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Record W4229002976 · doi:10.1371/journal.pone.0268095

Prevalence of arps10, fd, pfmdr-2, pfcrt and pfkelch13 gene mutations in Plasmodium falciparum parasite population in Uganda

2022· article· en· W4229002976 on OpenAlexfundno aff
Fred K. Ashaba, Savannah Mwesigwa, Edgar Kigozi, Moses R. Kamya, Samuel L. Nsobya

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of Dental and Craniofacial ResearchNational Institute of Neurological Disorders and StrokeInternational Development Research CentreNational Heart, Lung, and Blood InstituteFogarty International CenterNational Institutes of Health
KeywordsPlasmodium falciparumBiologyApicoplastMalariaArtemether/lumefantrineSingle-nucleotide polymorphismPopulationSanger sequencingHigh Resolution MeltGeneticsGenotypeVirologyArtemisininParasite hostingArtesunateDNA sequencingGeneMedicineApicomplexaImmunology

Abstract

fetched live from OpenAlex

In Uganda, Artemether-Lumefantrine and Artesunate are recommended for uncomplicated and severe malaria respectively, but are currently threatened by parasite resistance. Genetic and epigenetic factors play a role in predisposing Plasmodium falciparum parasites to acquiring Pfkelch13 (K13) mutations associated with delayed artemisinin parasite clearance as reported in Southeast Asia. In this study, we report on the prevalence of mutations in the K13, pfmdr-2 (P. falciparum multidrug resistance protein 2), fd (ferredoxin), pfcrt (P. falciparum chloroquine resistance transporter), and arps10 (apicoplast ribosomal protein S10) genes in Plasmodium falciparum parasites prior to (2005) and after (2013) introduction of artemisinin combination therapies for malaria treatment in Uganda. A total of 200 P. falciparum parasite DNA samples were screened. Parasite DNA was extracted using QIAamp DNA mini kit (Qiagen, GmbH, Germany) procedure. The PCR products were sequenced using Sanger dideoxy sequencing method. Of the 200 P. falciparum DNA samples screened, sequencing for mutations in K13, pfmdr-2, fd, pfcrt, arps10 genes was successful in 142, 186, 141, 128 and 74 samples respectively. Overall, we detected six (4.2%, 6/142; 95%CI: 1.4-7.0) K13 single nucleotide polymorphisms (SNPs), of which 3.9% (2/51), 4.4% (4/91) occurred in 2005 and 2013 samples respectively. All four K13 SNPs in 2013 samples were non-synonymous (A578S, E596V, S600C and E643K) while of the two SNPs in 2005 samples, one (Y588N) is non-synonymous and the other (I587I) is synonymous. There was no statistically significant difference in the prevalence of K13 (p = 0.112) SNPs in the samples collected in 2005 and 2013. The overall prevalence of SNPs in pfmdr-2 gene was 39.8% (74/186, 95%CI: 25.1-50.4). Of this, 4.2% (4/95), 76.9% (70/91) occurred in 2005 and 2013 samples respectively. In 2005 samples only one SNP, Y423F (4.2%, 4/95) was found while in 2013, Y423F (38.5%, 35/91) and I492V (38.5%, 35/91) SNPs in the pfmdr-2 gene were found. There was a statistically significant difference in the prevalence of pfmdr-2 SNPs in the samples collected in 2005 and 2013 (p<0.001). The overall prevalence of arps10 mutations was 2.7% (2/72, 95%CI: 0.3-4.2). Two mutations, V127M (4.5%: 1/22) and D128H (4.5%: 1/22) in the arps10 gene were each found in P. falciparum parasite samples collected in 2013. There was no statistically significant difference in the prevalence of arps10 SNPs in the samples collected in 2005 and 2013 (p = 0.238). There were more pfmdr-2 SNPs in P. falciparum parasites collected after introduction of Artemisinin combination therapies in malaria treatment. This is an indicator of the need for continuous surveillance to monitor emergence of molecular markers of artemisinin resistance and its potential drivers in malaria affected regions globally.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.280
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2022
Admission routes1
Has abstractyes

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