Characterizing the spatio-temporal behavior of cell populations through image auto- and cross-correlation microscopy.
We propose two methods for characterizing the spatio-temporal behavior of cell populations in culture. The first method, image auto-correlation microscopy (IACM), allows us to characterize the variation in the number of objects as a function of time, thus enabling the quantification of the clustering properties of cell populations to be performed. The second method, image cross-correlation microscopy (ICCM), allows us to characterize the migration properties of cell populations. The latter method does not require estimation or measurement of the trajectories of individual cells, which is very demanding when populations of >100 cells are examined. The capabilities of the two methods are demonstrated with simulated cell populations, and their usefulness is illustrated with experiments involving invasive and noninvasive tumor cell populations.
Bonnet
Noël
N
UMRS, Inserm 514, Université de Reims Champagne-Ardenne, Reims, France. noel.bonnet@univ-reims.fr
Delavoie
Franck
F
Zahm
Jean-Marie
JM
D000818:Animals; D002392:Catechin / Q000031:analogs & derivatives / Q000494:pharmacology; D002449:Cell Aggregation / Q000187:drug effects; D002460:Cell Line; D002465:Cell Movement / Q000187:drug effects; D002470:Cell Survival / Q000187:drug effects; D002477:Cells / Q000166:cytology*; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D008853:Microscopy / Q000379:methods*; D009369:Neoplasms / Q000473:pathology; D013997:Time Factors
D002392:Catechin; C045651:epigallocatechin gallate