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Automated Cell Lineage Construction: A Rapid Method to Analyze Clonal Development Established with Murine Neural Progenitor Cells

Omar Al-Kofahi, Richard J. Radke, Susan K. Goderie, Qin Shen, Sally Temple and Badrinath Roysam

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Understanding cell lineage relationships is fundamental to understanding development, and can shed light on disease etiology and progression. We present a method for automated tracking of lineages of proliferative, migrating cells from a sequence of images. The method is applicable to image sequences gathered either in vitro or in vivo. Currently, generating lineage trees from progenitor cells over time is a tedious, manual process, which limits the number of cell measurements that can be practically analyzed. In contrast, the automated method is rapid and easily applied, and produces a wealth of measurements including the precise position, shape, cell-cell contacts, motility and ancestry of each cell in every frame, and accurate timings of critical events, e.g. mitosis and cell death. Furthermore, it automatically produces graphical output that is immediately accessible. Application to clonal development of mouse neural progenitor cells growing in cell culture reveals complex changes in cell cycle rates during neuron and glia production. The method enables a level of quantitative analysis of cell behavior over time that was previously infeasible.

Authors

Omar Al-Kofahi

Richard J. Radke

Susan K. Goderie

Qin Shen

Sally Temple

Badrinath Roysam

 Download PDF

If the document does not open, please right-click on the link (control-click on a Macintosh) and select the option to save the file to disk.