Parametric analysis of colony morphology of non-labelled live human pluripotent stem cells for cell quality control
- PMID: 27667091
- PMCID: PMC5036041
- DOI: 10.1038/srep34009
Parametric analysis of colony morphology of non-labelled live human pluripotent stem cells for cell quality control
Abstract
Given the difficulties inherent in maintaining human pluripotent stem cells (hPSCs) in a healthy state, hPSCs should be routinely characterized using several established standard criteria during expansion for research or therapeutic purposes. hPSC colony morphology is typically considered an important criterion, but it is not evaluated quantitatively. Thus, we designed an unbiased method to evaluate hPSC colony morphology. This method involves a combination of automated non-labelled live-cell imaging and the implementation of morphological colony analysis algorithms with multiple parameters. To validate the utility of the quantitative evaluation method, a parent cell line exhibiting typical embryonic stem cell (ESC)-like morphology and an aberrant hPSC subclone demonstrating unusual colony morphology were used as models. According to statistical colony classification based on morphological parameters, colonies containing readily discernible areas of differentiation constituted a major classification cluster and were distinguishable from typical ESC-like colonies; similar results were obtained via classification based on global gene expression profiles. Thus, the morphological features of hPSC colonies are closely associated with cellular characteristics. Our quantitative evaluation method provides a biological definition of 'hPSC colony morphology', permits the non-invasive monitoring of hPSC conditions and is particularly useful for detecting variations in hPSC heterogeneity.
Conflict of interest statement
H.K., T.U. and Y.K. are employed by Nikon Corporation. BioStation CT and related software used in the present study are marketed products of Nikon Corporation. R.K. is one of the primary investigators on 7 patents (pending) related to basic algorithm technologies for cellular image processing. The other authors report no conflicts of interest.
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