Evidence map›Paper›PMID 22430961›Full record

ArticleAntimicrobial agents and chemotherapy2012

Rapid, field-deployable method for genotyping and discovery of single-nucleotide polymorphisms associated with drug resistance in Plasmodium falciparum.

Rachel Daniels, Daouda Ndiaye, Mikeal Wall, Jason McKinney, Papa Diogoye Séne, Pardis C Sabeti, Sarah K Volkman, Souleymane Mboup, Dyann F Wirth

Abstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed.

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  6. Detection of novelFrontiers in cellular and infection microbiology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Rachel DanielsBroad Institute, Cambridge, Massachusetts, USA. rdaniels@broadinstitute.org
Daouda Ndiaye
Mikeal Wall
Jason McKinney
Papa Diogoye Séne
Pardis C Sabeti
Sarah K Volkman
Souleymane Mboup
Dyann F Wirth

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite efforts to reduce malaria morbidity and mortality, drug-resistant parasites continue to evade control strategies. Recently, emphasis has shifted away from control and toward regional elimination and global eradication of malaria. Such a campaign requires tools to monitor genetic changes in the parasite that could compromise the effectiveness of antimalarial drugs and undermine eradication programs. These tools must be fast, sensitive, unambiguous, and cost-effective to offer real-time reports of parasite drug susceptibility status across the globe. We have developed and validated a set of genotyping assays using high-resolution melting (HRM) analysis to detect molecular biomarkers associated with drug resistance across six genes in Plasmodium falciparum. We improved on existing technical approaches by developing refinements and extensions of HRM, including the use of blocked probes (LunaProbes) and the mutant allele amplification bias (MAAB) technique. To validate the sensitivity and accuracy of our assays, we compared our findings to sequencing results in both culture-adapted lines and clinical isolates from Senegal. We demonstrate that our assays (i) identify both known and novel polymorphisms, (ii) detect multiple genotypes indicative of mixed infections, and (iii) distinguish between variants when multiple copies of a locus are present. These rapid and inexpensive assays can track drug resistance and detect emerging mutations in targeted genetic loci in P. falciparum. They provide tools for monitoring molecular changes associated with changes in drug response across populations and for determining whether parasites present after drug treatment are the result of recrudescence or reinfection in clinical settings.

Indexed as

AntimalarialsDrug ResistanceMutationParasitic Sensitivity TestsPlasmodium falciparumPolymorphism, Single NucleotideAntimalarials

Identifiers

PMID22430961
PMCPMC3370755

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.