Automated classification of Plasmodium sporozoite movement patterns reveals a shift towards productive motility during salivary gland infection

摘要

The invasive stages of malaria and other apicomplexan parasites use a unique motility machinery based on actin, myosin and a number of parasite-specific proteins to invade host cells and tissues. The crucial importance of this motility machinery at several stages of the life cycle of these parasites makes the individual components potential drug targets. The different stages of the malaria parasite exhibit strikingly diverse movement patterns, likely reflecting the varied needs to achieve successful invasion. Here, we describe a Tool for Automated Sporozoite Tracking (ToAST) that allows the rapid simultaneous analysis of several hundred motile Plasmodium sporozoites, the stage of the malaria parasite transmitted by the mosquito. ToAST reliably categorizes different modes of sporozoite movement and can be used for both tracking changes in movement patterns and comparing overall movement parameters, such as average speed or the persistence of sporozoites undergoing a certain type of movement. This allows the comparison of potentially small differences between distinct parasite populations and will enable screening of drug libraries to find inhibitors of sporozoite motility. Using ToAST, we find that isolated sporozoites change their movement patterns towards productive motility during the first week after infection of mosquito salivary glands.