Immediate pools of malaria infections at diagnosis combined with targeted deep sequencing accurately quantifies frequency of drug resistance mutations
Ozkan Aydemir,
Benedicta Mensah,
Patrick W. Marsh,
Benjamin Abuaku,
James Leslie Myers-Hansen,
Jeffrey A. Bailey,
Anita Ghansah
Affiliations
Ozkan Aydemir
Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Brown University, Providence, RI, United States of America
Benedicta Mensah
Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Accra, Ghana
Patrick W. Marsh
Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Brown University, Providence, RI, United States of America
Benjamin Abuaku
Department of Epidemiology, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Accra, Ghana
James Leslie Myers-Hansen
Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Accra, Ghana
Jeffrey A. Bailey
Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Brown University, Providence, RI, United States of America
Anita Ghansah
Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Accra, Ghana
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.
