Chrysalis: A New Method for High-Throughput Histo-Cytometry Analysis of Images and Movies

This information is current as Dmitri I. Kotov, Thomas Pengo, Jason S. Mitchell, Matthew of December 5, 2018. J. Gastinger and Marc K. Jenkins J Immunol published online 3 December 2018 http://www.jimmunol.org/content/early/2018/11/30/jimmun ol.1801202 Downloaded from

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2018 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published December 3, 2018, doi:10.4049/jimmunol.1801202 The Journal of Immunology

Chrysalis: A New Method for High-Throughput Histo-Cytometry Analysis of Images and Movies

Dmitri I. Kotov,*,†,1 Thomas Pengo,‡,1 Jason S. Mitchell,*,x,{ Matthew J. Gastinger,‖ and Marc K. Jenkins*,†

Advances in imaging have led to the development of powerful multispectral, quantitative imaging techniques, like histo-cytometry. The utility of this approach is limited, however, by the need for time consuming manual image analysis. We therefore developed the software Chrysalis and a group of Imaris Xtensions to automate this process. The resulting automation allowed for high-throughput histo-cytometry analysis of three-dimensional and two-photon time-lapse images of T cell–dendritic cell interactions in mouse spleens. It was also applied to epi-fluorescence images to quantify T cell localization within splenic tissue by using a “signal absorption” strategy that avoids computationally intensive distance measurements. In summary, this image

processing and analysis software makes histo-cytometry more useful for immunology applications by automating image Downloaded from analysis. The Journal of Immunology, 2019, 202: 000–000.

maging of biological samples has traditionally been used to images. The broad applicability of this protocol was confirmed by resolve anatomic structures (1) or identify specific cells in quantifying cell localization and cell-cell interactions in the I tissues (2). Recent advances in image analysis, like histo- spleen, using multiple imaging platforms. Automation should fa- cytometry (3) and dynamic in situ cytometry (4) have expanded cilitate the use of the powerful histo-cytometry technique. http://www.jimmunol.org/ the depth of analysis by increasing characterization of cell types and objective quantification of cells in images. These new tech- Materials and Methods niques combine multispectral image analysis with a quantitative Mice workflow. The image quantification is performed by analyzing Six- to eight-wk-old C57BL/6 (B6) female mice were purchased from the image-derived statistics in flow cytometry analysis software (3, 4). Jackson Laboratory or the National Cancer Institute Mouse Repository These approaches can quantify the number and location of cells (Frederick, MD). ItgaxYFP (13) and Rag12/2 UbcGFP (14) TEa TCR throughout a tissue (5), identify cell-cell interactions (6), and transgenic (Tg) (15) female mice were a gift from B.T. Fife (University of 2/2 2/2 correlate protein expression to cellular localization (7). Histo- Minnesota). Rag1 B3K506 TCR TG (16) and Rag1 B3K508 TCR