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A Video Bioinformatics Method to Quantify Cell Spreading and Its Application to Cells Treated with Rho-Associated Protein Kinase and Blebbistatin

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Video Bioinformatics

Part of the book series: Computational Biology ((COBO,volume 22))

Abstract

Commercial software is available for performing video bioinformatics analysis on cultured cells. Such software is convenient and can often be used to create suitable protocols for quantitative analysis of video data with relatively little background in image processing. This chapter demonstrates that CL-Quant software, a commercial program produced by DRVision, can be used to automatically analyze cell spreading in time-lapse videos of human embryonic stem cells (hESC). Two cell spreading protocols were developed and tested. One was professionally created by engineers at DRVision and adapted to this project. The other was created by an undergraduate student with 1 month of experience using CL-Quant. Both protocols successfully segmented small spreading colonies of hESC, and, in general, were in good agreement with the ground-truth which was measured using ImageJ. Overall the professional protocol performed better segmentation, while the user-generated protocol demonstrated that someone who had relatively little background with CL-Quant can successfully create protocols. The protocols were applied to hESC that had been treated with ROCK inhibitors or blebbistatin, which tend to cause rapid attachment and spreading of hESC colonies. All treatments enabled hESC to attach rapidly. Cells treated with the ROCK inhibitors or blebbistatin spread more than controls and often looked stressed. The use of the spreading analysis protocol can provide a very rapid method to evaluate the cytotoxicity of chemical treatment and reveal effects on the cytoskeleton of the cell. While hESC are presented in this chapter, other cell types could also be used in conjunction with the spreading protocol.

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Acknowledgments

We thank DRVision, Sam Alworth, Ned Jastromb, Randy Myers, and Mike Allegro of Nikon Inc. for their invaluable help with the BioStation IM and CL-Quant software training. Work in this chapter was supported by an NSF IGERT grant on Video Bioinformatics (#DGE 093667), the California Institute for Regenerative Medicine (CIRM NE-A0005A-1E), and a grant from the Tobacco-Related Disease Research Program of California (TRDRP 22RT-0127).

Author information

Authors and Affiliations

  1. Department of Cell Biology & Neuroscience, University of California, 2313 Spieth Hall, 900 University Ave., Riverside, CA, 92507, USA

    Nikki Jo-Hao Weng

  2. Department Cell, Molecular, and Developmental Biology, University of California, 2320 Spieth Hall, 900 University Ave., Riverside, CA, 92507, USA

    Rattapol Phandthong

  3. Department of Cell Biology & Neuroscience, University of California, 2320 Spieth Hall, 900 University Ave., Riverside, CA, 92507, USA

    Prue Talbot

Authors
  1. Nikki Jo-Hao Weng
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Correspondence to Nikki Jo-Hao Weng .

Editor information

Editors and Affiliations

  1. University of California, Riverside, California, USA

    Bir Bhanu

  2. University of California, Riverside, California, USA

    Prue Talbot

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Weng, N.JH., Phandthong, R., Talbot, P. (2015). A Video Bioinformatics Method to Quantify Cell Spreading and Its Application to Cells Treated with Rho-Associated Protein Kinase and Blebbistatin. In: Bhanu, B., Talbot, P. (eds) Video Bioinformatics. Computational Biology, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-23724-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-23724-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23723-7

  • Online ISBN: 978-3-319-23724-4

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