Abstract
With more than 40% of the world’s population at risk, 200–300 million infections each year, and an estimated 1.2 million deaths annually, malaria remains one of the most important public health problems of mankind today. With the propensity of malaria parasites to rapidly develop resistance to newly developed therapies, and the recent failures of artemisinin-based drugs in Southeast Asia, there is an urgent need for new antimalarial compounds with novel mechanisms of action to be developed against multidrug resistant malaria. We present here a novel image analysis algorithm for the quantitative detection and classification of Plasmodium lifecycle stages in culture as well as discriminating between viable and dead parasites in drug-treated samples. This new algorithm reliably estimates the number of red blood cells (isolated or clustered) per fluorescence image field, and accurately identifies parasitized erythrocytes on the basis of high intensity DAPI-stained parasite nuclei spots and Mitotracker-stained mitochondrial in viable parasites. We validated the performance of the algorithm by manual counting of the infected and non-infected red blood cells in multiple image fields, and the quantitative analyses of the different parasite stages (early rings, rings, trophozoites, schizonts) at various time-point post-merozoite invasion, in tightly synchronized cultures. Additionally, the developed algorithm provided parasitological effective concentration 50 (EC50) values for both chloroquine and artemisinin, that were similar to known growth inhibitory EC50 values for these compounds as determined using conventional SYBR Green I and lactate dehydrogenase-based assays.
Highlights
Malaria remains one of the most widespread infectious diseases of mankind, with 40% of the world’s population at risk and more than 240 million infections each year [1]
The validation of the malaria image analysis algorithm was achieved by comparing the obtained data from the red blood cells (RBC) number estimation, parasite signal detection, infected RBC segmentation processes with results from manual counting involving six different experimenters
We validated the algorithm for drug effective concentration 50 (EC50) determination by utilizing images from various dose-response experiments with known antimalarial compounds
Summary
Malaria remains one of the most widespread infectious diseases of mankind, with 40% of the world’s population at risk and more than 240 million infections each year [1]. P. falciparum preferentially infects mature and enucleated red blood cells (RBC), where they develop through a ring and trophozoite stage, and undergo three to four rounds of DNA synthesis, mitosis and nuclear division to produce a syncytial schizont with approximately 12 to 40 nuclei per infected RBC [5,6]. This asexual cycle occurs over a period of 48 hours resulting in the release of over 16 merozoites (1n) for additional rounds of host cell invasion and parasite proliferation. Finding novel drug candidates targeting the parasite’s developmental cycle remains a challenge, as all current antimalarial screening assays mostly rely on total DNA measurements or detection of various parasite proteins as a measure of parasite viability in vitro [7,8,9]
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