Quantitative analysis of cell migration using optical flow
- Authors
- Boric, K., Orio, P., Viéville, T., and Whitlock, K.
- ID
- ZDB-PUB-130903-20
- Date
- 2013
- Source
- PLoS One 8(7): e69574 (Journal)
- Registered Authors
- Boric, Katica
- Keywords
- none
- MeSH Terms
-
- Algorithms
- Animals
- Animals, Genetically Modified
- Cell Movement*
- Central Nervous System Depressants/pharmacology
- Embryo, Nonmammalian/cytology
- Embryo, Nonmammalian/drug effects
- Embryo, Nonmammalian/metabolism
- Ethanol/pharmacology
- Green Fluorescent Proteins/genetics
- Green Fluorescent Proteins/metabolism
- Models, Biological
- Neural Crest/cytology*
- Neural Crest/embryology
- Neural Crest/metabolism
- SOXE Transcription Factors/genetics
- SOXE Transcription Factors/metabolism
- Time-Lapse Imaging/methods*
- Videotape Recording/methods*
- Zebrafish/embryology
- Zebrafish/genetics
- Zebrafish/metabolism
- Zebrafish Proteins/genetics
- Zebrafish Proteins/metabolism
- PubMed
- 23936049 Full text @ PLoS One
Neural crest cells exhibit dramatic migration behaviors as they populate their distant targets. Using a line of zebrafish expressing green fluorescent protein (sox10:EGFP) in neural crest cells we developed an assay to analyze and quantify cell migration as a population, and use it here to characterize in detail the subtle defects in cell migration caused by ethanol exposure during early development. The challenge was to quantify changes in the in vivo migration of all Sox10:EGFP expressing cells in the visual field of time-lapse movies. To perform this analysis we used an Optical Flow algorithm for motion detection and combined the analysis with a fit to an affine transformation. Through this analysis we detected and quantified significant differences in the cell migrations of Sox10:EGFP positive cranial neural crest populations in ethanol treated versus untreated embryos. Specifically, treatment affected migration by increasing the left-right asymmetry of the migrating cells and by altering the direction of cell movements. Thus, by applying this novel computational analysis, we were able to quantify the movements of populations of cells, allowing us to detect subtle changes in cell behaviors. Because cranial neural crest cells contribute to the formation of the frontal mass these subtle differences may underlie commonly observed facial asymmetries in normal human populations.