Roche’s Cellavista System Successfully Used to Study the Self-Renewal Process of Embryonic Stem Cells
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A recent study depicted the use of Roche’s Cellavista System to effectively carry out a clonal analysis of embryonic stem (mES) colony self-renewal in an end-point assay. The Cellavista System proved to be useful for automated mES colony imaging, as well as characterization of colonies as differentiated and undifferentiated based on gating of morphological and intensity criteria. Little or no interference from the feeder cell layers was seen in the analysis of the images.
Embryonic stem cells are pluripotent cells that can differentiate into almost any specialized cell type and also have the ability to generate new, undifferentiated stem cells. The latter process is called self-renewal. Laboratories throughout the world routinely monitor embryonic stem cell colonies for signs of differentiation or self-renewal as a standard procedure for determining the effects of various factors on the self-renewal of mES cells.
Generally, cultures are scored manually using a microscope to determine the number of differentiating and non-differentiating colonies. However, manual scoring of individual colonies is known to be a tedious process subject to inter-individual and intra-individual variation.
In addition, due to the time-intensive nature of manual colony evaluation, experimental throughput is limited. As shown in the study, the Cellavista System offers an automated way to overcome these limitations and enables its user to check the differentiation status consistently.
Embryonic stem cells are pluripotent cells that can differentiate into almost any specialized cell type and also have the ability to generate new, undifferentiated stem cells. The latter process is called self-renewal. Laboratories throughout the world routinely monitor embryonic stem cell colonies for signs of differentiation or self-renewal as a standard procedure for determining the effects of various factors on the self-renewal of mES cells.
Generally, cultures are scored manually using a microscope to determine the number of differentiating and non-differentiating colonies. However, manual scoring of individual colonies is known to be a tedious process subject to inter-individual and intra-individual variation.
In addition, due to the time-intensive nature of manual colony evaluation, experimental throughput is limited. As shown in the study, the Cellavista System offers an automated way to overcome these limitations and enables its user to check the differentiation status consistently.
