Papers › Unsupervised Discovery of Toxoplasma gondii Motility Phenotypes

Unsupervised Discovery of Toxoplasma gondii Motility Phenotypes

8 Jan 2018arXiv:1801.02591archive 2025-07-28

Mojtaba S. Fazli, Stephen A. Vella, Silvia N. J. Moreno, Shannon Quinn

Toxoplasma gondii is a parasitic protozoan that causes dis- seminated toxoplasmosis, a disease that afflicts roughly a third of the worlds population. Its virulence is predicated on its motility and ability to enter and exit nucleated cells; therefore, studies elucidating its mechanism of motility and in particular, its motility patterns in the context of its lytic cycle, are critical to the eventual development of therapeutic strate- gies. Here, we present an end-to-end computational pipeline for identifying T. gondii motility phenotypes in a completely unsupervised, data-driven way. We track the parasites before and after addition of extracellular Ca2+ to study its effects on the parasite motility patterns and use this information to parameterize the motion and group it according to similarity of spatiotemporal dynamics.

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