May 2, 2018

Drug susceptibility was measured using the SYBR Green I method as previously described44 [/articles/s41467-018-04104-z#ref-CR44]. In brief, tightly synchronized 0â6 h rings were grown for 72 h in the presence of different concentrations of drugs in 384-clear-bottom well plates at 1% hematocrit, 1% starting parasitemia and 40 Îźl of 0.5% Albumax culture media. Growth at 72 h was measured by SYBR Green I (Lonza, Visp, Switzerland) staining of parasite DNA. A 24-point dilution of PPQ (Sigma-Aldrich, St. Louis, MO) and a 12-point dilution series of the rest of the drugs (DHA, ART, AS, MEF, and LUM; Sigma-Aldrich, St. Louis, MO) were carried out in triplicate and repeated with at least three biological replicates. Drug stocks were resuspended in dimethyl sulfoxide except for CQ prepared in 0.1% Triton X-100 in water and PPQ prepared in 0.1% Triton X-100 and 0.5% lactic acid in water to ensure complete dissolution, as lactic acid enhanced PPQ solubility45 [/articles/s41467-018-04104-z#ref-CR45]. Drugs dispensed by a HP D300 Digital Dispenser (Hewlett Packard Palo Alto, CA), with the Triton X-100 enhancing dispensing of aqueous drug stocks. Relative fluorescence units was measured at an excitation of 494 nm and emission of 530 nm on a SpectraMax M5 (Molecular Devices Sunnyvale, CA) and analyzed using GraphPad Prism version 7 (GraphPad Software La Jolla, CA). EC50 values were determined with the curve-fitting algorithm log(inhibitor) vs. responseâVariable slope except for PPQ. PPQs bimodal doseâresponse would not allow for any curve-fitting hence susceptibility was measured by calculating the area under the second response curve (AUC). AUC was calculated by fitting a six-dimensional least-square polynomial equation to each sampleâs doseâresponse curve and integrating the fitted equation over the region corresponding to the second response curve. These equations were fit to the data using the polyfit module in NumPy, a fundamental package for scientific computing using Python. We chose to use a six-dimensional least-square polynomial equation because it captures the dynamics of the second response curve better than equations with fewer dimensions. Using equations with dimensions > 6 do not result in major differences in calculated AUC values. In fact, AUC values calculated using the boundaries identified by our equation fitting method (0.10 ÎźM â 30 ÎźM) gave roughly the same result. The boundaries of the second response curve were determined by identifying the drug concentration corresponding to the average local minima before and after the second response curve across all drug-assayed samples

Multidrug resistant Plasmodium falciparum in Southeast Asia endangers regional malaria elimination and threatens to spread to other malaria endemic areas. Understanding mechanisms of piperaquine (PPQ) resistance is crucial for tracking its emergence and spread, and to develop effective strategies for overcoming it. Here we analyze a mechanism of PPQ resistance in Cambodian parasites. Isolates exhibit a bimodal dose-response curve when exposed to PPQ, with the area under the curve quantifying their survival in vitro. Increased copy number for plasmepsin II and plasmepsin III appears to explain enhanced survival when exposed to PPQ in most, but not all cases. A panel of isogenic subclones reinforces the importance of plasmepsin II-III copy number to enhanced PPQ survival. We conjecture that factors producing increased parasite survival under PPQ exposure in vitro may drive clinical PPQ failures in the field.

Bopp, S; Magistrado, P; Wong, W; Schaffner, SF; Mukherjee, A; Lim, P; Dhorda, M; Amaratunga, C; Woodrow, CJ; Ashley, EA; White, NJ; Dondorp, AM; Fairhurst, RM; Ariey, F; Menard, D; Wirth, DF; Volkman, SK;

Journal: Nat Commun Pages: 1769