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High resolution melting: a useful field-deployable method to measure dhfr and dhps drug resistance in both highly and lowly endemic Plasmodium populations

Overview of attention for article published in Malaria Journal, April 2017
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Title
High resolution melting: a useful field-deployable method to measure dhfr and dhps drug resistance in both highly and lowly endemic Plasmodium populations
Published in
Malaria Journal, April 2017
DOI 10.1186/s12936-017-1811-2
Pubmed ID
Authors

Yaye Dié Ndiaye, Cyrille K. Diédhiou, Amy K. Bei, Baba Dieye, Aminata Mbaye, Nasserdine Papa Mze, Rachel F. Daniels, Ibrahima M. Ndiaye, Awa B. Déme, Amy Gaye, Mouhamad Sy, Tolla Ndiaye, Aida S. Badiane, Mouhamadou Ndiaye, Zul Premji, Dyann F. Wirth, Souleymane Mboup, Donald Krogstad, Sarah K. Volkman, Ambroise D. Ahouidi, Daouda Ndiaye

Abstract

Emergence and spread of drug resistance to every anti-malarial used to date, creates an urgent need for development of sensitive, specific and field-deployable molecular tools for detection and surveillance of validated drug resistance markers. Such tools would allow early detection of mutations in resistance loci. The aim of this study was to compare common population signatures and drug resistance marker frequencies between two populations with different levels of malaria endemicity and history of anti-malarial drug use: Tanzania and Sénégal. This was accomplished by implementing a high resolution melting assay to study molecular markers of drug resistance as compared to polymerase chain reaction-restriction fragment length polymorphism (PCR/RFLP) methodology. Fifty blood samples were collected each from a lowly malaria endemic site (Sénégal), and a highly malaria endemic site (Tanzania) from patients presenting with uncomplicated Plasmodium falciparum malaria at clinic. Data representing the DHFR were derived using both PCR-RFLP and HRM assay; while genotyping data representing the DHPS were evaluated in Senegal and Tanzania using HRM. Msp genotyping analysis was used to characterize the multiplicity of infection in both countries. A high prevalence of samples harbouring mutant DHFR alleles was observed in both population using both genotyping techniques. HRM was better able to detect mixed alleles compared to PCR/RFLP for DHFR codon 51 in Tanzania; and only HRM was able to detect mixed infections from Senegal. A high prevalence of mutant alleles in DHFR (codons 51, 59, 108) and DHPS (codon 437) were found among samples from Sénégal while no mutations were observed at DHPS codons 540 and 581, from both countries. Overall, the frequency of samples harbouring either a single DHFR mutation (S108N) or double mutation in DHFR (C59R/S108N) was greater in Sénégal compared to Tanzania. Here the results demonstrate that HRM is a rapid, sensitive, and field-deployable alternative technique to PCR-RFLP genotyping that is useful in populations harbouring more than one parasite genome (polygenomic infections). In this study, a high levels of resistance polymorphisms was observed in both dhfr and dhps, among samples from Tanzania and Sénégal. A routine monitoring by molecular markers can be a way to detect emergence of resistance involving a change in the treatment policy.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 23%
Researcher 9 13%
Student > Master 9 13%
Student > Bachelor 7 10%
Student > Doctoral Student 5 7%
Other 9 13%
Unknown 15 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 23%
Medicine and Dentistry 11 16%
Agricultural and Biological Sciences 11 16%
Computer Science 3 4%
Nursing and Health Professions 2 3%
Other 6 9%
Unknown 21 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 April 2017.
All research outputs
#14,340,404
of 22,965,074 outputs
Outputs from Malaria Journal
#3,985
of 5,587 outputs
Outputs of similar age
#173,014
of 310,317 outputs
Outputs of similar age from Malaria Journal
#111
of 132 outputs
Altmetric has tracked 22,965,074 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,587 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 310,317 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.