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Quantification of Trypanosoma brucei social motility indicates different colony growth phases

colonies of the flagellated parasite exhibit characteristic fingering instability patterns. To enable data-driven and data-validated mechanistic modelling of these complex growth processes, it is crucial to first establish appropriate quantitative metrics beyond qualitative image comparisons. We pre...

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Bibliographic Details
Published in:Journal of the Royal Society interface 2024-12, Vol.21 (221), p.20240469
Main Authors: Kuhn, Andreas, Krüger, Timothy, Schüttler, Magdalena, Engstler, Markus, Fischer, Sabine C
Format: Article
Language:English
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Summary:colonies of the flagellated parasite exhibit characteristic fingering instability patterns. To enable data-driven and data-validated mechanistic modelling of these complex growth processes, it is crucial to first establish appropriate quantitative metrics beyond qualitative image comparisons. We present a quantification approach based on two scale-free metrics designed to characterize the shape of two-dimensional colonies. Originally developed for yeast colonies, we adapted, modified and extended this analysis pipeline for the system. By combining these quantitative measurements with colony growth simulations based on the Eden model, we identified two distinct growth phases in social motility-exhibiting colonies: an initial phase of mainly circular expansion, followed by a transition to an almost exclusive finger-growing phase. These phases remain robust with increasing cell numbers and upon partial inhibition of finger formation. A newly developed anisotropy index reveals that partial inhibition leads to increased colony anisotropy over time. Our results provide objective measurements that advance the understanding of social motility and serve as a foundation for future mechanistic modelling efforts. Furthermore, our approach offers a blueprint for investigations of other colony-forming microorganisms, such as yeast or bacteria, emphasizing the broader applicability of developing appropriate metrics for complex biological phenomena.
ISSN:1742-5662
1742-5689
1742-5662
DOI:10.1098/rsif.2024.0469