrile Children in the Sentinel Site for Malaria Surveillance of Melen in Gabon: Additional Data from the Plasmodium Diversity Network African Network. Tropical Medicine and Infectious Disease. 2023; 8(4):184. https://doi.org/10.3390/tropicalmed8040184

Chicago/Turabian Style

Ndong Ngomo, Jacques Mari, Denise Patricia Mawili-Mboumba, Noé Patrick M’Bondoukwé, Bridy Moutombi Ditombi, Jeanne Vanessa Koumba Lengongo, Fanny Bertrande Batchy Ognagosso, and Marielle Karine Bouyou-Akotet. 2023. "Drug Resistance Molecular Markers of Plasmodium falciparum and Severity of Malaria in Febrile Children in the Sentinel Site for Malaria Surveillance of Melen in Gabon: Additional Data from the Plasmodium Diversity Network African Network" Tropical Medicine and Infectious Disease 8, no. 4: 184. https://doi.org/10.3390/tropicalmed8040184

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