An in silico model of the African trypanosome: Moving in complex environments

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Trypanosoma brucei is a uni-cellular parasite that causes the sleeping sickness, a deadly disease for humans and also for livestock. The cell body of the trypanosome has the shape of a spindle, along which an eukaryotic flagellum is attached. While a bending wave runs along the flagellum, the trypanosome exhibits characteristic deformations and moves forward. In previous work we have developed an accurate, in silico model trypanosome in close collaboration with the group of M. Engstler using information from live cell analyses. It mimics the swimming behavior of the real trypanosome very well and allows to study in silico mutants.While the African trypanosome brucei has been considered to reside and move in the blood stream, research of the last decade has clearly shown that a substantial amount of the parasite can also be found in tissues outside the blood vessels. Trypanosomes move in the complex environment of the skin, fat tissue, in the interstitial space, and the brain. They have to squeeze through tight passages when entering a new environment or need to swim between fat cells. In the extracellular matrix they encounter collagen fibers forming a dense elastic network or they interact with a packing of fat cells and their elastic surfaces. And they experience the flow of the interstitial fluid.The goal of the project is a thorough computational investigation, in close cooperation with experiments in the group of M. Engstler, of how the in silico trypanosome moves in complex environments including fluid flow, which we simulate with the method of multi-particle collision dynamics. Increasing the complexity of the environment step by step, we aim for a full understanding how different features influence the swimming path of the trypanosome. Concretely, we will investigate the swimming in silico trypanosome in confining geometries also in flow. For this, we implement microchannels with increasing confinement as well as constrictions, and also obstacle arrays, where we look for geometric swimming. We then allow for two types of elastic deformations in the environment. Using bead-spring chains, we will model the highly deformable collagen network varying density and fiber stiffness. Finally, we will approach swimming in fat tissue by implementing soft obstacles using Hertzian contact forces. This brings us closer to real environments.