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Immediate pools of malaria infections at diagnosis combined with targeted deep sequencing accurately quantifies frequency of drug resistance mutations
Author(s) -
Özkan Aydemir,
Benedicta Ayiedu Mensah,
Patrick W Marsh,
Benjamin Abuaku,
James L Myers-Hansen,
Jeffrey A. Bailey,
Anita Ghansah
Publication year - 2021
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.11794
Subject(s) - malaria , drug resistance , pooling , plasmodium falciparum , deep sequencing , computational biology , medicine , biology , computer science , genetics , artificial intelligence , pathology , genome , gene
Antimalarial resistance surveillance in sub-Saharan Africa is often constrained by logistical and financial challenges limiting its breadth and frequency. At two sites in Ghana, we have piloted a streamlined sample pooling process created immediately by sequential addition of positive malaria cases at the time of diagnostic testing. This streamlined process involving a single tube minimized clinical and laboratory work and provided accurate frequencies of all known drug resistance mutations after high-throughput targeted sequencing using molecular inversion probes. Our study validates this method as a cost-efficient, accurate and highly-scalable approach for drug resistance mutation monitoring that can potentially be applied to other infectious diseases such as tuberculosis.

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