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Analysis of transient migration behavior of natural killer cells imaged in situ and in vitro
KTH, School of Engineering Sciences (SCI), Applied Physics, Cell Physics.
KTH, School of Engineering Sciences (SCI), Applied Physics.
KTH, School of Engineering Sciences (SCI), Applied Physics, Cell Physics.
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2011 (English)In: Integrative Biology, ISSN 1757-9694, E-ISSN 1757-9708, Vol. 3, no 7, 770-778 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2011. Vol. 3, no 7, 770-778 p.
National Category
Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-38154DOI: 10.1039/c1ib00007aISI: 000293504600007Scopus ID: 2-s2.0-79960024256OAI: oai:DiVA.org:kth-38154DiVA: diva2:436004
Funder
Swedish Research CouncilScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note
QC 20110822Available from: 2011-08-22 Created: 2011-08-22 Last updated: 2017-12-08Bibliographically approved
In thesis
1. Live Single Cell Imaging and Analysis Using Microfluidic Devices
Open this publication in new window or tab >>Live Single Cell Imaging and Analysis Using Microfluidic Devices
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Today many cell biological techniques study large cell populations where an average estimate of individual cells’ behavior is observed. On the other hand, single cell analysis is required for studying functional heterogeneities between cells within populations. This thesis presents work that combines the use of microfluidic devices, optical microscopy and automated image analysis to design various cell biological assays with single cell resolution including cell proliferation, clonal expansion, cell migration, cell-cell interaction and cell viability tracking. In fact, automated high throughput single cell techniques enable new studies in cell biology which are not possible with conventional techniques.

In order to automatically track dynamic behavior of single cells, we developed a microwell based device as well as a droplet microfluidic platform. These high throughput microfluidic assays allow automated time-lapse imaging of encapsulated single cells in micro droplets or confined cells inside microwells. Algorithms for automatic quantification of cells in individual microwells and micro droplets are developed and used for the analysis of cell viability and clonal expansion. The automatic counting protocols include several image analysis steps, e.g. segmentation, feature extraction and classification. The automatic quantification results were evaluated by comparing with manual counting and revealed a high success rate. In combination these automatic cell counting protocols and our microfluidic platforms can provide statistical information to better understand behavior of cells at the individual level under various conditions or treatments in vitro exemplified by the analysis of function and regulation of immune cells. Thus, together these tools can be used for developing new cellular imaging assays with resolution at the single cell level.

To automatically characterize transient migration behavior of natural killer (NK) cells compartmentalized in microwells, we developed a method for single cell tracking. Time-lapse imaging showed that the NK cells often exhibited periods of high motility, interrupted with periods of slow migration or complete arrest. These transient migration arrest periods (TMAPs) often overlapped with periods of conjugations between NK cells and target cells. Such conjugation periods sometimes led to cell-mediated killing of target cells. Analysis of cytotoxic response of NK cells revealed that a small sub-class of NK cells called serial killers was able to kill several target cells. In order to determine a starting time point for cell-cell interaction, a novel technique based on ultrasound was developed to aggregate NK and target cells into the center of the microwells. Therefore, these assays can be used to automatically and rapidly assess functional and migration behavior of cells to detect differences between health and disease or the influence of drugs.

The work presented in this thesis gives good examples of how microfluidic devices combined with automated imaging and image analysis can be helpful to address cell biological questions where single cell resolution is necessary. 

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. vi, 53 p.
Series
TRITA-BIO-Report, ISSN 1654-2312 ; 2013:14
Keyword
Single cell analysis, time-lapse fluorescence imaging, automated image analysis, microwell, droplet microfluidics, NK cells, single cell tracking, migration behavior analysis, cell-cell interaction, optical microscopy, image analysis, image processing, microfluidics, immune cells, tracking, counting, morphology analysis
National Category
Other Medical Biotechnology Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-129278 (URN)978-91-7501-846-1 (ISBN)
Public defence
2013-10-18, Gardaulan, Smittskyddsinstitutet, Nobels väg 18, Karolinska Institutet, Solna, 13:00 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 70784
Note

QC 20130927

Available from: 2013-09-26 Created: 2013-09-25 Last updated: 2014-02-28Bibliographically approved

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Brismar, HjalmarÖnfelt, Björn

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