Automated cell lineage construction: a rapid method to analyze clonal development established with murine neural progenitor cells.
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 glial production. The method enables a level of quantitative analysis of cell behavior over time that was previously infeasible.
Al-Kofahi
Omar
O
Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA.
Radke
Richard J
RJ
Goderie
Susan K
SK
Shen
Qin
Q
Temple
Sally
S
Roysam
Badrinath
B
D000465:Algorithms; D000818:Animals; D001331:Automation; D019070:Cell Lineage; D049109:Cell Proliferation; D002540:Cerebral Cortex / Q000196:embryology; D002999:Clone Cells; D007091:Image Processing, Computer-Assisted; D016013:Likelihood Functions; D051379:Mice; D018715:Microscopy, Video / Q000379:methods; D009474:Neurons / Q000166:cytology*; D013234:Stem Cells / Q000166:cytology*; D013997:Time Factors