Analysis of transient migration behavior of natural killer cells imaged in situ and in vitro

We present a simple method for rapid and automatic characterization of lymphocyte migration from time-lapse fluorescence microscopy data. Time-lapse imaging of natural killer (NK) cells in vitro and in situ, both showed that individual cells transiently alter their migration behavior. Typically, NK...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Integrative biology (Cambridge) 2011-01, Vol.3 (7), p.770-778
Hauptverfasser: Khorshidi, Mohammad Ali, Vanherberghen, Bruno, Kowalewski, Jacob M, Garrod, Kym R, Lindström, Sara, Andersson-Svahn, Helene, Brismar, Hjalmar, Cahalan, Michael D, Önfelt, Björn
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We present a simple method for rapid and automatic characterization of lymphocyte migration from time-lapse fluorescence microscopy data. Time-lapse imaging of natural killer (NK) cells in vitro and in situ, both showed that individual cells transiently alter their migration behavior. Typically, NK cells showed periods of high motility, interrupted by transient periods of slow migration or almost complete arrests. Analysis of in vitro data showed that these periods frequently coincided with contacts with target cells, sometimes leading to target cell lysis. However, NK cells were also commonly observed to stop independently of contact with other cells. In order to objectively characterize the migration of NK cells, we implemented a simple method to discriminate when NK cells stop or have low motilities, have periods of directed migration or undergo random movement. This was achieved using a sliding window approach and evaluating the mean squared displacement (MSD) to assess the migration coefficient and MSD curvature along trajectories from individual NK cells over time. The method presented here can be used to quickly and quantitatively assess the dynamics of individual cells as well as heterogeneity within ensembles. Furthermore, it may also be used as a tool to automatically detect transient stops due to the formation of immune synapses, cell division or cell death. We show that this could be particularly useful for analysis of in situ time-lapse fluorescence imaging data where most cells, as well as the extracellular matrix, are usually unlabelled and thus invisible.
ISSN:1757-9694
1757-9708
1757-9708
DOI:10.1039/c1ib00007a