Collective cell migration is an important process during biological development and tissue repair but may turn malignant during tumor invasion. Mathematical and computational models are essential to unravel the mechanisms of self-organization that underlie the emergence of collective migration from the interactions among individual cells. Recently, guidance-by-followers was identified as one such underlying mechanism of collective cell migration in the embryo of the zebrafish. This poses the question of how the guidance stimuli are integrated when multiple cells interact simultaneously. In this study, we extend a recent individual-based model by an integration step of the vectorial guidance stimuli and compare model predictions obtained for different variants of the mechanism (arithmetic mean of stimuli, dominance of stimulus with largest transmission interface, and dominance of most head-on stimulus). Simulations are carried out and quantified within the modeling and simulation framework Morpheus. Collective cell migration is found to be robust and qualitatively identical for all considered variants of stimulus integration. Moreover, this study highlights the role of individual-based modeling approaches for understanding collective phenomena at the population scale that emerge from cell-cell interactions.

In biology, it is common to study cultured cells (in vitro) with fluorescence time-lapse microscopy. The cells are recorded for longer period of time and can later be viewed at an accelerated speed. During the acquisition some live cells tend to migrate. This can be a problem if the cell’s migration speed is high enough to move outside the field of view (FOV) during the acquisition time. The cells that moves outside the FOV can no longer be recorded and the information about them will be lost. This thesis presents scripts that have been developed for ZEN (blue) to be able to track a specific migrating cell of interest in real-time with automated control of imaging parameters. The microscope stage position is modified on-the-fly to have the tracked cell in the center of the FOV for the whole experiment. Three different types of experiments to track migrating NK cells were performed with the scripts. The results show that the scripts were able to track one NK cell for more than 1 hour in both conventional wide-field and lattice light-sheet microscopy. The segmentation was inaccurate when one or more objects were in close proximity to the tracked cell. By applying a watershed algorithm the segmentation result can be improved in some cases. / Inom cellulär biologi är det vanligt att studera odlade celler (in vitro) med time- lapse-mikroskopi. Flertals bilder tas på cellerna under en längre tidsperiod och när experimentet är klart så kan man titta på bilderna som en video. Under förvärvet av bilderna så tenderar vissa levande celler att migrera. Ett problem som kan uppstå är om cellens migrationshastighet är tillräckligt hög för att röra sig utanför synfältet under anskaffningstiden. De celler som rör sig utanför synfältet kan inte längre avbildas och informationen om dem kommer att gå förlorad. I denna avhandling presenteras programmeringskoder som har utvecklats för ZEN (blue) som kan spåra en specifik migrerande cell i realtid med automatiserad kontroll av bildbehandlings parametrar. Mikroskopets scenposition modifieras under experimentets gång för att få den spårade cellen kontinuerligt i mitten av synfältet. Tre olika sorters experiment i kombination med programmeringskoderna utfördes för att spåra NK-celler. Resultaten visar att programmeringskoderna lyckades spåra en NK-cell i mer än 1 timme i både ett bredfältsfluorescensmikroskop och ett lattice light-sheet mikroskop. Segmenteringen var felaktig när ett eller flera objekt var i närheten av den spårade cellen. Genom att tillämpa en watershed algoritm kan segmenteringsresultatet förbättras i vissa fall.