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Article

Tracking Drug Resistance in Plasmodium falciparum: Genetic Diversity of Key Resistance Markers in Brazilian Malaria Hotspots

by
Rebecca de Abreu-Fernandes
1,2,
Lucas Tavares de Queiroz
1,
Natália Ketrin Almeida-de-Oliveira
1,2,
Aline Rosa de Lavigne Mello
1,2,
Jacqueline de Aguiar Barros
1,3,
Lilian Rose Pratt-Riccio
1,
Gisely Cardoso de Melo
4,5,
Patrícia Brasil
2,6,
Cláudio Tadeu Daniel-Ribeiro
1,2,
Didier Menard
7,8,9,10 and
Maria de Fátima Ferreira-da-Cruz
1,2,*
1
Laboratório de Pesquisa em Malária, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro 21041-361, Brazil
2
Centro de Pesquisa, Diagnóstico e Treinamento em Malária (CPD-Mal), Reference Laboratory for Malaria in the Extra-Amazonian Region for the Brazilian Ministry of Health, Secretaria de Vigilância Sanitária & Fiocruz, Rio de Janeiro 21041-361, Brazil
3
Núcleo de Controle da Malária, Departamento de Vigilância Epidemiológica, Coordenação Geral de Vigilância em Saúde, SESAU-RR, CIEVS/SVS/SMSA-BV, Boa Vista 69305-080, Brazil
4
Fundação de Medicina Tropical Dr. Heitor Vieira Dourado (FMT-HVD), Manaus 69040-000, Brazil
5
Universidade do Estado do Amazonas (UEAM), Manaus 69010-455, Brazil
6
Laboratório de Pesquisa Clínica em Doenças Febris Agudas, Instituto Nacional de Infectologia Evandro Chagas, Fiocruz, Rio de Janeiro 21040-360, Brazil
7
Malaria Parasite Biology and Vaccines Unit, Institut Pasteur, Université Paris Cité, F-75015 Paris, France
8
Malaria Genetics and Resistance Team (MEGATEAM), UR 3073—Pathogens Host Arthropods Vectors Interactions, Université de Strasbourg, F-67000 Strasbourg, France
9
CHU Strasbourg, Laboratory of Parasitology and Medical Mycology, F-67081 Strasbourg, France
10
Institut Universitaire de France (IUF), F-75231 Paris, France
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(13), 5977; https://doi.org/10.3390/ijms26135977
Submission received: 23 May 2025 / Revised: 16 June 2025 / Accepted: 19 June 2025 / Published: 21 June 2025
(This article belongs to the Special Issue Interactions Between Microbes and Hosts: Physiology, Pathology and Treatment)
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Abstract

Malaria remains a health problem, with Plasmodium falciparum accounting for 96% of cases in Africa and 15% in Brazil. The growing threat of drug resistance to artemisinin-based combination therapies (ACTs) jeopardizes progress toward elimination. This study examined P. falciparum samples collected from 141 patients in Brazil (2013–2023) by PCR and DNA sequencing to identify single-nucleotide polymorphisms in the pfcrt, pfmdr1, and pfk13 genes. Half of the samples carried the SVMNTMCGI haplotype in pfcrt, and none of the samples showed C350R mutations. In pfmdr1, the NYCDY haplotype was dominant (70%), with low occurrences of N86Y (4%) and no Y184F polymorphisms. No mutations linked to artemisinin partial resistance were detected in pfk13. Only one Amazonas sample exhibited wild-type haplotypes across all genes. Genetic diversity was more pronounced in pfcrt than pfmdr1, reflecting selective drug pressure. Significant linkage disequilibrium (LD) was observed within pfcrt (C72S and K76T) and pfmdr1 (S1034C and N1042D), but not between the two genes. The absence of pfk13-resistant mutations and the low prevalence of key pfmdr1 markers support the efficacy of ACTs. The persistence of diverse haplotypes and intragenic LD reflects ongoing drug pressure, underscoring the need for continuous genetic surveillance to anticipate emerging resistance.

1. Introduction

Malaria remains a major parasitic disease with high mortality rates, particularly in tropical and subtropical regions. Despite being a life-threatening infectious disease, malaria still affects millions globally [1]. In 2023, approximately 263 million malaria cases were reported, resulting in 619,000 deaths [2]. The lethal parasite Plasmodium falciparum accounted for 15% of the Brazilian cases [3]. Over the past two decades, substantial progress has been made in reducing malaria incidence, primarily through the widespread adoption of artemisinin-based combination therapies (ACTs) as the first-line treatment for uncomplicated Plasmodium falciparum malaria in endemic regions [1]. In Brazil, current treatment guidelines recommend either artemether/lumefantrine (AM–LM) or artesunate/mefloquine (AS–MQ), combined with a single dose of primaquine (SLDP), depending on regional availability [4]. However, this progress is under threat due to the emergence and spread of antimalarial drug resistance.
The P. falciparum drug resistance poses a significant challenge for malaria control programs. Chloroquine resistance (CQR) in the late 1950s marked a pivotal moment, seriously undermining global disease control efforts [5]. Since then, resistance has developed to multiple antimalarial drugs, including sulfadoxine–pyrimethamine (SP) [6], mefloquine (MQ) [7], and, more recently, artemisinin (ART) [8]. Documented resistance hotspots in Southeast Asia and South America further emphasize the urgent need for continuous surveillance [9,10]. Recently, the P. falciparum kelch propeller domain on chromosome 13 (pfk13) has been extensively studied and identified as a key marker for ART partial resistance (ART-R) [11,12,13,14]. To date, more than 200 SNPs have been identified in pfk13, though only 13 (F446I, N458Y, M476I, Y493H, R539T, I543T, P553L, R561H, P574L, C580Y, R622I, C469Y, and A675V) are officially linked to ART-R [14]. While ART-R is an emerging global threat, CQR remains persistent and particularly problematic in South America due to its distinct molecular mechanisms.
CQR is strongly associated with the K76T polymorphism and the SVMNT haplotype of the pfcrt gene, which have been detected globally but are particularly prevalent in South America [15]. Although the cessation of CQ use has led to the re-emergence of the wild-type allele and restored drug susceptibility in many regions, the persistence of the K76T allele in Brazil suggests ongoing selective pressure or other factors maintaining this polymorphism [16]. In South America, the reversal of CQR has been attributed to the pfcrt C350R mutation [9,17]. However, this mutation has not yet been investigated in Brazilian isolates, emphasizing the need to examine whether it is circulating to support an eventual reintroduction of CQ as a treatment option.
The pfmdr1 (multidrug resistance 1) gene modulates P. falciparum susceptibility to key heme-binding antimalarials, including CQ, MQ, LM, and ART [18]. Specific point mutations drive its influence on drug resistance and have been linked to treatment failures in ACTs [19,20]. Five significant SNPs have been identified in pfmdr1: N86Y, Y184F, S1034C, N1042D, and D1246Y, each with distinct effects on drug efficacy and resistance patterns. The N86Y mutation is linked to CQR and the ACT partner drug amodiaquine (AQ), and enhances the parasite’s sensitivity to MQ, LM, and dihydroartemisinin (DHA) [18,19,20]. In contrast, the Y184F mutation has been associated with reduced LM sensitivity [19]. Although S1034C, N1042D, and D1246Y do not independently confer phenotypic resistance, they contribute to the emergence of resistant haplotypes when combined with other mutations. By modifying drug transport kinetics, these variants can alter the parasite’s susceptibility to treatment and potentially compromise the efficacy of ACT regimens [18]. Their phenotypic impact is primarily determined by the specific genetic contexts in which they arise within the parasite genome. Notably, haplotypes such as YYY (86Y/184Y/1246Y) have been shown to modulate resistance and sensitivity patterns to antimalarial therapies, underscoring the complex genetic interactions that shape treatment outcomes [21,22].
Mutations in the pfcrt gene and those in pfmdr1 further enhance resistance to antimalarial drugs by creating synergistic effects that impair drug efficacy [21]. The wild-type K76 pfcrt allele and the NFD pfmdr1 haplotype (N86/184F/D1246) have been associated with decreased sensitivity to LM [20]. These alleles are frequently selected under AM–LM drug pressure [19,20,21], a first-line ACT therapy widely used in Brazil [4]. Moreover, the K76T mutation in pfcrt, when combined with the YYY haplotype in pfmdr1, has been strongly linked to clinical treatment failure (i.e., recrudescence following artesunate–amodiaquine, AS–AQ therapy) [21,22]. Monitoring these genetic markers is essential to predict therapeutic failure and preserve the long-term efficacy of ACTs. Identifying key haplotypes and their association with specific resistance phenotypes enables the development of more targeted treatment regimens and informs public health interventions to mitigate the spread of resistance.
Furthermore, understanding the genetic diversity of resistance-associated genes is crucial for identifying emerging mutations that could undermine the effectiveness of ACT. Linkage disequilibrium (LD) analysis enhances this understanding by revealing non-random associations between mutations, clarifying how resistance variants co-evolve and spread within parasite populations. By mapping the genetic structure and transmission dynamics of resistance markers, LD analysis can predict how multidrug resistance propagates, thereby guiding the development of targeted control strategies.
Thus, this study investigated the SNPs in key resistance-associated P. falciparum genes (pfcrt, pfmdr1, and pfk13) as well as their genetic diversity to provide critical insights into resistance dynamics and inform evidence-based treatment strategies.

2. Results

2.1. Prevalence of Drug Resistance Markers

Analysis of the sequences from 141 samples revealed no known mutations associated with ART-R in the pfk13 gene. Haplotype analysis indicated that the wild-type profile predominated among all tested samples. Among the 141 P. falciparum samples, mutations in the codons C72S and K76T were identified in 99% (139 out of 141) of the samples, while mutations in codon I356L were detected in 40% (56 out of 141). No mutations were observed in codons M343L or G353V. Notably, the pfcrt C350R mutation, which has recently been linked to a reverse phenotypic response involving CQ sensitivity and piperaquine resistance, was not detected. Haplotype analysis also showed that the most common variant was the double mutant haplotype (SVMNTMCGI), present in 59% (83 out of 141) of isolates. The triple mutant haplotype (SVMNTMCGL) was also identified in 40%, while the wild-type haplotype (CVMNKMCGI) was found in only 1% of the isolates (Table 1).
For the pfmdr1 gene, the analysis revealed highly prevalent mutations in codons S1034C (81%), N1042D (81%), and D1246Y (71%). The N86Y polymorphism was identified in only five isolates (4%), one from Roraima and four from Amazonas states. None of the isolates carried the Y184F mutation in this study. Five pfmdr1 haplotypes at the N86Y–Y184F–S1034C–N1042D–D1246Y loci were identified. The NYCDY haplotype was observed in 70% (98/141) of the isolates, while the NYSND wild-type haplotype was documented at a frequency of 13% (19/141) (Table 2).

2.2. Combined Haplotypes of pfk13, pfcrt, and pfmdr1

The pfk13, pfcrt, and pfmdr1 genes were genotyped successfully in all 141 cases, and the combined haplotypes are summarized in Table 3. They had 11 combined haplotypes, predominated by wild-type + SVMNTMCGI + NYCDY and wild-type + SVMNTMCGL + NYCDY, with 38% and 31% prevalence, respectively. Only one Amazonas sample carried a wild-type haplotype profile for the SNPs of the three analyzed genes (Table 3).
Complementary notification and clinical follow-up data were retrieved from the SIVEP-Malaria system for patients from Roraima and Amazonas. No cases of recrudescence were identified among the patients with available SIVEP records or those followed at CPD-Mal, as none presented a recurrence of P. falciparum infection within 28 days, or up to 42 days in the cases of suspected treatment failure [4].

2.3. Genetic Diversity and Linkage Disequilibrium (LD) Analysis

The analysis of genetic diversity revealed that pfcrt showed the highest genetic variation, exhibiting significantly greater nucleotide and haplotype diversity compared to pfmdr1, while pfk13 remained monomorphic with no detected polymorphisms (Table 4). Neutrality tests indicated negative Tajima’s D values for exon 2 of pfcrt (−0.39181|p  >  0.10), suggesting potential population expansion or purifying selection. In contrast, positive values were observed for exon 10 of pfcrt (1.72185|p  >  0.10), indicating balancing selection. Similarly, pfmdr1 exhibited negative values in its initial region (−0.66673|p  >  0.10) and positive values in its terminal region (1.58461|p  >  0.10), reflecting distinct selective pressures across the gene (Table 4).
To evaluate linkage disequilibrium (LD) within and between resistance haplotypes, the LD pattern for each SNP in the pfcrt and pfmdr1 genes was analyzed (Figure 1). Statistically significant intragenic associations were identified between the SNPs C72S and K76T in pfcrt and between 1034C and 1042D in pfmdr1. However, no significant intergenic LD association was detected between the two genes (Figure 1).

3. Discussion

ACT therapy is the World Health Organization’s recommended treatment for uncomplicated P. falciparum malaria in all malaria-endemic regions [2,23]. Artemisinin and its derivatives quickly reduce the majority of the parasite biomass. When combined with a long-acting partner drug, this strategy effectively eliminates any remaining parasites [4]. In 2006, the Brazilian government adopted this guideline as the first-line treatment for all diagnosed cases of uncomplicated P. falciparum malaria. Currently, two ACTs are endorsed: AM-LM and AS–MQ [4]. Due to widespread resistance, CQ is no longer used to treat P. falciparum infections. However, CQ remains the first-line therapy for P. vivax malaria in Brazil, alongside primaquine [24].
A comprehensive understanding of the genetic factors that influence drug resistance is essential for addressing the decline in antimalarial effectiveness. Examining key resistance genes such as pfk13, pfcrt, and pfmdr1 is crucial for revealing the molecular mechanisms that lead to therapeutic failure [17]. Ongoing genetic monitoring of these markers is crucial for maintaining the long-term efficacy of ACT regimens and for making timely adjustments to treatment strategies in response to emerging resistance trends. Consequently, this study assessed the prevalence of mutations associated with drug resistance in P. falciparum parasites from endemic regions in Brazil.
As seen in Southeast Asia, the pfk13 gene is crucial due to its association with ART-R, particularly from SNPs in the propeller domain [13,25]. Thus far, no pfk13 mutations linked to ART-R have been detected in Brazilian isolates [26,27,28,29], and our analysis confirmed the absence of mutations both in resistance-associated codons and other regions of the propeller domain, supporting the continued efficacy of ACTs in this country. However, emerging evidence from neighboring borders raises concerns about the spread of resistant parasite lineages. The pfk13 C580Y mutation in Guyana, associated with in vitro resistance to ART, has been confirmed [28]. Additionally, the pfk13 A481V mutation was reported in Manaus State, Brazil, though no clinical data were available to evaluate its impact [30]. Although this mutation is not classically associated with those described in Southeast Asia, emerging evidence suggests that other pfk13 mutations may be present in South America [28,29,30]. For instance, the A504D mutation has been identified at low frequency in Colombia [31], reinforcing the need for sustained genomic surveillance to determine its potential impact on drug efficacy. Detecting these mutations underscores the risk of resistance spreading across borders, mainly due to migration driven by illegal gold mining between Guyana, Brazil, and Venezuela [29,32]. This highlights the need for enhanced regional surveillance and coordinated monitoring to prevent the spread of ARTR P. falciparum strains in the Amazon basin.
Likewise, the pfcrt mutation K76T, commonly linked with other non-synonymous mutations at codons 72, 74, or 75, acts as the primary mediator of CQR [33]. Our analysis revealed a high prevalence of mutations in pfcrt codons 72–76, with the SVMNT haplotype present in 96% of isolates, aligning with previous studies in the Amazon Basin [16]. A greater prevalence of CQ-sensitive parasites was expected in Brazil, where CQ has not been utilized to treat uncomplicated falciparum malaria since the 1980s. However, the continued use of CQ for treating P. vivax malaria likely exerts selective pressure, contributing to the persistence of CQ-resistant P. falciparum populations [34,35]. Genetic diversity analysis further emphasized this ongoing selective pressure, revealing that pfcrt displayed the most variability, particularly in exon 2 (π = 0.00182; θ = 0.00249). In contrast, regions of Africa—where P. falciparum accounts for over 90% of malaria cases—have experienced significant declines in resistance due to reduced drug pressure, as CQ use has been restricted or considerably diminished [36].
We investigated mutations in exon 10 of the pfcrt gene (M343L, C350R, G353V, and I356T). All these mutations were absent in Brazilian samples, including pfcrt C350R, a key marker of CQ phenotypic reversion, and I356T, which is strongly associated with ART-R in Southeast Asia [30,37]. Instead, we detected a different substitution at this locus, I356L, in 40% of isolates. This mutation is commonly found in Latin America and seems more closely related to resistance against other antimalarials, such as CQ [17,38,39]. The absence of these key mutations, likely influenced by local drug usage patterns, contrasts with regions where piperaquine is commonly used and reflects the persistence of CQR in Brazilian isolates without phenotypic reversion.
The pfmdr1 polymorphisms, including point mutations and gene amplification, affect P. falciparum’s sensitivity to several antimalarial drugs [18,40]. Our study found a high prevalence of the S1034C, N1042D, and D1246Y SNPs, with the NYCDY haplotype detected in 70% of the samples. This finding aligns with previous research from our team [26] and other studies in Brazil [35,41], suggesting that these resistance alleles may be approaching fixation. The N86Y mutation, linked to an increased susceptibility to MQ, LM, and DHA, as well as elevated resistance to CQ [18,19,20], was observed at a low frequency (4%). On the other hand, the Y184F mutation, associated with diminished LM sensitivity [19,40], was not present. These results aligned with earlier Brazilian reports, which showed low or absent frequencies of these mutations and may imply a reduced parasite susceptibility to AM–LM, MQ, and DHA [34,35].
The combined allelic distributions of pfk13, pfcrt, and pfmdr1 among P. falciparum isolates revealed 11 distinct haplotype profiles. The wild-type pfk13, SVMNTMCGL pfcrt, and NYCDY pfmdr1 were the most prevalent haplotypes. Even though all isolates contained the wild-type pfk13, its association with pfcrt (76T) and pfmdr1 (86N, 184F, 1246D) mutations may contribute to drug resistance [20,21]. These mutations are particularly notorious in African regions, where specific haplotypes, such as SVMNT + NFCDD, have been linked to recurrent parasitemia and treatment failure following AM–LM therapy [20,21]. However, in this study, neither the SVMNT + NFCDD haplotype nor the SVMNT + YYY haplotype—typically associated with AS–AQ and CQ use [21,22]—was detected. These findings were further supported by the absence of recrudescence among patients with available follow-up at CPD-Mal and among those recorded in the SIVEP-Malaria system.
The absence of high-risk haplotypes indicated that current treatment regimens may limit their spread within the studied population. However, clinical efficacy, shown by the lack of recrudescence, does not eliminate the ongoing selection of resistant alleles. The presence of known resistance-associated mutations, primarily the pfcrt 76T and pfmdr1 variants, suggested that the potential for resistance remains, especially if drug pressure continues. This finding was further supported by the genetic diversity analysis, which revealed distinct variation patterns among the three resistance-associated genes. The high nucleotide diversity (π = 0.00182, θ = 0.00249) and haplotype diversity (Hd = 0.146) observed in exon 2 of pfcrt indicated significant genetic differentiation, likely driven by prolonged CQ usage. In contrast, pfmdr1 exhibited a varied diversity pattern, showing minimal variation in its initial region (π = 0.00012; Hd = 0.068) and increased diversity in its terminal region (π = 0.00112; Hd = 0.483), suggesting localized adaptation likely influenced by drug pressure. This variation was also noted in samples from Africa and India [42,43].
The lack of polymorphisms in pfk13 was a significant finding, confirming the absence of ART-R-associated mutations in the analyzed Brazilian samples. This result aligned with the relatively low prevalence of ART-R observed outside South America [28,44]. The neutrality tests further clarified the selection dynamics influencing these resistance-associated loci. Negative Tajima’s D values for exon 2 of pfcrt (−0.39181) and the initial region of pfmdr1 (−0.66673) indicated positive selection and the potential fixation of resistant variants, promoting the expansion of alleles related to drug resistance. In contrast, positive Tajima’s D values for exon 10 of pfcrt (1.72185) and the terminal region of pfmdr1 (1.58461) suggested balancing selection, likely influenced by varying drug pressure, which preserves both resistant and sensitive alleles within the parasite population. This was further supported by positive Fu and Li’s D* and F* test values in the same regions, confirming evidence of ongoing selection pressure.
LD analysis is a molecular tool for identifying non-random associations among resistance markers, providing essential insights into the evolutionary pathways of drug-resistant haplotypes and their potential spread. Our LD analysis revealed significant intragenic associations between the C72S and K76T codons in pfcrt and between the 1034C and 1042D codons in pfmdr1, indicating coordinated selection within each gene. However, no significant intergenic associations were found, suggesting that the resistance mechanisms involving pfcrt and pfmdr1 function independently and are affected by distinct selective pressures. These findings correspond with global studies emphasizing the critical role of intragenic associations in the persistence and evolution of drug-resistant populations [27,28,32].
The prevalence of the NYCDY haplotype in pfmdr1 and the high frequency of pfcrt mutations indicated that selective pressure from ACT regimens, particularly AM–LM, continues to influence resistance dynamics and may contribute to the stabilization of these haplotypes within the parasite population. These findings underscore the need to integrate genetic surveillance into malaria control strategies, enabling the early detection of emerging resistance and guiding evidence-based treatment adjustments. Optimizing ACT allocation and strategically implementing alternative therapies in high-risk areas could be essential for maintaining treatment efficacy and mitigating the spread of resistance.
This study presented some limitations. Firstly, although all patients who attended at CPD-Mal were clinically and laboratory followed up, this study focused exclusively on the molecular markers of drug resistance without assessing the in vitro susceptibility of the parasites to antimalarial drugs. Second, while this study provided a comprehensive analysis of genetic markers, it did not include clinical data on treatment outcomes or parasite clearance rates. Third, although this study spanned a decade (2013–2023), no temporal trend analysis was conducted to assess the evolution of resistance markers over time. Fourth, the samples analyzed were collected from multiple endemic regions in Brazil; however, regional variations in the prevalence of resistance markers were not thoroughly explored.
In addition to monitoring established resistance markers, future studies should prioritize examining emerging genes, such as pfcoronin and the beta-propeller (BTB) domain of pfk13. Recent findings have linked mutations in pfcoronin to ART resistance in Southeast Asia, highlighting its potential role in the survival of parasites under drug pressure [45]. Similarly, the BTB domain of pfk13, known for facilitating protein–protein interactions, may provide valuable insights into the underlying mechanisms of resistance [46]. By concentrating on these novel targets, we can refine treatment strategies, ensuring the sustained efficacy of ACTs in combating malaria.

4. Materials and Methods

4.1. Blood Samples and Study Areas

Between 2013 and 2023, a total of 141 blood samples were collected from symptomatic patients diagnosed with P. falciparum infection (Figure 2). Of these, 30 samples were obtained from patients treated at the Acute Febrile Syndrome Outpatient Clinic of the Evandro Chagas National Institute of Infectious Diseases (INI-Fiocruz) in Rio de Janeiro, a member of the Reference Center for Research, Diagnosis, and Training of Malaria (CPD-Mal/Fiocruz) for the extra-Amazonian region (22°54′ S, 43°12′ W), led by the Malaria Research Laboratory. These CPD-Mal samples were distributed across six Brazilian states: Amazonas (twenty-three samples, including two from Barcelos in 2013 and 2016; six from Manaus in 2014, 2017, 2022, and 2023; fourteen from São Gabriel da Cachoeira between 2019 and 2023; and one from Tefé in 2014), Pará (three samples from Santarém in 2023), Rondônia (two samples from Itapuã do Oeste in 2014 and 2023), and Roraima (two samples from Boa Vista in 2022). All CPD-Mal patients were monitored for treatment outcomes, including parasite clearance rates, clinical progression, and molecular diagnosis [47,48,49,50], as per the guidelines established by the Brazilian Ministry of Health [4]. If the patients returned, they were evaluated on days 0, 1, 2, 3, 7, 14, 28, and 42; if symptoms appeared, they were assessed at any time during the follow-up period.
In addition to the CPD-Mal samples, 111 blood samples were collected from malaria-endemic regions across Brazil. In Amazonas, 23 samples were obtained, seven from Manaus (6 in 2013 and 1 in 2014) and 16 from Guajará in 2016. In Acre, 55 samples were collected, including 30 from Cruzeiro do Sul (20 in 2016 and 10 in 2018) and 25 from Mâncio Lima (12 in 2016 and 13 in 2018). In Roraima, 33 samples were obtained from Boa Vista, with 5 in 2016, 12 in 2021, and 16 in 2022. In Amapá, a single sample was collected from Macapá in 2019.

4.2. Ethical Aspects and Consent to Participate

The study protocol was approved by the Ethics and Research Committee for Research Involving Human Beings at Fiocruz (CAAE 88554718.0.3002.5248 and CAAE 46084015.1.0000.5248 for the Acre samples). Additionally, the Boa Vista samples were approved by the Research Ethics Committee of the Federal University of Roraima (CEP/UFRR) under CAAE 24122619.6.0000.5302.
All participants were thoroughly informed about the study protocols and procedures to ensure their understanding. Informed consent was obtained from each participant, either in writing or via thumbprint for those unable to sign, allowing the use of remnant blood samples. All study procedures strictly adhered to the federal regulations mandated by the Brazilian Ministry of Health.

4.3. Malaria Diagnosis and Nucleic Acid Extraction

The diagnosis of P. falciparum was initially performed on-site using light microscopy with a thick blood smear, regardless of the blood collection location. To confirm P. falciparum mono-infection, all samples underwent nucleic acid extraction and molecular diagnosis via polymerase chain reaction (PCR). For DNA extraction, 1 mL of the blood samples was processed and purified using the QIAamp® DNA Mini kit, following the manufacturer’s instructions (Qiagen, Hilden, Germany). The extracted DNA was stored at −20 °C until PCR testing. Both conventional and real-time PCR assays were conducted using Plasmodium-specific primers [47]. Positive samples underwent further analysis with species-specific single or nested PCRs to detect P. vivax [48], P. falciparum [49], and/or P. malariae [50].
All samples were stored at the Malaria Research Laboratory (LPM) at Instituto Oswaldo Cruz (IOC), which serves as the headquarters for the Reference Center for Malaria Treatment and Diagnosis (CPD-Mal/Fiocruz). This study included only patients confirmed to have mono-infections of P. falciparum.

4.4. Gene Amplification and DNA Sequencing

Gene amplifications were conducted for pfk13, pfmdr1, and pfcrt. For pfk13, fragments of approximately 859 base pairs (bp) were amplified following the standard protocol [13]. Two fragments of the pfcrt gene were amplified: the first fragment, 145 bp, included exon 2 and covered positions 72–76, according to the protocol described by Zhou et al. (2016) [33]; the second fragment, 339 bp, included exon 10 and covered positions M343L, C350R, G353V, and I356T/L, as described by Foguim et al. (2020) [37]. For pfmdr1, amplification was carried out in two parts: a 501 bp fragment from the initial (start) region was amplified to analyze the SNPs N86Y and Y184F. Conversely, a 935 bp fragment from the terminal (end) region was used to assess the SNPs S1034C, N1042D, and D1246Y, following the previously described method [26]. The PCR products were analyzed using electrophoresis on a 2% agarose gel and visualized under a UV transilluminator (DigiDoc-It, UVP, Upland, CA, USA). Each PCR product was purified using the Wizard™ SV Gel and PCR Clean-Up System (Promega, Madison, WI, USA), following the manufacturer’s instructions. DNA sequencing was performed using the Big Dye™ Terminator Cycle Sequencing Ready Reaction version 3.1 (Applied Biosystems, Foster, CA, USA), with 3.2 μM of the forward and reverse PCR primers. DNA sequences were determined using the ABI Prism DNA Analyzer™ 3730 (Applied Biosystems, Foster, CA, USA) at the Fiocruz Genomic Platform PDTIS/Fiocruz RPT01A.

4.5. Data Analysis

Multiple nucleotide sequences were aligned using ClustalW within the free software BioEdit® version 7.7.1 (North Carolina State University, Raleigh, NC, USA [51]). All mutations were assessed by comparing each sequence to the PF3D7_0709000 (pfcrt), PF3D7_0523000 (pfmdr1), and PF3D7_1343700 (pfk13) from PlasmoDB (http://www.plasmodb.org, accessed on 22 February 2025). The nucleotide sequences and their corresponding deduced amino acid sequences for each antimalarial drug resistance gene were further analyzed to detect polymorphisms and were compared to known resistance-associated mutations. Each haplotype’s allele frequencies and prevalence were estimated by the number of isolates carrying the specific haplotype and the total samples with successful sequencing.
All DNA sequences generated in this study have been deposited in the GenBank™ database (NIH genetic sequence database; www.ncbi.nlm.nih.gov/GenBank, accessed on 22 February 2025). The sequences for pfk13 (PP584057–PP584104; PV172739–PV172845), pfcrt (exon 2: OQ672386–OQ672451 and PV172664–PV172738; exon 10: PV289785–PV289925), and pfmdr1 (initial region: PV172846–PV172986; terminal region: PV605939–PV606079) are accessible under their respective accession numbers.
Genetic parameters such as haplotype diversity (Hd), nucleotide diversities, and the measures of neutrality (Tajima’s D, Fu and Li’s D*, and Fu and Li’s F*) were computed by DnaSP 6.12 [52]. In addition, intergenic and intragenic LD tests were performed by calculating the r2 values to determine the association between the SNPs of the three genes investigated using Haploview 4.1 software [53].

5. Conclusions

This study provided an updated overview of Brazil’s key indicators of P. falciparum resistance. The absence of pfk13 resistance-associated mutations and the low prevalence of critical pfmdr1 markers (N86Y and Y184F) supported the sustained efficacy of ACTs. The high frequency of pfcrt mutations and the dominance of the pfmdr1 NYCDY haplotype suggested ongoing selective pressure and allele fixation driven by positive selection. The independent evolutionary paths of pfcrt and pfmdr1 highlighted their distinct roles in drug resistance. The persistence of diverse haplotypes and intragenic linkage disequilibrium indicated that there has been continuous drug pressure. Additional studies, including in vitro susceptibility assays, could yield new insights into this topic. Ongoing genomic surveillance is crucial for tracking emerging resistance and informing adaptive, region-specific treatment strategies to maintain effective malaria control and delay the development of resistance.

Author Contributions

Conceptualization: M.d.F.F.-d.-C.; supervision: M.d.F.F.-d.-C.; methodology: R.d.A.-F., L.T.d.Q., A.R.d.L.M. and M.d.F.F.-d.-C.; epidemiological survey: L.R.P.-R. and P.B.; formal analysis: R.d.A.-F., N.K.A.-d.-O., L.T.d.Q., J.d.A.B. and M.d.F.F.-d.-C.; investigation: M.d.F.F.-d.-C. and C.T.D.-R.; resources: R.d.A.-F. and M.d.F.F.-d.-C.; original draft preparation: R.d.A.-F.; writing—review: M.d.F.F.-d.-C., C.T.D.-R., L.R.P.-R., G.C.d.M., P.B. and D.M.; editing: R.d.A.-F.; project administration: M.d.F.F.-d.-C.; funding acquisition: M.d.F.F.-d.-C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; http://www.cnpq.br/, accessed on 10 March 2022) through Research Productivity Fellowships to C.T.D.-R. (310445/2017-5), M.d.F.F.-d.-C. (306025/2018-3), P.B. (311562/2021-3) that are also Cientistas do Nosso Estado (C.T.D.-R.—E-26/202.921/2018; M.d.F.F.-d.-C.—E-26/203.295/2015 and P.B.—E-26/200.925/2022) of the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado de Rio de Janeiro (FAPERJ; http://www.faperj.br/, accessed on 10 March 2022). This work was also supported by the Programa Nacional de Controle e Prevenção da Malária/Secretaria de Vigilância em Saúde/Ministério da Saúde (SVS/MS) and Fiocruz (Grant Number: 026-FIO-18-2-1). The Laboratório de Pesquisa em Malária (LPM-IOC, Fiocruz) is an Associate Laboratory of the Instituto Nacional de Ciência e Tecnologia em Neuroimunomodulação of the CNPq (INCT-NIM/CNPq Project 465489/2014-1) and of the Rede de Neuroinflamação da Faperj (Redes/Faperj, Project 26010.002418/2019).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study. Written informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

Data supporting the conclusions of this article are included within the article. The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

Acknowledgments

We would like to thank all the patients for their participation in this study. We would also to acknowledge the staff from the Genomic Platform for DNA sequencing facilities RPT01A/PDTIS/Fiocruz and the Coordenação de Vigilância em Saúde e Laboratórios de Referencia, Fiocruz/Coordination of Health Surveillance and Reference Laboratories for financial and logistical support. All authors have approved the final manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Ijms 26 05977 g001
Figure 1. LD plot between SNPs of the pfcrt and pfmdr1 genes in P. falciparum isolates from the Brazilian endemic areas. Each diamond represents the r2 value between two SNPs, and darker shades indicate stronger LD (r2 values closer to 1 reflect stronger linkage).
Figure 1. LD plot between SNPs of the pfcrt and pfmdr1 genes in P. falciparum isolates from the Brazilian endemic areas. Each diamond represents the r2 value between two SNPs, and darker shades indicate stronger LD (r2 values closer to 1 reflect stronger linkage).
Ijms 26 05977 g001
Ijms 26 05977 g002
Figure 2. The spatial distribution of malaria cases is classified as the following: from the Reference Center for Research, Diagnosis, and Training of Malaria in non-endemic areas (CPD-Mal) or from the endemic Brazilian regions (non-CPD-Mal). The size of the circles represents the number of samples from each municipality. Green-shaded areas indicate the locations of infection.
Figure 2. The spatial distribution of malaria cases is classified as the following: from the Reference Center for Research, Diagnosis, and Training of Malaria in non-endemic areas (CPD-Mal) or from the endemic Brazilian regions (non-CPD-Mal). The size of the circles represents the number of samples from each municipality. Green-shaded areas indicate the locations of infection.
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Table 1. Prevalence of pfcrt wild-type and mutant haplotypes in study areas.
Table 1. Prevalence of pfcrt wild-type and mutant haplotypes in study areas.
Genotype 1Samples N(%)Brazilian States
AcreAmazonasAmapáRoraimaRondôniaPará
(55 s)(46 s)(1 s)(34 s )(2 s) (3 s)
SVMNTMCGI 283 (59)44271722
SVMNTMCGL 356 (40)111702701
CVMNKMCGI 42 (1)020000
1 The bold and underlined characters represent a non-synonymous mutation. 2 S: codon 72; T: codon 76. 3 S: codon 72; T: codon 76; L: codon 356. 4 Reference Pf3D7 wild haplotype sequence; s = number of samples.
Table 2. Prevalence of pfmdr1 wild-type and mutant haplotypes, according to Brazilian states.
Table 2. Prevalence of pfmdr1 wild-type and mutant haplotypes, according to Brazilian states.
Genotype 1Number of Isolates (%)Brazilian States
AcreAmazonasAmapáRoraimaRondôniaPará
(n = 55)(n = 46)(n = 1)(n = 34)(n = 2)(n = 3)
NYCDD16 (11)1240000
NYCDY 298 (70)352713113
NYSND 319 (13)890200
NYSNY 43 (2)020010
YYSND 55 (4)04 01 00
1 The bold and underlined characters represent a non-synonymous mutation. 2 C: codon 1034; D: codon 1042; Y: codon 1246. 3 Reference Pf3D7 wild haplotype sequence. 4 Y: codon 1246. 5 Y: codon 86.
Table 3. Distributions of pfk13, pfcrt, and pfmdr1 combination alleles among 141 P. falciparum isolates from Brazilian endemic area.
Table 3. Distributions of pfk13, pfcrt, and pfmdr1 combination alleles among 141 P. falciparum isolates from Brazilian endemic area.
Haplotypes 1Combination TypeSamples
N (%)
pfk13pfcrtpfmdr1
Wild-type 2 +SVMNTMCGL+NYCDDQuintuple5 (4)
NYCDYSextuple44 (31)
NYSNDTriple5 (4)
YYSNDQuadruple2 (1)
Wild-type 2 +SVMNTMCGI+NYCDDQuadruple10 (7)
NYCDYQuintuple54 (38)
NYSNDDouble13 (9)
NYSNYTriple3 (2)
YYSNDTriple3 (2)
Wild-type 2 +CVMNKMCGI 2 +NYCDDDouble1 (1)
NYSND2Wild1 (1)
1 The bold and underlined characters represent a non-synonymous mutation. 2 Reference Pf3D7 wild haplotype sequence. “+” indicates the co-occurrence of specific allelic variants in pfk13, pfcrt, and pfmdr1 within the same P. falciparum isolate, representing a multilocus haplotype.
Table 4. Genetic diversity parameters of pfcrt, pfmdr1, and pfk13 genes.
Table 4. Genetic diversity parameters of pfcrt, pfmdr1, and pfk13 genes.
Parameters pfcrtpfmdr1pfk13
Exon 2Exon 10Initial RegionTerminal RegionHelix Domain
SNPs (n) 22130
Haplotypes (n) 32241
Nucleotide diversityπ0.001820.001650.000120.001120
θ0.002490.000630.000330.000580
Haplotype diversity 0.1460.4710.0680.4830
Variance Hd 0.001520.000450.000830.001840
SD Hd 0.0390.0210.0290.0430
Neutrality Tests
Tajima’s D −0.391811.72185−0.666731.584610
Fu and Li D * 0.659450.47190.47190.798310
Fu and Li F * 0.387270.99920.14511.23740
π: Pi; θ: Theta; Variance Hd: variance of the haplotype diversity; SD Hd: standard deviation of the haplotype diversity. For the neutrality tests, the p-value was >0.10 for all genes. * Fu and Li’s D and F* statistics were calculated using an outgroup sequence.
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de Abreu-Fernandes, R.; de Queiroz, L.T.; Almeida-de-Oliveira, N.K.; de Lavigne Mello, A.R.; de Aguiar Barros, J.; Pratt-Riccio, L.R.; Melo, G.C.d.; Brasil, P.; Daniel-Ribeiro, C.T.; Menard, D.; et al. Tracking Drug Resistance in Plasmodium falciparum: Genetic Diversity of Key Resistance Markers in Brazilian Malaria Hotspots. Int. J. Mol. Sci. 2025, 26, 5977. https://doi.org/10.3390/ijms26135977

AMA Style

de Abreu-Fernandes R, de Queiroz LT, Almeida-de-Oliveira NK, de Lavigne Mello AR, de Aguiar Barros J, Pratt-Riccio LR, Melo GCd, Brasil P, Daniel-Ribeiro CT, Menard D, et al. Tracking Drug Resistance in Plasmodium falciparum: Genetic Diversity of Key Resistance Markers in Brazilian Malaria Hotspots. International Journal of Molecular Sciences. 2025; 26(13):5977. https://doi.org/10.3390/ijms26135977

Chicago/Turabian Style

de Abreu-Fernandes, Rebecca, Lucas Tavares de Queiroz, Natália Ketrin Almeida-de-Oliveira, Aline Rosa de Lavigne Mello, Jacqueline de Aguiar Barros, Lilian Rose Pratt-Riccio, Gisely Cardoso de Melo, Patrícia Brasil, Cláudio Tadeu Daniel-Ribeiro, Didier Menard, and et al. 2025. "Tracking Drug Resistance in Plasmodium falciparum: Genetic Diversity of Key Resistance Markers in Brazilian Malaria Hotspots" International Journal of Molecular Sciences 26, no. 13: 5977. https://doi.org/10.3390/ijms26135977

APA Style

de Abreu-Fernandes, R., de Queiroz, L. T., Almeida-de-Oliveira, N. K., de Lavigne Mello, A. R., de Aguiar Barros, J., Pratt-Riccio, L. R., Melo, G. C. d., Brasil, P., Daniel-Ribeiro, C. T., Menard, D., & Ferreira-da-Cruz, M. d. F. (2025). Tracking Drug Resistance in Plasmodium falciparum: Genetic Diversity of Key Resistance Markers in Brazilian Malaria Hotspots. International Journal of Molecular Sciences, 26(13), 5977. https://doi.org/10.3390/ijms26135977

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