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A Quantitative Evaluation of Cell Migration by the Phagokinetic Track Motility Assay
Published on: December 4, 2012
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Migration and interaction tracking for quantitative analysis of phagocyte-pathogen confrontation assays
Susanne Brandes1, Stefanie Dietrich1, Kerstin Hünniger2
1Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany; Friedrich Schiller University, Jena, Germany.
Medical Image Analysis
|December 13, 2016
Summary
A new algorithm, AMIT, automates the analysis of live-cell imaging data to quantify interactions between immune cells and fungal pathogens. This tool enhances the study of invasive fungal infections by efficiently tracking phagocytosis events.
Area of Science:
- Immunology
- Microbiology
- Biophysics
Background:
- Invasive fungal infections pose a growing global health threat.
- Phagocytes are crucial for the innate immune response, engulfing and eliminating pathogens.
- Live-cell imaging offers dynamic insights into phagocyte-pathogen interactions but generates large datasets requiring manual analysis.
Purpose of the Study:
- To develop an automated, high-throughput framework for analyzing live-cell microscopy videos of phagocyte-pathogen interactions.
- To enable quantitative analysis of dynamic processes like phagocytosis in time and space.
- To advance existing cell tracking frameworks for multi-channel imaging and inter-cell type interaction tracking.
Main Methods:
- Introduction of the Algorithm for Migration and Interaction Tracking (AMIT) framework.
- Adaptation of a prior segmentation and tracking framework for non-rigid cells.
- Development of a state-transition model for polymorphonuclear neutrophils (PMNs) to represent phagocytic events.
- Validation through direct comparison with manual analysis and existing literature.
Main Results:
- AMIT enables automated segmentation and tracking of different cell types in multi-channel microscopy.
- The framework accurately detects phagocytic events, focusing on PMN-Candida glabrata interactions.
- Quantitative and multivariate analyses of phagocyte-fungus confrontation assays were performed.
Conclusions:
- AMIT provides a robust solution for high-throughput analysis of phagocyte-pathogen interactions.
- The automated approach significantly reduces the manual workload associated with live-cell imaging data.
- This framework facilitates a deeper quantitative understanding of innate immune responses to fungal infections.
