Maximum likelihood fitting of distance-dependent turning probabilities to cell trajectories recovers true interaction parameters even when migration behavior switches over time, unlike force-based models.
Detecting long-range attraction between migrating cells based on p-value distributions
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abstract
Immune cells have evolved to recognize and eliminate pathogens, and the efficiency of this process can be measured in a Petri dish. Yet, even if the cells are time-lapse recorded and tracked with high resolution, it is difficult to judge whether the immune cells find their targets by mere chance, or if they approach them in a goal-directed way, perhaps using remote sensing mechanisms such as chemotaxis. To answer this question, we assign to each step of an immune cell a 'p-value', the probability that a move, at least as target-directed as observed, can be explained with target-independent migration behavior. The resulting distribution of p-values is compared to the distribution of a reference system with randomized target positions. By using simulated data, based on various chemotactic search mechanisms, we demonstrate that our method can reliably distinguish between blind migration and target-directed 'hunting' behavior.
fields
q-bio.QM 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Inferring long-range interactions between immune and tumor cells -- pitfalls and (partial) solutions
Maximum likelihood fitting of distance-dependent turning probabilities to cell trajectories recovers true interaction parameters even when migration behavior switches over time, unlike force-based models.