Dataset Information

Molecular assessment of kelch13 non-synonymous mutations in Plasmodium falciparum isolates from Central African Republic (2017-2019).

ABSTRACT:

Background

Over the last decade, artemisinin-based combination therapy (ACT) has contributed substantially to the decrease in malaria-related morbidity and mortality. The emergence of Plasmodium falciparum parasites resistant to artemisinin derivatives in Southeast Asia and the risk of their spread or of local emergence in sub-Saharan Africa are a major threat to public health. This study thus set out to estimate the proportion of P. falciparum isolates, with Pfkelch13 gene mutations associated with artemisinin resistance previously detected in Southeast Asia.

Methods

Blood samples were collected in two sites of Bangui, the capital of the Central African Republic (CAR) from 2017 to 2019. DNA was extracted and nested PCR were carried out to detect Plasmodium species and mutations in the propeller domain of the Pfkelch13 gene for P. falciparum samples.

Results

A total of 255 P. falciparum samples were analysed. Plasmodium ovale DNA was found in four samples (1.57%, 4/255). Among the 187 samples with interpretable Pfkelch13 sequences, four samples presented a mutation (2.1%, 4/187), including one non-synonymous mutation (Y653N) (0.5%, 1/187). This mutation has never been described as associated with artemisinin resistance in Southeast Asia and its in vitro phenotype is unknown.

Conclusion

This preliminary study indicates the absence of Pfkelch13 mutant associated with artemisinin resistance in Bangui. However, this limited study needs to be extended by collecting samples across the whole country along with the evaluation of in vitro and in vivo phenotype profiles of Pfkelch13 mutant parasites to estimate the risk of artemisinin resistance in the CAR.

SUBMITTER: Nzoumbou-Boko R

PROVIDER: S-EPMC7247190 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Molecular assessment of kelch13 non-synonymous mutations in Plasmodium falciparum isolates from Central African Republic (2017-2019).

Nzoumbou-Boko Romaric R Panté-Wockama Chris-Boris Gildas CG Ngoagoni Carine C Petiot Nathalie N Legrand Eric E Vickos Ulrich U Gody Jean-Chrysostome JC Manirakiza Alexandre A Ndoua Christophe C Lombart Jean-Pierre JP Ménard Didier D

Malaria journal 20200524 1

<h4>Background</h4>Over the last decade, artemisinin-based combination therapy (ACT) has contributed substantially to the decrease in malaria-related morbidity and mortality. The emergence of Plasmodium falciparum parasites resistant to artemisinin derivatives in Southeast Asia and the risk of their spread or of local emergence in sub-Saharan Africa are a major threat to public health. This study thus set out to estimate the proportion of P. falciparum isolates, with Pfkelch13 gene mutations ass ...[more]

PMID: 32448203

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Project description:Since several malaria parasite species are usually present in a particular area, co-infections with more than one species of Plasmodium are more likely to occur in humans infected in these areas. In many mixed infections, parasite densities of the cryptic species may be low and often not recognized in clinical practice.Two children (3 and 6 years old) adopted recently from Central African Republic were admitted to hospital because of intermittent fever. Thin blood smears stained with Giemsa showed Plasmodium falciparum and Plasmodium malariae co-infection for both children at admission. They were both treated with atovaquone-proguanil combination for 3 days. At day 7, both thin blood smears examination remained negative but at day 28, thin blood smear was positive for P. malariae trophozoites and for Plasmodium ovale for the girl and her brother, respectively. Samples collected at day 1 and day 28 were submitted to real-time PCR showing the presence of the three parasite species (P. falciparum, P malariae and P. ovale) in admission blood samples from the two children and only P. ovale at day 28.Twenty-eight days follow-up after treatment led to detection of a third parasite species in the blood of these two patients suggesting covert co-infection and a delayed appearance of one cryptic species following treatment. Concurrently infecting malaria species could be mutually suppressive, with P. falciparum tending to dominate other species. These observations provide more evidence that recommendations for treatment of imported malaria should take into account the risk of concurrent or cryptic infection with Plasmodium species. Clinicians and biologists should be aware of the underestimated frequency of mixed infections with cryptic species and of the importance of patient follow-up at day 28. Future guidelines should shed more light on the treatment of mixed infection and on the interest of using artemisinin-based combinations for falciparum and non-falciparum species.

Project description:IntroductionDrug resistance remains a major challenge in malaria treatment, especially after the emergence of resistance to artemisinin-based combined therapies. Plasmodium falciparum Kelch13 gene mutations are implicated in conferring artemisinin resistance. Thus, this study was aimed at determining the occurrence of Kelch13 (K13) propeller resistance gene polymorphism mutations in Bushenyi district, Uganda.MethodsParticipants suspected to have malaria were recruited. P. falciparum was confirmed using antigen histidine-rich protein 2 (HRP2) (Pf) (Access Bio, Inc, USA) and microscopy. Malaria-positive patients were treated with artemeter-lumefantrine (AL). Blood was withdrawn from participants who tested positive for parasites after day 3 and kept in blood filter papers (ET31CHR; Whatman Limited, Kent, UK). DNA was extracted using chelex-suspension method. Nested polymerase chain reaction (PCR) was conducted and the second-round products sequenced using Sanger's method. Sequenced products were analyzed using DNAsp 5.10.01 software and then blasted on to the NCBI for K13-propeller gene sequence identity using the Basic Local Alignment Search Tool (BLAST).ResultsOut of 283 enrolled participants, 194 completed the follow-up schedule. A total of 134 (69%) had no parasites on day 3, while 60 (31%) had parasites on that day. Out of the 60 samples, 40 (62%) were positively amplified as P. falciparum, with polymorphisms in the K13-propeller gene detected in 3 (7.5%) out of the 40 amplicons. Polymorphisms at codon 1929, 1788 and 1801 were detected separately in one sample each. Sequences have been deposited in NCBI with accession numbers PRJNA720348 and PRJNA720800.ConclusionPolymorphisms in the K13-propeller gene previously reported to be associated with artemisinin resistance were not detected in the P. falciparum isolates from Bushenyi district, Uganda. More studies need to be conducted on the new mutations detected so as to understand their association, if any, with ACT resistance.

Project description:BackgroundCurrent malaria control and elimination strategies rely mainly on efficacious antimalarial drugs. However, drug resistance is a major threat facing malaria control programs. Determination of drug resistance molecular markers is useful in the monitoring and surveillance of malaria drug efficacy. This study aimed to determine the mutations and haplotypes frequencies of different genes linked with antimalarial drug resistance in certain areas in Sudan.MethodsA total of 226 dried blood spots (DBS) of microscopically diagnosed P. falciparum isolates were collected from Khartoum and three other areas in Sudan during 2015-2017. Plasmodium falciparum confirmation and multiplicity of infection was assessed using the Sanger's 101 SNPs-barcode and speciation was confirmed using regions of the parasite mitochondria. Molecular genotyping of drug resistance genes (Pfcrt, Pfmdr1, Pfdhfr, Pfdhps, exonuclease, Pfk13, parasite genetic background (PGB) (Pfarps10, ferredoxin, Pfcrt, Pfmdr2)) was also performed. All genotypes were generated by selective regions amplicon sequencing of the parasite genome using the Illumina MiSeq platform at the Wellcome Sanger Institute, UK then genotypes were translated into drug resistance haplotypes and species determination.FindingsIn total 225 samples were confirmed to be P. falciparum. A higher proportion of multiplicity of infection was observed in Gezira (P<0.001) based on the Sanger 101 SNPs -barcode. The overall frequency of mutant haplotype Pfcrt 72-76 CVIET was 71.8%. For Pfmdr1, N86Y was detected in 53.6%, Y184F was observed in 88.1% and D1246Y was detected in 1.5% of the samples. The most frequently observed haplotype was YFD 47.4%. For Pfdhfr (codons 51, 59,108,164), the ICNI haplotype was the most frequent (80.7%) while for Pfdhps (codons 436, 437, 540, 581, 613) the (SGEAA) was most frequent haplotype (41%). The Quadruple mutation (dhfr N51I, S108N + dhps A437G, K540E) was the highest frequent combined mutation (33.9%). In Pfkelch13 gene, 18 non-synonymous mutations were detected, 7 of them were detected in other African countries. The most frequent Pfk13 mutation was E433D detected in four samples. All of the Pfk13 mutant alleles have not been reported to belong to mutations associated with delayed parasite clearance in Southeast Asia. PGB mutations were detected only in Pfcrt N326S\I (46.3%) and Pfcrt I356T (8.2%). The exonuclease mutation was not detected. There was no significant variation in mutant haplotypes between study areas.ConclusionsThere was high frequency of mutations in Pfcrt, Pfdhfr and Pfdhps in this study. These mutations are associated with chloroquine and sulfadoxine-pyrimethamine (SP) resistance. Many SNPs in Pfk13 not linked with delayed parasite clearance were observed. The exonuclease E415G mutation which is linked with piperaquine resistance was not reported.

Project description:BackgroundThe devastating public health impact of malaria has prompted the need for effective interventions. Malaria control gained traction after the introduction of artemisinin-based combination therapy (ACT). However, the emergence of artemisinin (ART) partial resistance in Southeast Asia and emerging reports of delayed parasite sensitivity to ACT in African parasites signal a gradual trend towards treatment failure. Monitoring the prevalence of mutations associated with artemisinin resistance in African populations is necessary to stop resistance in its tracks. Mutations in Plasmodium falciparum genes pfk13, pfcoronin and pfatpase6 have been linked with ART partial resistance.MethodsFindings from published research articles on the prevalence of pfk13, pfcoronin and pfatpase6 polymorphisms in Africa were collated. PubMed, Embase and Google Scholar were searched for relevant articles reporting polymorphisms in these genes across Africa from 2014 to August 2021, for pfk13 and pfcoronin. For pfatpase6, relevant articles between 2003 and August 2021 were retrieved.ResultsEighty-seven studies passed the inclusion criteria for this analysis and reported 742 single nucleotide polymorphisms in 37,864 P. falciparum isolates from 29 African countries. Five validated-pfk13 partial resistance markers were identified in Africa: R561H in Rwanda and Tanzania, M476I in Tanzania, F446I in Mali, C580Y in Ghana, and P553L in an Angolan isolate. In Tanzania, three (L263E, E431K, S769N) of the four mutations (L263E, E431K, A623E, S769N) in pfatpase6 gene associated with high in vitro IC50 were reported. pfcoronin polymorphisms were reported in Senegal, Gabon, Ghana, Kenya, and Congo, with P76S being the most prevalent mutation.ConclusionsThis meta-analysis provides an overview of the prevalence 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 across the continent.

Dataset Information

Molecular assessment of kelch13 non-synonymous mutations in Plasmodium falciparum isolates from Central African Republic (2017-2019).

Background

Methods

Results

Conclusion

Publications

Molecular assessment of kelch13 non-synonymous mutations in Plasmodium falciparum isolates from Central African Republic (2017-2019).

Similar Datasets

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